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1
Rivaes, Rui Pedro, António Nascimento Pinheiro, Gregory Egger e Maria Teresa Ferreira. "Using CASIMIR-VEGETATION Model in the context of modeling riparian woods and fish species to support a holistic approach for environmental flows to be used on river management and conservation". Revista Eletrônica de Gestão e Tecnologias Ambientais 4, n. 1 (23 novembre 2016): 01. http://dx.doi.org/10.9771/gesta.v4i1.14292.
Abstract (sommario):
<p>The CASiMiR-vegetation model is a software that recreates the physical processes influencing the survival and recruitment of riparian vegetation, based on the relationship between ecologically relevant flow regime components and riparian vegetation metrics that reflect the vegetation’s responses to flow regime change. Working at a flow response guild level, this tool outperforms equivalent models by overriding various restrictions of the conventional modeling approaches. The potential of the CASiMiR-vegetation model is revealed in its application to different case studies during the development of a holistic approach to determine environmental flows in lowland Mediterranean rivers, based on woody riparian vegetation and fish species. Various modeling circumstances are described where CASiMiR-vegetation model was used with the purpose of sustaining the research addressing the thesis objectives. The main findings already accomplished in this research are highlighted to illustrate the outcomes that can be attained from the use of such a model.</p>
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Braun, Andreas Christian, Uwe Weidner e Stefan Hinz. "Support Vector Machines for Vegetation Classification – A Revision". Photogrammetrie - Fernerkundung - Geoinformation 2010, n. 4 (1 agosto 2010): 273–81. http://dx.doi.org/10.1127/1432-8364/2010/0055.
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Zhu, Xuan, J. McCosker, A. P. Dale e R. J. Bischof. "Web-based decision support for regional vegetation management". Computers, Environment and Urban Systems 25, n. 6 (novembre 2001): 605–27. http://dx.doi.org/10.1016/s0198-9715(00)00033-8.
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Nugraha, M. R., e O. C. Dewi. "Maintaining Environmental Sustainability through Existing Environment’s Vegetations". IOP Conference Series: Earth and Environmental Science 940, n. 1 (1 dicembre 2021): 012044. http://dx.doi.org/10.1088/1755-1315/940/1/012044.
Abstract (sommario):
Abstract Demands for building in urban areas have been increasing lately, especially educational buildings as support for the human development index. Unfortunately, only a few educational buildings can support green buildings as pilots and educational materials for their users. One of the initiators in becoming educational materials and examples of green buildings is the i-cell multipurpose educational building at the Universitas Indonesia. This study aims to find evidence of how reliable and sustainable planning of an educational building in Depok, Indonesia, can accommodate the needs of its users while being environmentally friendly for its surroundings. It observes the influences of vegetation in the surrounding building, one of which is by maximizing the function of vegetation around the building. The research methods include collecting data from the weather archive, vegetation literature, observing the subject, and analyzing the vegetation’s effect. This study shows that vegetation has an important role in generating a sound environment for humans and buildings, including healing and providing calmness. This study concludes that vegetation plays a role in generating a good environment by decreasing temperature, sound pollution, sun glare and providing shading areas for people. Those conditions lead to the sustainability of the environment surrounding the building.
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Ye, Danqin. "Structure and Functions of Green Roof and Its Development in Urban Areas, China". Highlights in Science, Engineering and Technology 75 (28 dicembre 2023): 1–7. http://dx.doi.org/10.54097/41cwrt42.
Abstract (sommario):
The green roof is an environmentally friendly design, which is important for sustainable development and improvement of resilience in urban areas. This paper offers a systematically review of the classification, material selection, functionality, limiting factors of green roofs, and provides suggestions. The green roof is classified into intensive, extensive and semi-intensive ones according to the substrate depth and vegetation type. Its basic structure includes vegetation, substrate, filter, drainage, protection, anti-root, insulation and waterproofing layers from top to base. Among which, vegetation, waterproofing and drainage are vital layers to decide the roof efficient. The factors such as light, temperature and humidity conditions of the site are vital for determination of vegetations for a green roof. Green roofs provide benefits for urban areas via saving energy, reducing stormwater runoff and improving aesthetic. Roof load-bearing, seepage, survival of vegetations and support from all sectors are the main issues for the development of green roofs at current stage.
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Zuidema, Pieter A., Benjamin Poulter e David C. Frank. "A Wood Biology Agenda to Support Global Vegetation Modelling". Trends in Plant Science 23, n. 11 (novembre 2018): 1006–15. http://dx.doi.org/10.1016/j.tplants.2018.08.003.
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Mohd Salleh, Mohd Radhie, Muhammad Zulkarnain Abd Rahman, Zamri Ismail, Mohd Faisal Abdul Khanan, Huey Tam Tze, Ismaila Usman Kaoje, Mohamad Jahidi Osman e Mohd Asraff Asmadi. "SUPPORT VECTOR MACHINE FOR LANDSLIDE ACTIVITY IDENTIFICATION BASED ON VEGETATION ANOMALIES INDICATOR". Journal of Information System and Technology Management 7, n. 25 (7 marzo 2022): 148–58. http://dx.doi.org/10.35631/jistm.725012.
Abstract (sommario):
Landslide activity identification is critical for landslide inventory mapping. A detailed landslide inventory map is highly required for various purposes such as landslide susceptibility, hazard, and risk assessments. This paper proposes a novel approach based on vegetation anomalies indicator (VAI) and applying machine learning method namely support vector machine (SVM) to identify status of natural-terrain landslides. First, high resolution airborne LiDAR data and satellite imagery were used to derive landslide-related VAIs, including tree height irregularities, canopy gap, density of different layer of vegetation, vegetation type, vegetation indices, root strength index (RSI), and distribution of water-loving trees. Then, SVM is utilized with different setting of parameter using grid search optimization. SVM Radial Basis Function (RBF) recorded the best optimal pair value with 0.062 and 0.092 misclassification rate for deep seated and shallow translational landslide, respectively. For landslide activity classification, SVM RBF recorded the best accuracy value for both deep seated and shallow translational landslides with 86.0 and 71.3, respectively. Overall, VAIs have great potential in tackling the landslide activity identification problem especially in tropical vegetated area.
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Dyderski, Marcin K., e Andrzej M. Jagodziński. "Context-Dependence of Urban Forest Vegetation Invasion Level and Alien Species’ Ecological Success". Forests 10, n. 1 (3 gennaio 2019): 26. http://dx.doi.org/10.3390/f10010026.
Abstract (sommario):
Research Highlights: Urban ecosystems are claimed to be more invaded than natural vegetation. Despite numerous studies, the patterns of alien species occurrence in urban forests are rarely linked to invasion ecology hypotheses. Background and Objectives: We assumed that patterns of invasion level (i.e., neophyte richness) and neophyte ecological success (cover) are context-dependent, i.e., depend on the type of vegetation, and that hypotheses connected with empty niche and biotic acceptance will have the strongest support in urban forests. We also tested biotic resistance, habitat filtering, disturbance, resource availability, and environmental heterogeneity hypotheses. Materials and Methods: Using a random forest algorithm, we tested the importance of factors related to invasion ecology hypotheses in a dataset of urban forest vegetation plots (n = 120). We studied seven types of forest plant communities occurring in Poznań (W Poland) and we assessed the vegetation’s taxonomic and functional composition. Results: We found that models of alien species richness and cover explained 28.5% and 35.0% of variance, respectively. Vegetation type was of the highest importance in both cases, suggesting that the occurrence of alien plant species is context-dependent. Resource availability and disturbance ecological indicator values were also of high importance. Conclusions: Our study supported resource availability and habitat filtering hypotheses as explanations of the level of invasion and ecological success of alien species in an urban forest, with partial support for the disturbance hypothesis. Our study revealed that predictors of invasion level are context-dependent, as patterns of alien species richness and cover differed among vegetation types. We highlight context-dependence of alien species invasion patterns in different vegetation types due to the habitat-forming role of dominant tree species and different availability of resources and disturbance levels, as well as different pools of native species. Thus, prevention and management of biological invasions in urban forests should account for forest vegetation type.
