Quantitative Inversion of Vegetation Biochemical Components Based on HJ1-A HSI in Coal Mining Area

This study investigates the applicability of estimating chlorophyll and water content at canopy level through empirical models and band combinations. The main goal is to evaluate and compare the accuracy of these two approaches for estimating and mapping canopy chlorophyll and water content through canopy reflectance and spaceborne HJ1-A HSI data acquired over Yanzhou coal mining area. An experiment was carried out. Canopy spectral measurements were acquired in the field using an ASD spectroradiometer along with simultaneous in situ measurements of leaf chlorophyll content. We tested seven variables derived from canopy reflectance for detecting canopy chlorophyll and water content: (1) R, (2) Log(1/R), (3) Log(1/R)′, (4) FDR, (5) SDR, (6) CRR, (7) BD. Stepwise multiple linear regressions were used to select wavelengths from HJ1-A HSI image bands. Correlation analysis was also done between different band combinations and biochemistry. A statistically significant relationship between Log(1/R) and chlorophyll was found at canopy level (R 2 = 0.516). SDR had the highest correlation with canopy water content (R 2 = 0.490). In addition, relationship between normalized different band combinations and chlorophyll and water content is also significantly obvious (R 2 = 0.577 and R 2 = 0.615). Canopy chlorophyll content was estimated with the intermediate accuracy (R 2 = 0.4144), while water content was estimated with an acceptable accuracy (R 2 = 0.4592). Canopy chlorophyll and water content spatial distribution were mapped. Chlorophyll and water stress levels were quantified by comparing different environmental stressors.