Paper
8 March 2018 A framework for farmland parcels extraction based on image classification
Author Affiliations +
Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 1060909 (2018) https://doi.org/10.1117/12.2282933
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
It is very important for the government to build an accurate national basic cultivated land database. In this work, farmland parcels extraction is one of the basic steps. However, during the past years, people had to spend much time on determining an area is a farmland parcel or not, since they were bounded to understand remote sensing images only from the mere visual interpretation. In order to overcome this problem, in this study, a method was proposed to extract farmland parcels by means of image classification. In the proposed method, farmland areas and ridge areas of the classification map are semantically processed independently and the results are fused together to form the final results of farmland parcels. Experiments on high spatial remote sensing images have shown the effectiveness of the proposed method.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guoying Liu, Wenying Ge, Xu Song, and Hongdan Zhao "A framework for farmland parcels extraction based on image classification", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060909 (8 March 2018); https://doi.org/10.1117/12.2282933
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KEYWORDS
Image classification

Remote sensing

Image segmentation

Feature extraction

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