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Woźniak, Gabriela, Damian Chmura, Teresa Nowak, Barbara Bacler-Żbikowska, Lynn Besenyei e Agnieszka Hutniczak. "Post-Extraction Novel Ecosystems Support Plant and Vegetation Diversity in Urban-Industrial Landscapes". Sustainability 14, n. 13 (22 giugno 2022): 7611. http://dx.doi.org/10.3390/su14137611.
Abstract (sommario):
Long-term exploitation of mineral resources has significantly changed the natural environment in urban-industrial landscapes. The changes on the surface of the extraction sites as a consequence of excavation of mineral resources provide specific mineral oligotrophic habitats on which plant species and thus vegetation can establish spontaneously. Some of these sites fulfill the prerequisites of novel ecosystems. This study was conducted on the spontaneous vegetation of post-extraction sites. Lists of species spontaneously covering these sites were prepared based on published data and our own records. This research revealed that species composition and vegetation types vary in time. These post-extraction novel ecosystems are also important for the presence of rare, endangered, and protected species noted in patches of different vegetation types. The variety of habitat conditions provided by these sites facilitates the occurrence of a wide spectrum of plants (both in terms of their socio-ecological origin and their ecological spectrum). This research proves how important these post-extraction novel ecosystems are for supporting plant and vegetation diversity in urban-industrial landscapes. Enhancing the biodiversity significantly increases the ecosystem services delivered by these sites and also the functioning of entire ecosystems. These natural processes on human habitats are essential in urban-industrial ecosystem landscape mosaics.
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Danin, Avinoam. "Flora and vegetation of Sinai". Proceedings of the Royal Society of Edinburgh. Section B. Biological Sciences 89 (1986): 159–68. http://dx.doi.org/10.1017/s026972700000899x.
Abstract (sommario):
SynopsisMost of Sinai belongs to the Saharo-Arabian phytogeographical region. It is covered with a sparse vegetation of semishrubs, restricted to wadis or growing on slopes of rocky hills and in sand fields. The high mountains of southern Sinai support a mainly Irano-Turanian steppe vegetation. Smooth-faced rock outcrops supply sufficient run-off water to permit the survival of trees, shrubs, many relict species, and most of the endemics of Sinai. There are 28 endemic species in Sinai, of which 25 occur in the mountainous districts of Sinai. The foothills of eastern Sinai and the coastal area of the Gulf of Elat have a savanna-like vegetation and support thermophilous Sudanian trees and shrubs in wadis and rock crevices.
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Du, Guoming, Shouhong Yan, Hang Chen, Jian Yang e Youyue Wen. "Intra-Annual Cumulative Effects and Mechanisms of Climatic Factors on Global Vegetation Biomes’ Growth". Remote Sensing 16, n. 5 (23 febbraio 2024): 779. http://dx.doi.org/10.3390/rs16050779.
Abstract (sommario):
Previous studies have shown that climate change has significant cumulative effects on vegetation growth. However, there remains a gap in understanding the characteristics of cumulative climatic effects on different vegetation types and the underlying driving mechanisms. In this study, using the normalized difference vegetation index data from 1982 to 2015, along with accumulated temperature, precipitation, and solar radiation data, we quantitatively investigated the intra-annual cumulative effects of climatic factors on global vegetation biomes across climatic zones. We also explored the underlying driving mechanisms. The results indicate that precipitation has a longer intra-annual cumulative effect on vegetation, with effects lasting up to 12 months for large percentages of most vegetation biomes. The cumulative effect of solar radiation is mostly concentrated within 0–6 months. Temperature has a shorter cumulative effect, with no significant cumulative effect of temperature on large percentages of tree-type vegetation. Compared to other vegetation types, evergreen broadleaf forests, close shrublands, open shrublands, savannas, and woody savannas exhibit more complex cumulative climatic effects. Each vegetation type shows a weak-to-moderate correlation with accumulated precipitation while exhibiting strong-to-extremely-strong positive correlations with accumulated temperature and accumulated solar radiation. The climate-induced regulations of water, heat, and nutrient, as well as the intrinsic mechanisms of vegetation’s tolerance, resistance, and adaptation to climate change, account for the significant heterogeneity of cumulative climatic effects across vegetation biomes in different climatic zones. This study contributes to enriching the theoretical understanding of the relationship between vegetation growth and climate change. It also offers crucial theoretical support for developing climate change adaptation strategies and improving future “vegetation-climate” models.
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Nijland, W., E. A. Addink, S. M. De Jong e F. D. Van der Meer. "Optimizing spatial image support for quantitative mapping of natural vegetation". Remote Sensing of Environment 113, n. 4 (aprile 2009): 771–80. http://dx.doi.org/10.1016/j.rse.2008.12.002.
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Miranda, Ciomara De Souza, Anny Keli Aparecida Alves Cândido, Camila Leonardo Mioto, Normandes Matos Da Silva, Antônio Conceição Paranhos Filho e Arnildo Pott. "Geotechnology as support for the management of conservation units in Brazil's Pantanal". Boletim do Museu Paraense Emílio Goeldi - Ciências Naturais 12, n. 2 (21 agosto 2020): 255–64. http://dx.doi.org/10.46357/bcnaturais.v12i2.388.
Abstract (sommario):
The aim of this paper is to study temporal variations in vegetation indices as a tool for monitoring the integral protection conservation units (parks, reserves, and ecological stations) in the Brazilian Pantanal, giving support to environmental management actions in these areas. The study was carried out in five conservation units. Evaluated data, beside the Normalized Difference Vegetation Index (NDVI), included information on wildfires and deforestation. Analyses showed that the Taiamã Ecological Station, the Pantanal Matogrossense National Park, and the Encontro das Águas State Park presented high vegetation indices, showing their effectiveness as areas of environmental protection. Although this latter state park presented one fire hotspot in 2015, there was significant improvement in this park. The Guirá State Park and the Pantanal of Rio Negro State Park presented relatively low NDVI values when compared with other analysed areas. The aggravating factor was that in the Rio Negro park 36 fire hotspots occurred in 2007, demonstrating the need for more vigorous monitoring and management of this protected area.
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Li, Yang, Yaochen Qin, Liqun Ma e Ziwu Pan. "Climate change: vegetation and phenological phase dynamics". International Journal of Climate Change Strategies and Management 12, n. 4 (6 luglio 2020): 495–509. http://dx.doi.org/10.1108/ijccsm-06-2019-0037.
Abstract (sommario):
Purpose The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau. Design/methodology/approach The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described. Findings The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November. Originality/value This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.
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Giora, Domenico, Alberto Assirelli, Silvia Cappellozza, Luigi Sartori, Alessio Saviane, Francesco Marinello e José A. Martínez-Casasnovas. "Remote Sensing Imaging as a Tool to Support Mulberry Cultivation for Silk Production". Remote Sensing 14, n. 21 (29 ottobre 2022): 5450. http://dx.doi.org/10.3390/rs14215450.
Abstract (sommario):
In recent decades there has been an increasing use of remotely sensed data for precision agricultural purposes. Sericulture, the activity of rearing silkworm (Bombyx mori L.) larvae to produce silk in the form of cocoons, is an agricultural practice that has rarely used remote sensing techniques but that could benefit from them. The aim of this work was to investigate the possibility of using satellite imaging in order to monitor leaf harvesting in mulberry (Morus alba L.) plants cultivated for feeding silkworms; additionally, quantitative parameters on silk cocoon production were related to the analyses on vegetation indices. Adopting PlanetScope satellite images, four M. alba fields were monitored from the beginning of the silkworm rearing season until its end in 2020 and 2021. The results of our work showed that a decrease in the multispectral vegetation indices in the mulberry plots due to leaf harvesting was correlated with the different parameters of silk cocoons spun by silkworm larvae; in particular, a decrease in the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) had high correlations with quantitative silk cocoon production parameters (R2 values up to 0.56, p < 0.05). These results led us to the conclusion that precision agriculture can improve sericultural practice, offering interesting solutions for estimating the quantity of produced silk cocoons through the remote analysis of mulberry fields.
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Xu, Binni, Jingji Li, Zhengyu Luo, Jianhui Wu, Yanguo Liu, Hailong Yang e Xiangjun Pei. "Analyzing the Spatiotemporal Vegetation Dynamics and Their Responses to Climate Change along the Ya’an–Linzhi Section of the Sichuan–Tibet Railway". Remote Sensing 14, n. 15 (26 luglio 2022): 3584. http://dx.doi.org/10.3390/rs14153584.
