Artykuły w czasopismach na temat „Habitat mapping”
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Enwright, Nicholas M., Lei Wang, Sinéad M. Borchert, Richard H. Day, Laura C. Feher i Michael J. Osland. "Advancing barrier island habitat mapping using landscape position information". Progress in Physical Geography: Earth and Environment 43, nr 3 (11.04.2019): 425–50. http://dx.doi.org/10.1177/0309133319839922.
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Barrier islands are dynamic ecosystems that change gradually from coastal processes, including currents and tides, and rapidly from episodic events, such as storms. These islands provide many important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. Habitat maps, developed by scientists, provide a critical tool for monitoring changes to these dynamic ecosystems. Barrier island monitoring often requires custom habitat maps due to several factors, including island size and the classification of unique geomorphology-based habitats, such as beach, dune, and barrier flats. In this study, we reviewed barrier-island-specific habitat mapping efforts and highlighted common habitat class types, source data, and mapping approaches. We also developed a framework for mapping geomorphology-based barrier island habitats using a rule-based, geographic object-based image analysis approach, which included the use of field data, tide data, high-resolution orthophotography, and lidar data. This framework integrates several barrier island mapping advancements with regard to the use of landscape position information for automated dune extraction and the use of Monte Carlo analyses for the treatment of elevation uncertainty for elevation-dependent habitats. Specifically, we used the uncertainty analyses to refine automated dune delineation based on elevation relative to extreme storm water levels and to increase the accuracy of intertidal and supratidal/upland habitat delineation. We found that dune extraction results were enhanced when elevation relative to storm water levels and visual interpretation were also applied. This framework could also be applied to beach–dune systems found along a mainland.
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Nel, Lyndre. "Riparian conservation management needs habitat quality mapping". Columella : Journal of Agricultural and Environmental Sciences 7, nr 2 (2020): 15–23. http://dx.doi.org/10.18380/szie.colum.2020.7.2.15.
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Riparian habitat quality has a significant influence on the water quality of rivers, primary resources for urban and agricultural use. River water quality deteriorates where normal ecological functioning is disrupted by harmful impacts from nearby land-use types. Important rivers are typically managed and protected by government-led conservation programs. These programs often lack a key tool for efficient conservation management, habitat quality mapping. The Berg River, an important water source in South Africa, was used as a case-study to assess how habitat quality mapping could broaden the current scope of river conservation programs. The river faces threats from nearby urban settlements, industrial areas, mining, encroachment, and agricultural practices. The aim of this study was to develop habitat quality and habitat degradation maps for a section of the Berg River to assess the value that mapping holds for conservation managers and spatial planners. InVEST modelling software and ArcGIS was used to produce these habitat quality maps based on land-use/land-cover and threat impact data. The resulting maps showed several specific locations of heavily threatened and degraded riparian habitat that had not specifically been included in current government conservation management or spatial planning. Habitat quality mapping is an important tool that conservation managers and spatial planners can use to successfully address habitat degradation and protection while facing resource limitations, such as lack of funding. Oversight of degraded riparian habitats will lead to further decreases in river water quality, adversely affecting human welfare and local economies.
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Mohamed, Hassan, Kazuo Nadaoka i Takashi Nakamura. "Semiautomated Mapping of Benthic Habitats and Seagrass Species Using a Convolutional Neural Network Framework in Shallow Water Environments". Remote Sensing 12, nr 23 (7.12.2020): 4002. http://dx.doi.org/10.3390/rs12234002.
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Benthic habitats are structurally complex and ecologically diverse ecosystems that are severely vulnerable to human stressors. Consequently, marine habitats must be mapped and monitored to provide the information necessary to understand ecological processes and lead management actions. In this study, we propose a semiautomated framework for the detection and mapping of benthic habitats and seagrass species using convolutional neural networks (CNNs). Benthic habitat field data from a geo-located towed camera and high-resolution satellite images were integrated to evaluate the proposed framework. Features extracted from pre-trained CNNs and a “bagging of features” (BOF) algorithm was used for benthic habitat and seagrass species detection. Furthermore, the resultant correctly detected images were used as ground truth samples for training and validating CNNs with simple architectures. These CNNs were evaluated for their accuracy in benthic habitat and seagrass species mapping using high-resolution satellite images. Two study areas, Shiraho and Fukido (located on Ishigaki Island, Japan), were used to evaluate the proposed model because seven benthic habitats were classified in the Shiraho area and four seagrass species were mapped in Fukido cove. Analysis showed that the overall accuracy of benthic habitat detection in Shiraho and seagrass species detection in Fukido was 91.5% (7 classes) and 90.4% (4 species), respectively, while the overall accuracy of benthic habitat and seagrass mapping in Shiraho and Fukido was 89.9% and 91.2%, respectively.
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Ostojić, Dragana, Biljana Krsteski, Zoran Stojković, Ana Petković, Bogosav Stojiljković, Ivana Jovanović i Tamara Bosić. "Composing a vegetation-stand map for the protected area of 'Radan' Nature Park". Zastita prirode 70, nr 1-2 (2020): 13–36. http://dx.doi.org/10.5937/zaspri2001013o.
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Protected areas are one of the priorities for mapping habitats, especially forest habitats, which are dominant in most protected areas of central Serbia, such as "Radan" Nature Park. This paper presents the forest habitat mapping in the protected area of "Radan" NP and the development of vegetation-stand map of the protected area in an effort to examine the methodology of forest habitats mapping in Serbia, which presumes a long term systematic data collection. Although much has been done on the classification of habitats in Serbia, considering both botanical and the forestry approach, the practical application of this knowledge in habitat mapping is still in its infancy, with the exception of longstanding practical work on data collection for Forest Management Plans for the state-owned forests. Data on forest stands in Nature Park "Radan" collected in this manner were essential to developing the vegetation-stand map of "Radan" NP. The results of data processing and harmonization of typology and classification of state-owned forests have been presented in this paper, as well as the analysis of forest habitat types in this protected area. The paper presents the vegetation-stand maps of the state-owned forests in the protected area and of the pilot area of privately owned forests, for which detailed field data collection was necessary. These maps are intended for the management of protected areas and systematic and efficient implementation of protection measures and activities. Habitat mapping in protected areas is a prerequisite for an adequate biodiversity monitoring, as well as for management and sustainable use of natural resources of the protected area.
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Valjavec, Mateja Breg, Rok Ciglič, Krištof Oštir i Daniela Ribeiro. "Modelling habitats in karst landscape by integrating remote sensing and topography data". Open Geosciences 10, nr 1 (11.06.2018): 137–56. http://dx.doi.org/10.1515/geo-2018-0011.
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Abstract Field mapping is an accurate but also time consuming method of detailed mapping of habitat types. Levels of habitat types are usually hierarchically nested at several levels. Our main research question therefore is: ‘How detailed can be modelling of habitat types with decision trees and digital data in karst landscape?’ Similar to studies in other (non-karst) environments we explored the basic properties of the habitats in Dinaric Karst study region (Classical Karst in Southwest Slovenia) and tested modelling of habitat types at three different levels of detail. To seek for the best set of predictor variables we used Rapid-Eye satellite images, airborne images and digital elevation model. We prepared more than 60 explanatory variables and divided habitat polygons into training and testing samples to validate the results. The results proved that modelling with decision trees in Dinaric Karst landscape does not result in high accuracy at high detailed levels. Due to the presence of mine fields in the large area of Dinaric Karst (e.g. in Croatia and Bosnia and Herzegovina) the field mapping in this area is difficult therefore the findings from this study can be used for further development of mapping through remote sensing.
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Astaman, I. Dewa Made Krisna Putra, I. Wayan Gede Astawa Karang, I. Gede Hendrawan i Kuncoro Teguh Setiawan. "Pemetaan Habitat Dasar Perairan Dangkal Menggunakan Citra Satelit SPOT-7 di Pulau Nusa Lembongan, Bali". Journal of Marine and Aquatic Sciences 7, nr 2 (1.12.2021): 184. http://dx.doi.org/10.24843/jmas.2021.v07.i02.p07.
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Shallow water habitat is one of the regions that has high dynamics and has an important role are ecologically and economically. The high dynamics of the ideal shallow water habitat is always followed by updating information so that an overview of the area is obtained in accordance with reality. Remote sensing technology is one of the technologies that can be used for mapping natural resource studies such as mapping of shallow water habitats with the satellite imagery. This study aims to map the distribution of shallow water habitats using SPOT-7 satellite imagery on Nusa Lembongan Island, Bali and test the level of accuracy. The method used true color composite and DII (Depth Invariant Index) transformation and uses the maximum likelihood classification. The classification scheme used 6 classes, namely sand, seagrass, macro algae, rubble, live coral, and dead coral. The results of this study indicate the distribution of shallow water habitat on Nusa Lembongan Island, Bali spread equally based on the level of water depth with a total area of shallow water habitat of 453.41 ha. The results of mapping accuracy test showed the overall accuracy of the DII transformation classification results is better than the composite image classification results with an overall accuracy of 75.43% and a kappa coefficient is 0.71. So from these results can be said that used of a water column correction with the DII method can improve image accuracy in mapping shallow water habitats.
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Foglini, Federica, Valentina Grande, Fabio Marchese, Valentina A. Bracchi, Mariacristina Prampolini, Lorenzo Angeletti, Giorgio Castellan i in. "Application of Hyperspectral Imaging to Underwater Habitat Mapping, Southern Adriatic Sea". Sensors 19, nr 10 (16.05.2019): 2261. http://dx.doi.org/10.3390/s19102261.
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Hyperspectral imagers enable the collection of high-resolution spectral images exploitable for the supervised classification of habitats and objects of interest (OOI). Although this is a well-established technology for the study of subaerial environments, Ecotone AS has developed an underwater hyperspectral imager (UHI) system to explore the properties of the seafloor. The aim of the project is to evaluate the potential of this instrument for mapping and monitoring benthic habitats in shallow and deep-water environments. For the first time, we tested this system at two sites in the Southern Adriatic Sea (Mediterranean Sea): the cold-water coral (CWC) habitat in the Bari Canyon and the Coralligenous habitat off Brindisi. We created a spectral library for each site, considering the different substrates and the main OOI reaching, where possible, the lower taxonomic rank. We applied the spectral angle mapper (SAM) supervised classification to map the areal extent of the Coralligenous and to recognize the major CWC habitat-formers. Despite some technical problems, the first results demonstrate the suitability of the UHI camera for habitat mapping and seabed monitoring, through the achievement of quantifiable and repeatable classifications.
