Application of Remote Sensing Image Ecological Land Classification Method in Extraction of Crop Planting Area
With China’s economic development and population increase, people’s demand for food is also increasing.
Obtaining crop planting area is one of the important basic tasks for crop yield estimation. However, traditional
methods of yield estimation have the disadvantage of inaccurate information. The purpose of this paper is to
study the application of remote sensing image ecological land classification method in the extraction of crop
planting area. This article analyzes the basic principles of remote sensing image processing and remote sensing
image segmentation methods, and introduces the object-oriented computer automatic classification method and
artificial visual interpretation method algorithm flow. In this paper, these two classification methods are selected,
and crop remote sensing measurements are carried out in three study areas, and the two measurement results are
compared and analyzed. The experimental results prove that the object-oriented method can improve the
processing speed compared with the manual visual interpretation method. About two times, and as the
measurement area increases, the speed measurement advantage becomes more obvious. In this paper, the
performance of the object-oriented classification method and the artificial visual interpretation method are tested
respectively, and the total time taken is 49 days and 13.5 days, respectively.