{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T03:20:01Z","timestamp":1772508001729,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,14]],"date-time":"2020-03-14T00:00:00Z","timestamp":1584144000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The coal resources of Protective exploitation and environmental effects in Xinjiang","award":["\uff08Grant No. U1903209\uff09"],"award-info":[{"award-number":["\uff08Grant No. U1903209\uff09"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Since the implementation of the great western development strategy in 2000, the ecological environment in the western region of China has been significantly improved. In order to explore the temporal and spatial characteristics of vegetation coverage in the western region, this paper adopted the method of Maximum Value Composite (MVC) to obtain the mean Normalized Difference Vegetation Index (NDVI) of vegetation on the basis of the Moderate-resolution Imaging Spector audiometer (MODIS) data of 2000\/2005\/2010\/2015\/2018. Thereafter, the spatio-temporal differentiation characteristics of vegetation in western China were analyzed. The results show that: (1) According to the time characteristics of vegetation coverage in the western region, the average annual NDVI value of vegetation coverage in the growing season in the western region fluctuated between 0.12 and 0.15, among which that of 2000 to 2010 fluctuated more greatly but did not show obvious change trend. (2) Based on Sen trend and Mann-Kendall test analysis, the area of vegetation coverage improvement in the western region from 2000 to 2018 was larger than that of significant vegetation degradation. (3) From the perspective of global autocorrelation coefficient, Moran\u2019s I values were all positive from 2000 to 2018, which indicates that the vegetation coverage in the west showed strong positive autocorrelation in each period. According to the average value and coefficient of variation of vegetation coverage, the vegetation coverage was lower in 2000, its internal variation was smaller, and the vegetation coverage increased with time. According to the local spatial autocorrelation analysis, the vegetation coverage levels in different regions varied greatly. (4) The standard deviation ellipse method was used to study the spatial distribution and directional transformation of vegetation. It makes the result more intuitive, and the three levels of gravity center shift, direction shift, and angle shift were considered: the vegetation growth condition in the spatial aggregation area improved in 2015; the standard deviation ellipses in 2000 and 2018 overlapped and shifted eastward, which indicates that the vegetation coverage conditions in the two years were similar and got ameliorated.<\/jats:p>","DOI":"10.3390\/rs12060945","type":"journal-article","created":{"date-parts":[[2020,3,18]],"date-time":"2020-03-18T08:20:44Z","timestamp":1584519644000},"page":"945","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["An Approach to the Temporal and Spatial Characteristics of Vegetation in the Growing Season in Western China"],"prefix":"10.3390","volume":"12","author":[{"given":"Junfang","family":"Yuan","sequence":"first","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengfu","family":"Bian","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingwu","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyun","family":"Gu","sequence":"additional","affiliation":[{"name":"Henan Institute of Geological Survey, Zhengzhou 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4600-4085","authenticated-orcid":false,"given":"Haochen","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,14]]},"reference":[{"key":"ref_1","unstructured":"Mustafa, K., and Hirable, S. 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