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Ljubičić, Ivica, Helena Paulik i Sandro Bogdanović. "Habitat mapping of Protected Landscape of Donji Kamenjak, Istria (Croatia)". Journal of Central European Agriculture 21, nr 3 (2020): 676–85. http://dx.doi.org/10.5513/jcea01/21.3.2697.
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Agrillo, Emiliano, Federico Filipponi, Alice Pezzarossa, Laura Casella, Daniela Smiraglia, Arianna Orasi, Fabio Attorre i Andrea Taramelli. "Earth Observation and Biodiversity Big Data for Forest Habitat Types Classification and Mapping". Remote Sensing 13, nr 7 (24.03.2021): 1231. http://dx.doi.org/10.3390/rs13071231.
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In the light of the “Biological Diversity” concept, habitats are cardinal pieces for biodiversity quantitative estimation at a local and global scale. In Europe EUNIS (European Nature Information System) is a system tool for habitat identification and assessment. Earth Observation (EO) data, which are acquired by satellite sensors, offer new opportunities for environmental sciences and they are revolutionizing the methodologies applied. These are providing unprecedented insights for habitat monitoring and for evaluating the Sustainable Development Goals (SDGs) indicators. This paper shows the results of a novel approach for a spatially explicit habitat mapping in Italy at a national scale, using a supervised machine learning model (SMLM), through the combination of vegetation plot database (as response variable), and both spectral and environmental predictors. The procedure integrates forest habitat data in Italy from the European Vegetation Archive (EVA), with Sentinel-2 imagery processing (vegetation indices time series, spectral indices, and single bands spectral signals) and environmental data variables (i.e., climatic and topographic), to parameterize a Random Forests (RF) classifier. The obtained results classify 24 forest habitats according to the EUNIS III level: 12 broadleaved deciduous (T1), 4 broadleaved evergreen (T2) and eight needleleaved forest habitats (T3), and achieved an overall accuracy of 87% at the EUNIS II level classes (T1, T2, T3), and an overall accuracy of 76.14% at the EUNIS III level. The highest overall accuracy value was obtained for the broadleaved evergreen forest equal to 91%, followed by 76% and 68% for needleleaved and broadleaved deciduous habitat forests, respectively. The results of the proposed methodology open the way to increase the EUNIS habitat categories to be mapped together with their geographical extent, and to test different semi-supervised machine learning algorithms and ensemble modelling methods.
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Olden, Julian D., Oliver Miler i Alexander Bijaye. "Lake-wide mapping of littoral habitat using underwater videography". Knowledge & Management of Aquatic Ecosystems, nr 423 (2022): 18. http://dx.doi.org/10.1051/kmae/2022018.
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Littoral zones − referring to benthic areas above the light compensation depth − provide numerous ecosystem functions, including mediating light, temperature, and nutrient dynamics, and supporting important foraging and refuge areas for macroinvertebrates, fishes and water birds. Habitat assessments of littoral zones remain fundamental to lake and fisheries management, however traditional field surveys are time-intensive and limited in their spatial extent, whereas desktop evaluations using remote sensing and aerial imagery are cost prohibitive and require considerable data processing expertise. In light of these challenges, this study demonstrated the ability to use simple, cost-effective underwater videography to conduct lake-wide spatially-continuous assessments of littoral habitat. For lakes across a gradient of shoreline and riparian development in northwestern United States, we map the areal coverage of macrophytes, coarse woody habitat, bottom substrates, and artificial structures in littoral zones. Underwater videography represents a relevant tool for environmental monitoring because it allows for the estimation of littoral habitats at fine spatial grains across broad spatial extents. Data can also be obtained rapidly and at relatively low cost, providing a permanent record of habitat conditions that can used to monitor trends over time.
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Doukari, M., i K. Topouzelis. "UAS DATA ACQUISITION PROTOCOL FOR MARINE HABITAT MAPPING: AN ACCURACY ASSESSMENT STUDY". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (22.08.2020): 1321–26. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1321-2020.
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Abstract. Marine habitat mapping is essential for updating existing information, preserving, and protecting the marine environment. Unmanned Aerial Systems (UAS) are an important tool for monitoring and mapping coastal and marine environment because of their ability to provide very high-resolution aerial imagery.Environmental conditions have a critical role in marine mapping using UAS. This is due to the limitations of UAS surveys in coastal areas, i.e. the environmental conditions prevailing in the area. The limitations of weather and oceanographic conditions affecting the quality of marine data led to the creation of a UAS protocol for the acquisition of reliable marine information. The produced UAS Data Acquisition Protocol consists of three main categories: (i) Morphology of the study area, (ii) Environmental conditions, (iii) Flight parameters. These categories include the parameters that must be considered for marine habitat mapping.The aim of the present study is the accuracy assessment of the UAS protocol for marine habitat mapping through experimental flights. For the accuracy assessment of the UAS protocol, flights on different dates and environmental conditions were conducted, over a study area. The flight altitude was the same for all the missions, so the results were comparable. The high-resolution orthophoto maps derived from each date of the experiment were classified. The classification maps show several differences in the shape and size of the marine habitats which are directly dependent on the conditions that the habitats were mapped. A change detection comparison was conducted in pairs to examine the exact changes between the classified maps.The results emphasize the importance of the environmental conditions prevailing in an area during the mapping of marine habitats. The present study proves that the optimal flight conditions that are proposed of the UAS Data Acquisition protocol, respond to the real-world conditions and are important to be considered for an accurate and reliable mapping of the marine environment.
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Wicaksono, Pramaditya, Prama Ardha Aryaguna i Wahyu Lazuardi. "Benthic Habitat Mapping Model and Cross Validation Using Machine-Learning Classification Algorithms". Remote Sensing 11, nr 11 (29.05.2019): 1279. http://dx.doi.org/10.3390/rs11111279.
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This research was aimed at developing the mapping model of benthic habitat mapping using machine-learning classification algorithms and tested the applicability of the model in different areas. We integrated in situ benthic habitat data and image processing of WorldView-2 (WV2) image to parameterise the machine-learning algorithm, namely: Random Forest (RF), Classification Tree Analysis (CTA), and Support Vector Machine (SVM). The classification inputs are sunglint-free bands, water column corrected bands, Principle Component (PC) bands, bathymetry, and the slope of underwater topography. Kemujan Island was used in developing the model, while Karimunjawa, Menjangan Besar, and Menjangan Kecil Islands served as test areas. The results obtained indicated that RF was more accurate than any other classification algorithm based on the statistics and benthic habitats spatial distribution. The maximum accuracy of RF was 94.17% (4 classes) and 88.54% (14 classes). The accuracies from RF, CTA, and SVM were consistent across different input bands for each classification scheme. The application of RF model in the classification of benthic habitat in other areas revealed that it is recommended to make use of the more general classification scheme in order to avoid several issues regarding benthic habitat variations. The result also established the possibility of mapping a benthic habitat without the use of training areas.
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Simioni, João Paulo, Laurindo Antonio Guasselli i Tatiana Silva da Silva. "Shifting habitat mosaic: identification and mapping". Ambiente e Agua - An Interdisciplinary Journal of Applied Science 14, nr 2 (22.03.2019): 1. http://dx.doi.org/10.4136/ambi-agua.2242.
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The Shifting Habitat Mosaic refers to temporal changes in the spatial pattern of habitats, through the flood and dry pulses. This work mapped the dynamics of a Shifting Mosaic associated with the flood and dry pulses in the Environmental Protection Area of the Banhado Grande (EPABG). The research was divided into four stages: i) acquisition of satellite images; ii) obtaining rainfall river basin data from the Gravataí River; iii) identification of the flood and dry pulses; and iv) mapping of the Shifting Mosaic in the wetlands of the EPABG. In large swaths of flooding, a shifting connectivity is established between the AUs of EPABG, providing several interactions among these wetlands, such as nutrient exchange, sediments and living organisms. It was found that in periods where the accumulation of precipitation in the last 30 days is greater than 200 mm, we have the presence of predominantly aquatic mosaic with the presence of predominantly aquatic animals and vegetation; In periods where the cumulative precipitation in the 30 days is less than 200 mm, a terrestrial mosaic predominates, with increase of ciliary vegetation.
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Amani, Meisam, Candace Macdonald, Abbas Salehi, Sahel Mahdavi i Mardi Gullage. "Marine Habitat Mapping Using Bathymetric LiDAR Data: A Case Study from Bonne Bay, Newfoundland". Water 14, nr 23 (23.11.2022): 3809. http://dx.doi.org/10.3390/w14233809.
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Marine habitats provide various benefits to the environment and humans. In this regard, an accurate marine habitat map is an important component of effective marine management. Newfoundland’s coastal area is covered by different marine habitats, which should be correctly mapped using advanced technologies, such as remote sensing methods. In this study, bathymetric Light Detection and Ranging (LiDAR) data were applied to accurately discriminate different habitat types in Bonne Bay, Newfoundland. To this end, the LiDAR intensity image was employed along with an object-based Random Forest (RF) algorithm. Two types of habitat classifications were produced: a two-class map (i.e., Vegetation and Non-Vegetation) and a five-class map (i.e., Eelgrass, Macroalgae, Rockweed, Fine Sediment, and Gravel/Cobble). It was observed that the accuracies of the produced habitat maps were reasonable considering the existing challenges, such as the error of the LiDAR data and lacking enough in situ samples for some of the classes such as macroalgae. The overall classification accuracies for the two-class and five-class maps were 87% and 80%, respectively, indicating the high capability of the developed machine learning model for future marine habitat mapping studies. The results also showed that Eelgrass, Fine Sediment, Gravel/Cobble, Macroalgae, and Rockweed cover 22.4% (3.66 km2), 51.4% (8.39 km2), 13.5% (2.21 km2), 6.9% (1.12 km2), and 5.8% (0.95 km2) of the study area, respectively.
