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Journal articles on the topic 'Suitability modelling'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Hirzel, Alexandre H., and Gwenaëlle Le Lay. "Habitat suitability modelling and niche theory." Journal of Applied Ecology 45, no. 5 (October 2008): 1372–81. http://dx.doi.org/10.1111/j.1365-2664.2008.01524.x.

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2

Koreň, Milan, Slavomír Find'o, Michaela Skuban, and Matúš Kajba. "Habitat suitability modelling from non-point data." Ecological Informatics 6, no. 5 (September 2011): 296–302. http://dx.doi.org/10.1016/j.ecoinf.2011.05.002.

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3

Kindt, R. "Ensemble species distribution modelling with transformed suitability values." Environmental Modelling & Software 100 (February 2018): 136–45. http://dx.doi.org/10.1016/j.envsoft.2017.11.009.

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4

Littleboy, M., D. M. Smith, and M. J. Bryant. "Simulation modelling to determine suitability of agricultural land." Ecological Modelling 86, no. 2-3 (May 1996): 219–25. http://dx.doi.org/10.1016/0304-3800(95)00055-0.

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5

Ray, Nicolas, and Mark A. Burgman. "Subjective uncertainties in habitat suitability maps." Ecological Modelling 195, no. 3-4 (June 2006): 172–86. http://dx.doi.org/10.1016/j.ecolmodel.2005.11.039.

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6

Dąbrowski, Tadeusz, Jerzy Chmiel, and Adam Rosiński. "Modelling of power supplies reliability in aspect of their technical and functional state." Journal of KONBiN 42, no. 1 (June 1, 2017): 191–208. http://dx.doi.org/10.1515/jok-2017-0025.

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Abstract The article presents issues related to the modeling of reliability of power supply in terms of their technical and functional condition. There are designated relations allowing to determine the probability of staying the power supply in the state: full suitability, incomplete suitability and unsuitability. There is also examined the impact of time restore of the state of full suitability for the value of the probability of staying the power supply in the state of incomplete suitability.

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7

Neilsen, D., S. Smith, G. Bourgeois, B. Qian, A. Cannon, G. Neilsen, and I. Losso. "Modelling changing suitability for tree fruits in complex terrain." Acta Horticulturae, no. 1160 (May 2017): 207–14. http://dx.doi.org/10.17660/actahortic.2017.1160.30.

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8

SUEL, H. "BROWN BEAR (URSUS ARCTOS) HABITAT SUITABILITY MODELLING AND MAPPING." Applied Ecology and Environmental Research 17, no. 2 (2019): 4245–55. http://dx.doi.org/10.15666/aeer/1702_42454255.

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9

Dabral, S., B. Bhatt, J. P. Joshi, and N. Sharma. "Groundwater suitability recharge zones modelling – A GIS application." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 347–53. http://dx.doi.org/10.5194/isprsarchives-xl-8-347-2014.

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Groundwater quality in Gujarat state is highly variable and due to multiplicity of factors viz. influenced by direct sea water encroachment, inherent sediment salinity, water logging, overexploitation leading to overall deterioration in ground water quality, coupled with domestic and industrial pollution etc. The groundwater scenario in the state is not very encouraging due to imbalance between recharge and groundwater exploitation. Further, the demand for water has increased manifold owing to agricultural, industrial and domestic requirement and this has led to water scarcity in many parts of the state, which is likely to become more severe in coming future due to both natural and manmade factors. Therefore, sustainable development of groundwater resource requires precise quantitative assessment based on reasonably valid scientific principles. Hence, delineation of groundwater potential zones (GWPZ), has acquired great significance. <br><br> The present study focuses on the integrated Geospatial and Multi-Criteria Decision Making (MCDM) techniques to determine the most important contributing factors that affect the groundwater resources and also to delineate the potential zones for groundwater recharge. The multiple thematic layers of influencing parameters viz. geology, geomorphology, soil, slope, drainage density and land use, weightages were assigned to the each factor according to their relative importance as per subject experts opinion owing to the natural setup of the region. The Analytical Hierarchy Process (AHP) was applied to these factors and potential recharge zones were identified. The study area for the assessment of groundwater recharge potential zones is Mahi-Narmada inter-stream region of Gujarat state. The study shows that around 28 % region has the excellent suitability of the ground water recharge.

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10

Jiménez‐Valverde, Alberto, Pedro Aragón, and Jorge M. Lobo. "Deconstructing the abundance–suitability relationship in species distribution modelling." Global Ecology and Biogeography 30, no. 1 (November 10, 2020): 327–38. http://dx.doi.org/10.1111/geb.13204.

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11

Streppel, A. H., L. J. de Vin, J. Brinkman, and H. J. J. Kals. "Suitability of sheet bending modelling techniques in CAPP applications." Journal of Materials Processing Technology 36, no. 3 (March 1993): 339–56. http://dx.doi.org/10.1016/0924-0136(93)90038-8.

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12

Lock, Koen, and Peter L. M. Goethals. "Habitat suitability modelling for mayflies (Ephemeroptera) in Flanders (Belgium)." Ecological Informatics 17 (September 2013): 30–35. http://dx.doi.org/10.1016/j.ecoinf.2011.12.004.

