Monitoring the changes of vegetation based on MODIS data and BFAST methods

doi:10.6046/gtzyyg.2016.03.23

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Abstract

Vegetation is a natural "link" which links soil, air and water and an "indicator" in global climate change research. Using normalized difference vegetation index (NDVI) time-series analyses, we can provide better support for the relevant researches and decision-making. Using MODIS NDVI data binding with BFAST (breaks for additive seasonal and trend) method, the authors implemented monitoring vegetation dynamics in the Laohahe River Basin and the surrounding areas, and identified its NDVI time-series abrupt change points occurring in time. The meteorological data and the quality of the data itself were also used as an influence factor analysis of the main reason for the breakpoints. It is found that precipitation, relative humidity, temperature, sunshine and water evaporation are positively correlated with NDVI trends, while wind speed is less correlated with NDVI trends. What's more, the precipitation and sunshine hour impact on NDVI change has a certain lag.

Keywords remote sensing image field parcel segmentation edge detection near-rectangle guided

TP79

Issue Date: 01 July 2016

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	LIANG Ruofei
	YANG Fengbao
	WANG Yimin
	MENG Yingchen
	WEI Hong

Cite this article:

LIANG Ruofei,YANG Fengbao,WANG Yimin, et al. Monitoring the changes of vegetation based on MODIS data and BFAST methods[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 146-153.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.03.23 OR https://www.gtzyyg.com/EN/Y2016/V28/I3/146

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