Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1 CCD data in Mu Us Sandland

The leaf area index (LAI) is an important ecological parameter that characterizes the interface between vegetation canopy and the atmosphere. In addition, it is used by most process-oriented ecosystem models. This paper investigates the potential of HJ-1 CCD data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of the shrub LAI in Wushen Banner of Inner Mongolia in the Mu Us Sandland. MODTRAN (Moderate Resolution Atmospheric Radiance and Transmittance Model) was used for atmospheric correction. Shrubland was extracted using the threshold of the normalized difference vegetation index, with which water bodies and farmland were separated, in combination with a vegetation map of the People’s Republic of China (1:1000000). Using the geometric-optical model, we derive the per-pixel reflectance as a simple linear combination of two components, namely sunlit background and other. The fraction of sunlit background is related to the shrub LAI. With the support of HJ-1 CCD data, we employ linear spectral unmixing to obtain the fraction of sunlit background in an atmospherically corrected HJ image. In addition, we use the measured shrub canopy structural parameters for shrub communities to invert the geometric-optical model and retrieve the pixel-based shrub LAI. In total, 18 sample plots collected in Wushen Banner of Inner Mongolia are used for validation. The results of the shrub LAI show good agreement with R ² of 0.817 and a root-mean-squared error of 0.173.     

A high-accuracy method for simulating the XCO<Subscript>2</Subscript> global distribution using GOSAT retrieval data

A high-accuracy surface modeling (HASM) method based on the fundamental theorem of surfaces, is developed to simulate XCO₂ surfaces using the GOSAT retrieval XCO₂ data. Two tests are designed to investigate the simulation accuracy. The first test divides the existing satellite retrieval XCO₂ data into training points and testing points, and simulates the XCO₂ surface using the training points while computing the simulation error using the testing points. The absolute mean error (MAE) of the testing points is 1.189 ppmv, and the corresponding values of the comparison methods, Ordinary Kriging, IDW, and Spline are 1.203, 1.301, and 1.355 ppmv, respectively. The second test simulates the XCO₂ surface using all the satellite retrieval points and uses the TCCON (Total Carbon Column Observing Network) site observation values as the ture values. For the six typical TCCON sites, the HASM simulation MAE is 1.688 ppmv, and the satellite retrieval MAE at the same sites is 2.147 ppmv. These results indicate that HASM can successfully simulate XCO₂ surfaces based on satellite retrieval data.