A Simple Approach for Guiding Classification of Forest and Crop from Remote Sensing Imagery: A Case Study of Suqian, China

Basic scientific research of land cover in Suqian is fundamental to ensure the sustainability of land resource management. The major study is to monitor the confusable land cover types according to the remote sensing, and the integrated information. It supplies a new direction for integrating date sets and improves the monitor on land cover. It presents a simple fusion approach for integrating time series of the MODIS Vegetation Index products and Landsat TM data. The fusion supplies the prior probability to distinguish forest with crop for guiding supervised classification which served in monitoring forest quantities-increasing in future. The entire operation just uses primarily the fusion method from the fuzzy mathematics to achieve various kinds of information with some simple parameters. However, the fusion is a spatial feature classification conduced remote sensing training mask data blending the advantages of the phonological information, the feature characteristics and the spatial-temporal data.