{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T21:05:41Z","timestamp":1772917541115,"version":"3.50.1"},"reference-count":91,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,5,26]],"date-time":"2020-05-26T00:00:00Z","timestamp":1590451200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2017YFE0100800"],"award-info":[{"award-number":["2017YFE0100800"]}]},{"name":"International Partnership Program of the Chinese Academy of Sciences","award":["131211KYSB20170046"],"award-info":[{"award-number":["131211KYSB20170046"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41671505\/41871345"],"award-info":[{"award-number":["41671505\/41871345"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"RFBR, MOST and DST","award":["19-55-80021"],"award-info":[{"award-number":["19-55-80021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Droughts are one of the primary natural disasters that affect agricultural economies, as well as the fire hazards of territories. Monitoring and researching droughts is of great importance for agricultural disaster prevention and reduction. The research significance of investigating the hysteresis of agricultural to meteorological droughts is to provide an important reference for agricultural drought monitoring and early warnings. Remote sensing drought monitoring indices can be employed for rapid and accurate drought monitoring at regional scales. In this paper, the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and the surface temperature product are used as the data sources. Calculating the temperature vegetation drought index (TVDI) and constructing a comprehensive drought disaster index (CDDI) based on the crop growth period allowed drought conditions and spatiotemporal evolution patterns in the Volgograd region in 2010 and 2012 to be effectively monitored. The causes of the drought were then analyzed based on the sensitivity of a drought to meteorological factors in rain-fed and irrigated lands. Finally, the lag time of agricultural to meteorological droughts and the hysteresis in different growth periods were analyzed using statistical analyses. The research shows that (1) the main drought patterns in 2010 were spring droughts from April to May and summer droughts from June to August, and the primary drought patterns in 2012 were spring droughts from April to June, with an affected area that reached 3.33% during the growth period; (2) local drought conditions are dominated by the average surface temperature factor. Rain-fed lands are sensitive to the temperature and are therefore prone to summer droughts. Irrigated lands are more sensitive to water shortages in the spring and less sensitive to extremely high temperature conditions; (3) there is a certain lag between meteorological and agricultural droughts during the different growth stages. The strongest lag relationship was found in the planting stage and the weakest one was found in the dormancy stage. Therefore, the meteorological drought index in the growth period has a better predictive ability for agricultural droughts during the appropriately selected growth stages.<\/jats:p>","DOI":"10.3390\/rs12111700","type":"journal-article","created":{"date-parts":[[2020,5,28]],"date-time":"2020-05-28T12:36:58Z","timestamp":1590669418000},"page":"1700","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Different Drought Legacies of Rain-Fed and Irrigated Croplands in a Typical Russian Agricultural Region"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3057-9653","authenticated-orcid":false,"given":"Yuanhuizi","family":"He","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0312-7376","authenticated-orcid":false,"given":"Huicong","family":"Jia","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7163-3644","authenticated-orcid":false,"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Valery G.","family":"Bondur","sequence":"additional","affiliation":[{"name":"Institute for Scientific Research of Aerospace Monitoring \u201cAEROCOSMOS\u201d, Gorokhovsky Pereulok 4, 105064 Moscow, Russia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,26]]},"reference":[{"key":"ref_1","unstructured":"Huschke, R.E. 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