{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T19:16:01Z","timestamp":1783106161610,"version":"3.54.6"},"reference-count":48,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,10,7]],"date-time":"2022-10-07T00:00:00Z","timestamp":1665100800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of China","award":["32060279"],"award-info":[{"award-number":["32060279"]}]},{"name":"Natural Science Foundation of China","award":["ZR2022MD063"],"award-info":[{"award-number":["ZR2022MD063"]}]},{"name":"Natural Science Foundation of China","award":["318052036"],"award-info":[{"award-number":["318052036"]}]},{"name":"Natural Science Foundation of China","award":["318052116"],"award-info":[{"award-number":["318052116"]}]},{"name":"Natural Science Foundation of Shandong Province","award":["32060279"],"award-info":[{"award-number":["32060279"]}]},{"name":"Natural Science Foundation of Shandong Province","award":["ZR2022MD063"],"award-info":[{"award-number":["ZR2022MD063"]}]},{"name":"Natural Science Foundation of Shandong Province","award":["318052036"],"award-info":[{"award-number":["318052036"]}]},{"name":"Natural Science Foundation of Shandong Province","award":["318052116"],"award-info":[{"award-number":["318052116"]}]},{"name":"Doctoral Startup Foundation of Liaocheng University","award":["32060279"],"award-info":[{"award-number":["32060279"]}]},{"name":"Doctoral Startup Foundation of Liaocheng University","award":["ZR2022MD063"],"award-info":[{"award-number":["ZR2022MD063"]}]},{"name":"Doctoral Startup Foundation of Liaocheng University","award":["318052036"],"award-info":[{"award-number":["318052036"]}]},{"name":"Doctoral Startup Foundation of Liaocheng University","award":["318052116"],"award-info":[{"award-number":["318052116"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The accuracy of drought monitoring models is crucial for drought monitoring and early warning. Random forest (RF) is being used widely in the field of artificial intelligence. Nonetheless, the application of a random forest model in grassland drought monitoring research is yet to be further explored. In this study, various drought hazard factors were integrated based on remote sensing data, including from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Precipitation Measurement (GPM), as multisource remote sensing data. Based on the RF, a comprehensive grassland drought monitoring model was constructed and tested in Inner Mongolia, China, as an example. The critical issue addressed is the construction of a grassland drought disaster monitoring model based on meteorological data and multisource remote sensing data by using an RF model, and the verification of the accuracy and reliability of its monitoring results. The results show that the grassland drought monitoring model could quantitatively monitor the drought situation in Inner Mongolia grasslands. There was a significantly positive correlation between the drought indicators output by the model and the standardized precipitation evapotranspiration index (SPEI) measured in the field. The correlation coefficients (R) between the drought degree were 0.9706 and 0.6387 for the training set and test set, respectively. The consistent rate between the model drought index and the SPEI reached 87.90%. Drought events in Inner Mongolia were monitored from April to September in wet years, normal years, and dry years using the constructed model. The monitoring results of the model constructed in this study were in accordance with the actual drought conditions, reflecting the development and spatial evolution of drought conditions. This study provides a new application method for the comprehensive assessment of grassland drought.<\/jats:p>","DOI":"10.3390\/rs14194981","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"4981","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Random Forest Model for Drought: Monitoring and Validation for Grassland Drought Based on Multi-Source Remote Sensing Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Qian","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Geographic Information Science, School of Geography and Environment, Liaocheng University, Liaocheng 252059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Geographic Information Science, School of Geography and Environment, Liaocheng University, Liaocheng 252059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mali","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Geographic Information Science, School of Geography and Environment, Liaocheng University, Liaocheng 252059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinjia","family":"Wu","sequence":"additional","affiliation":[{"name":"Grand Canal Research Centre, The Grand Canal Research Institute, Liaocheng University, Liaocheng 252000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qipeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Geographic Information Science, School of Geography and Environment, Liaocheng University, Liaocheng 252059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meie","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Management, Wuhan Polytechnic University, Wuhan 430048, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"112028","DOI":"10.1016\/j.jenvman.2021.112028","article-title":"Drought disaster monitoring using MODIS derived index for drought years: A space-based information for ecosystems and environmental conservation","volume":"284","author":"Orimoloye","year":"2021","journal-title":"J. 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