No abstract

Spectral index methodology has been widely used in Leaf Area Index (LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers (SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition (VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index (NDVI), Modified Simple Ratio Indices (MSRI) and Triangle Vegetation Index (TVI), although the coefficient of determination R 2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.

Exploring the distribution and evolution of soil nutrients, it is needed to maintain quality of land and ensure food production. Based on geostatistical theory, 1,054 soil sites were selected from the surface (0-20 cm) of the typical black soil area in Northeast China. The spatial structure of soil pH, alkali-hydrolyzed N, effective P, and available K was investigated using Kriging and spatial statistics. The soils in the study area are acidic, alkali-hydrolyzed N, effective P, and available K content at moderate to high levels. Coefficients of variation for various nutrients ranged from 5 to 80%, all showing moderate variation. The pH, alkali-hydrolyzed N, effective P, and available K increased from South to North, the value of soil nutrients near the city were high. The results provide reference values for future work targeted at improving food security and reducing the effect on the environment.