Abstract (sommario):
Vegetation dynamics and their responses to climate change are of significant spatial and temporal heterogeneity. The Sichuan–Tibet Railway (STR) is a major construction project of the 14th Five-Year Plan for Economic and Social Development of the People’s Republic of China that is of great significance to promoting the social and economic development of Sichuan–Tibet areas. The planned railway line crosses areas with a complex geological condition and fragile ecological environment, where the regional vegetation dynamics are sensitive to climate change, topographic conditions and human activities. So, analyzing the vegetation variations in the complex vertical ecosystem and exploring their responses to hydrothermal factors are critical for providing technical support for the ecological program’s implementation along the route of the planned railway line. Based on MOD13Q1 Normalized Difference Vegetation Index (NDVI) data for the growing season (May to October) during 2001–2020, a Theil-Sen trend analysis, Mann–Kendall test, Hurst exponent analysis and partial correlation analysis were used to detect the vegetation dynamics, predict the vegetation sustainability, examine the relationship between vegetation change and hydrothermal factors, regionalize the driving forces for vegetation growth and explore the interannual variation pattern of driving factors. The growing season NDVI along the Ya’an–Linzhi section of the STR showed a marked rate of increase (0.0009/year) during the past 20 years, and the vegetation’s slight improvement areas accounted for the largest proportion (47.53%). Among the three hydrothermal parameters (temperature, precipitation and radiation), the correlation between vegetation growth and the temperature was the most significant, and the vegetation response to precipitation was the most immediate. The vegetation changes were affected by the combined impact of climatic and non-climatic factors, and the proportion of hydrothermal factors’ combined driving force slightly increased during the study period. Based on the Hurst exponent, the future vegetation sustainability of the area along the Ya’an–Linzhi section of the STR faces a risk of degradation, and more effective conservations should be implemented during the railway construction period to protect the regional ecological environment.
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Seine, R., U. Becker, S. Porembski, G. Follmann e W. Barthlott. "Vegetation of inselbergs in Zimbabwe". Edinburgh Journal of Botany 55, n. 2 (luglio 1998): 267–93. http://dx.doi.org/10.1017/s0960428600002195.
Abstract (sommario):
Inselbergs are rounded rock outcrops, usually of Precambrian age, with sparse vegetation cover. The vegetation of inselbergs in Zimbabwe is described for the first time, based upon data sampled from 53 localities. Inselbergs support a range of habitats whose vegetation is described. Data on species richness and floristic composition of the inselberg flora (549 vascular plant, 25 bryophyte and 136 lichen species) are presented. Phytogeography and diversity of inselberg vegetation are discussed. First records for Zimbabwe are reported in lichens and vascular plants.
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Dion, Nancy, Keith A. Hobson e Serge Larivière. "Interactive Effects of Vegetation and Predators on the Success of Natural and Simulated Nests of Grassland Songbirds". Condor 102, n. 3 (1 agosto 2000): 629–34. http://dx.doi.org/10.1093/condor/102.3.629.
Abstract (sommario):
Abstract We examined the influence of vegetation and predator community on nesting success of songbirds in the grasslands of eastern North Dakota, USA. Each year, eight sites were chosen: four were subject to predator removal, and four were non-removal sites. On each site, nests of grassland songbirds were monitored, and simulated nests were used to examine how vegetation characteristics at nests affect nest success. Vegetative characteristics at simulated nests did not differ from those at natural nests, but successful natural nests had greater forb and lesser grass cover than unsuccessful nests, whereas no differences in vegetation were detected between successful and depredated simulated nests. On non-removal sites, small mammals and ground squirrels (Spermophilus sp.) depredated nests in taller and denser cover when compared to nests destroyed by medium-sized mammals and birds. On removal sites, we found no difference in vegetation characteristics of nests depredated by different predator types. However, each group of mammalian predators depredated simulated nests with different vegetation characteristics on removal versus non-removal sites. On sites where predators were removed, small mammals and ground squirrels preyed on simulated nests in shorter vegetation containing fewer forbs, ground squirrels preyed on nests with higher grass cover and lower vertical density, and medium-sized carnivores preyed on nests in taller vegetation. These results support the hypothesis that high predator diversity may reduce the chance of “safe” nest sites, and suggest that the behavior of low-level predators may change when top-level predators are removed.
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Reddy, R. Sanjeeva, G. Anjan Babu e A. Rama Mohan Reddy. "Geospatial Approach for the Analysis of Forest Cover Change Detection using Machine Learning". Geosfera Indonesia 5, n. 3 (30 dicembre 2020): 335. http://dx.doi.org/10.19184/geosi.v5i3.20157.
Abstract (sommario):
Spatial data classification is famous over recent years in order to extract knowledge and insights into the data. It occurs because vast experimentation was used with various classifiers, and significant improvement was examined in accuracy and performance. This study aimed to analyze forest cover change detection using machine learning. Supervised and unsupervised learning methods were used to analyze spatial data. A Vector machine was used to support the supervised learning, and a neural network method was used to support unsupervised learning. The Normalized Difference Vegetation Index (NDVI) was used to identify the bands and extract pixel information relevant to the vegetation. The supervised method shows better results because of its robust performance and better analysis of spatial data classification using vegetation index. The proposed system experimentation was implemented by analyzing the results obtained from Support Vector Machine (SVM) and NN (Neural Network) methods. It is demonstrated in the results that the use of NDVI mainly enhances the performance and increases the classifier's accuracy to a greater extent.
Keywords: Spatial data; Normalized Difference Vegetation Index; NDVI;Vegetation index, Support Vector Machine; Neural Network; Forest Cover Change
Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember
This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
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Paice, Robyn L., Jane M. Chambers e Belinda J. Robson. "Potential of submerged macrophytes to support food webs in lowland agricultural streams". Marine and Freshwater Research 68, n. 3 (2017): 549. http://dx.doi.org/10.1071/mf15391.
Abstract (sommario):
Submerged plants are often abundant in lowland streams in agricultural landscapes, but little is known of their role in stream ecosystems compared to riparian vegetation. We investigated the importance of submerged macrophytes as a basal resource of food webs in stream reaches with good and poor riparian vegetation condition, using mixing model analysis with stable carbon and nitrogen isotopes. Epilithic periphyton and terrestrial detritus were important basal resources in good condition reaches, although where macrophytes were present they contributed to food webs. Higher assimilation of either the macrophyte Cycnogeton huegelii or conspicuous epiphytes on C. huegelii leaves was associated with poor riparian condition. Where Potamogeton ochreatus and Ottelia ovalifolia occurred in poor condition reaches, these macrophytes contributed moderately to the food web, but were probably of greater importance as substrates for epiphytic algae. Mixing models indicated invertebrates commonly had generalist feeding strategies, feeding on the most available resource at each reach. Thus, where riparian vegetation is limited, submerged macrophytes may support opportunistic consumers both directly and as a substrate for epiphytes, thereby partially compensating for the loss of allochthonous resources in lowland agricultural streams.
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Edmaier, K., P. Burlando e P. Perona. "Mechanisms of vegetation uprooting by flow in alluvial non-cohesive sediment". Hydrology and Earth System Sciences 15, n. 5 (26 maggio 2011): 1615–27. http://dx.doi.org/10.5194/hess-15-1615-2011.
Abstract (sommario):
Abstract. The establishment of riparian pioneer vegetation is of crucial importance within river restoration projects. After germination or vegetative reproduction on river bars juvenile plants are often exposed to mortality by uprooting caused by floods. At later stages of root development vegetation uprooting by flow is seen to occur as a consequence of a marked erosion gradually exposing the root system and accordingly reducing the mechanical anchoring. How time scales of flow-induced uprooting do depend on vegetation stages growing in alluvial non-cohesive sediment is currently an open question that we conceptually address in this work. After reviewing vegetation root issues in relation to morphodynamic processes, we then propose two modelling mechanisms (Type I and Type II), respectively concerning the uprooting time scales of early germinated and of mature vegetation. Type I is a purely flow-induced drag mechanism, which causes alone a nearly instantaneous uprooting when exceeding root resistance. Type II arises as a combination of substantial sediment erosion exposing the root system and resulting in a decreased anchoring resistance, eventually degenerating into a Type I mechanism. We support our conceptual models with some preliminary experimental data and discuss the importance of better understanding such mechanisms in order to formulate sounding mathematical models that are suitable to plan and to manage river restoration projects.
