Multi-temporal Vegetation Canopy Parameters Retrieval Using PROSAIL Model Inversion Against Landsat Observations with Application to Drought Effects Detection
Abstract
Monitoring ecosystem responses to water stress in various phases of a drought is a vital need. Out of all elements of a terrestrial ecosystem, vegetation is of particular relevance due to its crucial role in controlling earth-atmosphere interactions and, therefore, is a valuable indicator of ecosystem responses. Thus, greater efforts are needed to understand the responses of vegetation biophysical and biochemical parameters to soil moisture deficit over time in a drought episode. In this study, the PROSAIL radiative transfer model was inverted against a time series of multi-temporal Landsat observations by means of a look-up table approach to retrieve vegetation parameters in a drought episode in California Mediterranean grasslands in 2004. The retrieved parameters are Leaf Area Index (LAI), Chlorophyll content (Cab), Leaf Water Content (Cw), Leaf Dry Matter Content (Cdm), Average Leaf Angle (ALA) and leaf structure parameter (N). Before model inversion, the atmospheric correction of all satellite images were performed by FLAASH algorithms based on local information recorded in the nearest AERONET station to the study site. A separate LUT were made for each of the satellite images taking the corresponding solar zenith angle and available a priori knowledge about the objects on the ground. Afterwards, we inverted PROSAIL model and retrieved vegetation parameters and mapped their spatial variations over time. The performance of the model inversion was assessed by calculating R2 (0.86) and RMSE (0.27) between (satellite) retrieved and (destructive) measured LAI. The trend of all retrieved parameters were investigated over time in various phases of water stress during the drought episode. We found that all parameters retrieved by model inversion have shown good correlations with soil moisture deficit in the drought episode. These parameters co-varied with soil moisture content (LAI: R2 = 0.78 and RMSE = 0.17, Cab: R2 = 0.77 and RMSE = 9.7, Cw: R2 = 0.97 and RMSE = 0.003, Cdm: R2 = 0.81 and RMSE = 0.004, ALA: R2 = 0.66 and RMSE = 2.6, N: R2 = 0.79 and RMSE = 0.002). Our results confirm that inverting of PROSAIL model against multispectral remote sensing observations might be a feasible approach to point the way towards using satellite optical observations for drought signals detection in the ecosystem.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.B52A..04B
- Keywords:
-
- 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCESDE: 0466 Modeling;
- BIOGEOSCIENCESDE: 0480 Remote sensing;
- BIOGEOSCIENCES