EXPLOITING VOLUNTEERED GEOGRAPHIC INFORMATION TO EASE LAND USE MAPPING OF AN URBAN LANDSCAPE

被引:0
|
作者
Arsanjani, J. Jokar [1 ]
Helbich, M. [1 ]
Bakillah, M. [1 ]
机构
[1] Heidelberg Univ, Inst Geog, GISci, D-69120 Heidelberg, Germany
来源
关键词
land use; urban landscape; volunteered geographic information; OpenStreetMap; supervised classification;
D O I
暂无
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Remote sensing techniques have eased land use/cover mapping substantially by observing the earth remotely through diminishing field surveying and in-site data collection. However, field measurement is still required to identify training sites for defining the existing land use classes, which requires visiting the study area. This paper is intended to utilize volunteered geographic information (VGI) contributions to the OpenStreetMap (OSM) project as an alternative data source instead of gathering training sites through in-site visits and to evaluate how accurate land use patterns can be mapped. High resolution imagery of RapidEye with 5 meter spatial resolution is selected to derive land use patterns of Koblenz, Germany through a maximum likelihood classification technique. The achieved land use map is compared with the Global Monitoring for Environment and Security Urban Atlas (GMESUA) and a Kappa Index of 89% is achieved. The outcomes prove that VGI can be integrated within remote sensing processes to facilitate the process of earth observation and monitoring.
引用
收藏
页码:51 / 54
页数:4
相关论文
共 50 条
  • [1] Toward mapping land-use patterns from volunteered geographic information
    Arsanjani, Jamal Jokar
    Helbich, Marco
    Bakillah, Mohamed
    Hagenauer, Julian
    Zipf, Alexander
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2013, 27 (12) : 2264 - 2278
  • [2] Exploiting deep learning and volunteered geographic information for mapping buildings in Kano, Nigeria
    Yuan, Jiangye
    Chowdhury, Pranab K. Roy
    Mckee, Jacob
    Yang, Hsiuhan Lexie
    Weaver, Jeanette
    Bhaduri, Budhendra
    SCIENTIFIC DATA, 2018, 5
  • [3] Exploiting deep learning and volunteered geographic information for mapping buildings in Kano, Nigeria
    Jiangye Yuan
    Pranab K. Roy Chowdhury
    Jacob McKee
    Hsiuhan Lexie Yang
    Jeanette Weaver
    Budhendra Bhaduri
    Scientific Data, 5
  • [4] Land Use Classification in Construction Areas Based on Volunteered Geographic Information
    Chen, Chenru
    Du, Zhenbo
    Zhu, Dehai
    Zhang, Chao
    Yang, Jianyu
    2016 FIFTH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS), 2016, : 32 - 35
  • [5] Assessment of volunteered geographic information for vegetation mapping
    Kellie A. Uyeda
    Douglas A. Stow
    Casey H. Richart
    Environmental Monitoring and Assessment, 2020, 192
  • [6] Assessment of volunteered geographic information for vegetation mapping
    Uyeda, Kellie A.
    Stow, Douglas A.
    Richart, Casey H.
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2020, 192 (08)
  • [7] Analysing the Sustainability of Urban Development: A review on the Potential Use of Volunteered Geographic Information
    Ibrahim, Nabila
    Ujang, Uznir
    Desa, Ghazali
    Ariffin, Azman
    ISPRS JOINT INTERNATIONAL GEOINFORMATION CONFERENCE 2015, 2015, II-2 (W2): : 169 - 174
  • [8] The Role of Mobile Volunteered Geographic Information in Urban Management
    Song, Weidong
    Sun, Guibo
    2010 18TH INTERNATIONAL CONFERENCE ON GEOINFORMATICS, 2010,
  • [9] Volunteered geographic information, urban forests, & environmental justice
    Foster, Alec
    Dunham, Ian M.
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2015, 53 : 65 - 75
  • [10] Soil landscape constraint mapping for coastal land use planning using geographic information system
    Yang X.
    Gray J.M.
    Chapman G.A.
    Young M.A.
    Journal of Coastal Conservation, 2007, 11 (3) : 143 - 151