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Edmaier, K., P. Burlando e P. Perona. "Mechanisms of vegetation uprooting by flow in alluvial non-cohesive sediment". Hydrology and Earth System Sciences Discussions 8, n. 1 (28 gennaio 2011): 1365–98. http://dx.doi.org/10.5194/hessd-8-1365-2011.
Abstract (sommario):
Abstract. The establishment of riparian pioneer vegetation is of crucial importance within river restoration projects. After germination or vegetative reproduction on river bars juvenile plants are often exposed to mortality by uprooting caused by floods. At later stages of root development vegetation uprooting by flow is seen to occur as a consequence of a marked erosion gradually exposing the root system and accordingly reducing the mechanical anchoring. How time scales of flow-induced uprooting do depend on vegetation stages growing in alluvial non-cohesive sediment is currently an open question that we conceptually address in this work. After reviewing vegetation root issues in relation to morphodynamic processes, we then propose two modelling mechanisms (Type I and Type II), respectively concerning the uprooting time scales of early germinated and of mature vegetation. Type I is a purely flow-induced drag mechanism, which causes alone a nearly instantaneous uprooting when exceeding root resistance. Type II arises as a combination of substantial sediment erosion exposing the root system and resulting in a decreased anchoring resistance, eventually degenerating into a Type I mechanism. We support our conceptual models with some preliminary experimental data and discuss the importance of better understanding such mechanisms in order to formulate sounding mathematical models that are suitable to plan and to manage river restoration projects.
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Shi, Xiaoliang, Fei Chen, Hao Ding, Mengqi Shi e Yi Li. "Assessing Vegetation Ecosystem Resistance to Drought in the Middle Reaches of the Yellow River Basin, China". International Journal of Environmental Research and Public Health 19, n. 7 (31 marzo 2022): 4180. http://dx.doi.org/10.3390/ijerph19074180.
Abstract (sommario):
The frequency and intensity of droughts are increasing in many parts of the world as a result of global climate change and human activity, posing a serious threat to regional ecological security. The climate in the middle reaches of the Yellow River Basin (MRYRB) has been warm and dry in recent years, with frequent droughts. In order to investigate the temporal trend of drought, and reveal the resistance of vegetation to drought in the MRYRB, this study used remotely-sensed vegetation index products (MODIS-NDVI and SPOT-NDVI) and the standardized precipitation evapotranspiration index (SPEI). The results indicated that: (1) drought intensity showed a weak upward trend in the study area from 2000 to 2018, with linear growth rates of SPEI at temporal scales of 1, 3, 6, 9 and 12 months of −0.002, 0.0034, 0.0198, 0.0234, and 0.0249, respectively; (2) drought was positively correlated with vegetation in most areas (97.6%), and vegetation was most affected by drought on long-term time scales (9 and 12 months); (3) with the extension of drought, vegetation resistance index decreased, then gradually recovered after the end of the drought. Forest had the longest resistance duration of 260 days, while grassland and cultivated land had resistance durations of only 170 days. This study adds to the understanding of vegetation’s ability to withstand drought, and these findings provide evidence to support drought response in the MRYRB.
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Li, Weilong, Jianjun Wang, Yuting Zhang, Quan Yin, Weiling Wang, Guisheng Zhou e Zhongyang Huo. "Combining Texture, Color, and Vegetation Index from Unmanned Aerial Vehicle Multispectral Images to Estimate Winter Wheat Leaf Area Index during the Vegetative Growth Stage". Remote Sensing 15, n. 24 (13 dicembre 2023): 5715. http://dx.doi.org/10.3390/rs15245715.
Abstract (sommario):
Leaf Area Index (LAI) is a fundamental indicator of plant growth status in agronomy and environmental research. With the rapid development of drone technology, the estimation of crop LAI based on drone imagery and vegetation indices is becoming increasingly popular. However, there is still a lack of detailed research on the feasibility of using image texture to estimate LAI and the impact of combining texture indices with vegetation indices on LAI estimation accuracy. In this study, two key growth stages of winter wheat (i.e., the stages of green-up and jointing) were selected, and LAI was calculated using digital hemispherical photography. The feasibility of predicting winter wheat LAI was explored under three conditions: vegetation index, texture index, and a combination of vegetation index and texture index, at flight heights of 20 m and 40 m. Two feature selection methods (Lasso and recursive feature elimination) were combined with four machine learning regression models (multiple linear regression, random forest, support vector machine, and backpropagation neural network). The results showed that during the vegetative growth stage of winter wheat, the model combining texture information with vegetation indices performed better than the models using vegetation indices alone or texture information alone. Among them, the best prediction result based on vegetation index was RFECV-MLR at a flight height of 40 m (R2 = 0.8943, RMSE = 0.4139, RRMSE = 0.1304, RPD = 3.0763); the best prediction result based on texture index was RFECV-RF at a flight height of 40 m (R2 = 0.8894, RMSE = 0.4236, RRMSE = 0.1335, RPD = 3.0063); and the best prediction result combining texture and index was RFECV-RF at a flight height of 40 m (R2 = 0.9210, RMSE = 0.3579, RRMSE = 0.1128, RPD = 3.5575). The results of this study demonstrate that combining vegetation indices and texture from multispectral drone imagery can improve the accuracy of LAI estimation during the vegetative growth stage of winter wheat. In addition, selecting a flight height of 40 m can improve efficiency in large-scale agricultural field monitoring, as this study showed that drone data at flight heights of 20 m and 40 m did not significantly affect model accuracy.
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Machar, Ivo, Veronika Vlckova, Lubomir Salek, Vilem Pechanec, Arkadiusz Nowak, Sylwia Nowak, Vitezslav Plasek, Juraj Svajda, Zdenek Oprsal e Osman Topacoglu. "Environmental Modelling of Forest Vegetation Zones as A Support Tool for Sustainable Management of Central European Spruce Forests". Journal of Landscape Ecology 11, n. 3 (1 dicembre 2018): 45–63. http://dx.doi.org/10.2478/jlecol-2018-0012.
Abstract (sommario):
Abstract The impact of climate change on forest ecosystems may manifest itself by a shift in forest vegetation zones in the landscape northward and into higher elevations. Studies of climate change-induced vegetation zone shifts in forest ecosystems have been relatively rare in the context of European temperate zone (apart from Alpine regions). The presented paper outlines the results of a biogeographic model of climatic conditions in forest vegetation zones applied in the Central European landscape. The objective of the study is a prediction of future silvicultural conditions for the Norway spruce (Picea abies L. Karst.), which is one of the principal tree species within European forests. The model is based on a general environmental dependence of forest vegetation zones on the long-term effect of altitudinal and exposure climates defined by the mean and extreme air temperatures and the amount and distribution of atmospheric precipitation. The climatological data for the model were provided by a validated regional climate database for 2010 – 2090 according to the SRES A1B scenario, bound to specific geo-referenced points in the landscape. The geobiocoenological data in the model were provided by the Biogeography Register database which contains ecological data on the landscape bound to individual cadastres of the entire Czech Republic. The biogeographic model applies special programs (the FORTRAN programming language) in the environment of geographic information systems. The model outputs can be clearly graphically visualized as scenarios of predicted future climatic conditions of landscape vegetation zones. Modelling of the regional scenario of changes in the climatic conditions of forest vegetation zones reveals that in the prediction period of 2070 and beyond, good and very good climatic conditions for the cultivation of forests with dominant Norway spruce will be found only in some parts of its today’s native range in forest vegetation zones 5 – 8. Based on the results provided by the regional scenario, the authors of this paper recommend fundamental reassessment of the national strategy of sustainable forest management in the Czech Republic, stipulating that the current practice of spruce cultivation be reduced only to areas specifically defined by the biogeographic model. The paper shows that biogeographic models based on the concept of vegetation zoning can be applied not only in regional scenarios of climate change in the landscape but also as support tools for the creation of strategies of sustainable forest management.
