Jiao, QJ; Liu, LY; Liu, JG; Zhang, H; Zhang, B (2020). Atmospherically resistant vegetation water indices using the 970-nm water absorption feature. JOURNAL OF APPLIED REMOTE SENSING, 14(3), 34504.

Atmospheric correction can introduce errors in surface spectral reflectance, and hence induces errors in plant water estimation from remote sensing water indices. We intend to develop water indices that are less impacted by atmospheric effects for plant water content estimation based on the 970-nm water absorption feature. A simulation study using the PROSAIL and 6S models showed that uncertainty in atmospheric water vapor (WV) content can induce large variation in existing 970-nm water indices, such as WI, NWI-1, and NWI-3. An attempt was made to incorporate atmospheric WV absorption at 940 nm to correct for the perturbation due to atmospheric WV variability, leading to the development of improved indices, named as ARWI, NARWI-1, and NARWI-3. The performance of these indices was evaluated using the simulated and field spectral reflectance data, as well as Hyperion and GF5 satellite data. Results showed that the new indices were resistant to uncertainty of WV and could be used to deliver improved estimation of canopy water content, with a smaller root-mean-square-error (ARWI: 7.4 mg/cm(2), NARWI-1: 8.3 mg/cm(2), and NARWI-3: 8.8 mg/cm(2)) compared to that obtained using the traditional water indices (WI: 8.9 mg/cm(2), NWI-1: 9.4 mg/cm(2), and NWI-3: 16.6 mg/cm(2)). The water indices developed in this study, although needing further assessment in wide application scenarios, have great potential for monitoring of vegetation water status using satellite hyperspectral data with reflectance measurement around 970 nm. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.