{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T22:46:27Z","timestamp":1772750787903,"version":"3.50.1"},"reference-count":75,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T00:00:00Z","timestamp":1629331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007907","name":"Ministry of Environment, Forest and Climate Change","doi-asserted-by":"publisher","award":["P-07\/683"],"award-info":[{"award-number":["P-07\/683"]}],"id":[{"id":"10.13039\/501100007907","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The integration of ecological and atmospheric characteristics for biodiversity management is fundamental for long-term ecosystem conservation and drafting forest management strategies, especially in the current era of climate change. The explicit modelling of regional ecological responses and their impact on individual species is a significant prerequisite for any adaptation strategy. The present study focuses on predicting the regional distribution of Rhododendron arboreum, a medicinal plant species found in the Himalayan region. Advanced Species Distribution Models (SDM) based on the principle of predefined hypothesis, namely BIOCLIM, was used to model the potential distribution of Rhododendron arboreum. This hypothesis tends to vary with the change in locations, and thus, robust models are required to establish nonlinear complex relations between the input parameters. To address this nonlinear relation, a class of deep neural networks, Convolutional Neural Network (CNN) architecture is proposed, designed, and tested, which eventually gave much better accuracy than the BIOCLIM model. Both of the models were given 16 input parameters, including ecological and atmospheric variables, which were statistically resampled and were then utilized in establishing the linear and nonlinear relationship to better fit the occurrence scenarios of the species. The input parameters were mostly acquired from the recent satellite missions, including MODIS, Sentinel-2, Sentinel-5p, the Shuttle Radar Topography Mission (SRTM), and ECOSTRESS. The performance across all the thresholds was evaluated using the value of the Area Under Curve (AUC) evaluation metrics. The AUC value was found to be 0.917 with CNN, whereas it was 0.68 with BIOCLIM, respectively. The performance evaluation metrics indicate the superiority of CNN for species distribution over BIOCLIM.<\/jats:p>","DOI":"10.3390\/rs13163284","type":"journal-article","created":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T09:58:06Z","timestamp":1629367086000},"page":"3284","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Integrating Multi-Sensors Data for Species Distribution Mapping Using Deep Learning and Envelope Models"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1086-5676","authenticated-orcid":false,"given":"Akash","family":"Anand","sequence":"first","affiliation":[{"name":"Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6943-6991","authenticated-orcid":false,"given":"Manish K.","family":"Pandey","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4155-630X","authenticated-orcid":false,"given":"Prashant K.","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6048-8069","authenticated-orcid":false,"given":"Ayushi","family":"Gupta","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratory, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed Latif","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Botany, Dr. Harisingh Gour Central University, Sagar 470003, Madhya Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Krishnan, R., Sanjay, J., Gnanaseelan, C., Mujumdar, M., Kulkarni, A., and Chakraborty, S. (2020). Climate change over the Himalayas. Assessment of Climate Change over the Indian Region, Springer.","DOI":"10.1007\/978-981-15-4327-2"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1038\/nature23878","article-title":"Impact of a global temperature rise of 1.5 degrees Celsius on Asia\u2019s glaciers","volume":"549","author":"Kraaijenbrink","year":"2017","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/S0006-3207(99)00128-7","article-title":"Status and conservation of rare and endangered medicinal plants in the Indian trans-Himalaya","volume":"93","author":"Kala","year":"2000","journal-title":"Biol. Conserv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1007\/s42965-020-00057-x","article-title":"Prediction of upslope movement of Rhododendron arboreum in Western Himalaya","volume":"60","author":"Veera","year":"2019","journal-title":"Trop. Ecol."