Study on Plain Afforestation Area Extraction with Mapping Satellite-1 Imagery

Plain afforestation refers to the non-crop vegetation in crop-dominated plain area. As the main forest vegetation it has provided favorable conditions for ecological environment construction. The plain afforestation in this paper mainly includes farmland shelterbelt, road shelterbelt, residence shelterbelt and wasteland shelterbelt. But due to their small patches, getting the information of plain afforestation requires high spatial resolution remote sensing imagery. And the different sizes of kinds of afforestation patches make it difficult to extract all of them at once. In addition, it is a problem, if they could be extracted all, to distinguish themselves from one another. Based on this point, the paper explores a more accurate object-oriented classification method based on Mapping Satellite-1(MS1) imagery in Fengqiu County, Henan province, China. The innovation of this method lies in the selection of proper segmentation scale according to different kinds of plain afforestation. Build optimal segmentation levels to insure the farmland shelterbelt, road shelterbelt, residence shelterbelt and wasteland shelterbelt could be segmented from their background imagery completely. Then contrast and analyze the spectral and spatial characteristics of different afforestation to develop classification rule sets. The classification rule sets could be conveyed between levels and current class could inherit them from parent class. Then build membership function to extract the plain afforestation area hierarchically. The results showed that the plain afforestation area of Fengqiu is 152.51 km2. More specifically, the farmland shelterbelt area is 36.09 km2, the road shelterbelt area is 21.29 km2, the residence shelterbelt area is 71.56 km2, and the wasteland shelterbelt area is 23.57 km2. The classification accuracy is 93.50% and the Kappa coefficient is 0.92. It showed that the study have achieved fine classification results. And the results also verified the potential of object-oriented plain afforestation information extraction based on Mapping Satellite-1(MS1) imagery. This method can provide a technical support for the area accurate estimation of plain afforestadion.