INDRO · Remote sensing INdicators for DROught monitoring

Remote sensing INdicators for DROught monitoring

The INDRO project started on 1 May 2017 and ended on 20 August 2019, and was conducted by Dr. Manuela Balzarolo under supervision of the project's coordinator Prof. Josep Peñuelas at the Centre for Research on Ecology and Forestry Applications (CREAF). Global patterns of air temperature and precipitation are changing. According to the 4th Assessment report of the IPCC (2012), a substantial part of the world will be affected by a decrease in precipitation. Under conservative scenarios, future climate changes are likely to include further increases in mean temperature (about 2–4 °C globally by 2100) with signicant drying in some regions, as well as increases in frequency and severity of extreme droughts, hot extremes, and heat waves. Drought affects the terrestrial carbon balance by modifying both the rates of carbon uptake by photosynthesis (i.e. Gross Primary Productivity−GPP) and release by total ecosystem respiration, and the coupling between them. The drought response of terrestrial ecosystems can be analyzed using remote sensing (RS) techniques. Remotely-sensed indicators can provide an effective way to obtain real-time conditions of ecosystems and offer a range of spatial and temporal observations on changes in ecosystem structure, function, and services. Different RS indicators differ in their sensitivity to changes in photosynthetic status, but most of them (including Normalized Different Vegetation Index−NDVI) are not sensitive to rapid changes in plant photosynthesis that are induced by common environmental stressors, such as drought. This is due to the fact that most RS indicators have no direct link to photosynthetic functioning and are rather indicators for green biomass and thus for canopy structure rather than functioning. Furthermore, the ecological modeling and the remote sensing communities are particularly interested in the Light Use Efficiency (LUE) concept. However, no consensus has been reached regarding the most suitable algorithm for LUE and scientists still need to fully understand if (and how) models should simulate LUE in function of environmental factors (i.e. temperature and water availability). The general objective of the INDRO project was to understand the spatial and temporal variability of ecosystem gross primary productivity under several environmental conditions by investigating the relationship between remotely-based indicators and plant physiological status at global scale. The general objective has been translated into the following specific objectives: Objective 1 - To review the definition of drought and to investigate the drought affect ecosystem productivity by analyzing in-situ observations. Objective 2 - To determine the most appropriate remote sensing indicators for assessing ecosystem productivity in drought conditions. Objective 3 - To demonstrate the applicability of the methodology and indicators defined by testing and validating them at specific test sites. To achieve these objectives the INDRO project coupled in situ observations of ecosystem structure (i.e. biomass, leaf nitrogen content, leaf area index) and productivity (i.e. GPP derived from eddy covariance technique) with satellite data available from different platforms (i.e. MODIS, Proba-V and Sentinel-2).

Data: CORDIS, © European Union