Monitoring the riparian vegetation cover after the Wenchuan earthquake along the Minjiang River valley based on multi-temporal Landsat TM images：a case study of the Yingxiu-Wenchuan section

2013 ◽  
Vol 33 (16) ◽  
pp. 4966-4974 ◽  
Author(s):  
许积层 XU Jiceng ◽  
唐斌 TANG Bin ◽  
卢涛 LU Tao
Keyword(s):  
Wenchuan Earthquake ◽  
Vegetation Cover ◽  
Riparian Vegetation ◽  
River Valley ◽  
Landsat Tm ◽  
The Wenchuan Earthquake ◽  
Minjiang River ◽  
Multi Temporal

Dynamic monitoring of fractional vegetation cover along Minjiang River from Wenchuan County to Dujiangyan City using multi-temporal Landsat 5 and 8 images

2016 ◽  
Vol 36 (7) ◽  
Author(s):  
彭文甫 PENG Wenfu ◽  
王广杰 WANG Guangjie ◽  
周介铭 ZHOU Jieming ◽  
徐新良 XU Xinliang ◽  
罗怀良 LUO Huailiang ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Dynamic Monitoring ◽  
Fractional Vegetation Cover ◽  
Minjiang River ◽  
Multi Temporal

scholarly journals Fractional Vegetation Cover Change Detection In Megacities Using Landsat Time-Series Images: A Case Study Of Hanoi City (Vietnam) During 1986-2019

2019 ◽  
Vol 12 (4) ◽  
pp. 175-187
Author(s):  
Thanh Tien Nguyen
Keyword(s):  
Rural Areas ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Classification Method ◽  
Landsat 8 ◽  
Landsat Images ◽  
Fractional Vegetation Cover ◽  
Multi Temporal

The objective of the study is to assess changes of fractional vegetation cover (FVC) in Hanoi megacity in period of 33 years from 1986 to 2016 based on a two endmember spectral mixture analysis (SMA) model using multi-spectral and multi-temporal Landsat-5 TM and -8 OLI images. Landsat TM/OLI images were first radiometrically corrected. FVC was then estimated by means of a combination of Normalized Difference Vegetation Index (NDVI) and classification method. The estimated FVC results were validated using the field survey data. The assessment of FVC changes was finally carried out using spatial analysis in GIS. A case study from Hanoi city shows that: (i) the proposed approach performed well in estimating the FVC retrieved from the Landsat-8 OLI data and had good consistency with in situ measurements with the statistically achieved root mean square error (RMSE) of 0.02 (R 2 =0.935); (ii) total FVC area of 321.6 km 2 (accounting for 9.61% of the total area) was slightly reduced in the center of the city, whereas, FVC increased markedly with an area of 1163.6 km 2 (accounting for 34.78% of the total area) in suburban and rural areas. The results from this study demonstrate the combination of NDVI and classification method using Landsat images are promising for assessing FVC change in megacities.

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