Design And Implementation Of Remote Sensing System For Rice Information Extraction

Rice is a major staple food for60%of China’s population. Rice production is crucial to national food security. Extracting remote sensing information on rice growing area and harvest plays an important role in monitoring rice production and policy-making related to rice farming and rice price prediction.Application of remote sensing in agriculture is a part of earth observations from space. Remote sensing data have advantages such as macroscale, comprehensiveness, objectivity, timeliness, and eco-efftciency, and play important roles in extracting data on rice planting area, reproductive stage identification, growth monitoring, and yield estimation, but slow processing speed due to the vast amount of raw data and complex formats limits the use of remote sensing data.Development of new remote sensing applications can meet new challenges in data processing, and general purpose application software may be tailored for specific needs. Multi-source remote sensing data fusion can provide a wealth of information on remote sensing applications for rice farming. As a fourth generation language, IDL is capable of extracting information from raw image data and analyzing shapes. Thus, IDL is a language of choice for devising the rice information extraction systems.The article explores key components of rice remote sensing information extraction. A model tailored for the remote sensing data was proposed to organize, analyze, and process the image data. The processes, structure, and templates for the rice remote sensing information extraction were designed.This paper mainly discussed the key techniques for the rice data extraction Sys-tem based on IDL including its graphical user interface, Xmanager Incident Response, direct Graphics system, object graphics system, image roaming and image scaling and program releasing with virtual machine, as well as the function and structure of this system for rice area extraction, growth status monitoring, and yield forecasting. Rice cultivation data extraction and assessment thus becomes automatic and efficient.