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13

Zohmann, Margit, Josef Pennerstorfer, and Ursula Nopp-Mayr. "Modelling habitat suitability for alpine rock ptarmigan (Lagopus muta helvetica) combining object-based classification of IKONOS imagery and Habitat Suitability Index modelling." Ecological Modelling 254 (April 2013): 22–32. http://dx.doi.org/10.1016/j.ecolmodel.2013.01.008.

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14

Vetharaniam, Indrakumar, Karin Müller, C. Jill Stanley, Carlo van den Dijssel, Levente Timar, and Brent Clothier. "Modelling Continuous Location Suitability Scores and Spatial Footprint of Apple and Kiwifruit in New Zealand." Land 11, no. 9 (September 9, 2022): 1528. http://dx.doi.org/10.3390/land11091528.

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Under climate change, land use suitability for horticultural production will change; this has prospects of both adverse socio-economic impacts for the industry in some regions, and beneficial impacts in others. Policy development and industry guidance are needed to develop adaptations to mitigate climate change risks and exploit new opportunities. For climate-change issues, models provide a powerful means for assessing future suitability at a patch, region or national scale in order to guide policy decisions. Here, we describe the development of a new continuous (sliding-scale) suitability modelling approach to assess the suitability of different locations for growing apple and kiwifruit in New Zealand, based on phenological and physiological considerations; these models used geographical information system (GIS) soil, land and weather data to develop maps showing the suitability of locations across New Zealand for cultivating apple and kiwifruit. The models were “ground-truthed” in an iterative process of expert parameterisation and recalibration to ensure maps aligned with current growing locations for the two crops. We estimated an econometric logit model that incorporated the continuous suitability scores as predictors of land use for apple and kiwifruit. Comparison of modelled suitability scores with industry-supplied maps of apple and kiwifruit orchards showed good consistency between predicted suitability and current land use. Compared with a range of alternative land uses, suitability for apple was highest for locations currently used to grow apple and suitability for kiwifruit was highest for locations currently used to grow kiwifruit. Our framework provides the capability to project incremental changes in the suitability of locations for apple and kiwifruit under different climate change pathways and to project consequential changes in their spatial footprints; this framework can be extended to other crops.

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15

Kidd, D. B., B. P. Malone, A. B. McBratney, B. Minasny, and M. A. Webb. "Digital mapping of a soil drainage index for irrigated enterprise suitability in Tasmania, Australia." Soil Research 52, no. 2 (2014): 107. http://dx.doi.org/10.1071/sr13100.

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An operational Digital Soil Assessment was developed to inform land suitability modelling in newly commissioned irrigation schemes in Tasmania, Australia. The Land Suitability model uses various soil parameters, along with other climate and terrain surfaces, to identify suitable areas for various agricultural enterprises for a combined 70 000-ha pilot project area in the Meander and Midlands Regions of Tasmania. An integral consideration for irrigable suitability is soil drainage. Quantitative measurement and mapping can be resource-intensive in time and associated costs, whereas more ‘traditional’ mapping approaches can be generalised, lacking the detail required for statistically validated products. The project was not sufficiently resourced to undertake replicated field-drainage measurements and relied on expert field drainage estimates at ~930 sites (260 of these for independent validation) to spatially predict soil drainage for both areas using various terrain-based and remotely sensed covariates, using three approaches: (a) decision tree spatial modelling of discrete drainage classes; (b) regression-tree spatial modelling of a continuous drainage index; (c) regression kriging (random-forests with residual-kriging) spatial modelling of a continuous drainage index. Method b was chosen as the best approach in terms of interpretation, and model training and validation, with a concordance coefficient of 0.86 and 0.57, respectively. A classified soil drainage map produced from the ‘index’ showed good agreement, with a linearly weighted kappa coefficient of 0.72 for training, and 0.37 for validation. The index mapping was incorporated into the overall land suitability model and proved an important consideration for the suitability of most enterprises.

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Usmadi, Didi, Sutomo Sutomo, Rajif Iryadi, Siti Fatimah Hanum, I. Dewa Putu Darma, and I. Putu Agus Hendra Wibawa. "Predicting Species Distribution for True Indigo (Indigofera tinctoria L.) in Citarum Watershed, West Java, Indonesia." Journal of Tropical Biodiversity and Biotechnology 6, no. 3 (September 20, 2021): 65398. http://dx.doi.org/10.22146/jtbb.65398.

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Citarum watershed is a region of approximately 6,610 km2 in West Java, Indonesia. Citarum watershed has been degraded through historical land use and vegetation clearing. Rehabilitation of Citarum watershed uses Indigofera tinctoria L. that has value as a source of natural blue dye and is considered suitable for the region. Species distribution modelling and Habitat suitability index (SDM/HSI) were undertaken for I. tinctoria. The occurrence and environment data (bioclimatic, topography, and soil type) were input to HSI. Results of the Indigofera tinctoria habitat suitability model in Citarum watershed are very good (0.9–1) for some parts of the Citarum watershed. The medium and high suitability areas were respectively 4.49% and 4.37% of the area were located in the lowlands (Bekasi Regency and Karawang Regency). Prediction based on climate modelling for 2050 and 2070 estimated that the medium-high suitability area of Indigofera tinctoria will be reduced relative to the present.

