Irrespective of several attempts to land use/cover mapping at local, regional, or global scales, mapping of vegetation physiognomic types is limited and challenging. The main objective of the research is to produce an accurate nationwide vegetation physiognomic map by using automated machine learning approach with the support of reference data. A time-series of the multi-spectral and multi-indices data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) were exploited along with the land-surface slope data. Reliable reference data of the vegetation physiognomic types were prepared by refining the existing vegetation survey data available in the country. The Random Forests based mapping framework adopted in the research showed high performance (Overall accuracy = 0.82, Kappa coefficient = 0.79) using 148 optimum number of features out of 231 featured used. A nationwide vegetation physiognomic map of year 2013 was produced in the research. The resulted map was compared to the existing MODIS Land Cover Type (MCD12Q1) product of year 2013. A huge difference was found between two maps. Validation with the reference data showed that the MCD12Q1 product did not work satisfactorily in Japan. The outcome of the research highlights the possibility of improving the accuracy of the MCD12Q1 product with special focus on reference data.
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.
ABSTRACT:Vegetation and land cover in Japan are rapidly changing. Abandoned farmland in 2010, for example, was 396,000 ha, or triple that of 1985. Efficient monitoring of changes in land cover is vital to both conservation of biodiversity and sustainable regional development. The Ministry of Environment is currently producing 1/25,000 scale vegetation maps for all of Japan, but the work is not yet completed. Traditional research is time consuming, and has difficulty coping with the rapid nature of change in the modern world. In this situation, classification of various scale remotely sensed data can be of premier use for efficient and timely monitoring of changes in vegetation.. In this research Terra/MODIS data is utilized to classify land cover in all of eastern Japan. Emphasis is placed on the Tohoku area, where large scale and rapid changes in vegetation have occurred in the aftermath of the Great Eastern Japan Earthquake of 11 March 2011. Large sections of coastal forest and agricultural lands, for example, were directly damaged by the earthquake or inundated by subsequent tsunami. Agricultural land was also abandoned due to radioactive contamination from the Fukushima nuclear power plant accident. The classification results are interpreted within the framework of a Landscape Transformation Sere model developed by Hara et al (2010), which presents a multi-staged pattern for tracking vegetation changes under successively heavy levels of human interference. The results of the research will be useful for balancing conservation of biodiversity and ecosystems with the needs for regional redevelopment.* Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.
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