1.College of Forestry, Nanjing Forestry University, Nanjing 210037, China 2. Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
Describing, quantifying and monitoring land use/land cover change play an important role in the global and environmental change investigation. Based on a comprehensive change detection method (CCDM), the authors mapped the land cover changes in the period between 2011 and 2016 over the Landsat image (Path33/Row33). CCDM integrates some spectral change based detection algorithms, which encompasses the multi-index integrated change analysis (MIICA) model and the Zone model, with an emphasis or core on MIICA. By calculating four spectral indices including change vector (CV), relative change vector maximum (RCVMAX), differenced normalized burn ratio (dNBR) and differenced normalized difference vegetation index (dNDVI), the land cover changes were extracted from the bi-temporal imagery. According to the previous and the current land cover change trends, coupled with the changes in results from MIICA and Zone models, the accuracies of change detection results by CCDM were evaluated. The results show that there is an accuracy of 96% for the category of no-change, and 40% for change category, with an overall accuracy of 68%. The CCDM is a simple, easily realized and widely used model to capture the potential land cover changes caused by the diverse natural and anthropengic disturbances in different landscapes.
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2018, Vol. 30 
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