Contribution of Earth Observation to emerging environmental challenges in Africa
Session
Remote Sensing
Full Paper Review
No
Authors
Tobias Landmann, International Centre of Insect Physiology and Ecology, Kenya,
Tino Johansson, International Centre of Insect Physiology and Ecology, Kenya,
Abstract
The effects of emerging environmental problems associated with climate change and human-induced land cover change often directly impede livelihoods of the rural populace in Africa. Erratic rainfalls, flooding, forest cover loss, and land degradation are causing unstable agricultural yields and incomes. This paper illustrates examples, possibilities and future perspectives from current Earth Observation (EO) research to address landscape dynamics in relation to emerging environmental issues in Africa.
Two experimental EO examples from eastern Africa are showcased; (1) a multi-sensor approach to map vegetation productivity decline over eastern Africa, and (2) an integrative (multi-data) approach to map the spatial distribution of flowering plants at a local to landscape scale. In example 1, vegetation productivity, mapped at a regional scale using 250m MODIS NDVI imagery, is related to very high resolution (VHR) imagery in Google Earth. The MODIS-based productivity declines could be effectively linked to land transformation processes (i.e. Deforestation) using the VHR imagery. Moreover, using rainfall trends from passive radar observations, climate induced change could be largely disentangled from the human-induced change. The results of the second example are instigated for the quantification of pollination effects and to sustain healthy honey bee colonies. We suggest that integrative that is multi-sensor and multi-scale monitoring of flowering plants is possible.
The up- or down-scaling and data fusion techniques such as layering or convolution techniques have to be probed separately for every site and application. The use of innovative, effective and fast field based data collection methods such as Smartphone crowdsourcing is of special relevance to data scarce environments. Smart data integration techniques are paramount in seamless and use case orientated monitoring of emerging environmental issues in Africa.