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Kwong, Ivan H. Y., Frankie K. K. Wong, Tung Fung, Eric K. Y. Liu, Roger H. Lee i Terence P. T. Ng. "A Multi-Stage Approach Combining Very High-Resolution Satellite Image, GIS Database and Post-Classification Modification Rules for Habitat Mapping in Hong Kong". Remote Sensing 14, nr 1 (24.12.2021): 67. http://dx.doi.org/10.3390/rs14010067.
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Identification and mapping of various habitats with sufficient spatial details are essential to support environmental planning and management. Considering the complexity of diverse habitat types in a heterogeneous landscape, a context-dependent mapping framework is expected to be superior to traditional classification techniques. With the aim to produce a territory-wide habitat map in Hong Kong, a three-stage mapping procedure was developed to identify 21 habitats by combining very-high-resolution satellite images, geographic information system (GIS) layers and knowledge-based modification rules. In stage 1, several classification methods were tested to produce initial results with 11 classes from a WorldView-2/3 image mosaic using a combination of spectral, textural, topographic and geometric variables. In stage 2, modification rules were applied to refine the classification results based on contextual properties and ancillary data layers. Evaluation of the classified maps showed that the highest overall accuracy was obtained from pixel-based random forest classification (84.0%) and the implementation of modification rules led to an average 8.8% increase in the accuracy. In stage 3, the classification scheme was expanded to all 21 habitats through the adoption of additional rules. The resulting habitat map achieved >80% accuracy for most of the evaluated classes and >70% accuracy for the mixed habitats when validated using field-collected points. The proposed mapping framework was able to utilize different information sources in a systematic and controllable workflow. While transitional mixed habitats were mapped using class membership probabilities and a soft classification method, the identification of other habitats benefited from the hybrid use of remote-sensing classification and ancillary data. Adaptive implementation of classification procedures, development of appropriate rules and combination with spatial data are recommended when producing an integrated and accurate map.
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Harvey, Kylie R., i Greg J. E. Hill. "Mapping the nesting habitats of saltwater crocodiles (Crocodylus porosus) in Melacca Swamp and the Adelaide River wetlands, Northern Territory: an approach using remote sensing and GIS". Wildlife Research 30, nr 4 (2003): 365. http://dx.doi.org/10.1071/wr00008.
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The utility of integrating remotely sensed data and other spatial information in a geographical information system (GIS) to model habitat suitability for nesting by saltwater crocodiles (Crocodylus porosus) was investigated in this study. The study areas, Melacca Swamp and the Adelaide River wetlands, are located 50 km east of Darwin, Northern Territory, and encompass areas of suitable nesting habitat for C. porosus. Melacca Swamp is a highly productive nesting area and is managed as a conservation reserve to protect its nesting habitat. Landsat TM, SPOT satellite imagery and large-scale colour aerial photography were evaluated for their utility in mapping habitats preferred for nesting by C. porosus within Melacca Swamp. Satellite imagery was capable of identifying generalised habitat classes used for nesting (e.g. open swamp with emergent trees). However, it was only with aerial photography that habitats could be discerned (e.g. sedges with scattered Melaleuca trees). Spatial information derived from satellite imagery and other sources was integrated in a GIS to model potentially suitable nesting habitat along the Adelaide River. This methodology effectively identified known preferred nesting areas of C. porosus on the basis of the analysis of environmental parameters (i.e. distance to water, vegetation type) that have an influence on selection of nesting habitat. The findings of this research demonstrate the utility of remote sensing and GIS for mapping nesting habitat of C. porosus at a range of scales and provide guidelines for application of the approaches used at the regional or State level.
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Siffert, Océane, Jérôme Pellet, Petra Ramseier, Ursina Tobler, Ariel Bergamini i Benedikt R. Schmidt. "Where Land and Water Meet: Making Amphibian Breeding Sites Attractive for Amphibians". Diversity 14, nr 10 (4.10.2022): 834. http://dx.doi.org/10.3390/d14100834.
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The protection of wetlands is a cornerstone in the conservation of pond-breeding amphibians. Because protected wetlands are rarely natural areas, but are often man-made, at least in Europe, it is important that they are well managed to fulfill their intended function. Appropriate management requires knowledge of the ecology of the species, particularly habitat requirements. Here, we combine species monitoring data and habitat mapping data in an analysis where our goal was to describe the factors that determine the occupancy of amphibian species in federally protected amphibian breeding sites. As expected, every species had its own habitat requirements, often a combination of both a terrestrial and aquatic habitat (i.e., landscape complementation). In most species, occupancy was strongly positively affected with the amount of aquatic habitat, but predicted occupancy probabilities were low because the amount of aquatic habitat was low in most sites. The area or proportion of ruderal vegetation also had positive effects on multiple species, while other types of terrestrial habitat (e.g., meadows) led to low occupancy probabilities. The total area of the protected breeding sites was never included in a final model and connectivity was important only for one species (Triturus cristatus). The latter finding implies that the quality of the landscape between breeding sizes is more important than distance per se, while the former implies that the area of some specific habitats within breeding sites is crucial for high occupancies. Thus, increasing the amount of aquatic habitats and likewise terrestrial habitats within protected areas would make them more likely to achieve their conservation objectives. Our study is an example of how the joint analysis of monitoring data and habitat data (based on mapping in the field) can lead to evidence-based suggestions on how to improve conservation practice.
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Subarno, Tarlan, Vincentius Paulus Siregar i Syamsul Bahri Agus. "OBIA AND BTM INTEGRATION FOR MAPPING HABITAT COMPLEXITY OF CORAL REEFS ON HARAPAN-KELAPA ISLANDS, KEPULAUAN SERIBU". Coastal and Ocean Journal (COJ) 2, nr 1 (10.05.2018): 11–22. http://dx.doi.org/10.29244/coj.2.1.11-22.
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The habitat complexity is indirectly closely related to reef fish abundance. This study aims to map reefs habitat complexity by integrating object-based image analysis (OBIA) and habitat complexity analysis using benthic terrain modeler (BTM). The datasets used were SPOT-7 imagery and water depth derived from satellite imagery. The ground check was conducted to collect field data used as reference for classification and accuracy assessment of classification results. Classification of SPOT-7 imagery was performed using support vector machines (SVM) algorithm, by grouping shallow waters habitats into 4 classes on level 2 and 3 classes on level 3. Accuracy assessment was done by confusion matrix and resulting overall accuracy (OA) 83.55% for level 2 and 79.66% for level 3. The habitat complexity was analyzed using rugosity analysis method (Arc-Chord Ratio) from benthic terrain modeler (BTM) to obtain rugosity index in reefs area. The substrate covers were obtained from OBIA and complexity of habitats were obtained from BTM, then the overlay result shows varying rugosity index on the reef area in Harapan-Kelapa Islands.
Keywords:
coral reefs, OBIA, habitat complexity, rugosity
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Tentelier, Cédric, Nicolas Larranaga, Olivier Lepais, Aurélie Manicki, Jacques Rives i Frédéric Lange. "Space use and its effects on reproductive success of anadromous Atlantic salmon". Canadian Journal of Fisheries and Aquatic Sciences 73, nr 10 (październik 2016): 1461–71. http://dx.doi.org/10.1139/cjfas-2015-0518.
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We combined habitat mapping, radio tracking of adults, redd mapping, and genetic parentage analysis on juveniles for 2 consecutive years to test eight predictions on the reproductive payoffs and individual features associated with space use tactics of anadromous Atlantic salmon (Salmo salar) in a natural population. Regarding payoffs, we found that (1) males settled in better habitat, visited more redds, and tended to get more mates than males settled in poorer habitat; (2) they also sired more offspring; (3) the latter effect was stronger in the first year, when redds were more aggregated; and (4) female reproductive success increased with habitat quality in their home range, especially in the first year. For individual features, (5) individuals that settled earlier in their home range had better habitat for juvenile production, but only in the first year; (6) females were less mobile than males, especially in the second year; (7) larger males did not settle in better habitats than smaller males; and (8) smaller males were not more mobile than larger males.
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Ilich, Alexander R., Jennifer L. Brizzolara, Sarah E. Grasty, John W. Gray, Matthew Hommeyer, Chad Lembke, Stanley D. Locker i in. "Integrating Towed Underwater Video and Multibeam Acoustics for Marine Benthic Habitat Mapping and Fish Population Estimation". Geosciences 11, nr 4 (13.04.2021): 176. http://dx.doi.org/10.3390/geosciences11040176.
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The west Florida shelf (WFS; Gulf of Mexico, USA) is an important area for commercial and recreational fishing, yet much of it remains unmapped and unexplored, hindering effective monitoring of fish stocks. The goals of this study were to map the habitat at an intensively fished area on the WFS known as “The Elbow”, assess the differences in fish communities among different habitat types, and estimate the abundance of each fish taxa within the study area. High-resolution multibeam bathymetric and backscatter data were combined with high-definition (HD) video data collected from a near-bottom towed vehicle to characterize benthic habitat as well as identify and enumerate fishes. Two semi-automated statistical classifiers were implemented for obtaining substrate maps. The supervised classification (random forest) performed significantly better (p = 0.001; α = 0.05) than the unsupervised classification (k-means clustering). Additionally, we found it was important to include predictors at a range of spatial scales. Significant differences were found in the fish community composition among the different habitat types, with both substrate and vertical relief found to be important with rock substrate and higher relief areas generally associated with greater fish density. Our results are consistent with the idea that offshore hard-bottom habitats, particularly those of higher vertical relief, serve as “essential fish habitat”, as these rocky habitats account for just 4% of the study area but 65% of the estimated total fish abundance. However, sand contributes 35% to total fish abundance despite comparably low densities due to its large area, indicating the importance of including these habitats in estimates of abundance as well. This work demonstrates the utility of combining towed underwater video sampling and multibeam echosounder maps for habitat mapping and estimation of fish abundance.
