The Spatio-Temporal Evolution Characteristics of the Vegetation NDVI in the Northern Slope of the Tianshan Mountains at Different Spatial Scales

Jie Fan (), Yanmin Fan (), Junhui Cheng, Hongqi Wu, Yang Yan, Kai Zheng, Mingjie Shi and Qiangjun Yang
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Jie Fan: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Yanmin Fan: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Junhui Cheng: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Hongqi Wu: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Yang Yan: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Kai Zheng: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Mingjie Shi: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China
Qiangjun Yang: School of Resources and Environmental, Xinjiang Agricultural University, Urumqi 830052, China

Sustainability, 2023, vol. 15, issue 8, 1-14

Abstract: The purposes of this study are to reveal the spatial pattern and dynamic changes of NDVI in the northern slope of the Tianshan Mountains for an extended period and to explore whether the spatial and temporal evolution of NDVI in different spatial scales is consistent so as to provide a reasonable theoretical basis for the selection of appropriate remote sensing spatial resolution in the study area. The GIMMS NDVI remote sensing data set was used to resample the NDVI data with three spatial resolutions of 0.5 km × 0.5 km, 1 km × 1 km, and 8 km × 8 km. The Mann-Kendall method was used to analyze the spatial-temporal evolution characteristics of vegetation NDVI on the NTSM from 1981 to 2015. The results showed that the interannual variation trend and spatial distribution of vegetation NDVI were consistent at different spatial scales. The change of NDVI displayed an increasing trend with changes concentrated in the middle of the NTSM. Five distinct trends were observed: no significant change (35% of the area), significant positive change (26%), significant single peak change (15%), a significant U-shaped change relationship (12%), and significant negative change (11%). Remote sensing NDVI data with a spatial resolution of 8 km could be used to analyze the long-term interannual variation trend of vegetation NDVI on the NTSM.

Keywords: the northern slope of the Tianshan Mountains; vegetation NDVI; spatial scale; change trend; spatio-temporal distribution characteristics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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