Fractional vegetation cover estimation in aird and rare vegetation area aided by GF-2 remote sensing data

doi:10.13474/j.cnki.11-2246.2019.0214

Abstract

Abstract: The dimidiate pixel model has been widely used in the estimation of fractional vegetation cover because of its simple form and strong applicability. However, studies have shown that selecting parameters in model from 250 m spatial resolution images is very difficult in arid area with low fractional vegetation cover and desert. The estimation result is generally overestimated by using the parameters in model, NDVI_veg and NDVI_soil, acquired by the commonly used histogram accumulation method in the low fractional vegetation cover area with more bare soil and desert. So, this paper firstly used GF-2 high-resolution images of the same time with MODIS to map vegetation cover pixel. Then, Pixel Aggregate method was used to resample vegetation cover map from 0.8 m to 250 m spatial resolution to map pure vegetation cover pixels and pure bare soil pixels with 250 m spatial resolution. The maximum value of MODIS NDVI data corresponding to the spatial position of pure vegetation and pure bare soil pixels was taken as the NDVI_veg and NDVI_soil parameters required by the model to estimate the vegetation cover in the study area to estimate fractional vegetation cover. The estimation accuracy of linear regression method, nonlinear regression method, dimidiate pixel model based on histogram accumulation method to get parameters and based on GF-2 images to get parameters were compared.The results of experiment indicate that dimidiate pixel model based on GF-2 images accurately selected the parameters, NDVI_veg and NDVI_soil, in the low fractional vegetation cover area. This method improves the estimation accuracy of fractional vegetation cover in the arid area, and suppresses the result overestimation in low fractional vegetation cover area due to the effect of the higher NDVI problem in the sparse vegetation area.

Key words: GF-2, MODIS NDVI, dimidiate pixel model, fractional vegetation cover

CLC Number:

P237

SHEN Qian, ZHU Changming, ZHANG Xin. Fractional vegetation cover estimation in aird and rare vegetation area aided by GF-2 remote sensing data[J]. 测绘通报, 2019, 0(7): 33-38.

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