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Hamidah, M., R. A. Pasaribu i F. A. Aditama. "Benthic habitat mapping using Object-Based Image Analysis (OBIA) on Tidung Island, Kepulauan Seribu, DKI Jakarta". IOP Conference Series: Earth and Environmental Science 944, nr 1 (1.12.2021): 012035. http://dx.doi.org/10.1088/1755-1315/944/1/012035.
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Abstract Tidung Island is one of the islands in Kepulauan Seribu, DKI Jakarta, Indonesia. This island has various benthic that live on the coastal areas, and benthic habitat has various functions both ecologically and economically. Nowadays, remote sensing technology is one way to detect benthic habitats in coastal areas. Mapping benthic habitat is essential for sustainable coastal resource management and to predict the distribution of benthic organisms. This study aims to map the benthic habitats using the object-based image analysis (OBIA) and calculate the accuracy of benthic habitat classification results in Tidung Island, Kepulauan Seribu, DKI Jakarta. The field data were collected on June 2021, and the image data used is satellite Sentinel-2 imagery acquired in June 2021. The result shows that the benthic habitat classification was produced in 4 classes: seagrass, rubble, sand, and live coral. The accuracy test result obtained an overall accuracy (OA) of 74.29% at the optimum value of the MRS segmentation scale 15;0,1;0.7 with the SVM algorithm. The results of benthic habitat classification show that the Seagrass class dominates the shallow water area at the research site with an area of 118.77 ha followed by Life Coral 104.809 ha, Sand 43.352 ha, and the smallest area is the Rubble class of 42.28 Ha.
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Hafizt, Muhammad, Marindah Yulia Iswari i Bayu Prayudha. "Kajian Metode Klasifikasi Citra Landsat-8 untuk Pemetaan Habitat Bentik di Kepulauan Padaido, Papua". Oseanologi dan Limnologi di Indonesia 2, nr 1 (5.05.2017): 1. http://dx.doi.org/10.14203/oldi.2017.v2i1.69.
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<strong>Assessment of Landsat-8 Classification Method for Benthic Habitat Mapping in Padaido Islands, Papua.</strong> Indonesia is the biggest archipelagic country in the world with an area of coral reefs of 39,583 km.This area has to be managed effectively and efficiently utilizing satellite remote sensing technique capable of mapping of benthic habitat coverage, such as coral reefs, seagrasses, macroalgae, and bare substrates. The technique is supported by the availability of Landsat-8 OLI satellite images that have been recording the regions of Indonesia continuously every 16 days. This research was carried out in June 2015 in parts of Padaido Islands, Papua. This area was selected due to high coral reef damages. This study utilized Landsat-8 OLI to compare two classification methods, namely pixel based and object based methods using ‘maximum 2 likelihood’ (ML) and ‘example based feature extraction’ classifications, respectively, after water column correction (Lyzenga method). The results showed that both methods produced benthic habitat maps with 7 class covers. The pixel-based classification resulted in a better overall accuracy (47.57%) in the mapping of benthic habitats than object-based classification approach (36.17%). Thus, the ML classification is applicable for benthic habitat mapping in Padaido Islands. However, the consistency of this method must be analyzed in many diffrent locations of Indonesian waters.
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Zhang, W., B. Hu i M. Woods. "Mapping forest stand complexity for woodland caribou habitat assessment using multispectral airborne imagery". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2 (11.11.2014): 179–85. http://dx.doi.org/10.5194/isprsarchives-xl-2-179-2014.
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The decline of the woodland caribou population is a result of their habitat loss. To conserve the habitat of the woodland caribou and protect it from extinction, it is critical to accurately characterize and monitor its habitat. Conventionally, products derived from low to medium spatial resolution remote sensing data, such as land cover classification and vegetation indices are used for wildlife habitat assessment. These products fail to provide information on the structure complexities of forest canopies which reflect important characteristics of caribou’s habitats. Recent studies have employed the LiDAR system (Light Detection And Ranging) to directly retrieve the three dimensional forest attributes. Although promising results have been achieved, the acquisition cost of LiDAR data is very high. In this study, utilizing the very high spatial resolution imagery in characterizing the structural development the of forest canopies was exploited. A stand based image texture analysis was performed to predict forest succession stages. The results were demonstrated to be consistent with those derived from LiDAR data.
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Li, Jiwei, Steven R. Schill, David E. Knapp i Gregory P. Asner. "Object-Based Mapping of Coral Reef Habitats Using Planet Dove Satellites". Remote Sensing 11, nr 12 (18.06.2019): 1445. http://dx.doi.org/10.3390/rs11121445.
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High spatial resolution benthic habitat information is essential for coral reef protection and coastal environmental management. Satellite-based shallow benthic composition mapping offers a more efficient approach than traditional field measurements, especially given the advancements in high spatial and temporal resolution satellite imagery. The Planet Dove satellite constellation now has more than 150 instruments in orbit that offer daily coverage at high spatial resolution (3.7 m). The Dove constellation provides regularly updated imagery that can minimize cloud in tropical oceans where dense cloud cover persists. Daily image acquisition also provides an opportunity to detect time-sensitive changes in shallow benthic habitats following coral bleaching events, storms, and other disturbances. We developed an object-based coral reef habitat mapping approach for Dove and similar multispectral satellites that provides bathymetry estimation, bottom reflectance retrieval, and object-based classification to identify different benthic compositions in shallow coastal environments. We tested our approach in three study sites in the Dominican Republic using 18 Dove images. Benthic composition classification results were validated by field measurements (overall accuracy = 82%). Bathymetry and bottom reflectance significantly contributed to identifying benthic habitat classes with similar surface reflectance. This new object-based approach can be effectively applied to map and manage coral reef habitats.
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Sundblad, Göran, Ulf Bergström, Alfred Sandström i Peter Eklöv. "Nursery habitat availability limits adult stock sizes of predatory coastal fish". ICES Journal of Marine Science 71, nr 3 (18.04.2013): 672–80. http://dx.doi.org/10.1093/icesjms/fst056.
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Abstract Habitat protection is a strategy often proposed in fisheries management to help maintain viable populations of exploited species. Yet, quantifying the importance of habitat availability for population sizes is difficult, as the precise distribution of essential habitats is poorly known. To quantify the contribution from coastal nursery habitats to exploited fish population sizes, we related adult density to the amount of nursery habitat available for 12 populations of the two dominant predatory fish species in a 40 000-km2 archipelago area of the Baltic Sea. Habitat distribution was mapped using three conceptually different techniques, Maxent, generalized additive models, and random forest, using spawning and 0-group point samples. Adult densities were estimated from gillnet surveys. Regressions demonstrated no evident effect from fishing, whereas habitat availability had a positive effect, explaining almost half of the variation in population sizes of both species. This result shows that a substantial proportion of the potential production of adult fish can be estimated by mapping essential nursery habitats distribution. Responses were non-linear, indicating that habitat protection has largest effects where there is little available habitat. By demonstrating the importance of habitat limitation of two exploited fish species, we provide quantitative support to the benefits of habitat protection for fisheries.
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Nababan, Bisman, La Ode Khairum Mastu, Nurul Hazrina Idris i James P. Panjaitan. "Shallow-Water Benthic Habitat Mapping Using Drone with Object Based Image Analyses". Remote Sensing 13, nr 21 (5.11.2021): 4452. http://dx.doi.org/10.3390/rs13214452.
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Spatial information on benthic habitats in Wangiwangi island waters, Wakatobi District, Indonesia was very limited in recent years. However, this area is one of the marine tourism destinations and one of the Indonesia’s triangle coral reef regions with a very complex coral reef ecosystem. The drone technology that has rapidly developed in this decade, can be used to map benthic habitats in this area. This study aimed to map shallow-water benthic habitats using drone technology in the region of Wangiwangi island waters, Wakatobi District, Indonesia. The field data were collected using a 50 × 50 cm squared transect of 434 observation points in March–April 2017. The DJI Phantom 3 Pro drone with a spatial resolution of 5.2 × 5.2 cm was used to acquire aerial photographs. Image classifications were processed using object-based image analysis (OBIA) method with contextual editing classification at level 1 (reef level) with 200 segmentation scale and several segmentation scales at level 2 (benthic habitat). For level 2 classification, we found that the best algorithm to map benthic habitat was the support vector machine (SVM) algorithm with a segmentation scale of 50. Based on field observations, we produced 12 and 9 benthic habitat classes. Using the OBIA method with a segmentation value of 50 and the SVM algorithm, we obtained the overall accuracy of 77.4% and 81.1% for 12 and 9 object classes, respectively. This result improved overall accuracy up to 17% in mapping benthic habitats using Sentinel-2 satellite data within the similar region, similar classes, and similar method of classification analyses.
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Bekkby, Trine, i Martin Isæus. "Mapping large, shallow inlets and bays: modelling a Natura 2000 habitat with digital terrain and wave-exposure models". ICES Journal of Marine Science 65, nr 2 (1.03.2008): 238–41. http://dx.doi.org/10.1093/icesjms/fsn005.
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Abstract Bekkby, T., and Isæus, M. 2008. Mapping large, shallow inlets and bays: modelling a Natura 2000 habitat with digital terrain and wave-exposure models. – ICES Journal of Marine Science, 65: 238–241. EU member countries are obliged to protect a certain share of Natura 2000 habitats. Hence, these habitats must be mapped. This paper is an attempt to provide a tool for modelling one of the Natura 2000 habitat, the “large shallow inlets and bays” (Natura 2000 habitat 1160), using a Norwegian archipelagic area as a case study. The Natura 2000 definition of the habitat is interpreted into criteria used for modelling, and a spatial prediction is presented on a map. The effect of scale, regarding both spatial resolution of data and methodology, is also tested. This is the first publicly accessible attempt to model the Natura 2000 habitat. It shows that the result of the modelling depends on the spatial resolution of the data and the methods used in the modelling process. Using data at a 10-m and a 25-m resolution provides good results, and even the model based on the 50-m data provided an acceptable overall picture.
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Cotsell, Nigel, Mark Fisher, David Scotts i Mark Cameron. "Identifying High Value Arboreal Habitat in forested areas using high-resolution digital imagery". Pacific Conservation Biology 22, nr 4 (2016): 367. http://dx.doi.org/10.1071/pc15031.
