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Your search keyword '"ecologically vulnerable areas"' showing total 2 results
Start Over Descriptor "ecologically vulnerable areas" Topic phenology
2 results on '"ecologically vulnerable areas"'

1. Analyzing Ecological Vulnerability and Vegetation Phenology Response Using NDVI Time Series Data and the BFAST Algorithm

Author

Wanling Chen, Hao Guo, Lulu Gao, Huan Wang, Wenju Yun, Jiani Ma, and Chao Zhang

Subjects
010504 meteorology & atmospheric sciences, BFAST, NDVI, Science, 010501 environmental sciences, 01 natural sciences, Normalized Difference Vegetation Index, medicine, Time series, phenological response, Restoration ecology, 0105 earth and related environmental sciences, Phenology, Vegetation biomass, Vegetation phenology, negative changes, ecologically vulnerable areas, MODIS, time series analysis, Geography, General Earth and Planetary Sciences, medicine.symptom, Vegetation (pathology), Algorithm, Ecological vulnerability
Abstract

Identifying ecologically vulnerable areas and understanding the responses of phenology to negative changes in vegetation growth are important bases for ecological restoration. However, identifying ecologically vulnerable areas is difficult because it requires high spatial resolution and dense temporal resolution data over a long time period. In this study, a novel method is presented to identify ecologically vulnerable areas based on the normalized difference vegetation index (NDVI) time series from MOD09A1. Here, ecologically vulnerable areas are defined as those that experienced negative changes frequently and greatly in vegetation growth after the disturbances during 2000–2018. The number and magnitude of negative changes detected by the Breaks for Additive Season and Trend (BFAST) algorithm based on the NDVI time-series data were combined to identify ecologically vulnerable areas. TIMESAT was then used to extract the phenology metrics from an NDVI time series dataset to characterize the vegetation responses due to the abrupt negative changes detected by the BFAST algorithm. Focus was given to Jilin Province, a region of China known to be ecologically vulnerable because of frequent drought. The results showed that 13.52% of the study area, mostly in Jilin Province, is ecologically vulnerable. The vulnerability of trees is the lowest, while that of sparse vegetation is the highest. The response of phenology is such that the relative amount of vegetation biomass and length of the growing period were decreased by negative changes in growth for dense vegetation types. The present research results will be useful for the protection of environments being disturbed by regional ecological restoration.

Published
2020

2. Analyzing Ecological Vulnerability and Vegetation Phenology Response Using NDVI Time Series Data and the BFAST Algorithm.

Author

Ma, Jiani, Zhang, Chao, Guo, Hao, Chen, Wanling, Yun, Wenju, Gao, Lulu, and Wang, Huan

Subjects
*ALGORITHMS, *NORMALIZED difference vegetation index, *PHENOLOGY, *RESTORATION ecology, *PLANT phenology, *ENVIRONMENTAL protection, *TIME series analysis
Abstract

Identifying ecologically vulnerable areas and understanding the responses of phenology to negative changes in vegetation growth are important bases for ecological restoration. However, identifying ecologically vulnerable areas is difficult because it requires high spatial resolution and dense temporal resolution data over a long time period. In this study, a novel method is presented to identify ecologically vulnerable areas based on the normalized difference vegetation index (NDVI) time series from MOD09A1. Here, ecologically vulnerable areas are defined as those that experienced negative changes frequently and greatly in vegetation growth after the disturbances during 2000–2018. The number and magnitude of negative changes detected by the Breaks for Additive Season and Trend (BFAST) algorithm based on the NDVI time-series data were combined to identify ecologically vulnerable areas. TIMESAT was then used to extract the phenology metrics from an NDVI time series dataset to characterize the vegetation responses due to the abrupt negative changes detected by the BFAST algorithm. Focus was given to Jilin Province, a region of China known to be ecologically vulnerable because of frequent drought. The results showed that 13.52% of the study area, mostly in Jilin Province, is ecologically vulnerable. The vulnerability of trees is the lowest, while that of sparse vegetation is the highest. The response of phenology is such that the relative amount of vegetation biomass and length of the growing period were decreased by negative changes in growth for dense vegetation types. The present research results will be useful for the protection of environments being disturbed by regional ecological restoration. [ABSTRACT FROM AUTHOR]

Published
2020
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