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17

Sulistyo, Bambang, Dewi Purnama, Maya Anggraini, Dede Hartono, Mukti Dono Wilopo, Ully Wulandari, and Noviyanti Listyaningrum. "Refining Suitability Modelling for Sea Cucumber (Holothuria scabra) Using Fully Raster-Based Data." Forum Geografi 32, no. 2 (November 23, 2018): 119–30. http://dx.doi.org/10.23917/forgeo.v32i2.6662.

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Geographical Information System (GIS) modelling using vector data is a commonly used method of modelling offering simple data input and analysis. However, the vector-data model assumes homogeneity in mapping units based on subjectively applied classification and simplification, and this may lead to over-simplification and consequent reduction in the variety of information obtained and uncertainty in results. This research aimed at refining the suitability modelling for sea cucumber (Holothuria scabra) using fully raster-based data for the waters of Kiowa Bay, Kahyapu village in the district of Enggano, North Bengkulu, Indonesia. Using a GIS, all parameters affecting suitability for sea cucumber were rasterised to improve compatibility. The relevant data includes nine parameters of sea water namely acidity, depth, current velocity, temperature, salinity, brightness, dissolved oxygen concentration, condition of the sea floor, and coastal protection of the area. These parameters were surveyed in the field at 51 stations and each parameter was then digitized and interpolated (using Kriging method) to create a continuous raster-dataset. Correlation analysis was then conducted to check parameter correlation. Parameters with a correlation coefficient of > 0.75 were excluded from further analysis since results could be derived from the remaining parameter set. Principal component analysis (PCA) was then applied to ascertain the weight of each component. Furthermore, scree plotting was employed to choose which principal components were relevant for insertion into the formula of suitability. The final result was then compared to the map of suitability from the analysis of vector-based data as the reference data set. The research results showed that this method can be used to locate areas that are suitable for sea cucumber farming. The suitability map for sea cucumber generated from the analysis using fully raster-based data displayed less uncertainty than the suitability map generated using vector-based data.

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18

Khahro, Shabir Hussain, Abd Nasir Matori, Imtiaz Ahmed Chandio, and Mir Aftab Hussain Talpur. "Data Preparation for GIS based Land Suitability Modelling: A Stepped Approach." E3S Web of Conferences 101 (2019): 02001. http://dx.doi.org/10.1051/e3sconf/201910102001.

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The land suitability analysis of any facility has become a complex affair. Each aspect of the landscape has inherent properties that are, to some extent, appropriate or inappropriate for planned activities. Compliance with government guidelines, installation guidelines and customer needs has made this task more complex. Land-use suitability analysis is identifying the most suitable spatial pattern for future land uses according to specific requirements, preferences, or predictors of some activity. Land-use suitability can mean different things to different experts depending on the purpose. Geographic Information System (GIS) has proven to be a key tool in addressing these land compatibility issues. GIS is a science of analysing position information that can count several numbers of these parameters at the same time, and it can be used to identify and analyse earth compatibility for all types of physical planning. A spatial aptitude model generally corresponds to the scientific question “Where is the best location for a particular facility or business? Therefore, this paper aims to provide an intensified approach to prepare datasets and layers for such land suitability problems using GIS. This paper will be valuable to land managers in land-use planning for any facility.

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19

Hirzel, A. H., V. Helfer, and F. Metral. "Assessing habitat-suitability models with a virtual species." Ecological Modelling 145, no. 2-3 (November 2001): 111–21. http://dx.doi.org/10.1016/s0304-3800(01)00396-9.

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20

Muhamad, M. A. H., and R. Che Hasan. "SEAGRASS HABITAT SUITABILITY MAP AT MERAMBONG SHOAL, JOHOR: A PRELIMINARY STUDY USING MULTIBEAM ECHOSOUNDER AND MAXENT MODELLING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 (October 1, 2019): 463–70. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w16-463-2019.

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Abstract. In recent years, there has been an increasing interest to use high-resolution multibeam dataset and Species Distribution Modelling (SDM) for seagrass habitat suitability model. This requires a specific variable derived from multibeam data and in-situ seagrass occurrence samples. The purpose of this study was (1) to derive variables from multibeam bathymetry data to be used in seagrass habitat suitability model, (2) to produce seagrass habitat suitability model using Maximum Entropy (MaxEnt), and (3) to quantify the contribution of each variable for predicting seagrass habitat suitability map. The study area was located at Merambong Shoal, covering an area of 0.04 km2, situated along Johor Strait. First, twelve (12) variables were derived from bathymetry data collected from multibeam echosounder using Benthic Terrain Modeller (BTM) tool. Secondly, all variables and seagrass occurrence samples were integrated in MaxEnt to produce seagrass habitat suitability map. The results showed that the Area Under Curve (AUC) values based on training and test data were 0.88 and 0.65, respectively. The northwest region of survey area indicated higher habitat suitability of seagrass, while the southeast region of survey area indicated lower suitability. Bathymetry mean found to be the most contributed variables among others. The spatial distribution of seagrass from modelling technique agreed with the previous studies and they are found to be distributed at depths ranging from 2.2 to 3.4 meters whilst less suitable with increasing of water depth. This study concludes that seagrass habitat suitability map with high-resolution pixel size (0.5 meter) can be produced at Merambong Shoal using acoustic data from multibeam echosounder coupled with MaxEnt and underwater video observations.