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Kalinowska, Monika Barbara, Kaisa Västilä, Michael Nones, Adam Kiczko, Emilia Karamuz, Andrzej Brandyk, Adam Kozioł e Marcin Krukowski. "Influence of vegetation maintenance on flow and mixing: case study comparing fully cut with high-coverage conditions". Hydrology and Earth System Sciences 27, n. 4 (2 marzo 2023): 953–68. http://dx.doi.org/10.5194/hess-27-953-2023.
Abstract (sommario):
Abstract. In temperate climates, agricultural ditches are generally bounded by seasonal vegetation, which affects the hydrodynamics and mixing processes within the channel and acts as a buffer strip to reduce a load of pollutants coming from the surrounding cultivated fields. However, even if the control of such vegetation represents a key strategy to support sediment and nutrient management, the studies that investigated the effect of different vegetation maintenance scenarios or vegetation coverage on the flow and mixing dynamics at the reach scale are very limited. To overcome these limitations and provide additional insights into the involved processes, tracer tests were conducted in an agricultural ditch roughly 500 m long close to Warsaw in Poland, focusing on two different vegetation scenarios: highly vegetated and fully cut. Under the highly vegetated scenario, sub-reaches differing in surficial vegetation coverage are analysed separately to better understand the influence of the vegetation conditions on the flow and mixing parameters. Special attention has been paid to the longitudinal dispersion coefficient in complex natural conditions and its dependency on vegetation coverage (V). The vegetation maintenance decreased the travel and residence times of the solute by 3–5 times, moderately increasing the peak concentrations. We found that the dispersion coefficient decreased approximately linearly with the increase of vegetation coverage at V>68 %. Further research is needed at lower vegetation coverage values and different spatial plant distributions. The obtained longitudinal dispersion coefficient values complement dispersion value datasets previously published in the literature, which are barely available for small natural streams. The new process understanding supports the design of future investigations with more environmentally sound vegetation maintenance scenarios.
27
Nuijten, Rik J. G., Nicholas C. Coops, Catherine Watson e Dustin Theberge. "Monitoring the Structure of Regenerating Vegetation Using Drone-Based Digital Aerial Photogrammetry". Remote Sensing 13, n. 10 (16 maggio 2021): 1942. http://dx.doi.org/10.3390/rs13101942.
Abstract (sommario):
Measures of vegetation structure are often key within ecological restoration monitoring programs because a change in structure is rapidly identifiable, measurements are straightforward, and structure is often a good surrogate for species composition. This paper investigates the use of drone-based digital aerial photogrammetry (DAP) for the characterization of the structure of regenerating vegetation as well as the ability to inform restoration programs through spatial arrangement assessment. We used cluster analysis on five DAP-derived metrics to classify vegetation structure into seven classes across three sites of ongoing restoration since linear disturbances in 2005, 2009, and 2014 in temperate and boreal coniferous forests in Alberta, Canada. The spatial arrangement of structure classes was assessed using land cover maps, mean patch size, and measures of local spatial association. We observed DAP heights of short-stature vegetation were consistently underestimated, but strong correlations (rs > 0.75) with field height were found for juvenile trees, shrubs, and perennials. Metrics of height and canopy complexity allowed for the extraction of relatively tall and complex vegetation structures, whereas canopy cover and height variability metrics enabled the classification of the shortest vegetation structures. We found that the boreal site disturbed in 2009 had the highest cover of classes associated with complex vegetation structures. This included early regenerative (22%) and taller (13.2%) wood-like structures as well as structures representative of tall graminoid and perennial vegetation (15.3%), which also showed the highest patchiness. The developed tools provide large-scale maps of the structure, enabling the identification and assessment of vegetational patterns, which is challenging based on traditional field sampling that requires pre-defined location-based hypotheses. The approach can serve as a basis for the evaluation of specialized restoration objectives as well as objectives tailored towards processes of ecological succession, and support prioritization of future inspections and mitigation measures.
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Mahdi Elsiddig Haroun, Fathi, Siti Noratiqah Mohamed Deros, Mohd Zafri Bin Baharuddin e Norashidah Md Din. "Detection of Vegetation Encroachment in Power Transmission Line Corridor from Satellite Imagery Using Support Vector Machine: A Features Analysis Approach". Energies 14, n. 12 (9 giugno 2021): 3393. http://dx.doi.org/10.3390/en14123393.
Abstract (sommario):
Vegetation encroachment along electric power transmission lines is one of the major environmental challenges that can cause power interruption. Many technologies have been used to detect vegetation encroachment, such as light detection and ranging (LiDAR), synthetic aperture radar (SAR), and airborne photogrammetry. These methods are very effective in detecting vegetation encroachment. However, they are expensive with regard to the coverage area. Alternatively, satellite imagery can cover a wide area at a relatively lower cost. In this paper, we describe the statistical moments of the color spaces and the textural features of the satellite imagery to identify the most effective features that can increase the vegetation density classification accuracy of the support vector machine (SVM) algorithm. This method aims to distinguish between high- and low-density vegetation regions along the power line corridor right-of-way (ROW). The results of the study showed that the statistical moments of the color spaces contribute positively to the classification accuracy while some of the gray level co-occurrence matrix (GLCM) features contribute negatively to the classification accuracy. Therefore, a combination of the most effective features was used to achieve a recall accuracy of 98.272%.
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Cienciala, Piotr. "Vegetation and Geomorphic Connectivity in Mountain Fluvial Systems". Water 13, n. 5 (25 febbraio 2021): 593. http://dx.doi.org/10.3390/w13050593.
Abstract (sommario):
Rivers are complex biophysical systems, constantly adjusting to a suite of changing governing conditions, including vegetation cover within their basins. This review seeks to: (i) highlight the crucial role that vegetation’s influence on the efficiency of clastic material fluxes (geomorphic connectivity) plays in defining mountain fluvial landscape’s behavior; and (ii) identify key challenges which hinder progress in the understanding of this subject. To this end, a selective literature review is carried out to illustrate the pervasiveness of the plants’ effects on geomorphic fluxes within channel networks (longitudinal connectivity), as well as between channels and the broader landscape (lateral connectivity). Taken together, the reviewed evidence lends support to the thesis that vegetation-connectivity linkages play a central role in regulating geomorphic behavior of mountain fluvial systems. The manuscript is concluded by a brief discussion of the need for the integration of mechanistic research into the local feedbacks between plants and sediment fluxes with basin-scale research that considers emergent phenomena.
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Wahyuningrum, Nining, Agung Budi Supangat e Diah Auliyani. "Biophysical landscape characterization of the upper pacal reservoir to support its sustainable management". IOP Conference Series: Earth and Environmental Science 1109, n. 1 (1 novembre 2022): 012081. http://dx.doi.org/10.1088/1755-1315/1109/1/012081.
Abstract (sommario):
Abstract Pacal Reservoir provides irrigation to a total area of 16,688 hectares. Because of its critical importance for the downstream, activities in the upstream must be carefully controlled to maintain their functions. Information on the basic characteristics of landscape conditions is essential at the earliest stage of planning for sustainable land management. This paper aims to determine the characteristics of the upstream Pacal Reservoir and to analyze the areas that are likely suffering from degradation and contributing sediment. Thematic maps such as Area Function, Land Systems, Administration, Roads, and Rivers were used as well as Digital Elevation Model and Google Earth Imagery. The distribution of permanent vegetation, erosion hazard, the proper use of area function with actual land cover, and landslide hazard were investigated further. The spatial analysis indicates a moderate to very severe erosion hazard distributed in all land cover types. Deviations are in protected and production forest areas (2.15%) Land with a slope of >15% should be covered by permanent vegetation but used for seasonal covers (3.65%). Landslide hazards are low and moderate. Land rehabilitation is recommended mainly by maintaining/adding permanent vegetation in the degraded and potentially degraded areas.
31
Johnson, J. Bradley. "Phytosociology and gradient analysis of a subalpine treed fen in Rocky Mountain National Park, Colorado". Canadian Journal of Botany 74, n. 8 (1 agosto 1996): 1203–13. http://dx.doi.org/10.1139/b96-145.
