Semi-supervised Hopfield-Type Neural Network for change detection in remotely sensed images

2012 ◽  
Author(s):  
Moumita Roy ◽  
Suvadeep Das ◽  
Susmita Ghosh ◽  
Ashish Ghosh
Keyword(s):  
Neural Network ◽  
Change Detection ◽  
Remotely Sensed ◽  
Remotely Sensed Images

Change Detection of Land Cover at Zheng Lanqi County of Inner Mongolia

2012 ◽  
Vol 518-523 ◽  
pp. 1371-1374
Author(s):  
Chu La Sa ◽  
Gui Xiang Liu ◽  
Mu Lan Wang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Inner Mongolia ◽  
Remotely Sensed ◽  
Landsat Tm ◽  
Remotely Sensed Images ◽  
Second Period

In the study we mapped and analyzed the land use/cover changes in Zheng Lanqi county by visual interpreting the 3 sets of Landsat TM and ETM remotely sensed images received in 1990, 2000 and 2005.The 6 broad types of land use/ cover were interpreted for the study area. Through analyzing land use/cover changes, our study indicated that the grassland and built-up area is dominant landscape in the study area.The grassland in the study area shrank 588.68km2 for urbanization and farmland cultivation for first periods. The unchanged land is 10639.75km2 and 10743.18km2 for the two periods (1990-2000 and 2000-2005), respectively. This indicated that the landscape conversion in second period became stable than that of first period, and environment is improved since 2000.

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