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Old-growth forest is recognised as a high-value habitat in conservation assessment programs because of its importance to hollow-dependent species. Previous mapping undertaken at regional scales does not map patches of old forest smaller than 5 ha. While small patches of old forest may not be as ecologically important as large areas they provide opportunities for connectivity and specific habitat resources for arboreal wildlife within a broader landscape matrix. Previously, smaller patches of old forest have been overlooked because the tools have not been available to map at finer scales. This study incorporates a methodology using recent advances in technology, including aerial photography, to map old forest at a fine scale for the purposes of land-use assessment and planning. The term ‘High Value Arboreal Habitat’ is introduced to convey the ecological importance of hollow-bearing trees as part of a wider identification and mapping of high-value habitats across the landscape. The assessment was undertaken across the forested areas of the Coffs Harbour Local Government Area using high-resolution digital imagery. It is anticipated that the High Value Arboreal Habitat mapping process will be adopted by a range of stakeholders and natural resource managers to better manage and conserve these old forests across the landscape whatever their size.
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Lavrinenko, I. A. "Approaches of european ecologists to typology and mapping of habitats". Geobotanical mapping, nr 2020 (grudzień 2020): 51–77. http://dx.doi.org/10.31111/geobotmap/2020.51.
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The presence of appropriate habitats is a necessary condition for the existence of flora and fauna. In recent decades, it has become obvious that monitoring of a state not only populations of rare species, and, first, habitats which for a biota are vital, is necessary (Galdenzi et al., 2012; Rodríguez et al., 2012; Izco, 2015; Keith et al., 2015; etc.). The paper discusses the main European programs and projects devoted to the classification, mapping and inventory of habitats, the formation of lists of biotopes in need of protection (Berne Convention, Habitats Directive, Nature 2000, CORINE, EUNIS, etc.). The implementation of these projects makes a significant contribution to the state environmental policy of European countries. Since the Berne Convention for the Conservation of European Wildlife and Natural Habitats, adopted in 1979 and to date, great importance has been given to the protection of natural habitats in the countries of the European Union. Given their diversity, the most important tasks of diagnostics and monitoring of habitats were the development of classification schemes, inventory and allocation of biotopes that require protection. In 1985, the European Commission initiated the CORINE (Coordination of Information on the Environment) project on the inventory of habitats or biotopes. Its main goal was information support for pan-European and national policies in the field of environmental management, control of their consequences and the proposal of corrective measures. The CORINE habitat classification was first published in 1991 and served as the basis for the selection of habitats listed in Annex I of the 1992 (EU Habitat Directive 92/43/EEC). Since the adoption of this document, known as the “Habitats Directive”, there has been a turning point in the EU in the prospects for the management of biological diversity and the transition of scientific research in the field of ecology and nature protection to a qualitatively new level. Annex I lists 233 European types of natural habitats, including 71 priority ones, that are at risk of extinction and whose natural areas mainly distributed into the EU. The most important achievement of the Habitats Directive is the creation of a network of protected areas in Europe, known as Natura 2000, the world’s largest ecological network created to protect the rarest and most endangered species of plants, animals and habitats in Europe. Natura 2000 is not a Specially Protected Natural Areas system, but also includes all EU protected areas, although most of the land in this network is privately owned. EU member States have an obligation to ensure the sustainable management of all Natura 2000 facilities, regardless of ownership, both environmentally and economically. In 1995, the International Seminar in Paris recognized the need to develop an improved European classification. Since that time, the development of the EUNIS (European Union Nature Information System) habitat classification has begun. This classification covers all European habitats: marine, terrestrial and freshwater, natural, semi-natural and anthropogenic and is currently one of the main systems developed for the study and protection of European Union habitats. Despite its shortcomings, EUNIS serves as a pan-European integration system with certain standards for the identification and characterization of habitats. It ensures comparability between national and international classifications. The system provides extensive opportunities to establish relationships (crosswalks) of habitat categories with other pan-European (Habitat Directive, NATURE 2000, CORINE, Palaearctic Habitats) and national classifications. Approaches to mapping habitats at different scales are considered — display on the map physiognomically and topographically expressed territorial units of vegetation using remote sensing, reflecting the ecological characteristics and originality of the earth’s surface. It is noted that the diagnostics and inventory of habitats, their mapping are based, first of all, on the materials of geobotanical mapping. The mapping of habitat types and categories can be presented at different scales. For inventory and monitoring purposes, large-scale mapping is most widely used, which is based on the allocation and diagnosis of territorial units of vegetation. A review of several dozen European projects showed that the scale from 1 : 5 000 to 1 : 50 000 is mainly used to display habitat types on the map (Terrestrial ..., 2014). A smaller scale is used to map the distribution of individual habitat types and categories within wide areas. In this case, a grid with cells of different sizes (from 1 to 10 km2) is often used. One of the main tasks in the study and evaluation of the current state of habitats is the identification and organization of monitoring of biotopes that are under the threat of degradation or complete disappearance under the impact, first of all, of human activities. For this purpose, pan-European and national Red Lists of Habitats are being created, which are taken into account in the development plans of the territories of the EU countries. The problems of classification, mapping and inventory of habitats, the preparation of Red Lists of Habitats are currently among the priority areas of environmental science and make a significant contribution to the state environmental policy of the EU countries. The high efficiency of this approach at all levels, from municipal to European, is evidenced by the large number of programs implemented in Europe in the last decade, which were funded both at the national and EU level. Considering that such an approach underlies the formation of an environmentally oriented economy and environmental protection activities in many European countries, it seems promising to implement it in the Russian Federation and, first of all, for the Arctic, as the territory most vulnerable to the impact of anthropogenic and climatic factors. This region is currently experiencing a significant anthropogenic impact due to the development of dozens of hydrocarbon deposits, the construction of industrial facilities and infrastructure elements, and numerous oil and gas pipelines. At the same time, the Russian Arctic is a territory of high concentration of species of biota in need of protection, numerous populations of waterfowl and mammals (polar bear, walrus), many of which have international protection status. Due to the high sensitivity to anthropogenic and climatic factors, not only individual protected areas, but the entire territory of the Russian Arctic should be under constant control by the state. In the context of industrial development of Arctic territories, it is necessary to monitor the state not only of populations of certain species of plants and animals in need of protection, but especially habitats that are vital to them. Among the top-priority tasks is the preparation of a list of habitats in the Russian Arctic requiring constant control and protection by the state (Red List of Russian Arctic Habitats). These include areas of concentration of populations of Red Data Book species, the most important resource species and species that are of high importance for maintaining homeostasis and supporting the potential of Arctic ecosystems. The creation of such a list will significantly complement the system of protected areas in the Arctic, since it will allow taking into account and monitoring the state of not only the natural complexes of the existing reserves, but also habitats outside this system, which are of great importance for the preservation of arctic ecosystems and biota. Giving them the status of protected areas of a certain rank, given their multiplicity and dispersion in the territory, is certainly impractical. However, when planning economic activities, special attention will need to be paid to the presence of Red List Habitats and to monitor their condition. The latter, taking into account Remote Sensing technologies, is now quite feasible, and allows for large-scale monitoring in such a vast area.
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Strong, James Asa, Annika Clements, Helen Lillis, Ibon Galparsoro, Tim Bildstein i Roland Pesch. "A review of the influence of marine habitat classification schemes on mapping studies: inherent assumptions, influence on end products, and suggestions for future developments". ICES Journal of Marine Science 76, nr 1 (14.11.2018): 10–22. http://dx.doi.org/10.1093/icesjms/fsy161.
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Abstract The production of marine habitat maps typically relies on the use of habitat classification schemes (HCSs). The choice of which HCS to use for a mapping study is often related to familiarity, established practice, and national desires. Despite a superficial similarity, HCSs differ greatly across six key properties, namely, purpose, environmental and ecological scope, spatial scale, thematic resolution, structure, and compatibility with mapping techniques. These properties impart specific strengths and weaknesses for each HCS, which are subsequently transferred to the habitat maps applying these schemes. This review has examined seven HCSs (that are commonly used and widely adopted for national and international mapping programmes), over the six properties, to understand their influence on marine habitat mapping. In addition, variation in how mappers interpret and apply HCSs introduces additional uncertainties and biases into the final maps. Recommendations are provided for improving HCSs for marine habitat mapping as well as for enhancing the working practices of mappers using habitat classification. It is hoped that implementation of these recommendations will lead to greater certainty and usage within mapping studies and more consistency between studies and adjoining maps.
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Yebeyen, Dagnew, Sileshi Nemomissa, Binyam Tesfaw Hailu, Worku Zewdie, Gudeta W. Sileshi, Rosana López Rodríguez i Tefera M. Woldie. "Modeling and Mapping Habitat Suitability of Highland Bamboo under Climate Change in Ethiopia". Forests 13, nr 6 (31.05.2022): 859. http://dx.doi.org/10.3390/f13060859.
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Highland bamboo (Oldeania alpina formerly Arundinaria alpina or Yushania alpina) is a species of significant conservation value in Afromontane ecosystems across Africa. It also plays a significant role in the livelihoods of local communities. However, global climate change is anticipated to alter its ecological niche, leading to range shifts and possible habitat contractions. This study aimed to identify potentially suitable habitats for highland bamboo in Ethiopia, determine the resilience of the species under climate change, and establish the environmental factors affecting its habitat. Species distribution modeling (SDM) was implemented in the SDM R package using 231 georeferenced presence records together with climate, topographic, and soil data. To assess climate change risks to the species, predictive models were developed assuming climate scenarios for 2061–2080 under two shared socio-economic pathways (SSPs), namely, SSP2-45 and SSP5-85. The results indicated that highland bamboo mainly grows in high elevation areas with altitudes of 2100–3100 m asl with mean annual temperatures of 11.5–19.3 °C, annual precipitation of 873–1962 mm, precipitation of the driest quarter of 36–147 mm, soil pH of 5.6, and soil CEC of 30.7 cmolc/kg. The current potentially suitable habitat for this species in Ethiopia was estimated at 61,831.58 km2, with the majority of habitats being in the southern and southwestern parts of the country. Our models predicted that the suitable habitat will shrink by 13.4% under the SSP5-85 scenario, while potential new suitable areas for this species were identified under the SSP2-45 scenario. Future vulnerable areas were mostly found in central Ethiopia. Based on the predictions, we conclude that most of the suitable habitats for highland bamboo will remain suitable between the years 2061 and 2080.