Abstract (sommario):
The vegetation of a subalpine fen in Colorado was studied. Insight was sought into the community structure and factors influencing species distribution of a vegetation type heretofore undescribed in the southern Rocky Mountains. A vegetational gradient was evaluated using detrended correspondence analysis (DCA). Four types of vegetation were subjectively defined; these same types were distinguished by the DCA. DCA further revealed marked differences in the vegetation occurring on peat hummocks versus in hollows. Species composition was related to environment using canonical correspondence analysis (CCA). Water-table depth, hummock height, shading, groundwater temperature, and conductivity were significantly correlated with species distribution, accounting for 51% of the total species variance. Univariate regression was used to examine how tree density varied with environment. The above factors, except for shading and conductivity, were also significantly correlated with tree density. It is suggested that the peat hummocks that form on this moderate fen provide an environment similar to that of an ombrotrophic bog and that these "miniature bogs" form in areas unable to support expansive bogs. Further, these hummocks provide small-scale environmental heterogeneity that exerts a strong control over species composition that would not be evident in studies based on samples of a large areal extent. Keywords: Colorado, gradient analysis, ordination, heterogeneity, peatlands, phytosociology.
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Lwin, A., D. Yang, X. Hong, S. Cheraghi Shamsabadi e W. A. Ahmed. "SPACEBORNE GNSS-R RETRIEVING ON GLOBAL SOIL MOISTURE APPROACHED BY SUPPORT VECTOR MACHINE LEARNING". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (21 agosto 2020): 605–10. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-605-2020.
Abstract (sommario):
Abstract. GNSS Reflectometry system is an excellent to sense soil moisture content. In recent, GNSS-R technique could be aided to detect soil moisture contents but still have many difficulities issues, most especially vegetation impact. Soil moisture observing is a major concept for enhancing the sustainability of the earth’s system and process. On retrieving soil moisture from spaceborne GNSS-R technology has been challenging to the system, retrieving model and geophysical parameters. In this research, we use the Support Vector Machine (SVM) method to retrieve global soil moisture, the TDS-1 Delay Doppler Map (DDM) and the AVHRR Normalized Difference Vegetation Index (NDVI) imagery as inputs and the Soil Moisture and Ocean Salinity (SMOS) soil moisture data as a reference to retrieve global SM daily basis. The results have shown that the squared correlation coefficient (R) values are much higher in TDS-1 fused with NDVI than using DDM alone, which indicates that vegetation impact has effectively weakened. The feasibility of this approach could provide the performance for spaceborne GNSS-R retrieving to soil moisture analysis.
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Anderson, Patricia M., Richard E. Reanier e Linda B. Brubaker. "Late Quaternary vegetational history of the Black River region in northeastern Alaska". Canadian Journal of Earth Sciences 25, n. 1 (1 gennaio 1988): 84–94. http://dx.doi.org/10.1139/e88-009.
Abstract (sommario):
Two pollen diagrams describe the previously unknown vegetational history of the Black River and Little Black River drain ages of northeastern Alaska. Tundra grew throughout much of the region between ca. 19 800 and 15 000 years BP. Prior to 18 000 years BP, the vegetation was dominated perhaps by xeric Cyperaceae communities, but apparently between ca. 18 000 and 15 000 years BP a more diverse herb tundra characterized the vegetation. Herbaceous species continued to be important in the vegetation until ca. 9700 years BP, although Betula nana–glandulosa and Salix species became more common after 15 000 years BP. At ca. 9700 years BP a major change in the vegetation occurred with the spread of Populus (probably P. balsamifera), B. nana–glandulosa, and Salix, possibly resulting in a mosaic of shrub tundra and Populus gallery forest. Picea glauca migrated into the Black River region ca. 7500 years BP, followed by Alnus ca. 7200 years BP and Picea mariana ca. 6000 years BP.Herb zone records from the Black River region support the hypothesis that eastern Beringian vegetation was characterized by a tundra mosaic prior to 14 000 years BP. Chronological and geographical patterns in the Populus subzone from eastern Beringia suggest that the expansion of Populus populations may not have been exclusively in response to climate change. Dates of Picea arrival on the western Porcupine Plateau indicate that this area probably was not an early Holocene migration route for Picea.
34
Xu, Xue, Luyao Liu, Peng Han, Xiaoqian Gong e Qing Zhang. "Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV". International Journal of Environmental Research and Public Health 19, n. 24 (14 dicembre 2022): 16793. http://dx.doi.org/10.3390/ijerph192416793.
Abstract (sommario):
Grassland desertification has become one of the most serious environmental problems in the world. Grasslands are the focus of desertification research because of their ecological vulnerability. Their application on different grassland desertification grades remains limited. Therefore, in this study, 19 vegetation indices were calculated for 30 unmanned aerial vehicle (UAV) visible light images at five grades of grassland desertification in the Mu Us Sandy. Fractional Vegetation Coverage (FVC) with high accuracy was obtained through Support Vector Machine (SVM) classification, and the results were used as the reference values. Based on the FVC, the grassland desertification grades were divided into five grades: severe (FVC < 5%), high (FVC: 5–20%), moderate (FVC: 21–50%), slight (FVC: 51–70%), and non-desertification (FVC: 71–100%). The accuracy of the vegetation indices was assessed by the overall accuracy (OA), the kappa coefficient (k), and the relative error (RE). Our result showed that the accuracy of SVM-supervised classification was high in assessing each grassland desertification grade. Excess Green Red Blue Difference Index (EGRBDI), Visible Band Modified Soil Adjusted Vegetation Index (V-MSAVI), Green Leaf Index (GLI), Color Index of Vegetation Vegetative (CIVE), Red Green Blue Vegetation Index (RGBVI), and Excess Green (EXG) accurately assessed grassland desertification at severe, high, moderate, and slight grades. In addition, the Red Green Ratio Index (RGRI) and Combined 2 (COM2) were accurate in assessing severe desertification. The assessment of the 19 indices of the non-desertification grade had low accuracy. Moreover, our result showed that the accuracy of SVM-supervised classification was high in assessing each grassland desertification grade. This study emphasizes that the applicability of the vegetation indices varies with the degree of grassland desertification and hopes to provide scientific guidance for a more accurate grassland desertification assessment.
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Alfian, Rizki, e Nuraini Nuraini. "Kajian Tingkat Kenyamanan Berdasarkan Termal Humidity Index (THI) Lanskap Jalan Soekarno Hatta Kota Malang". BUANA SAINS 19, n. 1 (11 ottobre 2019): 47. http://dx.doi.org/10.33366/bs.v19i1.1526.
Abstract (sommario):
Streets as part of the city's landscape that support the function and activities of the city. Each street in the city area has a streetscape which aims to support the users activities. Soekarno Hatta street is one of the protocol street in Malang city with the track area which is quite famous and one of the loud route in Malang City. This research aims to: 1) identify vegetation on the streetscape on Soekarno Hatta street; 2) analyze thermal comfort on the Soekarno-Hatta streetscape. Based on the observation, it is known that the trembesi population dominates at the Soekarno Hatta streetscape. Soekarno Hatta street has an average temperature of 31.1 ° C and an average humidity of 57%. Soekarno Hatta street has THI value of 28.43 whereas THI value which is categorized as comfortable is between 21 - 27. Based on the physical observation on Soekarno Hatta streetscape needs to be done vegetation arrangement because the vegetation in Soekarno Hatta Street has a high density of trees that will interfere with canopy growth when reaching the maximum size. Selection of appropriate shade vegetation and regular maintenance is expected to improve the comfort level in each way. In addition to vegetation, the physical condition of the pedestrian on Soekarno Hatta Road also needs a redesign to support the comfort of pedestrians.
36
Parracciani, Cecilia, Daniela Gigante, Federica Bonini, Anna Grassi, Luciano Morbidini, Mariano Pauselli, Bernardo Valenti, Emanuele Lilli, Francesco Antonielli e Marco Vizzari. "Leveraging Google Earth Engine for a More Effective Grassland Management: A Decision Support Application Perspective". Sensors 24, n. 3 (27 gennaio 2024): 834. http://dx.doi.org/10.3390/s24030834.