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21

DeRoy, Bryant C., Vernon Brown, Christina N. Service, Martin Leclerc, Christopher Bone, Iain McKechnie, and Chris T. Darimont. "Combining high-resolution remotely sensed data with local and Indigenous Knowledge to model the landscape suitability of culturally modified trees: biocultural stewardship in Kitasoo/Xai’xais Territory." FACETS 6, no. 1 (January 1, 2021): 465–89. http://dx.doi.org/10.1139/facets-2020-0047.

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Environmental management and monitoring must reconcile social and cultural objectives with biodiversity stewardship to overcome political barriers to conservation. Suitability modelling offers a powerful tool for such “biocultural” approaches, but examples remain rare. Led by the Stewardship Authority of the Kitasoo/Xai’xais First Nation in coastal British Columbia, Canada, we developed a locally informed suitability model for a key biocultural indicator, culturally modified trees (CMTs). CMTs are trees bearing evidence of past cultural use that are valued as tangible markers of Indigenous heritage and protected under provincial law. Using a spatial multi-criteria evaluation framework to predict CMT suitability, we developed two cultural predictor variables informed by Kitasoo/Xai’xais cultural expertise and ethnographic data in addition to six biophysical variables derived from LiDAR and photo interpretation data. Both cultural predictor variables were highly influential in our model, revealing that proximity to known habitation sites and accessibility to harvesters (by canoe and foot) more strongly influenced suitability for CMTs compared with site-level conditions. Applying our model to commercial forestry governance, we found that high CMT suitability areas are 51% greater inside the timber harvesting land base than outside. This work highlights how locally led suitability modelling can improve the social and evidentiary dimensions of environmental management.

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22

Caminade, Cyril, Jan Van Dijk, Matthew Baylis, and Diana Williams. "Modelling recent and future climatic suitability for fasciolosis in Europe." Geospatial Health 9, no. 2 (March 19, 2015): 301. http://dx.doi.org/10.4081/gh.2015.352.

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<em>Fasciola hepatica</em> is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, <em>F. hepatica</em> will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated.

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23

Hirzel, Alexandre, and Antoine Guisan. "Which is the optimal sampling strategy for habitat suitability modelling." Ecological Modelling 157, no. 2-3 (November 2002): 331–41. http://dx.doi.org/10.1016/s0304-3800(02)00203-x.

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24

Bellamy, Chloe, Katherine Boughey, Charlotte Hawkins, Sonia Reveley, Rebecca Spake, Carol Williams, and John Altringham. "A sequential multi-level framework to improve habitat suitability modelling." Landscape Ecology 35, no. 4 (March 16, 2020): 1001–20. http://dx.doi.org/10.1007/s10980-020-00987-w.

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25

Banchuin, Rawid. "Comparative analysis of suitability of fractional derivatives in modelling the practical capacitor." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 41, no. 1 (November 19, 2021): 304–18. http://dx.doi.org/10.1108/compel-08-2021-0293.

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Purpose The purpose of this paper is to compare the suitability of fractional derivatives in the modelling of practical capacitors. Such suitability refers to ability to provide the analytical capacitance function that matches the experimental ones of each fractional derivative. Design/methodology/approach The analytical capacitance functions based on various fractional derivatives of both local and nonlocal types including the author’s have been derived. The derived capacitance functions have been simulated and compared with the experimental ones of aluminium electrolytic and electrical double layer capacitors (EDLCs). Findings This paper has found that any local fractional derivative with fractional power law-based relationship with the conventional one is suitable for modelling the aluminium electrolytic capacitor (AEC) by incorporating with the conventional capacitance definition. On the other hand, the author’s nonlocal fractional derivatives have been found to be more suitable than the others for modelling the EDLC by incorporating with the revisited definition of capacitance. Originality/value The proposed comparative analysis has been originally presented in this work. The criterion for local fractional derivative, to be suitable for modelling the AEC, has been found. The nonlocal fractional operators which are most suitable for modelling the EDLC have been derived where the unsuitable one has been pointed out.

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26

Morris, Liz, and David Ball. "Habitat suitability modelling of economically important fish species with commercial fisheries data." ICES Journal of Marine Science 63, no. 9 (January 1, 2006): 1590–603. http://dx.doi.org/10.1016/j.icesjms.2006.06.008.