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Alifatri, La Ode, Bayu Prayudha i Kasih Anggraini. "Klasifikasi Habitat Bentik Berdasarkan Citra Sentinel-2 di Kepulauan Kei, Maluku Tenggara". Jurnal Ilmu Pertanian Indonesia 27, nr 3 (1.07.2022): 372–84. http://dx.doi.org/10.18343/jipi.27.3.372.
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Imagery classification has long been used in analyzing remote sensing data. The use of the classification algorithm model can affect the results in interpreting benthic habitats in shallow water. This study aimed to determine the best classification algorithm model for mapping benthic habitat cover through Sentinel-2 satellite imagery. Three algorithm models were employed: Maximum Likelihood Classification (MLC), Minimum Distance Classification (MDC), and Mahalanobis Distance Classification (MaDC). The benthic habitat types were extracted using Lyzenga correction, giving three categories: coral, seagrass, and sand. The results showed that the application algorithm models of the MLC, MDC, and MaDC on the benthic habitat mapping resulted in an accuracy value that was not significantly different at the 95% confidence interval. However, of the three algorithms used, the MaDC algorithm provides the best results in overall accuracy (78.35%) than the MDC (74.45%) and the MLC (74.33%). It shows that the MaDC algorithm can be referred to as the mapped benthic habitat cover in the Kei Islands. However, this algorithm model needs to be continuously studied and compared to other models in other locations.
Keywords: benthic, habitat classification, Kei Islands, sentinel
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Bullimore, Ross D., Nicola L. Foster i Kerry L. Howell. "Coral-characterized benthic assemblages of the deep Northeast Atlantic: defining “Coral Gardens” to support future habitat mapping efforts". ICES Journal of Marine Science 70, nr 3 (23.01.2013): 511–22. http://dx.doi.org/10.1093/icesjms/fss195.
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Abstract Bullimore, R. D., Foster, N. L., and Howell, K. L. 2013. Coral-characterized benthic assemblages of the deep Northeast Atlantic: defining “Coral Gardens” to support future habitat mapping efforts – ICES Journal of Marine Science, 70: 511–522. Providing statistically robust maps of habitat distributions on which to base spatial planning and management of the marine area is reliant upon established and agreed descriptions and definitions of habitats. “Coral Gardens” is an Oslo–Paris Convention (OSPAR) listed habitat, which currently cannot be reliably mapped as a result of poorly developed deep-sea habitat classification systems and habitat definitions. The aim of this study is to assess and inform development of the current definition of this habitat to support future mapping efforts. This study uses multivariate community analysis of video data to identify deep-sea benthic assemblages characterized by coral taxa and thus constituting a potential “coral gardens” habitat. Assemblages are assessed against a set of qualifying criteria, derived from current definitions of “coral gardens”, first at the assemblage level then sample by sample. The current definition of “coral gardens” captures a range of benthic assemblages, thus “Coral Gardens” cannot be considered a single “habitat”. While 19 assemblages are identified as being characterized by one or more coral garden taxa, only 8 meet the qualifying criteria. It is suggested that the current definition incorporates descriptions of the different “Coral Gardens” assemblages together with guidance on threshold densities for coral species specific to each assemblage type.
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Lisson, Amanda, Kathryn H. Taffs i Leslie Christidis. "Mapping foraging habitat for migratory shorebirds in their Australian non-breeding grounds and prioritising sites for conservation and management". Pacific Conservation Biology 23, nr 1 (2017): 32. http://dx.doi.org/10.1071/pc16011.
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Shorebird populations are declining worldwide as a result of the loss of the intertidal habitats upon which they depend. Conservation status is particularly dire for shorebirds on the East Asian–Australasian Flyway. While the flyway transects many international boundaries and involves numerous bilateral conservation agreements, management of remaining habitat at a local scale is imperative to conserving these species. Coastal habitat is affected by multiple anthropogenic stressors, including loss and degradation due to increasing demand for coastal land. In Australia, migration coincides with the summer holiday season when shorebirds are significantly impacted by human disturbance. Managers are frequently required to make trade-offs between wildlife conservation and anthropogenic land uses and when specific quantitative shorebird habitat data and mapping are absent, human interests will naturally take precedence. This paper demonstrates a method for mapping and prioritising management of shorebird non-breeding habitat using an Australian coastal site, the Richmond River estuary. Foraging habitat was surveyed and mapped using GIS with a range of attributes including habitat types, foraging values, disturbance levels and specific foraging distribution of each species. The results highlighted several important foraging areas that were impacted by disturbance and would require intervening management actions to reduce impacts on shorebirds. The GIS data created provide local managers with an effective tool to consider shorebird habitat in the decision-making process. This method could be replicated at other important shorebird habitat sites, leading to enhanced conservation of these declining species.
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Rahmani, Elvita, I. Wayan Gede Astawa Karang i I. Dewa Nyoman Nurweda Putra. "Pemetaan Habitat Bentik Menggunakan Citra Sentinel-2A dan Unmanned Aerial Vehicle (UAV) di Perairan Pemuteran, Bali". Journal of Marine Research and Technology 5, nr 1 (28.02.2022): 29. http://dx.doi.org/10.24843/jmrt.2022.v05.i01.p06.
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The benthic habitat has a huge ecological and economic role in the sustainability of the coastal environment and is vulnerable to change. The importance of the existence of the benthic habitat requires identification and monitoring of the habitat's existence and status. One of the technologies that can be utilized is remote sensing technology, which is able to provide solutions to the limitations of conventional methods, such as time that is relatively long, costly, and difficult to reach remote and risky areas. Selection of sensing vehicles takes into consideration the needs and desired qualities because the sensors brought in to detect habitats have different abilities. Sentinel-2A imagery is an open-source satellite with a 10 m spatial resolution capability, while the image from Unmanned Aerial Vehicle (UAV) has a high spatial resolution of up to 1 cm per pixsel depending on flight level. The purpose of this study is to identify the degree of accuracy and the scattered conditions of the benthic habitat by the sentinel-2A imagery and the UAV imagery in mapping the benthic habitat in the shallow waters of Pemuteran. The two images for classification use classification based objects and accuracy tests using the confusion matrix method. Based on field observations, five kinds of habitat composition with vast dead corals, dead coral, rubble, biorock, sand, and stone sand are 13.63 ha, 1.45 ha, 0.87 ha, 6.05 ha, and 1.67 ha on the sentinel-2A imagery and 12.86 ha, 1.54 ha, 0.18 ha, 7.32 ha, and 1.76 ha on the UAV imagery. The Sentinel-2a's imagery capability in mapping the benthic habitat is adopted by 73.95%, whereas the UAV imagery is 81.51%. The value of accuracy obtained in the study shows the use of remote sensing data using both imagery can be used for the mapping of habitat benthic.
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Sativa, Denianto Yoga, I. Gede Nano Septian i Febrian Kusuma Atmanegara. "Benthic Habitat Mapping Using Sentinel-2A Satellite Imagery in Serewe Bay". Jurnal Biologi Tropis 22, nr 1 (26.12.2021): 55–61. http://dx.doi.org/10.29303/jbt.v22i1.3157.
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Serewe Bay is an important area for sustainable fisheries. This information on benthic habitats is important to know for sustainable management. However, at the moment there is no information on the distribution of benthic habitats in Serewe Bay. The research utilizes Sentinel 2A satellite imagery where the image used is obtained through the earthexplorer.usgs.gov website. Image data will be analyzed through several correction analysis processes, namely reflectance correction, sunglint, and water column or Lyzenga in order to obtain an image display that can be used to identify benthic habitats in Serewe Bay. In addition, a field data survey was also carried out to test the accuracy of the results of processing the Sentinel 2A satellite image of Serewe Bay. Image processing results show that there are 3 categories of benthic habitats, namely Seagrass, Sand and Mixed habitats in which there are macroalgae, dead coral, and coral fractures. The results of the field survey and accuracy calculations show that the accuracy of sentinel 2A image processing in Serewe Bay reaches 63.41% with the dominant benthic distribution consisting of seagrass, mixed benthic habitat and sand. Meanwhile, the calculation of the area of important benthic habitats such as seagrass beds in Serewe Bay can reach 156 Ha.
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Knudby, Anders, Ellsworth LeDrew i Candace Newman. "Progress in the use of remote sensing for coral reef biodiversity studies". Progress in Physical Geography: Earth and Environment 31, nr 4 (sierpień 2007): 421–34. http://dx.doi.org/10.1177/0309133307081292.
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Coral reefs are hotspots of marine biodiversity, and their global decline is a threat to our natural heritage. Conservation management of these precious ecosystems relies on accurate and up-to-date information about ecosystem health and the distribution of species and habitats, but such information can be costly to gather and interpret in the field. Remote sensing has proven capable of collecting information on geomorphologic zones and substrate types for coral reef environments, and is cost-effective when information is needed for large areas. Remote sensing-based mapping of coral habitat variables known to influence biodiversity has only recently been undertaken and new sensors and improved data processing show great potential in this area. This paper reviews coral reef biodiversity, the influence of habitat variables on its local spatial distribution, and the potential for remote sensing to produce maps of these habitat variables, thus indirectly mapping coral reef biodiversity and fulfilling information needs of coral reef managers.
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Ruliansyah, Andri, Wawan Ridwan i Asep Jajang Kusnandar. "Pemetaan Habitat Jentik Nyamuk Di Kecamatan Cibalong, Kabupaten Garut, Provinsi Jawa Barat". Jurnal Vektor Penyakit 13, nr 2 (30.12.2019): 115–24. http://dx.doi.org/10.22435/vektorp.v13i2.946.
