A Rice Mapping Method Based on Adaptive Feature Selection

Abstract

The invention relates to a rice mapping method based on adaptive feature selection, comprising the following steps: establishing a time series data set of enhanced vegetation index and water body index in the research area; establishing time series data of cloud distribution in the research area; based on remote sensing of key phenological periods of rice According to the cloud distribution of the image, the research area is divided into cloudy area and cloudless area; based on the time series analysis method, the classification results of rice in the cloudless area are obtained; the features of remote sensing images based on pixels are extracted; the image with the least cloud interference is selected and divided into The cloudy area and the cloudless area are segmented sequentially to obtain remote sensing image objects; the remote sensing image features based on pixels are integrated to extract object-oriented remote sensing image features; the rice classification results in the cloudless area are used as training data to obtain the rice classification in the cloudy area Results: The rice classification results in the cloudless area and the rice classification results in the cloudy area were combined to obtain the spatial distribution map of rice in the study area. The invention has the characteristics of high degree of automation, simple and easy to use, good robustness, high classification precision and the like.

Description

technical field [0001] The invention relates to a rice mapping method based on adaptive feature selection. Background technique [0002] As rice is the most important food crop in China and even in the world, it is very important to accurately grasp its planting area to ensure food security. At the same time, since the rice growth process requires a large amount of irrigation water and emits considerable methane gas, it is particularly important to quickly and efficiently monitor the spatial and temporal distribution of rice for the sustainable development of regional resources and the environment. The traditional artificial ground survey method is limited by various aspects such as manpower, material resources and natural conditions, and it is difficult to meet the current situational demand for rapid monitoring of crop planting area. With the in-depth development of remote sensing technology, especially the launch of Landsat 8 and China's Gaofen series satellites, which a...

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