USING GEOBIA AND DATA FUSION APPROACH FOR LAND USE AND LAND COVER MAPPING

被引:7
|
作者
Wezyk, Piotr [1 ]
Hawrylo, Pawel [1 ]
Szostak, Marta [1 ]
Pierzchalski, Marcin [2 ]
de Kok, Roeland [2 ]
机构
[1] Univ Agr, Inst Forest Resources Management, Krakow, Poland
[2] ProGea Consulting, Fac Forestry Krakow, Krakow, Poland
关键词
classification; hydrology; OBIA; RapidEye; SaLMaR;
D O I
10.1515/quageo-2016-0009
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Land Use and Land Cover (LULC) maps play an important role in an environmental modelling, and for many years efforts have been made to improve and streamline the expensive mapping process. The aim of the study was to create LULC maps of three selected water catchment areas in South Poland using a Geographic Object-Based Image Analysis (GEOBIA) in order to highlight the advantages of this innovative, semi-automatic method of image analysis. the classification workflow included: multi-stage and multi-scale analyses based on a data fusion approach. Input data consisted mainly of BlackBridge (RapidEye) high resolution satellite imagery, although for distinguishing particular LULC classes, additional satellite images (LANDSAT TM5) and GIS-vector data were used. Accuracy assessment of GeoBia classification results varied from 0.83 to 0.87 (kappa), depending on the specific catchment area. The main recognized advantages of GEOBIA in the case study were: performing of multi-stage and multi-scale image classification using different features for specific LULC classes and the ability to using knowledge-based classification in conjunction with the data fusion approach in an efficient and reliable manner.
引用
收藏
页码:93 / 104
页数:12
相关论文
共 50 条
  • [41] Mapping Annual Land Use and Land Cover Changes Using MODIS Time Series
    Yin, He
    Pflugmacher, Dirk
    Kennedy, Robert E.
    Sulla-Menashe, Damien
    Hostert, Patrick
    [J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2014, 7 (08) : 3421 - 3427
  • [42] Combining land cover products using a minimum divergence and a Bayesian data fusion approach
    Gengler, Sarah
    Bogaert, Patrick
    [J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2018, 32 (04) : 806 - 826
  • [43] Land-Use and Land-Cover Mapping Using a Gradable Classification Method
    Kitada, Keigo
    Fukuyama, Kaoru
    [J]. REMOTE SENSING, 2012, 4 (06) : 1544 - 1558
  • [44] Impacts of Feature Normalization on Optical and SAR Data Fusion for Land Use/Land Cover Classification
    Zhang, Hongsheng
    Lin, Hui
    Li, Yu
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2015, 12 (05) : 1061 - 1065
  • [45] A Hybrid Approach for Land Use/Land Cover Classification
    Tang, Yanbing
    Pannell, Clifton W.
    [J]. GISCIENCE & REMOTE SENSING, 2009, 46 (04) : 365 - 387
  • [46] HYPERSPECTRAL DATA FOR LAND USE/LAND COVER CLASSIFICATION
    Vijayan, Divya V.
    Shankar, G. Ravi
    Shankar, T. Ravi
    [J]. ISPRS TECHNICAL COMMISSION VIII SYMPOSIUM, 2014, 40-8 : 991 - 995
  • [47] Landscape approach for land-use/land-cover classification and mapping at different scales
    Milanova, E
    Alexeev, B
    Sennikova, M
    Kalutskova, N
    Solntsev, V
    [J]. Understanding Land-Use and Land-Cover Change in Global and Regional Context, 2005, : 233 - 247
  • [48] Visual interpretation of FCC image for land use & land cover mapping: An expert system approach
    Prasad, R
    Sinha, AK
    Ranjan, KR
    [J]. SICE 2002: PROCEEDINGS OF THE 41ST SICE ANNUAL CONFERENCE, VOLS 1-5, 2002, : 2093 - 2098
  • [49] An approach for establishing correspondence between OpenStreetMap and reference datasets for land use and land cover mapping
    Zhou, Qi
    Jia, Xuecan
    Lin, Hao
    [J]. TRANSACTIONS IN GIS, 2019, 23 (06) : 1420 - 1443
  • [50] Integrating Remote Sensing and Geospatial Big Data for Land Cover and Land Use Mapping and Monitoring
    See, Linda
    Lesiv, Myroslava
    Schepaschenko, Dmitry
    [J]. LAND, 2024, 13 (06)