},{"key":"ref_5","first-page":"158","article-title":"Rhododendron arboreum: An overview","volume":"2","author":"Srivastava","year":"2012","journal-title":"J. Appl. Pharm. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1007\/s12524-019-01089-0","article-title":"Prediction mapping through maxent modeling paves the way for the conservation of Rhododendron arboreum in Uttarakhand Himalayas","volume":"48","author":"Bhandari","year":"2020","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_7","first-page":"1377","article-title":"Reproductive behaviour and genetic variability in geographically isolated populations of Rhododendron arboreum (Ericaceae)","volume":"79","author":"Jain","year":"2000","journal-title":"Curr. Sci."},{"key":"ref_8","unstructured":"Sharma, G. (2013). Development and Charaterization of UGMS Markers for Genetic Diversity Analysis in Rhododendron Arboreum, Guru Kashi University."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"430","DOI":"10.4172\/2157-7617.1000430","article-title":"Composition, population structure and regeneration of Rhododendron arboreum Sm. temperate broad-leaved evergreen forest in Garhwal Himalaya, Uttarakhand, India","volume":"8","author":"Chauhan","year":"2017","journal-title":"J. Earth Sci. Clim. Chang."},{"key":"ref_10","unstructured":"Humboldt, A.V., and Bonpland, A. (1807). Ideen Zu Einer Geographie Der Pflanzen Nebst Einem Naturgem\u00e4lde Der Tropenl\u00e4nder, Cotta."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"De Candolle, A. (1855). G\u00e9ographie Botanique Raisonn\u00e9e Ou Exposition Des Faits Principaux Et Des Lois Concernant La Distribution G\u00e9ographique Des Plantes De L\u2019\u00e9poque Actuelle, V. Masson.","DOI":"10.5962\/bhl.title.62718"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"725","DOI":"10.2307\/1929830","article-title":"Notes on the ecological concepts of habitat, biotope and niche","volume":"40","author":"Udvardy","year":"1959","journal-title":"Ecology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.ecoleng.2016.01.006","article-title":"Modeling impacts of future climate on the distribution of Myristicaceae species in the Western Ghats, India","volume":"89","author":"Priti","year":"2016","journal-title":"Ecol. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.ecoleng.2011.12.004","article-title":"Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India","volume":"40","author":"Adhikari","year":"2012","journal-title":"Ecol. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1111\/j.1472-4642.2010.00641.x","article-title":"Moving beyond static species distribution models in support of conservation biogeography","volume":"16","author":"Franklin","year":"2010","journal-title":"Divers. Distrib."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1111\/j.1600-0587.2011.07050.x","article-title":"Species distribution modelling as a macroecological tool: A case study using New World amphibians","volume":"35","author":"Vasconcelos","year":"2012","journal-title":"Ecography"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1111\/j.1472-4642.2007.00356.x","article-title":"The application of predictive modelling of species distribution to biodiversity conservation","volume":"13","author":"Brotons","year":"2007","journal-title":"Divers. Distrib."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5268","DOI":"10.1016\/j.eswa.2010.10.031","article-title":"Comparing machine learning classifiers in potential distribution modelling","volume":"38","author":"Lorena","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1146\/annurev.ecolsys.110308.120159","article-title":"Species distribution models: Ecological explanation and prediction across space and time","volume":"40","author":"Elith","year":"2009","journal-title":"Annu. Rev. of Ecol. Evol. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"107127","DOI":"10.1016\/j.ecolind.2020.107127","article-title":"Estimating climate-induced \u2018Nowhere to go\u2019range shifts of the Himalayan Incarvillea Juss. using multi-model median ensemble species distribution models","volume":"121","author":"Rana","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.ecolmodel.2005.01.030","article-title":"Predicting species distributions: Use of climatic parameters in BIOCLIM and its impact on predictions of species\u2019 current and future distributions","volume":"186","author":"Beaumont","year":"2005","journal-title":"Ecol. Model."