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Abstract
The environment is an important factor in transmitting vector-borne diseases where an environment is a place of interaction between hosts, agents, and vectors. The existence of mosquitoes as a vector of various types of diseases is influenced by the existence of mosquito breeding habitats in an area. The results of mapping can be a guide to finding larva habitat when carrying out vector control. In addition, there is no map of larva habitat in Cibalong Subdistrict, Garut Regency so that mapping of breeding sites and behavior of mosquitoes becomes very important. The purpose of this study was to map the mosquito larval habitats in Cibalong District, Garut regency. Data collection was done by plotting habitats using Global Positioning System (GPS) and larva identifications using a compound microscope. Habitat larvae found in Karangparanje, Karyasari Village and Sakambangan, Mekarwangi Village, dominated by rice fields and water streams. While larvae found were Culex sp, Anopheles sp, Aedes sp, and Malaya sp. This finding confirmed that Cibalong District receptive as a transmitting area of Malaria, DHF, and Filaria, so it is necessary to be aware of the possibility of transmission of vector-borne diseases in those areas.
Abstrak
Lingkungan merupakan faktor penting dalam penularan penyakit tular vektor di mana lingkungan merupakan tempat berinteraksi antara host , agen dan vektor. Keberadaan nyamuk sebagai vektor berbagai macam penyakit dipengaruhi oleh keberadaan habitat perkembangbiakan nyamuk di suatu wilayah. Hasil suatu pemetaan dapat menjadi panduan untuk menemukan habitat jentik pada saat melakukan pengendalian vektor. Selain itu belum adanya suatu peta habitat jentik di Kecamatan Cibalong Kabupaten Garut sehingga pemetaan tempat perkembangbiakan dan perilaku nyamuk menjadi sangat penting. Tujuan kajian ini untuk memetakan habitat jentik nyamuk di Kecamatan Cibalong Kabupaten Garut. Pengumpulan data dilakukan dengan membuat titik (plotting) habitat dengan menggunakan Global Positioning System (GPS) dan identifikasi jentik menggunakan mikroskop binokuler. Habitat jentik yang ditemukan di Dusun Karangparanje Desa Karyasari dan Dusun Sakambangan Desa Mekarwangi, didominasi oleh sawah dan aliran sungai. Sedangkan jentik yang ditemukan yaitu Culex sp, Anopheles sp, Aedes sp dan Malaya sp. Hal ini menjadikan Kecamatan Cibalong reseptif sebagai daerah penular malaria, DBD, dan filaria, sehingga perlu diwaspadai kemungkinan terjadinya penularan penyakit tular vektor di wilayah tersebut.
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Wilson, Kristen L., Melisa C. Wong i Emmanuel Devred. "Comparing Sentinel-2 and WorldView-3 Imagery for Coastal Bottom Habitat Mapping in Atlantic Canada". Remote Sensing 14, nr 5 (4.03.2022): 1254. http://dx.doi.org/10.3390/rs14051254.
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Satellite remote sensing is a valuable tool to map and monitor the distribution of marine macrophytes such as seagrass and seaweeds that perform many ecological functions and services in coastal habitats. Various satellites have been used to map the distribution of these coastal bottom habitat-forming species, with each sensor providing unique benefits. In this study, we first explored optimal methods to create bottom habitat maps using WorldView-3 satellite imagery. We secondly compared the WorldView-3 bottom habitat maps to previously produced Sentinel-2 maps in a temperate, optically complex environment in Nova Scotia, Canada to identify the top performing classification and the advantages and disadvantages of each sensor. Sentinel-2 provides a global, freely accessible dataset where four bands are available at a 10-m spatial resolution in the visible and near infrared spectrum. Conversely, WorldView-3 is a commercial satellite where eight bands are available at a 2-m spatial resolution in the visible and near infrared spectrum, but data catalogs are costly and limited in scope. Our optimal WorldView-3 workflow processed images from digital numbers to habitat classification maps, and included a semiautomatic stripe correction. Our comparison of bottom habitat maps explored the impact of improved WorldView-3 spatial resolution in isolation, and the combined advantage of both WorldView’s increased spatial and spectral resolution relative to Sentinel-2. We further explored the effect of tidal height on classification success, and relative changes in water clarity between images collected at different dates. As expected, both sensors are suitable for bottom habitat mapping. The value of WorldView-3 came from both its increased spatial and spectral resolution, particularly for fragmented vegetation, and the value of Sentinel-2 imagery comes from its global dataset that readily allows for large scale habitat mapping. Given the variation in scale, cost and resolution of the two sensors, we provide recommendations on their use for mapping and monitoring marine macrophyte habitat in Atlantic Canada, with potential applications to other coastal areas of the world.
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Nandika, Muhammad Rizki, Azura Ulfa, Andi Ibrahim i Anang Dwi Purwanto. "Assessing the Shallow Water Habitat Mapping Extracted from High-Resolution Satellite Image with Multi Classification Algorithms". Geomatics and Environmental Engineering 17, nr 2 (30.01.2023): 69–87. http://dx.doi.org/10.7494/geom.2023.17.2.69.
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Remote sensing technology is reliable in identifying the distribution of seabed cover yet there are still challenges in retrieving the data collection of shallow water habitats than with other objects on land. Classification algorithms based on remote sensing technology have been developed for application to map benthic habitats, such as Maximum Likelihood, Minimum Distance, and Support Vector Machine. This study focuses on examining those three classification algorithms to retrieve information on the benthic habitat in Pari Island, Jakarta using visual interpretation data for classification, and data field measurements for accuracy testing. This study used five classes of benthic objects, namely sand, sand-seagrass, rubble, seagrass, and coral. The results show how the proposed approach in this study provides an overall good classification of marine habitat with an accuracy produced 63.89–81.95%. The Support Vector Machine algorithm produced the highest accuracy rate of about 81.95%. The Support Vector Machine algorithm at a very high spatial resolution is considered to be capable of identifying, monitoring, and performing the rapid assessment of benthic habitat objects.
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Lavrinenko, Igor A. "Habitat classification of East-European tundra". Transaction Kola Science Centre 12, nr 6-2021 (31.12.2021): 13–18. http://dx.doi.org/10.37614/2307-5252.2021.6.12.9.001.
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The small contour and mosaic of tundra landscapes leads to the predominance of complex territorial units of vegetation (complexes, serial and ecological series, combinations). For accurate diagnostics and mapping of habitat categories in the tundra zone, we have developed a typological scheme based on the types of combinations of territorial units of vegetation. It takes into account not only the syntaxonomic composition, but also the peculiarities of the spatial organization of habitats.
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McDermid, Gregory J., Steven E. Franklin i Ellsworth F. LeDrew. "Remote sensing for large-area habitat mapping". Progress in Physical Geography: Earth and Environment 29, nr 4 (grudzień 2005): 449–74. http://dx.doi.org/10.1191/0309133305pp455ra.
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Remote sensing has long been identified as a technology capable of supporting the development of wildlife habitat maps over large areas. However, progress has been constrained by underdeveloped linkages between resource managers with extensive knowledge of ecology and remote sensing scientists with backgrounds in geography. This article attempts to traverse that gap by (i) clarifying the imprecise and commonly misunderstood concept of ‘habitat’, (ii) exploring the recent use of remote sensing in previous habitat-mapping exercises, (iii) reviewing the remote sensing toolset developed for extracting information from optical satellite imagery, and (iv) outlining a framework for linking ecological information needs with remote sensing techniques.
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Stohlgren, Thomas J., Peter Ma, Sunil Kumar, Monique Rocca, Jeffrey T. Morisette, Catherine S. Jarnevich i Nate Benson. "Ensemble Habitat Mapping of Invasive Plant Species". Risk Analysis 30, nr 2 (luty 2010): 224–35. http://dx.doi.org/10.1111/j.1539-6924.2009.01343.x.
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Lee, Sonny T. M., Michelle Kelly, Tim J. Langlois i Mark J. Costello. "Baseline seabed habitat and biotope mapping for a proposed marine reserve". PeerJ 3 (10.12.2015): e1446. http://dx.doi.org/10.7717/peerj.1446.
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Seabed mapping can quantify the extent of benthic habitats that comprise marine ecosystems, and assess the impact of fisheries on an ecosystem. In this study, the distribution of seabed habitats in a proposed no-take Marine Reserve along the northeast coast of Great Barrier Island, New Zealand, was mapped using underwater video combined with bathymetry and substratum data. As a result of the boundary extending to the 12 nautical mile Territorial Limit, it would have been the largest coastal Marine Reserve in the country. Recreational and commercial fisheries occur in the region and would be expected to affect species’ abundance. The seabed of the study area and adjacent coastal waters has been trawled up to five times per year. Benthic communities were grouped by multivariate cluster analysis into four biotope classes; namely (1) shallow water macroalgaeEckloniasp. andUlvasp. on rocky substrata (Eck.Ulv); and deeper (2) diverse epifauna of sponges and bryozoans on rocky substrata (Por.Bry), (3) brittle starAmphiurasp. and sea anemoneEdwardsiasp. on muddy sand (Amph.Edw), and (4) hydroids on mud (Hyd). In biotopes Por.Bry, Amph.Edw and Hyd, there where boulders and rocks were present, and diverse sponge, bryozoan and coral communities. Fifty species were recorded in the deep water survey including significant numbers of the shallow-water hexactinellid glass spongesSymplectella rowiDendy, 1924 andRossella ijimaiDendy, 1924, the giant pipe demospongeIsodictya cavicornutaDendy, 1924, black corals, and locally endemic gorgonians. The habitats identified in the waters to the northeast of Great Barrier Island are likely to be representative of similar depth ranges in northeast New Zealand. This study provides a baseline of the benthic habitats so that should the area become a Marine Reserve, any habitat change might be related to protection from fishing activities and impacts, such as recovery of epifauna following cessation of trawling. The habitat map may also be used to stratify future sampling that would aim to collect and identify epifauna and infauna for identification, and thus better describe the biodiversity of the area.
