XXII ISPRS Congress 2012: Technical Commission VII

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Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/4: METHODS FOR LAND COVER CLASSIFICATION]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ACCURACY EVALUATION OF TWO GLOBAL LAND COVER DATA SETS OVER WETLANDS OF CHINA Z. G. Niu, Y. X. Shan, P. Gong

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia ACCURACY EVALUATION OF TWO GLOBAL LAND COVER DATA SETS OVER WETLANDS OF CHINA Z. G. Niu**, Y. X. Shan*, P. Gong?" * State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, 100101, zhgniu(ggmail.com ? Institute for Global Change Studies Tsinghua University, Beijing, 100084 Theme or Special Session: VII/4: Methods for Land Cover KEY WORDS: GLC2000, MODIS, China, Wetland, Remote sensing, Accuracy Evaluation ABSTRACT: Although wetlands are well known as one of the most important ecosystems in the world, there are still few global wetland mapping efforts at present. To evaluate the wetland-related types of data accurately for both the Global Land Cover 2000 (GLC2000) data set and MODIS land cover data set (MOD12Q1), we used the China wetland map of 2000, which was interpreted manually based on Landsat TM images, to examine the precision of these global land cover data sets from two aspects (class area accuracy, and spatial agreement) across China. The results show that the area consistency coefficients of wetland-related types between the two global data sets and the reference data are 77.27% and 56.85%, respectively. However, the overall accuracy of relevant wetland types from GLC2000 is only 19.81% based on results of confusion matrix of spatial consistency, and similarly, MOD12Q1 is merely 18.91%. Furthermore, the accuracy of the peatlands is much lower than that of the water bodies according to the results of per-pixel comparison. The categories where errors occurred frequently mainly include grasslands, croplands, bare lands and part of woodland (deciduous coniferous forest, deciduous broadleaf forest and open shrubland). The possible reasons for the low precision of wetland-related land cover types include (1)the different aims of various products and therefore the inconsistent wetland definitions in their systems; (2) the coarse spatial resolution of satellite images used in global data; (3) Discrepancies in dates when images were acquired between the global data set and the reference data. Overall, the unsatisfactory results highlight that more attention should be paid to the application of these two global data products, especially in wetland-relevant types across China. 1. INTRODUCTION Wetlands are among the most valuable ecosystems in the world and supply highly valuable services for human welfare (Costanza, 1997). Accurate information on global wetland areas and their spatial distribution is therefore important for wetland management and research. However, there are few global wetland mapping efforts at present. The Ramsar Sites Database includes 1757 internationally important wetland sites covering 158 countries. [http://ramsar.wetlands.org/Database /AbouttheRamsarSitesDatabase/tabid/812/language/en-US/Def ault.aspx]. The Global Lakes and Wetlands Database (GLWD), which has been developed jointly by the World Wide Fund for Nature (WWF) and the Center for Environmental Systems Research, University of Kassel, Germany, provide the current generation of a variety of existing maps, data and information on the global wetlands together with the application of Geographic Information System. (Lehner et al, 2004) . However, the application of the GLWD faces challenges because the information cannot be updated in time. Though GlobWetland II project, launched by the European Space Agency (ESA) in collaboration with the Ramsar Secretariat in 2009, aimed principally to develop a Global Wetlands Observing System information system, only over 200 wetland sites in the Mediterranean basin were included in the system. Until now there has been no global wetland data products based on identical satellite remote data. Therefore, the global land cover data sets, though which were not designed for the extraction of wetland, are the only available data sets at global scale. China, with the unique Tibetan wetlands, has extensive rich wetland types and the total wetland area (except for rice paddies) is about 3.595*10°km® (Niu,et al, 2009). China wetlands, therefore, are representative of the world’s wetlands both in amount and wetland types, and can be used to evaluate the precision of the wetland-related types in global land cover datasets. Since the 1990s, a series of improvements have been made in Land Use/Cover mapping based on the remote sensing data source at global scale. So far, there are four global land cover data sets available with 1 km spatial resolution, which include IGBP DISCover, UMD land cover products, the MODIS land cover products and Global Land Cover 2000 (GLC2000) , in which the AVHRR, MODIS, VEGETATION images are used respectively. Another new data set - Globcover Land Cover (2005 and 2009) with 300m spatial resolution - has been produced recently by ESA through an international partnership at global scale. All landcover types, including wetland, of the global land cover data sets were evaluated during existed research. Herold et al. (2008) found that precision of the peatlands from MODI12Ql1 and GLC2000 was 38.1% and 45.9% respectively. Chandra Giria's (2005) study makes a strong case for the inconsistency of the global land cover data sets which mainly occurs in the wetlands where the coefficient is only 36.66%. Ran ef al. (2010) used China land use/cover data to evaluate the existing four data sets across China and found that peatland type of IGBP DIScover data set had the highest precision, although it was just 38%. However, the peatland precision from GLC2000 and MOD12Q1 data set reached only 0.15% and 0.29%, respectively. For the UMD data set, as yet there is no separate peatland category in its classification system. The precision of the water from IGBP DIScover, UMD, GLC2000 and MOD12Q1 are 9.25%, 35.12%, 9%, and 9.43% respectively. The above wetland precision of MOD12Q1 and GLC2000 was

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