@inproceedings{65123619f42b49cb8ad9e822ad0f17e6,
title = "An improved back propagation neural network approach to the remote sensing land use and land cover classification",
abstract = "Land Use and Land Cover (LULC) is always an essential research focus as it is of great use in many fields. Though more and more data with high resolution can be used in LULC classification as time goes by, the remote sensing data is always useful because it contains a lot of information and can offer an overview of the study area. Thus, it is still important to find good methods to use the remote sensing data in the LULC classification. In this paper, the Back Propagation (BP) neural network improved by the Simulated Annealing (SA) algorithm is used as an approach and the result turns out to be good. This method can effectively classify the surface features into different categories.",
author = "Qiongshan Cao and Zhongyang Guo and Yong Yang",
note = "Publisher Copyright: {\textcopyright} 2015 Taylor \& Francis Group, London.; Proceedings of the Asia-Pacific Conference on Computer Science and Applications, CSAC 2014 ; Conference date: 27-12-2014 Through 28-12-2014",
year = "2015",
doi = "10.1201/b18508-64",
language = "英语",
isbn = "9781138028111",
series = "Computer Science and Applications - Proceedings of the Asia-Pacific Conference on Computer Science and Applications, CSAC 2014",
publisher = "CRC Press/Balkema",
pages = "369--373",
editor = "Ally Hu",
booktitle = "Computer Science and Applications - Proceedings of the Asia-Pacific Conference on Computer Science and Applications, CSAC 2014",
}
