Estimation of Land Cover Mixing Ratio within a Pixel by Scaling between NOAA/AVHRR and LANDSAT/TM Data.
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概要
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A scaling technique was investigated to extrapolate the local information on land cover derived from high spatial resolution data (LANDSAT/TM) to more extensive area through low spatial resolution data (NOAA/AVHRR). The error of overlay between AVHRR data and TM data was evaluated to ensure the following analysis. Over a combined data set of TM and AVHRR, at first, land cover types were classified into three categories including vegetation, water, and dried non-vegetation with TM data, and next, AVHRR image density was statistically regressed with category mixture conditions derived from TM pixels in each AVHRR pixel. Based on the regression model, the land cover category mixing ratio was estimated from AVHRR data by extrapolate the model to the whole coverage of AVHRR data. As a result, we found that end-members of AVHRR data for each land cover category was under estimated. It is partially because that a large part of TM pixels are also mixture pixels. Taking this into account, we used the vegetation-soil-water index (VSWI) as a key to estimate the end-member of AVHRR data from related TM data. AVHRR VSW index is difficult to determine from AVHRR data only, because there are very few pure pixels for vegetation, soil or water to determine accurate end-members for each land cover category. In this study, we investigated a scaling method to estimate AVHRR VSW index by means of the regression analysis relating NOAA/AVHRR CCT counts in both of ch.1 and 2 with LANDSAT/TM VSW index.
- 社団法人 日本リモートセンシング学会の論文