Spatial dependency of soil line coefficients derived from Landsat ETM+ and MODIS imagery in Kyrgyzstan

Kunihiko Yoshino*, Taohong Zou, Khishigsuren Nyamsambuu, Tien Dat Pham, Hiroshi Okabe

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

Remotely sensed data in vegetated lands always consist of signals from vegetation, soil surface and path radiance. In order to analyze aspects of vegetation such as estimation of vegetation vigor or aboveground biomass, noise from soil surface and path radiance must be properly treated. The effects of path radiance are removed by atmospheric correction and the background reflection from soil surface is taken into account in some vegetation indices such as TSAVI (Transformed Soil Adjusted Vegetation Index) or SAVI (Soil Adjusted Vegetation Index). In these two vegetation indices, soil line coefficients, a (gain) and b (offset) shall be known to apply those vegetation indices in the study area. However, these soil line coefficients are dependent on existing soil types in the study area, especially on soil properties such as soil color, organic matter content and metal content. The spatial characteristics of soil line coefficients must be well understood in the analysis. This research studied, 1) the spatial dependency of soil line coefficients using geo-statistics, 2) differences in coefficients a and b among soil types which are categorized in the FAO soil classification system using the Student t-test, and 3) consistency between soil line coefficients derived from temporal Landsat TM data and those derived from temporal MODIS data by comparing their coefficients in Kyrgyzstan, a semi-arid region. In conclusion, 1) a value, the gain of the soil line shows a range in the semi-variograms.2) Soil line coefficients a and b for the seven soil types that exist in Kyrgyzstan are significantly different by statistical test.3) Coefficients derived from MODIS data and Landsat TM data have almost the same values.4) Vegetation information in vegetated lands can be more accurately obtained by using proper soil line coefficients corresponding to soil types in the FAO soil map. 5)A variety of soil colours for one type of soil and similarity of land slope classes may affect the identification of soil coefficients in different soil types.

Original languageEnglish
Title of host publicationACRS 2015 - 36th Asian Conference on Remote Sensing
Subtitle of host publicationFostering Resilient Growth in Asia
EditorsAlfredo Mahar Lagmay
Place of PublicationRed Hook, NY
PublisherAsian Association on Remote Sensing
Pages1022-1029
Number of pages8
ISBN (Electronic)9781510817210
Publication statusPublished - 2015
Externally publishedYes
Event36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015 - Quezon City, Metro Manila, Philippines
Duration: 24 Oct 201528 Oct 2015

Other

Other36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015
CountryPhilippines
CityQuezon City, Metro Manila
Period24/10/1528/10/15

Keywords

  • FAO soil map
  • Geo-statistics
  • Student t-test

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