Application of Artificial Neural Network for Paddy Field Classification using Spatiotemporal Information

作者：Yamaguchi Takashi^*; Kishida Kazuya; Nunohiro Eiji; Park Jong Geol; Mackin Kenneth J; Hara Keitaro; Matsushita Kotaro; Harada Ippei

来源：Information-An International Interdisciplinary Journal, 2010, 13(3B): 967-974.

• Artificial neural network
• Classification
• Remote sensing
• MODIS

Monitoring changes in paddy field area is important in Asia. For monitoring change in land surface, various applications using different satellites were researched in the field of remote sensing. However monitoring paddy field area with remote sensing is difficult due to the temporal change in land surface, and difference of spatiotemporal characteristics in countries and regions. In this paper, we applied artificial neural network to classify paddy field areas using moderate resolution sensor data that includes spatiotemporal information. Our aim is to automatically generate a paddy field classifier in order to create localized classifiers for each country and region.

• 出版日期2010-5