{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T06:50:02Z","timestamp":1776063002424,"version":"3.50.1"},"reference-count":86,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T00:00:00Z","timestamp":1624579200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2019R1G1A1005770"],"award-info":[{"award-number":["2019R1G1A1005770"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The spatial patterns of species richness can be used as indicators for conservation and restoration, but data problems, including the lack of species surveys and geographical data gaps, are obstacles to mapping species richness across large areas. Lack of species data can be overcome with remote sensing because it covers extended geographic areas and generates recurring data. We developed a Deep Learning (DL) framework using Moderate Resolution Imaging Spectroradiometer (MODIS) products and modeled potential species richness by stacking species distribution models (S-SDMs) to ask, \u201cWhat are the spatial patterns of potential plant species richness across the Korean Peninsula, including inaccessible North Korea, where survey data are limited?\u201d First, we estimated plant species richness in South Korea by combining the probability-based SDM results of 1574 species and used independent plant surveys to validate our potential species richness maps. Next, DL-based species richness models were fitted to the species richness results in South Korea, and a time-series of the normalized difference vegetation index (NDVI) and leaf area index (LAI) from MODIS. The individually developed models from South Korea were statistically tested using datasets that were not used in model training and obtained high accuracy outcomes (0.98, Pearson correlation). Finally, the proposed models were combined to estimate the richness patterns across the Korean Peninsula at a higher spatial resolution than the species survey data. From the statistical feature importance tests overall, growing season NDVI-related features were more important than LAI features for quantifying biodiversity from remote sensing time-series data.<\/jats:p>","DOI":"10.3390\/rs13132490","type":"journal-article","created":{"date-parts":[[2021,6,25]],"date-time":"2021-06-25T11:07:40Z","timestamp":1624619260000},"page":"2490","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Mapping Potential Plant Species Richness over Large Areas with Deep Learning, MODIS, and Species Distribution Models"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2130-1622","authenticated-orcid":false,"given":"Hyeyeong","family":"Choe","sequence":"first","affiliation":[{"name":"Department of Agriculture, Forestry and Bioresources, Seoul National University, Seoul 08826, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4943-3790","authenticated-orcid":false,"given":"Junhwa","family":"Chi","sequence":"additional","affiliation":[{"name":"Center of Remote Sensing and GIS, Korea Polar Research Institute, Incheon 21990, Korea"}]},{"given":"James H.","family":"Thorne","sequence":"additional","affiliation":[{"name":"Department of Environmental Science and Policy, University of California Davis, Davis, CA 95616, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1046\/j.1461-0248.2001.00230.x","article-title":"Quantifying biodiversity: Procedures and pitfalls in the measurement and comparison of species richness","volume":"4","author":"Gotelli","year":"2001","journal-title":"Ecol. 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