},{"key":"ref_22","unstructured":"Doran, B., and Olsen, P. (2001, January 24\u201326). Customizing BIOCLIM to investigate spatial and temporal variations in highly mobile species. Proceedings of the 6th International Conference in GeoComputation, Brisbane, Australia."},{"key":"ref_23","first-page":"746","article-title":"Assessment of risk of introduction of pine wood nematode, bursaphelenchus xylophilus in Yunnan Province using BIOCLIM ecological niche model","volume":"23","author":"Xu","year":"2008","journal-title":"J. Yunnan Agric. Univ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e49459","DOI":"10.21425\/F5FBG49459","article-title":"A pan-Himalayan test of predictions on plant species richness based on primary production and water-energy dynamics","volume":"13","author":"Bhatta","year":"2021","journal-title":"Front. Biogeogr."},{"key":"ref_25","first-page":"261","article-title":"Species Distribution Modelling of Rhododendron arboreum Sm.\u2013A Keystone Species, in India and Adjoining Region","volume":"44","author":"Mamgain","year":"2018","journal-title":"Int. J. Ecol. Environ. Sci."},{"key":"ref_26","unstructured":"Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, MIT press."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/0304-3800(95)00142-5","article-title":"Application of neural networks to modelling nonlinear relationships in ecology","volume":"90","author":"Lek","year":"1996","journal-title":"Ecol. Model."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1046\/j.1365-2486.2003.00666.x","article-title":"BIOMOD\u2013optimizing predictions of species distributions and projecting potential future shifts under global change","volume":"9","author":"Thuiller","year":"2003","journal-title":"Glob. Chang. Biol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, J., and Li, S. (2017, January 2\u20133). A Review of Machine Learning Based Species\u2019 Distribution Modelling. Proceedings of the 2017 International Conference on Industrial Informatics-Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), Wuhan, China.","DOI":"10.1109\/ICIICII.2017.76"},{"key":"ref_30","unstructured":"Kumar, K. (1996). Water Management in Himalayan Ecosystem: A Study of Natural Springs of Almora, Indus Publishing."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.ecolmodel.2005.03.026","article-title":"Maximum entropy modeling of species geographic distributions","volume":"190","author":"Phillips","year":"2006","journal-title":"Ecol. Model."},{"key":"ref_32","unstructured":"Tewari, A.P. (1973). Recent changes in the position of the snout of the Pindari glacier (Kumaon Himalaya), Almora District, Uttar Pradesh, India. Proceedings of the Role of Snow and Ice in Hydrology, Banff Symposia, September 1972, WMO-IAHS-Unesco."},{"key":"ref_33","first-page":"284","article-title":"Conservation of rhododendrons in Sikkim Himalaya: An overview","volume":"5","author":"Singh","year":"2009","journal-title":"World J. Agric. Sci."},{"key":"ref_34","unstructured":"Secretariat, G. (2017). GBIF backbone taxonomy. Checklist Dataset, 10, Available online: https:\/\/www.gbif.org\/dataset\/d7dddbf4-2cf0-4f39-9b2a-bb099caae36c."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s13596-017-0289-3","article-title":"Review on Rhododendron arboreum\u2014A magical tree","volume":"17","author":"Rawat","year":"2017","journal-title":"Orient. Pharm. Exp. Med."},{"key":"ref_36","first-page":"623","article-title":"Biodiversity and conservation of rhododendrons in Arunachal Pradesh in the Indo-Burma biodiversity hotspot","volume":"89","author":"Paul","year":"2005","journal-title":"Curr. Sci."},{"key":"ref_37","unstructured":"Chauhan, N.S. (1999). Medicinal and Aromatic Plants of Himachal Pradesh, Indus Publishing."},{"key":"ref_38","unstructured":"Watts, J.S. (2010). When a Billion Chinese Jump: How China Will Save Mankind\u2014Or Destroy It, Simon and Schuster."},{"key":"ref_39","unstructured":"Singh, V.K., and Ali, Z.A. (1998). Herbal Drugs of Himalaya, Today & Tomorrow\u2019s Printers and Publishers."},{"key":"ref_40","first-page":"106","article-title":"Phenological events along the elevation gradient and effect of climate change on Rhododendron arboreum Sm. in Kumaun Himalaya","volume":"108","author":"Singh","year":"2015","journal-title":"Curr. Sci."},{"key":"ref_41","unstructured":"Paul, A., Khan, M.L., and Das, A.K. (2010). Utilization of Rhododendrons by Monpas in Western Arunachal Pradesh, India, Assam University."