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本文叙述了在农业方面利用人造地球卫星资料的遥感技术的现状后，对得到的１９７５年１１月１１日的北海道十胜厅的大地卫星ＭＳＳ资料，用 ＬＡＲＳＹＳ软件系统进行了解析，表明了地表覆被物在广大地区解析的可能性。根据地表覆被物的光谱反射特性不同，把草地分成５类、林地４类、耕地５类、城市街区４类、水体５类；其它１０类，其解析结果是略可容许的。就错误比较多的来说，可以列出：草地１（ＧＲＡＳＳ１）和云 （ＣＬＱＵＤ ４） ，燕麦、黑麦（ ＯＡＴ／ＰＹＹ）和森林地带的森林（ＦＯＲＥＳＴ）云 ２和雪（ＳＮＯＷ），土壤／植物的（ＳＯＩ／ＶＥＧ）和水田，草地３和海滨植物，草地和落叶松。为了减轻这样的混乱，提高解析精度，除了使用没云的资料之外，还要利用季节变化的观测资料。而且可以期望今后由于使用美国大地卫星Ｄ的ＴＭ资料能提高解析能力。
This article describes the status quo of remote sensing using agricultural satellite data. After analyzing the satellite MSS data of Tokachi Hall of Hokkaido on November 11, 1975 using the LARSYS software system, it is shown that the surface coverage The possibility that the thing is analyzed in the vast area. According to the spectral reflectance characteristics of surface coverings, the grassland is divided into 5 categories, 4 types of forest land, 5 types of cultivated land, 4 types of urban blocks and 5 types of water bodies. The other 10 types are slightly admissible. In the more erroneous case, the following can be listed: FOREST 2 and SNOW for GRASS 1 and CLQUD 4, OAT / PYY and FOREST, / Plant (SOI / VEG) and paddy fields, meadow 3 and beach plants, meadow and larch. In order to reduce such confusion and improve the accuracy of the analysis, in addition to the use of cloud-free data, seasonal changes in the observation data are also used. And it is expected that analytic capabilities will be improved in the future due to the use of TM data from US Earth satellite D.