Estimation of Vegetation Changes in East Asia with SPOT-Vegetation and Terra-MODIS

• KOYANAGI Tomokazu

  Master's Program of Life Environmental Sciences,University of Tsukuba

• MOTOHKA Takeshi

  Master's Program of Life Environmental Sciences,University of Tsukuba

• NISHIDA Kenlo

  Institute of Agricultural and Forest Engineering, University of Tsukuba

• MAITA Hideji

  Master's Program of Life Environmental Sciences,University of Tsukuba

Bibliographic Information

Other Title

• SPOT-VegetationとTerra-MODISによる東アジアの植生変動推定
• SPOT Vegetation ト Terra MODIS ニ ヨル ヒガシアジア ノ ショクセイ ヘンドウ スイテイ

Abstract

In recent years, distribution of forests is changing in many countries due to desertification and planting. Satellite remote sensing provides detailed distribution of the vegetation changes. In particular, the new satellite sensors, such as MODIS and SPOT-Vegetation, have provided more accurate data than old sensors such as NOAA-AVHRR for such purpose. In this research, we analyzed vegetation changes from year 2000 to 2005 in eastern Asia with data taken by SPOT-Vegetation and Terra-MODIS. In order to remove cloud contaminations, we applied annual MVC (maximum value composite) to time series in NDVI (Normalized Difference Vegetation Index) taken by each sensor. The annual MVC made it easy to see inter-annual variability because it is hardly influenced by seasonality of vegetation. Then we calculated the linear trend of inter-annual NDVI at each pixel. We applied these procedure to each sensor's NDVI data independently for the sake of cross-validation. As a result, both sensors consistently showed increase of NDVI in north-eastern to central China, whereas decrease in eastern Mongolia. By extracting the trends of NDVI with statistical significance of p=0.05 for both sensor's data, we estimated that NDVI increased in an area of 177,000km², whereas decreased in an area of 63,000km². Most of the increase happened in China. This estimation was consistent with FRA2005 (Global Forest Research Assessment 2005), in which Chinese forest reportedly increased in more than 200,000km² from 2000 to 2005.

Journal

• Journal of The Remote Sensing Society of Japan

  Journal of The Remote Sensing Society of Japan 28 (1), 36-43, 2008

  The Remote Sensing Society of Japan

Keywords

• NDVI
• vegetation
• cross-validation
• inter-annual change

Details

• CRID: 1390001204667475840
• NII Article ID: 10021141791
• NII Book ID: AN10035665
• DOI: 10.11440/rssj.28.36
• ISSN: 18831184
• ISSN: 02897911
• NDL BIB ID: 9378764
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I9378764
• Text Lang: en
• Data Source:
  • JaLC
  • NDL
  • CiNii Articles
• Abstract License Flag: Disallowed