Object-oriented Classification Technique for Extracting Abandoned Farmlands by Using Remote Sensing Images

Abstract

The abandonment phenomenon has become one of the most serious problems in China in the last 20 years. Preventing the farmland from abandonment is an urgent issue for authority. Thus, abandoned farmland monitoring is very important. The conventional field investigation approach of abandonment status cannot meet the demand of large area because of the lack of efficiency and timeliness. Remote sensing technology has applied in terms of investigation and assessment of arable land abandonment. Visual interpretation can extract abandoned farmlands accurately, but this method is inefficiency. Image classification is a method of automatic recognition by machine, but the commonly used pixel-based classification has poor result and low accuracy in extraction of abandoned farmlands. Object-oriented classification technique can provide efficiency and accuracy. In this work, SPOT-5 image was used for surveying and extracting the abandoned farmland. This paper introduces the theory, process and result of object-oriented classification for abstracting abandoned farmland on the basic of remote sensing, and compares the result with pixel-based classification's result.