},{"key":"ref_42","first-page":"61","article-title":"Bioprospecting of Rhododendron arboreum for livelihood enhancement in central Himalaya, India","volume":"8","author":"Negi","year":"2013","journal-title":"Environ. We Int. Jouranl Sci. Technol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1746-4269-2-14","article-title":"Traditional use of medicinal plants among the tribal communities of Chhota Bhangal, Western Himalaya","volume":"2","author":"Uniyal","year":"2006","journal-title":"J. Ethnobiol. Ethnomedi."},{"key":"ref_44","first-page":"77","article-title":"Diversity, distribution and indigenous uses of medicinal plants in Parbati Valley of Kullu district in Himachal Pradesh, Northwestern Himalaya","volume":"2","author":"Sharma","year":"2014","journal-title":"Asian J. Adv. Basic Sci."},{"key":"ref_45","first-page":"89","article-title":"Indigenous knowledge on utilization of plant biodiversity for treatment and cure of diseases of human beings in Nagaland, India: A case study","volume":"4","author":"Zhasa","year":"2015","journal-title":"Int. Res. J. Biol. Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1007\/s10531-012-0279-1","article-title":"Assessment of impact of climate change on Rhododendrons in Sikkim Himalayas using Maxent modelling: Limitations and challenges","volume":"21","author":"Kumar","year":"2012","journal-title":"Biodivers. Conserv."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1111\/j.1472-4642.2008.00482.x","article-title":"Effects of sample size on the performance of species distribution models","volume":"14","author":"Wisz","year":"2008","journal-title":"Divers. Distrib."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1885","DOI":"10.1109\/TGRS.2006.871215","article-title":"MODIS leaf area index products: From validation to algorithm improvement","volume":"44","author":"Yang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2004JD004869","article-title":"Evaluation of GOME satellite measurements of tropospheric NO2 and HCHO using regional data from aircraft campaigns in the southeastern United States","volume":"109","author":"Martin","year":"2004","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1641\/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2","article-title":"Terrestrial ecoregions of the world: A new map of life on earth","volume":"51","author":"Olson","year":"2001","journal-title":"BioScience"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1139\/X08-151","article-title":"Tree species distribution and its impact on soil properties, and nitrogen and phosphorus mineralization in a humid subtropical forest ecosystem of northeastern India","volume":"39","author":"Kamei","year":"2009","journal-title":"Can. J. For. Res."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1111\/j.1654-1103.2002.tb02104.x","article-title":"Patterns of plant species distribution in the Trans-Himalayan region of Ladakh, India","volume":"13","author":"Kala","year":"2002","journal-title":"J. Veg. Sci."},{"key":"ref_53","first-page":"54","article-title":"Species\u2019 distribution modeling for conservation educators and practitioners","volume":"50","author":"Pearson","year":"2007","journal-title":"Synth. Am. Mus. Nat. Hist."},{"key":"ref_54","first-page":"4","article-title":"A biogeographic analysis of Australian elapid snakes","volume":"7","author":"Nix","year":"1986","journal-title":"Atlas Elapid Snakes Aust."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1080\/11956860.1999.11682533","article-title":"Metapopulation theory, landscape models, and species diversity","volume":"6","author":"Haydon","year":"1999","journal-title":"Ecoscience"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1111\/j.1461-0248.2005.00792.x","article-title":"Predicting species distribution: Offering more than simple habitat models","volume":"8","author":"Guisan","year":"2005","journal-title":"Ecol. Lett."},{"key":"ref_57","first-page":"652","article-title":"Biodiversity of Piper in South India\u2013application of GIS and cluster analysis","volume":"91","author":"Parthasarathy","year":"2006","journal-title":"Curr. Sci."},{"key":"ref_58","first-page":"565","article-title":"Prediction of environmental suitability for invasion of Mikania micrantha in India by species distribution modelling","volume":"36","author":"Rameshprabu","year":"2015","journal-title":"J. Environ. Biol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/ddi.12144","article-title":"BIOCLIM: The first species distribution modelling package, its early applications and relevance to most current MAXENT studies","volume":"20","author":"Booth","year":"2014","journal-title":"Divers. Distrib."