The spatio-temporal distribution of biocrusts can be used to monitor regional water resources in desert ecosystems. However, a lack of biocrust products from remotely sensed images with fine spatial resolution (FSR) limits scientific research in this area. To address this issue, we establish an estimation model for biocrusts (EMBC) in three steps for FSR images and map the large-scale fractional biocrust coverage ( FBC ) in deserts using Sentinel-2 images with a spatial resolution of 10 m. Firstly, we develop a fraction biocrust cover index ( FBCI ) based on radiative transfer theory. Next, a multi-angle calculation equation involving FBCI is established and the parameters for a pixel dichotomy model are solved by an inverse method using a linear kernel-driven model. Finally, this pixel dichotomy model with FBCI is used to calculate FBC . We validate the model using field measurements and compare the validation results with those estimated by a random forest model and a backpropagation neural network model. This comparison demonstrates that the value of FBC estimated by EMBC is highly consistent with field measurements (root mean square error (RMSE) = 0.0774, systematic deviation = -4.05%). Furthermore, the values of FBC estimated with EMBC and the two other models show a high level of consistency in terms of spatial distribution (RMSE < 0.0998). We conclude that our EMBC can accurately estimate FBC in a desert and is an important technique for monitoring drought in an arid environment.

#	Concept	H-Index	Publications	Citations
1	Engineering	2	2	73
2	Social Sciences	1	1	28
3	Geography	1	1	28
4	Biogeography	1	1	28
5	Fluid Mechanics	1	1	45

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