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摘要:
This paper presents an improved classification and mapping of vegetation types for all of Japan by utilizing the Moderate-resolution Imaging Spectroradiometer (MODIS) data. The Nadir BRDF-Adjusted Reflectance (MCD43A4 product) data were compared to the conventional Surface Reflectance (MOD09A1/MOY09A1 products) data for the classification of vegetation types: evergreen coniferous forest, evergreen broadleaf forest, deciduous coniferous forest, deciduous broadleaf forest, shrubs, herbaceous, arable;and non-vegetation. Very rich spectral and temporal features were prepared from MCD43A4 and MOD09A1/MOY09A1 products. Random Forests classifier was employed for the classification of vegetation types with the support of ground truth data prepared in the research. Accuracy metrics—confusion matrix, overall accuracy, and kappa coefficient calculated through 10-fold cross-validation approach—were used for quantitative comparison of MCD43A4 and MOD09A1/MOY09A1 products. The cross-validation results indicated better performance of the MCD43A4 (Overall accuracy = 0.73;Kappa coefficient = 0.69) product than conventional MOD09A1/MOY09A1 products (Overall accuracy = 0.70;Kappa coefficient = 0.66) for the classification. McNemar’s test was also used to confirm a significant difference (p-value = 0.0003) between MCD43A4 and MOD09A1/MOY09A1 products. Based on these results, by utilizing the MCD43A4 features, a new vegetation map was produced for all of Japan. The newly produced map showed better accuracy than the extant, MODIS Land Cover Type product (MCD12Q1) and Global Land Cover by National Mapping Organizations (GLCNMO) product in Japan.
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篇名 Improvement of Countrywide Vegetation Mapping over Japan and Comparison to Existing Maps
来源期刊 遥感技术进展(英文) 学科 医学
关键词 VEGETATION Classification MODIS RANDOM FORESTS MAPPING JAPAN
年,卷(期) 2018,(3) 所属期刊栏目
研究方向 页码范围 163-170
页数 8页 分类号 R73
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研究主题发展历程
节点文献
VEGETATION
Classification
MODIS
RANDOM
FORESTS
MAPPING
JAPAN
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研究去脉
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遥感技术进展(英文)
季刊
2169-267X
武汉市江夏区汤逊湖北路38号光谷总部空间
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148
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0
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