Extraction Method of Stand Density Based on High-Resolution Remote Sensing Imagery

Abstract

In this paper, a stand density extraction method is proposed based on QuickBird high-resolution satellite image data of Baisha artificial forest farm in Minhou, Fujian. Firstly, through the analysis band canopy image of QuickBird panchromatic, it is known that there is a maximum reflectivity point in the canopy. Then, the vegetation-covered area was extracted by the normalized difference vegetation index ( NDVI ). The canopy image of the forest was extracted through the decision tree classification algorithm. The texture information and spectral information were comprehensively utilized to classify the images. Then, the number of stand trees was extracted by the maximum filtering method, and the stand density was calculated to produce the stand density map. The experiment verified that this method can meet the needs of a stand density survey.