The high spatial resolution remote sensing image classification based on SVM with the multi-source data

被引：0
|
作者：
Zhang, JS [1 ]
Pan, YZ [1 ]
He, CY [1 ]
Li, J [1 ]
机构：
[1] Beijing Normal Univ, Minist Educ China, Key Lab Environm Change & Nat Disaster, Beijing 100875, Peoples R China
来源：
IGARSS 2005: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, PROCEEDINGS | 2005年
关键词：
high spatial resolutiont; SVM; optimum hyperplane; texture; structure;
D O I：
暂无
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
High spatial remote sensing images have a promising prospect in land use and cover change study. In this article, we combined spectral, textural and structure information to classify IKONOS image by using SVM. Results indicated the method proposed by us could solve fragmented problem brought by single source data classification and attain higher accuracy.
引用
下载
收藏
页码：3818 / 3821
页数：4
相关论文
共 50 条
  • [1] On the classification of remote sensing high spatial resolution image data
    Batista, Marlos Henrique
    Haertel, Victor
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (20) : 5533 - 5548
  • [2] Multi-Source High Resolution Remote Sensing Image Fusion based on Intelligent Decision
    Zhang, Wanfeng
    Li, Shengyang
    Hao, Zhongweng
    Yang, Song
    PROCEEDINGS OF 2016 5TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), 2016, : 370 - 375
  • [3] High Resolution Remote Sensing Image Classification based on SVM and FCM
    Li, Qin
    Bao, Wenxing
    Li, Xing
    Li, Bin
    PROCEEDINGS OF THE 2015 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER ENGINEERING AND ELECTRONICS (ICECEE 2015), 2015, 24 : 1271 - 1278
  • [4] Evaluation of Multi-Source High-Resolution Remote Sensing Image Fusion in Aquaculture Areas
    Zhou, Weifeng
    Wang, Fei
    Wang, Xi
    Tang, Fenghua
    Li, Jiasheng
    APPLIED SCIENCES-BASEL, 2022, 12 (03):
  • [5] EFFECTIVE CLASSIFICATION OF LOCAL CLIMATE ZONES BASED ON MULTI-SOURCE REMOTE SENSING DATA
    Jing, Hao
    Feng, Yingchao
    Zhang, Wenkai
    Zhang, Yue
    Wang, Siyue
    Fu, Kun
    Chen, Kaiqiang
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 2666 - 2669
  • [6] Crop classification based on multi-source remote sensing data fusion and LSTM algorithm
    Xie Y.
    Zhang Y.
    Xun L.
    Chai X.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2019, 35 (15): : 129 - 137
  • [7] Development of classification scheme applicable to multi-source remote sensing data
    Jeong, JJ
    Chon, JC
    Kim, KO
    Yang, YK
    6TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL IX, PROCEEDINGS: IMAGE, ACOUSTIC, SPEECH AND SIGNAL PROCESSING II, 2002, : 119 - 124
  • [8] A Soil Moisture Spatial and Temporal Resolution Improving Algorithm Based on Multi-Source Remote Sensing Data and GRNN Model
    Cui, Yaokui
    Chen, Xi
    Xiong, Wentao
    He, Lian
    Lv, Feng
    Fan, Wenjie
    Luo, Zengliang
    Hong, Yang
    REMOTE SENSING, 2020, 12 (03)
  • [9] MODIS DATA-BASED SPATIAL CONSISTENCY CORRECTION OF LOW-RESOLUTION MULTI-SOURCE REMOTE SENSING IMAGERY
    Zhao, Yongquan
    Shan, Xiaojun
    Tang, Ping
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 2524 - 2527
  • [10] High-resolution urban vegetation coverage estimation based on multi-source remote sensing data fusion
    Pi X.
    Zeng Y.
    He C.
    National Remote Sensing Bulletin, 2021, 25 (06) : 1216 - 1226
12345