Estimating fractional cover of non-photosynthetic vegetation in a typical grassland area of northern China based on Moderate Resolution Imaging Spectroradiometer (MODIS) image data

Rapid accurate estimation of the fractional cover of non-photosynthetic vegetation (fNPV) is essential for monitoring desertification, managing grassland resources, assessing soil erosion and grassland fire risk, and preserving the grassland ecological environment. However, there have been very few studies using multispectral remote sensing images (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS) images in this study) to estimate fNPV in typical grassland areas in northern China. In this study, using field spectra obtained from ground measurements in May and October 2017 and corresponding fNPV data, we calculated eight non-photosynthetic vegetation indices (NPVIs) from the simulated MODIS bands. We then determined the NPVIs that were suitable for the estimation of fNPV. Based on the determined NPVIs, we established a remote sensing estimation model for fNPV in typical grassland areas using MODIS image data. The spatial distribution of fNPV in the studied area was also investigated. The results indicated that the determined NPVIs, including the dead fuel index (DFI), shortwave-infrared ratio (SWIR₃₂), normalized difference tillage index (NDTI), modified soil-adjusted crop residue index (MSACRI), and soil tillage index (STI), used bands 6 and 7 in the shortwave-infrared region of the MODIS data; the DFI had the best performance, with a coefficient of determination (R²) of 0.68 and root mean square error of leave-one-out cross-validation (RMSECV) of 0.1390. The models based on MODIS image data for the estimation of fNPV using NPVIs had relatively good regression relations, and we determined that the DFI linear regression model was the best remote sensing model for monitoring fNPV in typical grassland areas, with an estimation accuracy exceeding 73.00%. Additionally, our results indicated that the distribution of non-photosynthetic vegetation exhibited substantial spatial heterogeneity and that fNPV gradually decreased from the north-eastern to south-western portions of the study area.