{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T05:06:59Z","timestamp":1735016819154,"version":"3.32.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685694","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,20]]},"abstract":"<jats:p>Droughts impose severe global challenges by affecting water resources, agricultural productivity, and ecosystems, and presenting considerable socioeconomic risks. In the Western United States, increasing aridity and reliance on limited water sources aggravate these issues. Accurate and timely drought forecasting is essential for effective water management, mitigating agricultural impacts, and addressing broader economic and environmental concerns. This research introduces a novel approach for early drought prediction by using remotely sensed data, with a specific focus on the drought-prone states of California and Nevada. We analyse MODIS (Moderate Resolution Imaging Spectroradiometer) time series data from 2001 to 2015 to derive indices such as the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI), These indices serve as monthly indicators of drought severe. We utilize the Long Short-Term Memory (LSTM) model to predict the Vegetation Condition Index (VCI), Temperature Condition Index (TCI). Subsequently, the annual average values of these indices are employed with linear regression to estimate drought severity levels. The results indicate that this hybrid approach enhances predictive accuracy by effectively integrating temporal dynamics with vegetation indices, providing actionable drought forecasts.<\/jats:p>","DOI":"10.3233\/faia241434","type":"book-chapter","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:48:47Z","timestamp":1734947327000},"source":"Crossref","is-referenced-by-count":0,"title":["Early Drought Prediction Using MODIS Time Series with LSTM: A Study of the Western United States"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4740-8903","authenticated-orcid":false,"given":"Somsak","family":"Limchupanpanich","sequence":"first","affiliation":[{"name":"Department of Interdisciplinary Science and Internationalization, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0557-527X","authenticated-orcid":false,"given":"Tanakorn","family":"Sritarapipat","sequence":"additional","affiliation":[{"name":"School of Mathematics and Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9682-559X","authenticated-orcid":false,"given":"Sayan","family":"Kaennakham","sequence":"additional","affiliation":[{"name":"School of Mathematics and Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2296-0374","authenticated-orcid":false,"given":"Suwit","family":"Ongsomwang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining X"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA241434","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:48:48Z","timestamp":1734947328000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA241434"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,20]]},"ISBN":["9781643685694"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia241434","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,20]]}}}