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Abstract In this study we used catch and effort data from a commercial fishery to generate habitat suitability models for Port Phillip Bay, Victoria, Australia. Species modelled were King George whiting (Sillaginodes punctata), greenback flounder (Rhombosolea tapirina), Australian salmon (Arripis trutta and A. truttaceus), and snapper (Pagrus auratus). Locations of commercial catches were reported through a grid system of fishing blocks. Spatial analyses in a Geographic Information System (GIS) were applied to describe each fishing block by its habitat area. A multivariate approach was adopted to group each fishing block by its dominant habitats. Standardized catch per unit effort values were overlaid on these groups to identify those that returned high or low catches for each species. A simple set of rules was then devised to predict the habitat suitability for each habitat combination in a fishing block. The spatial distribution of these habitats was presented in a GIS. These habitat suitability models were consistent with existing anecdotal information and expert opinion. While the models require testing, we have shown that in the absence of adequate fishery-independent data, commercial catch and effort data can be used to produce habitat suitability models at a bay-wide scale.

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Hinrichsen, Hans-Harald, Mark Dickey-Collas, Martin Huret, Myron A. Peck, and Frode B. Vikebø. "Evaluating the suitability of coupled biophysical models for fishery management." ICES Journal of Marine Science 68, no. 7 (April 21, 2011): 1478–87. http://dx.doi.org/10.1093/icesjms/fsr056.

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Abstract Hinrichsen, H-H., Dickey-Collas, M., Huret, M., Peck, M. A., and Vikebø, F. B. 2011. Evaluating the suitability of coupled biophysical models for fishery management. – ICES Journal of Marine Science, 68: 1478–1487. The potential role of coupled biophysical models in enhancing the conservation, management, and recovery of fish stocks is assessed, with emphasis on anchovy, cod, herring, and sprat in European waters. The assessment indicates that coupled biophysical models are currently capable of simulating transport patterns, along with temperature and prey fields within marine ecosystems; they therefore provide insight into the variability of early-life-stage dynamics and connectivity within stocks. Moreover, the influence of environmental variability on potential recruitment success may be discerned from model hindcasts. Based on case studies, biophysical modelling results are shown to be capable of shedding light on whether stock management frameworks need re-evaluation. Hence, key modelling products were identified that will contribute to the development of viable stock recovery plans and management strategies. The study also suggests that approaches combining observation, process knowledge, and numerical modelling could be a promising way forward in understanding and simulating the dynamics of marine fish populations.

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Vetharaniam, Indrakumar, Levente Timar, C. Jill Stanley, Karin Müller, Carlo van den Dijssel, and Brent Clothier. "Modelling Climate Change Impacts on Location Suitability and Spatial Footprint of Apple and Kiwifruit." Land 11, no. 10 (September 23, 2022): 1639. http://dx.doi.org/10.3390/land11101639.

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The threats and opportunities faced by primary production industries from future climate changes can be adequately prepared for only with the guidance of model projections that can assist the development of robust policy and climate adaptation plans by governments and industries. We used continuous suitability models capable of reflecting incremental changes to project the suitability of locations across New Zealand for cultivating apple and kiwifruit in the mid- and late-century. These projections used future weather data from climate model simulations for two contrasting greenhouse gas (GHG) pathways: stringent GHG mitigation and unabated GHG emissions. To improve the suitability of the modelled temperature data, specifically for use with biologically driven, crop suitability models, we developed new bias-variance adjustments that preserved climate change signals within the data. Preliminary projections of land use across a range of alternative primary industries were obtained from a multinomial logit model incorporating continuous suitability scores as predictors. We refined the preliminary land-use projections by providing them as inputs into a simulation model of land use incorporating other drivers and constraints. This methodology provides a means for projecting future land use and the spatial footprints of primary industries, based on biological and econometric considerations, under different modelled climate change scenarios.

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Singh, Priyanka, Sameer Saran, and Sultan Kocaman. "Role of Maximum Entropy and Citizen Science to Study Habitat Suitability of Jacobin Cuckoo in Different Climate Change Scenarios." ISPRS International Journal of Geo-Information 10, no. 7 (July 6, 2021): 463. http://dx.doi.org/10.3390/ijgi10070463.

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Recent advancements in spatial modelling and mapping methods have opened up new horizons for monitoring the migration of bird species, which have been altered due to the climate change. The rise of citizen science has also aided the spatiotemporal data collection with associated attributes. The biodiversity data from citizen observatories can be employed in machine learning algorithms for predicting suitable environmental conditions for species’ survival and their future migration behaviours. In this study, different environmental variables effective in birds’ migrations were analysed, and their habitat suitability was assessed for future understanding of their responses in different climate change scenarios. The Jacobin cuckoo (Clamator jacobinus) was selected as the subject species, since their arrival to India has been traditionally considered as a sign for the start of the Indian monsoon season. For suitability predictions in current and future scenarios, maximum entropy (Maxent) modelling was carried out with environmental variables and species occurrences observed in India and Africa. For modelling, the correlation test was performed on the environmental variables (bioclimatic, precipitation, minimum temperature, maximum temperature, precipitation, wind and elevation). The results showed that precipitation-related variables played a significant role in suitability, and through reclassified habitat suitability maps, it was observed that the suitable areas of India and Africa might decrease in future climatic scenarios (SSPs 2.6, 4.5, 7.0 and 8.5) of 2030 and 2050. In addition, the suitability and unsuitability areas were calculated (in km2) to observe the subtle changes in the ecosystem. Such climate change studies can support biodiversity research and improve the agricultural economy.