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Price, Bronwyn, Nica Huber, Anita Nussbaumer i Christian Ginzler. "The Habitat Map of Switzerland: A Remote Sensing, Composite Approach for a High Spatial and Thematic Resolution Product". Remote Sensing 15, nr 3 (21.01.2023): 643. http://dx.doi.org/10.3390/rs15030643.
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Habitat maps at high thematic and spatial resolution and broad extents are fundamental tools for biodiversity conservation, the planning of ecological networks and the management of ecosystem services. To derive a habitat map for Switzerland, we used a composite methodology bringing together the best available spatial data and distribution models. The approach relies on the segmentation and classification of high spatial resolution (1 m) aerial imagery. Land cover data, as well as habitat and species distribution models built on Earth observation data from Sentinel 1 and 2, Landsat, Planetscope and LiDAR, inform the rule-based classification to habitats defined by the hierarchical Swiss Habitat Typology (TypoCH). A total of 84 habitats in 32 groups and 9 overarching classes are mapped in a spatially explicit manner across Switzerland. Validation and plausibility analysis with four independent datasets show that the mapping is broadly plausible, with good accuracy for most habitats, although with lower performance for fine-scale and linear habitats, habitats with restricted geographical distributions and those predominantly characterised by understorey species, especially forest habitats. The resulting map is a vector dataset available for interactive viewing and download from open EnviDat data sharing platform. The methodology is semi-automated to allow for updates over time.
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Pesaresi, Simone, Adriano Mancini, Giacomo Quattrini i Simona Casavecchia. "Mapping Mediterranean Forest Plant Associations and Habitats with Functional Principal Component Analysis Using Landsat 8 NDVI Time Series". Remote Sensing 12, nr 7 (2.04.2020): 1132. http://dx.doi.org/10.3390/rs12071132.
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The classification of plant associations and their mapping play a key role in defining habitat biodiversity management, monitoring, and conservation strategies. In this work we present a methodological framework to map Mediterranean forest plant associations and habitats that relies on the application of the Functional Principal Component Analysis (FPCA) to the remotely sensed Normalized Difference Vegetation Index (NDVI) time series. FPCA, considering the chronological order of the data, reduced the NDVI time series data complexity and provided (as FPCA scores) the main seasonal NDVI phenological variations of the forests. We performed a supervised classification of the FPCA scores combined with topographic and lithological features of the study area to map the forest plant associations. The supervised mapping achieved an overall accuracy of 87.5%. The FPCA scores contributed to the global accuracy of the map much more than the topographic and lithological features. The results showed that (i) the main seasonal phenological variations (FPCA scores) are effective spatial predictors to obtain accurate plant associations and habitat maps; (ii) the FPCA is a suitable solution to simultaneously express the relationships between remotely sensed and ecological field data, since it allows us to integrate these two different perspectives about plant associations in a single graph. The proposed approach based on the FPCA is useful for forest habitat monitoring, as it can contribute to produce periodically detailed vegetation-based habitat maps that reflect the “current” status of vegetation and habitats, also supporting the study of plant associations.
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DeLancey, Evan R., Brian Brisco, Logan J. T. McLeod, Richard Hedley, Erin M. Bayne, Kevin Murnaghan, Fiona Gregory i Jahan Kariyeva. "Modelling, Characterizing, and Monitoring Boreal Forest Wetland Bird Habitat with RADARSAT-2 and Landsat-8 Data". Water 13, nr 17 (25.08.2021): 2327. http://dx.doi.org/10.3390/w13172327.
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Earth observation technologies have strong potential to help map and monitor wildlife habitats. Yellow Rail, a rare wetland obligate bird species, is a species of concern in Canada and provides an interesting case study for monitoring wetland habitat with Earth observation data. Yellow Rail has highly specific habitat requirements characterized by shallowly flooded graminoid vegetation, the availability of which varies seasonally and year-to-year. Polarimetric Synthetic Aperture Radar (SAR) in combination with optical data should, in theory, be a great resource for mapping and monitoring these habitats. This study evaluates the use of RADARSAT-2 data and Landsat-8 data to characterize, map, and monitor Yellow Rail habitat in a wetland area within the mineable oil sands region. Specifically, we investigate: (1) The relative importance of polarimetric SAR and Landsat-8 data for predicting Yellow Rail habitat; (2) characterization of wetland habitat with polarimetric SAR data; (3) yearly trends in available habitat; and (4) predictions of potentially suitable habitat across northeastern Alberta. Results show that polarimetric SAR using the Freeman–Durden decomposition and polarization ratios were the most important predictors when modeling the Yellow Rail habitat. These parameters also effectively characterize this habitat based on high congruence with existing descriptions of suitable habitat. Applying the prediction model across all wetland areas showed accurate predictions of occurrence (validated on field occurrence data), and high probability habitats were constrained to very specific wetland areas. Using the RADARSAT-2 data to monitor yearly changes to Yellow Rail habitat was inconclusive, likely due to the different image acquisition times of the 2014 and 2016 images, which may have captured seasonal, rather than inter-annual, wetland dynamics. Polarimetric SAR has proved to be very useful for capturing the specific hydrology and vegetation structure of the Yellow Rail habitat, which could be a powerful technology for monitoring and conserving wetland species habitat.
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Bianchi, Carlo Nike, Annalisa Azzola, Silvia Cocito, Carla Morri, Alice Oprandi, Andrea Peirano, Sergio Sgorbini i Monica Montefalcone. "Biodiversity Monitoring in Mediterranean Marine Protected Areas: Scientific and Methodological Challenges". Diversity 14, nr 1 (10.01.2022): 43. http://dx.doi.org/10.3390/d14010043.
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Biodiversity is a portmanteau word to indicate the variety of life at all levels from genes to ecosystems, but it is often simplistically equated to species richness; the word ecodiversity has thus been coined to address habitat variety. Biodiversity represents the core of the natural capital, and as such needs to be quantified and followed over time. Marine Protected Areas (MPAs) are a major tool for biodiversity conservation at sea. Monitoring of both species and habitat diversity in MPAs is therefore mandatory and must include both inventory and periodic surveillance activities. In the case of inventories, the ideal would be to census all species and all habitats, but while the latter goal can be within reach, the former seems unattainable. Species inventory should be commeasured to investigation effort, while habitat inventory should be based on mapping. Both inventories may profit from suitability spatial modelling. Periodic surveillance actions should privilege conspicuous species and priority habitats. Efficient descriptor taxa and ecological indices are recommended to evaluate environmental status. While it seems obvious that surveillance activities should be carried out with regular recurrence, diachronic inventories and mapping are rarely carried out. Time series are of prime importance to detect marine ecosystem change even in the absence of direct human impacts.
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Espriella, Michael, Tyler Schaper, Alison Atchia, Katherine Rose i Vincent Lecours. "Habitat mapping of giant kelp (Macrocystis pyrifera) and devil weed (Sargassum horneri) off the coast of Santa Catalina Island, California". McGill Science Undergraduate Research Journal 14, nr 1 (10.04.2019): 34–39. http://dx.doi.org/10.26443/msurj.v14i1.51.
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Background: Macrocystis pyrifera, commonly known as giant kelp, is a fast-growing brown alga that typically inhabits temperate waters. In southern California, M. pyrifera provides many ecologically and economically significant ecosystem services. Sargassum horneri, a non-native brown macroalga commonly known as devil weed, often outcompetes M. pyrifera while providing fewer ecological or economical benefits. Examining potential areas of species overlap is key to understanding the invasion potential of S. horneri and essential to the implementation of removal efforts. This study aims to map the suitable habitat of M. pyrifera and invasive S. horneri in the coastal waters of Santa Catalina Island, California, and to quantify any overlapping habitat between the two macroalgae. Methods: Broadly defined potential habitats were characterized around Santa Catalina Island using an unsupervised approach to habitat mapping based on a series of abiotic surrogates mapped at a 2 m spatial resolution. In situ substrate data were then overlaid onto the unsupervised classification to identify spatial associations between substrate type and potential habitats, and to interpret the classes. To predict the distribution of M. pyrifera and S. horneri around Santa Catalina Island based on their respective association with the environment, maximum entropy (MaxEnt) was used to produce species distribution models. The resulting models for M. pyrifera and S. horneri were overlaid to identify potential areas of conflict based on suitable habitat overlap. Results: The unsupervised approach to habitat mapping resulted in a map of four potential habitats around Santa Catalina Island based on substrate cover. Sand was the most dominant type of substrate. The supervised approach using MaxEnt identified 10.27% of the study area as suitable habitat for M. pyrifera and 7.37% as suitable habitat for S. horneri. A total of 33.56% of the suitable habitat for M. pyrifera was found to also be suitable for S. horneri. Limitations: The characterization of habitats and the species distribution modeling were limited to the study of benthic terrain characteristics due to the unavailability of other high-resolution environmental data (e.g., hydrodynamics and chemical data) around Santa Catalina Island. In addition, data were not available for the very shallow waters near the coast, where giant kelp is often found. Given the complexity of this ecosystem, the addition of other variables and data coverage closer to the coast would potentially make the maps and models more representative of the actual distribution of M. pyrifera and S. horneri and provide a more complete understanding of their environmental preferences. Conclusion: This study provides insight into the kelp forest ecosystems found in California’s Channel Islands; it is a vital first step in order to understand the potential areas for invasion of M. pyrifera by S. horneri, thus supporting decision making and efforts to control S. horneri abundance.
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Wang, Kai, Steven E. Franklin, Xulin Guo, Yuhong He i Gregory J. McDermid. "Problems in remote sensing of landscapes and habitats". Progress in Physical Geography: Earth and Environment 33, nr 6 (14.10.2009): 747–68. http://dx.doi.org/10.1177/0309133309350121.
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Wildlife habitat mapping strongly supports applications in natural resource management, environmental conservation, impacts of anthropogenic activity, perturbed ecosystem restoration, species-at-risk recovery and species inventory. Remote sensing has long been identified as a feasible and effective technology for large-area habitat mapping. However, existing and future uncertainties in remote sensing will definitely have a significant effect on the relevant scientific research. This article attempts to identify the current challenges and opportunities in remote sensing for large-area wildlife habitat mapping, and accordingly provide possible solutions and directions for further research.