Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model
Japan, with over 75% forest cover, is one of the most heavily forested countries in the world. Various types of climax forest are distributed according to latitude and altitude. At the same time, human intervention in Japan has historically been intensive, and many forest habitats show the influence...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Sciendo
2015-01-01
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| Series: | Journal of Landscape Ecology |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/jlecol-2014-0019 |
| _version_ | 1819020415782092800 |
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| author | Harada Ippei Hara Keitarou Tomita Mizuki Short Kevin Park Jonggeol |
| author_facet | Harada Ippei Hara Keitarou Tomita Mizuki Short Kevin Park Jonggeol |
| author_sort | Harada Ippei |
| collection | DOAJ |
| description | Japan, with over 75% forest cover, is one of the most heavily forested countries in the world. Various types of climax forest are distributed according to latitude and altitude. At the same time, human intervention in Japan has historically been intensive, and many forest habitats show the influence of various levels of disturbance. Furthermore, Japanese landscapes are changing rapidly, and a system of efficient monitoring is needed. The aim of this research was to identify major historical trends in Japanese landscape change and to develop a system for identifying and monitoring patterns of landscape change at the national level. To provide a base for comparison, Warmth Index (WI) climatic data was digitalized and utilized to map potential climax vegetation for all of Japan. Extant Land Use Information System (LUIS) data were then modified and digitalized to generate national level Land Use/Land Cover (LU/LC) distribution maps for 1900, 1950 and 1985. In addition, MODIS data for 2001 acquired by the Tokyo University of Information Sciences were utilized for remote LU/LC classification using an unsupervised method on multi-temporal composite data. Eight classification categories were established using the ISODATA (cluster analyses) method; alpine plant communities, evergreen coniferous forest, evergreen broad-leaved forest, deciduous broad-leaved forest, mixed forest, arable land (irrigated rice paddy, non-irrigated, grassland), urban area, river and marsh. The results of the LUIS analyses and MODIS classifications were interpreted in terms of a Landscape Transformation Sere model assuming that under increasing levels of human disturbance the landscape will change through a series of stages. The results showed that overall forest cover in Japan has actually increased over the century covered by the data; from 72.1% in 1900 to 76.9% in 2001. Comparison of the actual vegetation and the potential vegetation as predicted by WI, however, indicated that in many areas the climax vegetation has been replaced by secondary forests such as conifer timber plantations. This trend was especially strong in the warm and mid temperate zones of western Japan. This research also demonstrated that classification of moderate resolution remote sensing data, interpreted within a LTS framework, can be an effective tool for efficient and repeat monitoring of landscape changes at the national level. In the future, the authors plan to continue utilizing this approach to track rapidly occurring changes in Japanese landscapes at the national level. |
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| format | Article |
| id | doaj.art-c5c139a200914696a7e4953a40000bb9 |
| institution | Directory Open Access Journal |
| issn | 1805-4196 |
| language | English |
| last_indexed | 2024-12-21T03:50:51Z |
| publishDate | 2015-01-01 |
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| spelling | doaj.art-c5c139a200914696a7e4953a40000bb92022-12-21T19:16:58ZengSciendoJournal of Landscape Ecology1805-41962015-01-0173233810.2478/jlecol-2014-0019jlecol-2014-0019Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) ModelHarada Ippei0Hara Keitarou1Tomita Mizuki2Short Kevin3Park Jonggeol4Department of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai Wakaba-ku, Chiba, 265-8501 JapanDepartment of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai Wakaba-ku, Chiba, 265-8501 JapanDepartment of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai Wakaba-ku, Chiba, 265-8501 JapanDepartment of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai Wakaba-ku, Chiba, 265-8501 JapanDepartment of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai Wakaba-ku, Chiba, 265-8501 JapanJapan, with over 75% forest cover, is one of the most heavily forested countries in the world. Various types of climax forest are distributed according to latitude and altitude. At the same time, human intervention in Japan has historically been intensive, and many forest habitats show the influence of various levels of disturbance. Furthermore, Japanese landscapes are changing rapidly, and a system of efficient monitoring is needed. The aim of this research was to identify major historical trends in Japanese landscape change and to develop a system for identifying and monitoring patterns of landscape change at the national level. To provide a base for comparison, Warmth Index (WI) climatic data was digitalized and utilized to map potential climax vegetation for all of Japan. Extant Land Use Information System (LUIS) data were then modified and digitalized to generate national level Land Use/Land Cover (LU/LC) distribution maps for 1900, 1950 and 1985. In addition, MODIS data for 2001 acquired by the Tokyo University of Information Sciences were utilized for remote LU/LC classification using an unsupervised method on multi-temporal composite data. Eight classification categories were established using the ISODATA (cluster analyses) method; alpine plant communities, evergreen coniferous forest, evergreen broad-leaved forest, deciduous broad-leaved forest, mixed forest, arable land (irrigated rice paddy, non-irrigated, grassland), urban area, river and marsh. The results of the LUIS analyses and MODIS classifications were interpreted in terms of a Landscape Transformation Sere model assuming that under increasing levels of human disturbance the landscape will change through a series of stages. The results showed that overall forest cover in Japan has actually increased over the century covered by the data; from 72.1% in 1900 to 76.9% in 2001. Comparison of the actual vegetation and the potential vegetation as predicted by WI, however, indicated that in many areas the climax vegetation has been replaced by secondary forests such as conifer timber plantations. This trend was especially strong in the warm and mid temperate zones of western Japan. This research also demonstrated that classification of moderate resolution remote sensing data, interpreted within a LTS framework, can be an effective tool for efficient and repeat monitoring of landscape changes at the national level. In the future, the authors plan to continue utilizing this approach to track rapidly occurring changes in Japanese landscapes at the national level.https://doi.org/10.2478/jlecol-2014-0019landscape changelandscape transformation seremonitoringmodisremote sensing |
| spellingShingle | Harada Ippei Hara Keitarou Tomita Mizuki Short Kevin Park Jonggeol Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model Journal of Landscape Ecology landscape change landscape transformation sere monitoring modis remote sensing |
| title | Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model |
| title_full | Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model |
| title_fullStr | Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model |
| title_full_unstemmed | Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model |
| title_short | Monitoring Landscape Changes in Japan Using Classification of Modis Data Combined with a Landscape Transformation Sere (LTS) Model |
| title_sort | monitoring landscape changes in japan using classification of modis data combined with a landscape transformation sere lts model |
| topic | landscape change landscape transformation sere monitoring modis remote sensing |
| url | https://doi.org/10.2478/jlecol-2014-0019 |
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