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30

Saxena, Ankita, and Mahesh Kumar Jat. "Land suitability and urban growth modeling: Development of SLEUTH-Suitability." Computers, Environment and Urban Systems 81 (May 2020): 101475. http://dx.doi.org/10.1016/j.compenvurbsys.2020.101475.

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31

Lyimo, Neema Nicodemus, Zhenfeng Shao, Ally Mgelwa Ally, Nana Yaw Danquah Twumasi, Orhan Altan, and Camilius A. Sanga. "A Fuzzy Logic-Based Approach for Modelling Uncertainty in Open Geospatial Data on Landfill Suitability Analysis." ISPRS International Journal of Geo-Information 9, no. 12 (December 9, 2020): 737. http://dx.doi.org/10.3390/ijgi9120737.

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Besides OpenStreetMap (OSM), there are other local sources, such as open government data (OGD), that have the potential to enrich the modeling process with decision criteria that uniquely reflect some local patterns. However, both data are affected by uncertainty issues, which limits their usability. This work addresses the imprecisions on suitability layers generated from such data. The proposed method is founded on fuzzy logic theories. The model integrates OGD, OSM data and remote sensing products and generate reliable landfill suitability results. A comparison analysis demonstrates that the proposed method generates more accurate, representative and reliable suitability results than traditional methods. Furthermore, the method has facilitated the introduction of open government data for suitability studies, whose fusion improved estimations of population distribution and land-use mapping than solely relying on free remotely sensed images. The proposed method is applicable for preparing decision maps from open datasets that have undergone similar generalization procedures as the source of their uncertainty. The study provides evidence for the applicability of OGD and other related open data initiatives (ODIs) for land-use suitability studies, especially in developing countries.

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Martínez-Meyer, Enrique, A. Townsend Peterson, Jorge I. Servín, and Lloyd F. Kiff. "Ecological niche modelling and prioritizing areas for species reintroductions." Oryx 40, no. 4 (October 2006): 411–18. http://dx.doi.org/10.1017/s0030605306001360.

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Species reintroduction programmes, in prioritizing areas for reintroductions, have traditionally used tools that include measures of habitat suitability and evaluations of area requirements for viable populations. Here we add two tools to this approach: evaluation of ecological requirements of species and evaluation of future suitability for species facing changing climates. We demonstrate this approach with two species for which reintroduction programmes are in the planning stages in Mexico: California condor Gymnogyps californianus and Mexican wolf Canis lupus baileyi. For the condor, we identify three areas clustered in the Sierra San Pedro Mártir, Baja California; for the wolf, we identify a string of suitable sites along the Sierra Madre Occidental of western Mexico. We discuss the limitations of this approach, identifying ways in which the models illustrated could be made more realistic and directly useful to reintroduction programmes.

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Burian, Jaroslav, Stanislav Šťastný, Jan Brus, Vilém Pechanec, and Vít Voženílek. "Urban Planner: model for optimal land use scenario modelling." Geografie 120, no. 3 (2015): 330–53. http://dx.doi.org/10.37040/geografie2015120030330.

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This paper describes a new approach to automatic optimal land use scenario modelling using the developed ArcGIS “Urban Planner” extension. The first part of the paper addresses the implementation of geoinformatic technologies in spatial planning. The study presents several models and approaches, which focus mainly on the evaluation of land suitability, spatial modelling, and the possibilities of their use in urban planning. The main part of the paper describes the theoretical basis of the model, which is built on a weighted raster overlay. This study also elaborately analyses the functionality of the extension, which lies in the assessment of land suitability and the detection of optimal areas suitable for urban development. The paper also offers some testing of the model, specifically its robustness and sensitivity in the Olomouc region and its possible use for the creation of development scenarios.

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Lu, Hui, Fu Ping Lu, Xue Lian Xu, and Qing Chen. "Environmental Suitability of the Cassava Mealybug Assessments Using Ecological Niche Modelling." Applied Mechanics and Materials 651-653 (September 2014): 1432–35. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1432.

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The cassava mealybug (Phenacoccus manihoti) is one of the main pests in the world and the risk of invasion posed by this pest is becoming more and more serious with regard to increasing areas of planting cassava in Asia. It is urgent to analyze the potential geography distribution of P. manihoti among cassava in China. In this study, three different ecological modeling methods (Maxent, ENFA and Mahalanobis typicality) were used to predict its potential distribution. The results show that Maxent has the best prediction performance, followed by ENFA, and Mahalanobis typicality has the poorest performance. Based on prediction outcome of Maxent suitable areas of P. manihoti in China are limited in Hainan, Yunnan, Guangxi, Guangdong, Fujian and a few regions of Sichuan, Hunan and Jiangxi. The jackknife analysis indicates that four variables have notable influence on the distribution pattern of P. manihoti, including in in Temperature annual range, Min temperature of coldest month, r, Temperature seasonality and Isothermality.

