Medium resolution remote sensing based winter wheat mapping corrected by low-resolution time series remote sensing images

doi:10.6046/gtzyyg.2020.01.04

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Abstract

Owing to influences of the same spectrum with the different thing and the same thing with the different spectrum, the medium resolution remotely sensed image, Landsat8 OLI, extracts the wheat extraction with the wrong information, which leads to low accuracy. The coarse resolution image with multi-temporal trait can discriminate the wheat information from other similar land cover. In this paper, the multi-temporal trait is adopted to solve the “wrong coming or wrong going” error of the OLI classification so as to increase the wheat extraction accuracy. The experiment shows that the OLI and MODIS can extract the wheat with high consistence, so the result of MODIS can correct the error of the OLI, where the phenomenon of the same spectrum with the different thing and the same thing with the different spectrum occurs. In the region of the same thing with different spectrum, the RMSE of OLI result is 0.758, while that of the MODIS correction result is 0.142. In the region of the different thing with the same spectrum, the RMSE of OLI result is 0.901, while that of the MODIS correction result is 0.122. All the results show that the MODIS result can correct OLI result for higher wheat extraction accuracy, which can solve the phenomenon of the same spectrum with the different thing and the same thing with the different spectrum.

Keywords time series linear mixed spectral unmixing fraction consistency analysis rectification

TP79

Corresponding Authors: Jinshui ZHANG E-mail: zhangjs@bnu.edu.cn

Issue Date: 14 March 2020

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	Shuang ZHU
	Jinshui ZHANG

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Shuang ZHU,Jinshui ZHANG. Medium resolution remote sensing based winter wheat mapping corrected by low-resolution time series remote sensing images[J]. Remote Sensing for Land & Resources, 2020, 32(1): 19-26.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.01.04 OR https://www.gtzyyg.com/EN/Y2020/V32/I1/19

Fig.1 Remote sensing image of OLI in the study area

Fig.2 Spectrum of land cover types in OLI image

Fig.3 Technology flowchart

Fig.4 Wheat extraction results of OLI image in the study area

Tab.1 Accuracy assessment of wheat classification from OLI image

Fig.5 Temporal curves of several typical land types from MODIS data

Fig.6 Scatter diagram from the MODIS endmembers and wheat distribution

Fig.7 Wheat result consistence between MODIS and OLI

Fig.8 MODIS correct OLI wheat result

Fig.9 MODIS correct OLI wheat result

Tab.2 RMSE of MODIS wheat result in OLI wheat region with error

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