リモートセンシングによる農作物畑の分布解析  [in Japanese] Distribution Analysis of Farm Product Field by Remote Sensing  [in Japanese]

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Author(s)

    • 脇田 英治 WAKITA Eiji
    • 国立群馬工業高等専門学校環境都市工学科 Environmental Engineering Department, National Gunma College of Technology

Abstract

This paper proposes a new method to estimate the distribution of farm product fields by analyzing the satellite image. In this study the konjac field is dealt with mainly as the farm product field. However, it is expected that the result of this study is applicable to the other farm products as well as the konjac. The procedure of the land cover classification by the proposed method is as follows.<BR>1) The likelihood values are estimated by using the pixel values of the band 1-3 of the satellite image, the NDVI and the NDCI as the evaluation index.<BR>2) The land cover classification is performed by judging the likelihood values with the standard likelihood value corresponding to the reliability.<BR>The field survey and satellite image photography were executed simultaneously in the region where the farm product fields crowd. The proposed method and the maximum likelihood method were applied to the obtained satellite image, and the classification analysis of the satellite image was executed. It was confirmed that the both method results correspond with the field survey result with a fair degree of precision. It became clear that the proposed method gives more satisfactory result than the maximum likelihood method by comparing the both methods.

Journal

  • Journal of The Remote Sensing Society of Japan

    Journal of The Remote Sensing Society of Japan 28(3), 256-264, 2008-06-25

    The Remote Sensing Society of Japan

References:  13

Codes

  • NII Article ID (NAID)
    10024344292
  • NII NACSIS-CAT ID (NCID)
    AN10035665
  • Text Lang
    JPN
  • Article Type
    ART
  • ISSN
    02897911
  • NDL Article ID
    9565568
  • NDL Source Classification
    ZM15(科学技術--科学技術一般--測定・測定器)
  • NDL Call No.
    Z14-1022
  • Data Source
    CJP  NDL  J-STAGE 
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