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Meiklejohn, Natalie A., Timothy L. Staples, and Rod J. Fensham. "Modelling climatic suitability for myrtle rust with a widespread host species." Biological Invasions 24, no. 3 (November 30, 2021): 831–44. http://dx.doi.org/10.1007/s10530-021-02689-z.

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MATSUZAWA, Yuki, Shinji FUKUDA, and Mitsuru OHIRA. "MODELLING HABITAT SUITABILITY OF LEFUA ECHIGONIA USING RANDOM FORESTS." Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 75, no. 2 (2019): I_541—I_546. http://dx.doi.org/10.2208/jscejhe.75.2_i_541.

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Carolli, Mauro, Guido Zolezzi, Davide Geneletti, Annunziato Siviglia, Fabiano Carolli, and Oscar Cainelli. "Modelling white-water rafting suitability in a hydropower regulated Alpine River." Science of The Total Environment 579 (February 2017): 1035–49. http://dx.doi.org/10.1016/j.scitotenv.2016.11.049.

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Thomas, Haydn J. D., James S. Paterson, Marc J. Metzger, and Louise Sing. "An evaluation of Scottish woodland grant schemes using site suitability modelling." Land Use Policy 80 (January 2019): 309–17. http://dx.doi.org/10.1016/j.landusepol.2016.03.030.

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Niño, A., C. Muñoz-Caro, and M. L. Senent. "Suitability of different levels of theory for modelling of hydroxamic acids." Journal of Molecular Structure: THEOCHEM 530, no. 3 (October 2000): 291–300. http://dx.doi.org/10.1016/s0166-1280(00)00342-0.

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Jacquin, Anne, Véronique Chéret, Jean-Philippe Denux, Michel Gay, Jonathan Mitchley, and Panteleimon Xofis. "Habitat suitability modelling of Capercaillie (Tetrao urogallus) using earth observation data." Journal for Nature Conservation 13, no. 2-3 (July 2005): 161–69. http://dx.doi.org/10.1016/j.jnc.2005.02.002.

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Oja, Tõnu, Katrin Alamets, and Henn Pärnamets. "Modelling bird habitat suitability based on landscape parameters at different scales." Ecological Indicators 5, no. 4 (November 2005): 314–21. http://dx.doi.org/10.1016/j.ecolind.2005.03.008.

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Wright, Patrick G. R., Frazer G. Coomber, Chloe C. Bellamy, Sarah E. Perkins, and Fiona Mathews. "Predicting hedgehog mortality risks on British roads using habitat suitability modelling." PeerJ 7 (January 21, 2020): e8154. http://dx.doi.org/10.7717/peerj.8154.

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Road vehicle collisions are likely to be an important contributory factor in the decline of the European hedgehog (Erinaceus europaeus) in Britain. Here, a collaborative roadkill dataset collected from multiple projects across Britain was used to assess when, where and why hedgehog roadkill are more likely to occur. Seasonal trends were assessed using a Generalized Additive Model. There were few casualties in winter—the hibernation season for hedgehogs—with a gradual increase from February that reached a peak in July before declining thereafter. A sequential multi-level Habitat Suitability Modelling (HSM) framework was then used to identify areas showing a high probability of hedgehog roadkill occurrence throughout the entire British road network (∼400,000 km) based on multi-scale environmental determinants. The HSM predicted that grassland and urban habitat coverage were important in predicting the probability of roadkill at a national scale. Probabilities peaked at approximately 50% urban cover at a one km scale and increased linearly with grassland cover (improved and rough grassland). Areas predicted to experience high probabilities of hedgehog roadkill occurrence were therefore in urban and suburban environments, that is, where a mix of urban and grassland habitats occur. These areas covered 9% of the total British road network. In combination with information on the frequency with which particular locations have hedgehog road casualties, the framework can help to identify priority areas for mitigation measures.

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Van Broekhoven, Ester, Veronique Adriaenssens, Bernard De Baets, and Piet F. M. Verdonschot. "Fuzzy rule-based macroinvertebrate habitat suitability models for running waters." Ecological Modelling 198, no. 1-2 (September 2006): 71–84. http://dx.doi.org/10.1016/j.ecolmodel.2006.04.006.

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Store, Ron, and Jukka Jokimäki. "A GIS-based multi-scale approach to habitat suitability modeling." Ecological Modelling 169, no. 1 (November 2003): 1–15. http://dx.doi.org/10.1016/s0304-3800(03)00203-5.

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Simpson, Hope, Earnest Njih Tabah, Richard O. Phillips, Michael Frimpong, Issaka Maman, Edwin Ampadu, Joseph Timothy, Paul Saunderson, Rachel L. Pullan, and Jorge Cano. "Mapping suitability for Buruli ulcer at fine spatial scales across Africa: A modelling study." PLOS Neglected Tropical Diseases 15, no. 3 (March 3, 2021): e0009157. http://dx.doi.org/10.1371/journal.pntd.0009157.