Abstract (sommario):
Grasslands cover a substantial portion of the earth’s surface and agricultural land and is crucial for human well-being and livestock farming. Ranchers and grassland management authorities face challenges in effectively controlling herders’ grazing behavior and grassland utilization due to underdeveloped infrastructure and poor communication in pastoral areas. Cloud-based grazing management and decision support systems (DSS) are needed to address this issue, promote sustainable grassland use, and preserve their ecosystem services. These systems should enable rapid and large-scale grassland growth and utilization monitoring, providing a basis for decision-making in managing grazing and grassland areas. In this context, this study contributes to the objectives of the EU LIFE IMAGINE project, aiming to develop a Web-GIS app for conserving and monitoring Umbria’s grasslands and promoting more informed decisions for more sustainable livestock management. The app, called “Praterie” and developed in Google Earth Engine, utilizes historical Sentinel-2 satellite data and harmonic modeling of the EVI (Enhanced Vegetation Index) to estimate vegetation growth curves and maturity periods for the forthcoming vegetation cycle. The app is updated in quasi-real time and enables users to visualize estimates for the upcoming vegetation cycle, including the maximum greenness, the days remaining to the subsequent maturity period, the accuracy of the harmonic models, and the grassland greenness status in the previous 10 days. Even though future additional developments can improve the informative value of the Praterie app, this platform can contribute to optimizing livestock management and biodiversity conservation by providing timely and accurate data about grassland status and growth curves.
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Štroner, Martin, Rudolf Urban e Tomáš Suk. "Filtering Green Vegetation Out from Colored Point Clouds of Rocky Terrains Based on Various Vegetation Indices: Comparison of Simple Statistical Methods, Support Vector Machine, and Neural Network". Remote Sensing 15, n. 13 (24 giugno 2023): 3254. http://dx.doi.org/10.3390/rs15133254.
Abstract (sommario):
Filtering out vegetation from a point cloud based on color is only rarely used, largely due to the lack of knowledge of the suitability of input information (color, vegetation indices) and the thresholding methods. We have evaluated multiple vegetation indices (ExG, ExR, ExB, ExGr, GRVI, MGRVI, RGBVI, IKAW, VARI, CIVE, GLI, and VEG) and combined them with 10 methods of threshold determination based on training set selection (including machine learning methods) and the renowned Otsu’s method. All these combinations were applied to four clouds representing vegetated rocky terrain, and the results were compared. The ExG and GLI indices were generally the most suitable for this purpose, with the best F-scores of 97.7 and 95.4, respectively, and the best-balanced accuracies for the same combination of the method/vegetation index of 98.9 and 98.3%, respectively. Surprisingly, these best results were achieved using the simplest method of threshold determination, considering only a single class (vegetation) with a normal distribution. This algorithm outperformed all other methods, including those based on a support vector machine and a deep neural network. Thanks to its simplicity and ease of use (only several patches representing vegetation must be manually selected as a training set), this method can be recommended for vegetation removal from rocky and anthropogenic surfaces.
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Putra, Erianto Indra, Robi D. Waldi, Ahmad Rifaldo, Yovielachicha Khairunisa, Deya Akmalia, Siti Labora Siburian, Rian Dwirizqi Mifhathul Huda et al. "Assessing Vegetation Density to Determine Green Open Space (RTH) in Bogor Regency". Journal of Tropical Silviculture 14, n. 03 (28 dicembre 2023): 268–72. http://dx.doi.org/10.29244/j-siltrop.14.03.268-272.
Abstract (sommario):
Green Open Space (RTH) is part of the open spaces of an urban area filled with plants and vegetation to support ecological, socio-cultural, and architectural benefits. An approach that can be done to determine green open space is by analyzing the density of vegetation. The minimum distribution of vegetation in an urban area should be 30% of the total area. This vegetation distribution can be calculated using Landsat 8 imagery. This research was conducted to determine Green Open Space in Bogor Regency by using Landsat 8 imagery. This study clearly showed that some areas in Bogor Regency are still having lack of vegetation, bring a need to develop green open spaces in the areas.
Keywords: Landsat 8 imagery, Bogor Regency, Green Open Space, Vegetation
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Thierion, Vincent, Samuel Alleaume, Christine Jacqueminet, Christelle Vigneau, Kristell Michel e Sandra Luque. "The potential of Pléiades imagery for vegetation mapping: an example of grasslands and pastoral environments". Revue Française de Photogrammétrie et de Télédétection, n. 208 (23 ottobre 2014): 105–10. http://dx.doi.org/10.52638/rfpt.2014.124.
Abstract (sommario):
Nowadays the use of remote sensing for vegetation mapping over large areas is becoming progressively common, with the increase of satellites providing a good trade-off between metric spatial resolution and large swath (e.g. Spot 5, RapidEye). In France, the government launched an ambitious project to map all terrestrial habitats of the national territory. — Thus, CarHAB project uses remote sensing technology to support field work and ground observations for vegetation mapping in support to the 11 National Botanical Conservatories working on the whole of French territory. For this purpose, a physiognomic typology has been produced. This typology captures the intrinsic structure of vegetation and potentially its land use. In order to improve semantic and geometric accuracy of the vegetation cover, the use of infra-metric imagery, such as the ones provided by Pléiades constellation offer valuable insights. This imagery offers visual and geometric potentialities closed to aerial photos but with the advantage of better spectral information. Results presented in this research focus on physiognomic mapping of natural and semi-natural vegetation of pasture, grasslands and farmland areas in Isere Department in France. The potentialities of Pléiades imagery are demonstrated by evaluating separability capabilities of textural analysis of woody and herbaceous habitats and vegetation associated to screes.
40
Li, Xijia, Ying Qu e Zhiqiang Xiao. "Reponses of Land Surface Albedo to Global Vegetation Greening: An Analysis Using GLASS Data". Atmosphere 14, n. 1 (24 dicembre 2022): 31. http://dx.doi.org/10.3390/atmos14010031.
Abstract (sommario):
Global vegetation greening during recent decades has been observed from various remote sensing data. The global and regional climate can be altered by an increase in carbon storage, as well as changes in land surface albedo (LSA) and evaporation. However, the LSA changes induced by global vegetation greening are still not clear, and contrasting responses of LSA to vegetation changes were reported in previous studies. In this study, we analyzed the LSA in response to global vegetation greening using the Global Land Surface Satellite (GLASS) data and a vegetation-induced LSA change model. The results showed that vegetation greening trends could be observed worldwide, which resulted in contrasting LSA responses at regional scales (LSA increased as leaf area index (LAI) increased, or LSA decreased as LAI increased). Moreover, these contrasting LSA responses to global vegetation greening were effectively explained by the albedo difference between a vegetation and soil background. The results provide new insights into the relationship between LSA changes and global vegetation dynamics, and can support recommendations for policies of vegetation protection, and large-scale afforestation and deforestation.
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Wulandari, Sri. "Arboretum as Carbon Stock and Carbon dioxide Uptake to Support the Realization of Green Campus at Riau University". International Journal of Ecophysiology 2, n. 1 (19 maggio 2020): 11–17. http://dx.doi.org/10.32734/ijoep.v2i1.3983.
Abstract (sommario):
The University of Riau Arboretum is one of the natural environments contained within the campus, having various types of vegetation that can be utilized to support the realization of a green campus. This study aims to determine the benefits of arboretum as carbon reserves and CO2 uptake to support the realization of Riau University's green campus. Research using survey methods by observing in the arboretum. Determination of sampling locations by purposive random sampling by considering the condition of vegetation and topography. Research parameters are: (1) vegetation analysis; (2) carbon stocks and (3) CO2 uptake. The University of Riau Arboretum has a vegetation composition in all strata, namely seedlings, saplings, poles and trees. The number of individual seedlings is higher than other strata, namely 349 individuals. Diversity index in all strata classified as high criteria ranged from 3.22 to 3.42. The total carbon stock of 1.12 tons / ha and CO2 absorption of 4.11 tons / ha, with the arboretum of Riau University (± 10 ha), the CO2 absorption that occurs is 41.1 tons. Thus the existence of arboretum can be used to further optimize its function as carbon reserves and CO2 absorption in realizing the green campus program of the University of Riau.Arboretum
42
Mulley, Maggie, Lammert Kooistra e Laurens Bierens. "High-Resolution Multisensor Remote Sensing to Support Date Palm Farm Management". Agriculture 9, n. 2 (31 gennaio 2019): 26. http://dx.doi.org/10.3390/agriculture9020026.
