Support to NRM activities in Ethiopia and Afghanistan
Local communities in fragile states have been extremely vulnerable to deteriorating environmental conditions affecting agricultural productivity and livelihoods. Climate change, overgrazing, under maintenance increase pressure on livelihoods and induce local conflicts.
NGOs aim to improve resilience of communities by education and introducing investments into sustainable environmental and agriculture practices. Often, they lack sufficient evidence about distribution and intensity of both causal factors and impacts. Furthermore, in absence of baseline spatial data it is difficult to monitor effectivity of mitigations and investments in short- to long-term horizons.
Generally, multi-scale and multi-temporal satellite imagery are a means to building tailored mapping tools to support investments planning and monitoring their effectiveness. Gisat has developed several custom solutions for operations of People in Need in Afghanistan and Ethiopia. Analytical results provided insights into intensity and distribution of agricultural patterns and practices, level of impacts of drought, erosion, overexploitation or conflicts, population distribution and accessibility of water or other sources. Geostatistical assessment and time series analysis facilitated estimation of trends, identification of potential driving factors and determination of affected communities and population as well as modeling level of impact under specific real or hypothetical scenarios.
Satellite mapping improved targeting of mitigation measures and targeting of long-term development aid resulting in building local capacity, improved access to water or agriculture resources, designing anti-erosion measures and re-forestation activities. Simple and intuitive visualisations and mapping outputs were a must to allow understanding by local authorities and villagers. Factual-based assessment positively shaped discussion with local authorities by providing indisputable evidence of levels of deterioration and extent of impacted population.