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Buruli ulcer (BU) is a disabling and stigmatising neglected tropical disease (NTD). Its distribution and burden are unknown because of underdiagnosis and underreporting. It is caused by Mycobacterium ulcerans, an environmental pathogen whose environmental niche and transmission routes are not fully understood. The main control strategy is active surveillance to promote early treatment and thus limit morbidity, but these activities are mostly restricted to well-known endemic areas. A better understanding of environmental suitability for the bacterium and disease could inform targeted surveillance, and advance understanding of the ecology and burden of BU. We used previously compiled point-level datasets of BU and M. ulcerans occurrence, evidence for BU occurrence within national and sub-national areas, and a suite of relevant environmental covariates in a distribution modelling framework. We fitted relationships between BU and M. ulcerans occurrence and environmental predictors by applying regression and machine learning based algorithms, combined in an ensemble model to characterise the optimal ecological niche for the disease and bacterium across Africa at a resolution of 5km x 5km. Proximity to waterbodies was the strongest predictor of suitability for BU, followed potential evapotranspiration. The strongest predictors of suitability for M. ulcerans were deforestation and potential evapotranspiration. We identified patchy foci of suitability throughout West and Central Africa, including areas with no previous evidence of the disease. Predicted suitability for M. ulcerans was wider but overlapping with that of BU. The estimated population living in areas predicted suitable for the bacterium and disease was 46.1 million. These maps could be used to inform burden estimations and case searches which would generate a more complete understanding of the spatial distribution of BU in Africa, and may guide control programmes to identify cases beyond the well-known endemic areas.

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Ajibade, Oluwatoyin Opeyemi, Kiran Tota-Maharaj, Colin D. Hills, and Cecilia MacLeod. "Modelling of a sustainable refugee camp drainage system for stormwater management." Environmental Science: Water Research & Technology 5, no. 12 (2019): 2150–61. http://dx.doi.org/10.1039/c9ew00350a.

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Bulka, K. A., A. A. Kuzmin, S. P. Sidorov, O. V. Chubar, and Yu Sh Khalimov. "Modelling of Inhalation Poisoning with Sulphur Mustard Gas." Journal Biomed 16, no. 3 (September 3, 2020): 106–10. http://dx.doi.org/10.33647/2074-5982-16-3-106-110.

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The present work describes the currently existing experimental models of sulphur mustard gas inhalation injury. These models were analysed in terms of their suitability for the development of medical protective equipment. It is proposed to use micro-sprayers, which provide the possibility of transferring mustard gas from a liquid state to an aerosol form while exhibiting an increased ergonomic simplicity and safety.

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Zidarova, Sirma Asenova, and Vasil Vulkov Popov. "Long term (1985–2018) changes of the habitat suitability of European souslik assessed by Maxent modelling based on Landsat satellite imagery – a case study from a mountain landscape of Central Bulgaria." Acta Zoologica Academiae Scientiarum Hungaricae 68, no. 3 (August 12, 2022): 277–92. http://dx.doi.org/10.17109/azh.68.3.277.2022.

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The spatial and temporal aspects of the habitat suitability of the European souslik (Spermophilus citellus L.) in an area of Sredna Gora Mountain (Bulgaria) were studied. We used Landsat satellite imagery data to model changes in the habitat suitability of the species from 1985 to 2018. The obtained results demonstrate that the habitat suitability of the European souslik increased during the studied period, presumably due to raised temperatures and the accompanying drought during summertime, as well as the human-caused modifications in pasture livestock breeding. Based on statistical modelling, the employed procedure applies to long-term monitoring and assessment of the role of land cover change because of climate change and human activity on the habitat suitability of the European souslik. This approach can be useful for conservation planning.

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Huang, Ziye, Anmin Huang, Terence P. Dawson, and Li Cong. "The Effects of the Spatial Extent on Modelling Giant Panda Distributions Using Ecological Niche Models." Sustainability 13, no. 21 (October 22, 2021): 11707. http://dx.doi.org/10.3390/su132111707.

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Climate change and biodiversity loss have become increasingly prominent in recent years. To evaluate these two issues, prediction models have been developed on the basis of ecological-niche (or climate-envelope) models. However, the spatial scale and extent of the underlying environmental data are known to affect results. To verify whether the difference in the modelled spatial extent will affect model results, this study uses the MaxEnt model to predict the suitability range of giant pandas in the Min Mountain System (MMS) area through modelling performed (1) at a nationwide scale and (2) at a restricted MMS extent. The results show that, firstly, both models performed well in terms of accuracy. Secondly, extending the modelling extent does help improve the modelling results when the distribution data is incomplete. Thirdly, when environmental information is insufficient, the qualitative analysis should be combined with quantitative analysis to ensure the accuracy and practicality of the research. Finally, when predicting a suitability distribution of giant pandas, the modelling results under different spatial extents can provide management agencies at the various administrative levels with more targeted giant panda protective measures.

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Hirzel, Alexandre H., Gwenaëlle Le Lay, Véronique Helfer, Christophe Randin, and Antoine Guisan. "Evaluating the ability of habitat suitability models to predict species presences." Ecological Modelling 199, no. 2 (November 2006): 142–52. http://dx.doi.org/10.1016/j.ecolmodel.2006.05.017.

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