Abstract (sommario):
Date palms are a valuable crop in areas with limited water availability such as the Middle East and sub-Saharan Africa, due to their hardiness in tough conditions. Increasing soil salinity and the spread of pests including the red palm weevil (RPW) are two examples of growing threats to date palm plantations. Separate studies have shown that thermal, multispectral, and hyperspectral remote sensing imagery can provide insight into the health of date palm plantations, but the added value of combining these datasets has not been investigated. The current study used available thermal, hyperspectral, Light Detection and Ranging (LiDAR) and visual Red-Green-Blue (RGB) images to investigate the possibilities of assessing date palm health at two “levels”; block level and individual tree level. Test blocks were defined into assumed healthy and unhealthy classes, and thermal and height data were extracted and compared. Due to distortions in the hyperspectral imagery, this data was only used for individual tree analysis; methods for identifying individual tree points using Normalized Difference Vegetation Index (NDVI) maps proved accurate. A total of 100 random test trees in one block were selected, and comparisons between hyperspectral, thermal and height data were made. For the vegetation index red-edge position (REP), the R-squared value in correlation with temperature was 0.313 and with height was 0.253. The vegetation index—the Vogelmann Red Edge Index (VOGI)—also has a relatively strong correlation value with both temperature (R2 = 0.227) and height (R2 = 0.213). Despite limited field data, the results of this study suggest that remote sensing data has added value in analyzing date palm plantations and could provide insight for precision agriculture techniques.
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Ingram, J. Carter, e Terence P. Dawson. "Climate change impacts and vegetation response on the island of Madagascar". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 363, n. 1826 (15 gennaio 2005): 55–59. http://dx.doi.org/10.1098/rsta.2004.1476.
Abstract (sommario):
The island of Madagascar has been labelled the world's number one conservation ‘hot spot’ because of increasing anthropogenic degradation of its natural habitats, which support a high level of species endemism. However, climatic phenomena may also have a significant impact upon the island's flora and fauna. An analysis of 18 years of monthly satellite images from the National Oceanographic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometer (AVHRR) have demonstrated that there is a dynamic pattern in Madagascar's vegetative cover both annually and seasonally throughout 1982–1999. Over interannual time–scales, we show that this vegetation response, calculated using the normalized difference vegetation index (NDVI), has a strong negative correlation with the El Niño Southern Oscillation (ENSO), which can be attributable to drought events and associated wildfires. Global climate change is predicted to increase the frequency of the ENSO phenomenon, resulting in further decline of Madagascar's natural environment.
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Zaitsev, Andrey A., Georgiy A. Voronov, Svetlana А. Kulakova e Julia L. Mishlanova. "ASSESSMENT OF THE STATE OF VEGETATION AND ANIMAL POPULATION IN FORESTED AREAS: METHODOLOGICAL APPROACH IN SUSTAINABLE DESIGN". Географический вестник = Geographical bulletin, n. 4(55) (2020): 137–51. http://dx.doi.org/10.17072/2079-7877-2020-4-137-151.
Abstract (sommario):
Materials for environmental impact assessment must contain a description of vegetation and animal population, and an assessment of possible changes in the components caused by human impact. Methodological support for such works is poorly developed in Russia, so there are difficulties in preparing these sections of pre-project documentation for environmentally sustainable design. The purpose of the research is to develop requirements for describing and evaluating vegetation and animal population when performing an environmental impact assessment (EIA). The article offers the authors' approach and provides a list of criteria for the successful development of sections for assessing the state of vegetation and animal population in sustainable design. The proposed approach is based on the authors' personal experience and generalization of existing methods, techniques and regulatory support.
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Pan, Tong, Xiao Jing Li, Hao Peng Wang e Kai Zhao. "Research on LAI Retrieving Applied for Virtual Reality Simulation of Vegetation". Applied Mechanics and Materials 263-266 (dicembre 2012): 1473–77. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1473.
Abstract (sommario):
It is the key process for developing usability of virtual reality simulation of vegetation taking into account soil, chemistry elements of water, temperature and humidity of land surface, and lighting. Retrieving the characteristics of vegetation from remote sensing data effectively and exactly, building the relationship between remote sensing data and interfaces of VR-vegetation models are important. The paper discusses dense vegetation model, nondense vegetation model, and two-stream approximation model applied for LAI retrieving, analyzes the efficiency of the methods; presents the process and method of LAI retrieving based on FPAR. The research offers the key methods and theoretic support for virtual reality simulation of vegetation based on spatial remote sensing information. The research is the primary work of digital agriculture, and important for monitoring corn growth and estimating in northeast of China.
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Moura, Ana Clara M., e Bráulio M. Fonseca. "ESDA (Exploratory Spatial Data Analysis) of Vegetation Cover in Urban Areas—Recognition of Vulnerabilities for the Management of Resources in Urban Green Infrastructure". Sustainability 12, n. 5 (3 marzo 2020): 1933. http://dx.doi.org/10.3390/su12051933.
Abstract (sommario):
From the mapping of urban vegetation cover by high-resolution orthoimages, using IR band and NDVI classification (Normalized Difference Vegetation Index), added to three-dimensional representation obtained by LiDAR capture (Light Detection and Ranging), the volumetric values of vegetal cover are obtained as a base to construct spatial analysis in the district of Pampulha, in Belo Horizonte, investigating the role it plays in the neighborhood. The article aims to analyze the relationship between vegetation cover, income distribution and population density, as a support to urban environmental quality management. It applies Exploratory Spatial Data Analysis (ESDA) to identify the presence of clusters and patterns of spatial distribution and to examine spatial autocorrelation. The results confirm the concentration of vegetation cover in areas of high income and lower population density but the main contribution of the study is the use of a method to analyze the spatial behavior of this distribution. Calculating Moran global index and local index (LISA), these spatial combinations are mainly used to identify transformation pressures, which may result in the definition of priorities for public actions and the construction of proposals for parameterization of vegetation cover to support plans related to green infrastructure in urban areas.
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SUZUKI, Masatomo, Yoichi KAGEYAMA, Chikako ISHIZAWA, Makoto NISHIDA, Koshi SATO, Mitsuyoshi KANEKO e Takashi NAGAKI. "Generating Learning Data for Hierarchical Vegetation Classification Methods using Support Vector Machine". International Journal of the Society of Materials Engineering for Resources 23, n. 2 (30 settembre 2018): 215–19. http://dx.doi.org/10.5188/ijsmer.23.215.
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Miller, Mary Ellen, Michael Lefsky e Yong Pang. "Optimization of Geoscience Laser Altimeter System waveform metrics to support vegetation measurements". Remote Sensing of Environment 115, n. 2 (15 febbraio 2011): 298–305. http://dx.doi.org/10.1016/j.rse.2010.09.002.
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KAWAGUCHI, Shuya, Hiroshi MIZOGUCHI, Ryohei Egusa, Yoshiaki Takeda, Etsuji Yamaguchi, Shigenori Inagaki, Fusako Kusunoki, Hideo Funaoi e Masanori Sugimoto. "Study on Vegetation Succession Learning Support System Using a Forest Management Game". Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2018 (2018): 2P2—B06. http://dx.doi.org/10.1299/jsmermd.2018.2p2-b06.
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Dong, L., H. Jiang e L. Yang. "SPATIO-TEMPORAL CHANGE OF VEGETATION COVERAGE AND ITS DRIVING FORCES BASED ON LANDSAT IMAGES: A CASE STUDY OF CHANGCHUN CITY". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (30 aprile 2018): 295–98. http://dx.doi.org/10.5194/isprs-archives-xlii-3-295-2018.
Abstract (sommario):
Based on the Landsat images in 2006, 2011 and 2015, and the method of dimidiate pixel model, the Normalized Difference Vegetation Index (NDVI) and the vegetation coverage, this paper analyzes the spatio-temporal variation of vegetation coverage in Changchun, China from 2006 to 2015, and investigates the response of vegetation coverage change to natural and artificial factors. The research results show that in nearly 10 years, the vegetation coverage in Changchun dropped remarkably, and reached the minimum in 2011. Moreover, the decrease of maximum NDVI was significant, with a decrease of about 27.43&thinsp;%, from 2006 to 2015. The vegetation coverage change in different regions of the research area was significantly different. Among them, the vegetation change in Changchun showed a little drop, and it decreased firstly and then increased slowly in Yushu, Nong’an and Dehui. In addition, the temperature and precipitation change, land reclamation all affect the vegetation coverage. In short, the study of vegetation coverage change contributes scientific and technical support to government and environmental protection department, so as to promote the coordinated development of ecology and economy.