Publications des scientifiques de l'IRD

Li Z., Feng Y. J., Gurgel H. L., Xu L., Dessay Nadine, Gong P. (2019). Use of spatial autocorrelation and time series Landsat images for long-term monitoring of surface water shrinkage and expansion in Guanting Reservoir, China. Remote Sensing Letters, 10 (12), 1192-1200. ISSN 2150-704X.

Titre du document
Use of spatial autocorrelation and time series Landsat images for long-term monitoring of surface water shrinkage and expansion in Guanting Reservoir, China
Année de publication
2019
Type de document
Article référencé dans le Web of Science WOS:000487609000001
Auteurs
Li Z., Feng Y. J., Gurgel H. L., Xu L., Dessay Nadine, Gong P.
Source
Remote Sensing Letters, 2019, 10 (12), 1192-1200 ISSN 2150-704X
Reservoirs are closely related to anthropic activities, and quantifying the long-term dynamics of surface water in reservoirs could be useful for decision-makers to improve the actual strategies of reservoir management. This study used the global Moran's I index, modi?ed Normalized Difference Water Index (MNDWI) and a total of 596 Landsat images during 1985-2018 for tracking the annual dynamics of water extent in the process of water shrinkage and expansion in Guanting Reservoir, China. Landscape metrics related to the area, elongation, fragmentation, and edge complexity of surface water in reservoir landscape were computed for tracking the annual dynamics of surface water patterns. Statistical comparison between the results of global Moran's I index and landscape metrics indicates that except for the complexity of water and non-water edge, global Moran's I index can successfully estimate the dynamics of the area, elongation and fragmentation of surface water in the reservoir. This study proposed a continuous approach of long-term monitoring of surface water patterns using spatial autocorrelation that might be used in the areas where the surface water extraction is difficult and water dynamics are complex.
Plan de classement
Hydrologie [062] ; Télédétection [126]
Description Géographique
CHINE ; PEKIN
Localisation
Fonds IRD [F B010077050]
Identifiant IRD
fdi:010077050
Contact