MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP
Accuracy assessment of forest type maps is essential to evaluate the classification of forest ecosystems quantitatively. However, map users do not understand in which regions those forest types are well classified from conventional static accuracy measures. Hence, the objective of this study is to u...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-03-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3-W1/57/2019/isprs-annals-IV-3-W1-57-2019.pdf |
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| author | N. Tsutsumida S. Nagai P. Rodríguez-Veiga P. Rodríguez-Veiga P. Rodríguez-Veiga J. Katagi K. Nasahara T. Tadono |
| author_facet | N. Tsutsumida S. Nagai P. Rodríguez-Veiga P. Rodríguez-Veiga P. Rodríguez-Veiga J. Katagi K. Nasahara T. Tadono |
| author_sort | N. Tsutsumida |
| collection | DOAJ |
| description | Accuracy assessment of forest type maps is essential to evaluate the classification of forest ecosystems quantitatively. However, map users do not understand in which regions those forest types are well classified from conventional static accuracy measures. Hence, the objective of this study is to unveil spatial heterogeneities of accuracies of forest type classification in a map. Four forest types (deciduous broadleaf forest (DBF), deciduous needleleaf forest (DNF), evergreen broadleaf forest (EBF), and evergreen needleleaf forest (ENF)) found in the JAXA’s land use / cover map of Japan were assessed by a volunteered Site-based dataset for Assessment of Changing LAnd cover by JAXA (SACLAJ). A geographically weighted (GW) correspondence matrix was applied to them to calculate the degree of overall agreements of forest type classes (forest overall accuracy), and the degree of accuracy for each forest class (forest user’s and producer’s accuracies) in a spatially varying way. This study compared spatial surfaces of these measures with static ones of them. The results show that the forest overall accuracy of the forest map tends to be relatively more accurate in the central Japan, while less in the Kansai and Chubu regions and the northern edge of Hokkaido. Static forest user’s accuracy measures for DBF, DNF, and ENF are better than forest producer’s accuracy ones, while the GW approach tells us such characteristics vary spatially and some areas have opposite trends. This kind of spatial accuracy assessment provides a more informative description of the accuracy than the simple use of conventional accuracy measures. |
| first_indexed | 2024-12-22T15:16:17Z |
| format | Article |
| id | doaj.art-d3edf73e7c7d4b7787593f6f8117ec3c |
| institution | Directory Open Access Journal |
| issn | 2194-9042 2194-9050 |
| language | English |
| last_indexed | 2024-12-22T15:16:17Z |
| publishDate | 2019-03-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-d3edf73e7c7d4b7787593f6f8117ec3c2022-12-21T18:21:45ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502019-03-01IV-3-W1576310.5194/isprs-annals-IV-3-W1-57-2019MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAPN. Tsutsumida0S. Nagai1P. Rodríguez-Veiga2P. Rodríguez-Veiga3P. Rodríguez-Veiga4J. Katagi5K. Nasahara6T. Tadono7Graduate School of Global Environmental Studies, Kyoto University, Kyoto, JapanDepartment of Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Kanagawa, JapanGraduate School of Global Environmental Studies, Kyoto University, Kyoto, JapanCentre for Landscape and Climate Research, University of Leicester, Leicester, UKNERC National Centre for Earth Observation (NCEO), Leicester, UKGraduate School of Life and Environmental Sciences, University of Tsukuba, Ibaraki, JapanFaculty of Life and Environmental Sciences, University of Tsukuba, Ibaraki, JapanEarth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Ibaraki, JapanAccuracy assessment of forest type maps is essential to evaluate the classification of forest ecosystems quantitatively. However, map users do not understand in which regions those forest types are well classified from conventional static accuracy measures. Hence, the objective of this study is to unveil spatial heterogeneities of accuracies of forest type classification in a map. Four forest types (deciduous broadleaf forest (DBF), deciduous needleleaf forest (DNF), evergreen broadleaf forest (EBF), and evergreen needleleaf forest (ENF)) found in the JAXA’s land use / cover map of Japan were assessed by a volunteered Site-based dataset for Assessment of Changing LAnd cover by JAXA (SACLAJ). A geographically weighted (GW) correspondence matrix was applied to them to calculate the degree of overall agreements of forest type classes (forest overall accuracy), and the degree of accuracy for each forest class (forest user’s and producer’s accuracies) in a spatially varying way. This study compared spatial surfaces of these measures with static ones of them. The results show that the forest overall accuracy of the forest map tends to be relatively more accurate in the central Japan, while less in the Kansai and Chubu regions and the northern edge of Hokkaido. Static forest user’s accuracy measures for DBF, DNF, and ENF are better than forest producer’s accuracy ones, while the GW approach tells us such characteristics vary spatially and some areas have opposite trends. This kind of spatial accuracy assessment provides a more informative description of the accuracy than the simple use of conventional accuracy measures.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3-W1/57/2019/isprs-annals-IV-3-W1-57-2019.pdf |
| spellingShingle | N. Tsutsumida S. Nagai P. Rodríguez-Veiga P. Rodríguez-Veiga P. Rodríguez-Veiga J. Katagi K. Nasahara T. Tadono MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP |
| title_full | MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP |
| title_fullStr | MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP |
| title_full_unstemmed | MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP |
| title_short | MAPPING SPATIAL ACCURACY OF FOREST TYPE CLASSIFICATION IN JAXA’s HIGH-RESOLUTION LAND USE AND LAND COVER MAP |
| title_sort | mapping spatial accuracy of forest type classification in jaxa s high resolution land use and land cover map |
| url | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3-W1/57/2019/isprs-annals-IV-3-W1-57-2019.pdf |
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