Community-based groundwater and ecosystem restoration in semi-arid north Rajasthan (3): Evidence from remote sensing

- Remote sensing enables examination of trends in vegetation as a surrogate for service provision.
- Resolution of current data produces equivocal results, but the analytical methods offer potential.
- Improved imagery and analytical methods will enhance resolution of trends across landscapes.
- Landscape-scale analysis may highlight the important role of local management for broader goals.

Community-based measures recharging groundwater in semi-arid India has historically underpinned rural socio-ecological resilience, though are declining through technological, policy and other changes. Nevertheless, exemplars of community action are achieving catchment regeneration, including in Alwar District (Rajasthan) since the mid-1980s. This study analysed satellite remote sensing (RS) data to detect trends in groundwater and linked ecosystem services. Data from Landsat satellite missions offered a long time series and free access, though data gaps in the LandSat archive prior to 1997 limited time series analysis. ISODATA (Iterative Self Organising Data Analysis Technique) was used to analyse land cover trends, detecting increasing vegetation cover but not river rejuvenation due to limited spatial and spectral resolution. Analyses of NDVI (Normalised Difference Vegetation Index) and MSI (Moisture Stress Index) were used to assess change in vegetation cover, vigour and moisture stress over time. Analytical outputs were equivocal, although inter-annual fluctuations were observed to follow antecedent rainfall as vegetation responded to rising soil moisture and groundwater. Despite these equivocal conclusions, the research strongly suggests that analysis of RS data with improved resolution can provide surrogate indicators of change in groundwater and associated ecosystem services, supporting formulation of flexible policies incorporating local action to regenerate socio-ecological systems.