Publication Date

1985

Location

Kyoto Japan

Description

The emergence of remote sensing has provided an advanced means for surveys and planning of grassland resources. In 1979, China started and since then has developed technical cooperations in agricultural remote sensing with FAO and UNDP respectively. With the cooperation, National Training and Application Center for Agricultural Remote Sensing was established at Beijing Agricultural University. We study on application of remote sensing to grassland resource surveys total area of 50,000 km2. All those indicate that remote sensing provides a mean of grassland surveys to achieve greater, faster, better and more economical results and also bears extensive prospects for use on grassland resource. For grassland remote sensing there is a significant working method that depends much upon Landsat imagery interpretation of grassland types, analysis of sampling surveys and accuracy with statistics and biomass estimation with available data derived from ground measurings. We use frequency sampling methods to calculate different grassland areas, reliability 95%, accuracy 90%, significance test on two results of interpretation, t< 1.96, results of twice-mode interpretation remained stable with little variance. We also made estimation of grassland productivity and density of stocking and described map of grassland-type interpretation from remote sensing imagery. This can be used by production department and the work efficiency has been raised 3-5 times.

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A Study on Application of Landsat Imagery to Grassland Resource Surveys

Kyoto Japan

The emergence of remote sensing has provided an advanced means for surveys and planning of grassland resources. In 1979, China started and since then has developed technical cooperations in agricultural remote sensing with FAO and UNDP respectively. With the cooperation, National Training and Application Center for Agricultural Remote Sensing was established at Beijing Agricultural University. We study on application of remote sensing to grassland resource surveys total area of 50,000 km2. All those indicate that remote sensing provides a mean of grassland surveys to achieve greater, faster, better and more economical results and also bears extensive prospects for use on grassland resource. For grassland remote sensing there is a significant working method that depends much upon Landsat imagery interpretation of grassland types, analysis of sampling surveys and accuracy with statistics and biomass estimation with available data derived from ground measurings. We use frequency sampling methods to calculate different grassland areas, reliability 95%, accuracy 90%, significance test on two results of interpretation, t< 1.96, results of twice-mode interpretation remained stable with little variance. We also made estimation of grassland productivity and density of stocking and described map of grassland-type interpretation from remote sensing imagery. This can be used by production department and the work efficiency has been raised 3-5 times.