Early and late rice identification from Tiangong- 2 wide band images based on CNN

¹ Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, China
² Key Laboratory of Space Utilization, Chinese Academy of Sciences, China

^* Corresponding author: zhouzhuang@csu.ac.cn

Abstract

The wide band images acquired from the Tiangong-2 space laboratory covers many spectral bands such as visible light, shortwave infrared and thermal infrared. These high-quality images can be used for space science experiments such as earth observation. In this paper, we use CNN (convolutional neural networks) to extract the spectral features of different landcover from the wide band images, then identify the early rice and the late rice accurately in Huarong County, Hunan Province, China. With advanced techniques such as deep learning, the spatial distribution information of crops can be effectively obtained from the wide band images which can provide data services for agricultural production management.