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","article-title":"Deep learning in neural networks: An overview","volume":"61","author":"Schmidhuber","year":"2015","journal-title":"Neural Netw."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","article-title":"Deep learning for visual understanding: A review","volume":"187","author":"Guo","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.envsoft.2013.04.005","article-title":"Habitat prediction and knowledge extraction for spawning European grayling (Thymallus thymallus L.) using a broad range of species distribution models","volume":"47","author":"Fukuda","year":"2013","journal-title":"Environ. Model. Softw."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1111\/2041-210X.12332","article-title":"Generating realistic assemblages with a joint species distribution model","volume":"6","author":"Harris","year":"2015","journal-title":"Methods Ecol. Evol."},{"key":"ref_64","unstructured":"Lin, M., Chen, Q., and Yan, S. (2013). Network in network. arXiv Prepr."},{"key":"ref_65","unstructured":"Agarap, A.F. (2018). Deep learning using rectified linear units (relu). arXiv Prepr."},{"key":"ref_66","first-page":"1875","article-title":"Nonparametric regression using deep neural networks with ReLU activation function","volume":"48","year":"2020","journal-title":"Ann. Stat."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1148\/radiology.143.1.7063747","article-title":"The meaning and use of the area under a receiver operating characteristic (ROC) curve","volume":"143","author":"Hanley","year":"1982","journal-title":"Radiology"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2143","DOI":"10.1007\/s10531-019-01698-8","article-title":"Spatial distribution of mangrove forest species and biomass assessment using field inventory and earth observation hyperspectral data","volume":"28","author":"Pandey","year":"2019","journal-title":"Biodivers. Conserv."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Anand, A., Malhi, R.K.M., Pandey, P.C., Petropoulos, G.P., Pavlides, A., Sharma, J.K., and Srivastava, P.K. (2020). Use of Hyperion for Mangrove Forest Carbon Stock Assessment in Bhitarkanika Forest Reserve: A Contribution Towards Blue Carbon Initiative. Remote Sens., 12.","DOI":"10.3390\/rs12040597"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Malhi, R.K.M., Anand, A., Srivastava, P.K., Kiran, G.S., Petropoulos, G.P., and Chalkias, C. (2020). An Integrated Spatiotemporal Pattern Analysis Model to Assess and Predict the Degradation of Protected Forest Areas. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9090530"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1007\/s42965-020-00068-8","article-title":"Synergetic use of in situ and hyperspectral data for mapping species diversity and above ground biomass in Shoolpaneshwar Wildlife Sanctuary, Gujarat","volume":"61","author":"Malhi","year":"2020","journal-title":"Trop. Ecol."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1111\/j.2006.0906-7590.04596.x","article-title":"Novel methods improve prediction of species\u2019 distributions from occurrence data","volume":"29","author":"Elith","year":"2006","journal-title":"Ecography"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1111\/j.1365-2664.2007.01408.x","article-title":"The influence of spatial errors in species occurrence data used in distribution models","volume":"45","author":"Graham","year":"2008","journal-title":"J. Appl. Ecol."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1007\/s10980-020-01007-7","article-title":"Comparing multi-and single-scale species distribution and abundance models built with the boosted regression tree algorithm","volume":"35","author":"Hallman","year":"2020","journal-title":"Landsc. Ecol."},{"key":"ref_75","first-page":"8","article-title":"BIOCLIM-a bioclimate analysis and prediction system","volume":"61","author":"Busby","year":"1991","journal-title":"Plant. Prot. Q."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3284\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:47:20Z","timestamp":1760165240000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3284"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,19]]},"references-count":75,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13163284"],"URL":"https:\/\/doi.org\/10.3390\/rs13163284","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,19]]}}}