{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T17:13:38Z","timestamp":1773249218755,"version":"3.50.1"},"reference-count":92,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T00:00:00Z","timestamp":1636329600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding the spatio-temporal pattern of natural vegetation helps decoding the responses to climate change and interpretation on forest resilience. Satellite remote sensing based data products, by virtue of their synoptic and repetitive coverage, offer to study the correlation and lag effects of rainfall on forest growth in a relatively longer time scale. We selected central India as the study site. It accommodates tropical natural vegetation of varied forest types such as moist and dry deciduous and evergreen and semi-evergreen forests that largely depend on the southwest monsoon. We used the MODIS derived NDVI and CHIRPS based rainfall datasets from 2001 to 2018 in order to analyze NDVI and rainfall trend by using Sen\u2019s slope and standard anomalies. The study observed a decreasing rainfall trend over 41% of the forests, while the rest of the forest area (59%) demonstrated an increase in rainfall. Furthermore, the study estimated drought conditions during 2002, 2004, 2009, 2014 and 2015 for 98.2%, 92.8%, 89.6%, 90.1% and 95.8% of the forest area, respectively; and surplus rainfall during 2003, 2005, 2007, 2011, 2013 and 2016 for 69.5%, 63.9%, 71.97%, 70.35%, 94.79% and 69.86% of the forest area, respectively. Hence, in the extreme dry year (2002), 93% of the forest area showed a negative anomaly, while in the extreme wet year (2013), 89% of forest cover demonstrated a positive anomaly in central India. The long-term vegetation trend analysis revealed that most of the forested area (&gt;80%) has a greening trend in central India. When we considered annual mean NDVI, the greening and browning trends were observed over at 88.65% and 11.35% of the forested area at 250 m resolution and over 93.01% and 6.99% of the area at 5 km resolution. When we considered the peak-growth period mean NDVI, the greening and browning trends were as follows: 81.97% and 18.03% at 250 m and 88.90% and 11.10% at 5 km, respectively. The relative variability in rainfall and vegetation growth at five yearly epochs revealed that the first epoch (2001\u20132005) was the driest, while the third epoch (2011\u20132015) was the wettest, corresponding to the lowest vegetation vigour in the first epoch and the highest in the third epoch during the past two decades. The study reaffirms that rainfall is the key climate variable in the tropics regulating the growth of natural vegetation, and the central Indian forests are dominantly resilient to rainfall variation.<\/jats:p>","DOI":"10.3390\/rs13214474","type":"journal-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T22:08:41Z","timestamp":1636409321000},"page":"4474","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Resilience of the Central Indian Forest Ecosystem to Rainfall Variability in the Context of a Changing Climate"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9129-5654","authenticated-orcid":false,"given":"Beependra","family":"Singh","sequence":"first","affiliation":[{"name":"Department of Remote Sensing, Birla Institute of Technology (BIT), Mesra, Ranchi 835215, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2375-7677","authenticated-orcid":false,"given":"Chockalingam","family":"Jeganathan","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Birla Institute of Technology (BIT), Mesra, Ranchi 835215, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5700-2109","authenticated-orcid":false,"given":"Virendra Singh","family":"Rathore","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Birla Institute of Technology (BIT), Mesra, Ranchi 835215, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9976-6270","authenticated-orcid":false,"given":"Mukunda Dev","family":"Behera","sequence":"additional","affiliation":[{"name":"Centre for Oceans, Rivers, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology (IIT), Kharagpur 721302, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7412-057X","authenticated-orcid":false,"given":"Chandra Prakash","family":"Singh","sequence":"additional","affiliation":[{"name":"Agriculre and Land Ecosystem Division, Space Applications Centre (SAC), ISRO, Ahmedabad 380015, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6803-6785","authenticated-orcid":false,"given":"Parth Sarathi","family":"Roy","sequence":"additional","affiliation":[{"name":"Sustainable Landscapes and Restoration, World Resources Institute India, New Delhi 110016, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5489-6880","authenticated-orcid":false,"given":"Peter M.","family":"Atkinson","sequence":"additional","affiliation":[{"name":"Lancaster Environment Centre, Lancaster University, Bailrigg, Lancaster LA1 4YW, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,8]]},"reference":[{"key":"ref_1","unstructured":"Pachauri, R.K., and Meyer, L.A. 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