Analysis of temporal and spatial pattern evolution characteristics of NDVI based on RS and GIS

Ping Song; Guangtong Sun; Yonghong Zhang; Muniang E Qi

doi:10.1117/12.2634674

12 May 2022 Analysis of temporal and spatial pattern evolution characteristics of NDVI based on RS and GIS

Ping Song, Guangtong Sun, Yonghong Zhang, Muniang E Qi

Proceedings Volume 12173, International Conference on Optics and Machine Vision (ICOMV 2022); 121730R (2022) https://doi.org/10.1117/12.2634674
Event: International Conference on Optics and Machine Vision (ICOMV 2022), 2022, Guangzhou, China

Abstract

Vegetation is an important part of any ecosystem, and its change has a far-reaching impact on regional and even global ecosystems.Normalized vegetation index (NDVI) is often used to reflect the growth status of vegetation. Combined with the seasonal change trend of topography and vegetation in the region, the evolution characteristics of vegetation temporal and spatial pattern in the region are analyzed. This paper selects Chengdu as the research object. Through the processing of Landsat8 remote sensing data in the third quarter of each year from 2013 to 2020, combined with Chengdu administrative regional data and DEM data, the temporal and spatial pattern change law of normalized vegetation index (NDVI) in Chengdu from 2013 to 2020 is studied by using trend analysis method and stability analysis method. According to the above analysis, taking all district level administrative regions of Chengdu as the center, the vegetation in Chengdu shows a fluctuating growth of low outside and high inside, and the vegetation outside the urban area tends to grow steadily; Spatially, the vegetation in the area below 2000m increases gradually with the increase of altitude, while the vegetation in the area above 2000m decreases gradually with the increase of altitude.

Citation Download Citation

Ping Song, Guangtong Sun, Yonghong Zhang, and Muniang E Qi "Analysis of temporal and spatial pattern evolution characteristics of NDVI based on RS and GIS", Proc. SPIE 12173, International Conference on Optics and Machine Vision (ICOMV 2022), 121730R (12 May 2022); https://doi.org/10.1117/12.2634674

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