Grassland dry matter mass remote sensing estimating method

Abstract

The invention discloses a grassland dry matter mass remote sensing estimating method, which belongs to the field of remote sensing application. The method comprises the following steps of: collecting and processing field test data; downloading and processing Modis (Moderate Resolution Imaging Spectroradiometer) satellite data; analyzing and modeling the data and detecting the accuracy and the like. The method for establishing a ground spectrum model for predicating ground dry matter mass and correcting a Modis spectrum model through ground hyperspectral experiments is different from the method for directly predicating biomass liveweight by using NDVI (Normalized Difference Vegetation Index) data of the Modis remote sensing satellite in other like researches so that the grassland dry matter mass remote sensing estimating method is helpful for improving the predicating accuracy, is beneficial for scientific management and reasonable utilization of the grassland resources and has important practical significance in correct evaluation of the real productivity of the grassland and the sustainable use of the grass resources.

Description

technical field [0001] The invention relates to a method for estimating dry matter mass on grassland by remote sensing, in particular to a non-destructive method that can accurately and quickly determine the pattern and dynamics of grassland productivity by using ground hyperspectral data and satellite remote sensing data, and belongs to the field of remote sensing applications. . Background technique [0002] The method of estimating aboveground dry matter mass using grassland spectral reflectance first originated in the 1970s. American scholars Pearson R. L. and Miller L. D. et al. used a portable spectrometer to measure the short grass grassland grassland on the Colorado Prairie grassland. Spectral reflectance of the community; they found a correlation between the spectral reflectance and the aboveground biomass of the plot. In the late 1970s, TUCHER C. J. pointed out that the establishment of mathematical models based on the ratio of infrared and red light bands (Infrar...

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Problems solved by technology

[0005] However, in terms of existing related technology research, environmental remote sensing researchers mostly focus on directly using high-altitude remote sensing data to extract vegetation indices to predict grassland dry matter, and grassland vegetation hyperspectral measurement data for large-scale production estimation are obviously less; Plant hyperspectral researchers mostly focus on exploring the relationship between plant spectral characteristics and plant physiological characteristics; the above two studies lack a combination and connection point, and there is no case to prove that ground hyperspectral extraction of vegetation index and remote sensing data extraction of vegetation Validity of Estimating Aboveground Dry Matter by Combining Indexes

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