Africa Flores

A Global Capacity Building Vision for Societal Applications of Earth Observing Systems and Data: Key Questions and Recommendations

Capacity building using Earth observing (EO) systems and data (i.e., from orbital and nonorbital platforms) to enable societal applications includes the network of human, nonhuman, technical, nontechnical, hardware, and software dimensions that are necessary to successfully cross the valley [of death; see NRC (2001)] between science and research (port of departure) and societal application (port of arrival). In many parts of the world (especially where ground-based measurements are scarce or insufficient), applications of EO data still struggle for longevity or continuity for a variety of reasons, foremost among them being the lack of resilient capacity. An organization is said to have resilient capacity when it can retain and continue to build capacity in the face of unexpected shocks or stresses. Stresses can include intermittent power and limited Internet bandwidth, constant need for education on ever-increasing complexity of EO systems and data, communication challenges between the ports of departure and arrival (especially across time zones), and financial limitations and instability. Shocks may also include extreme events such as disasters and losing key staff with technical and institutional knowledge.

Identifying critical areas for conservation: Biodiversity and climate change in central America, Mexico, and the Dominican Republic

Abstract Given the rapidity and intensity of anthropogenic impacts on natural systems, assessing the effectiveness of current protected areas in preserving biodiversity is especially important in Mesoamerica and the Caribbean, which contain a wide array of species and ecosystems. In light of the growing need to consider climate change in policymaking, combining climate change projections with biodiversity maps allows scientists and decision-makers to understand possible climate change impacts on biodiversity. In this study, we use GIS to identify spatial relationships between regional climate change models and species habitat ranges for Mesoamerica and the Caribbean. Evaluating possible effects of climate change in terms of temperature and precipitation involves three factors: historical averages, historical ranges, and future averages. Because different ecosystems and species exist at different temperature and precipitation ranges, we consider “comfort zones” of each area. We develop a quantitative, spatial measurement of climate change intensity of each area by calculating the difference between historical and future averages and dividing that difference by the areas comfort zone, at a spatial resolution of 1km2. The result is a normalized grid of projected climate change severity. According to the modeling results, should worst case scenario conditions prevail, by the 2020s, the Caribbean coasts of Costa Rica, Honduras, Nicaragua, Panama, and the Dominican Republic, will be significantly impacted by climate change. By the 2080s, all of the ecosystems and species of Central America and the Dominican Republic may be subjected to conditions well outside of their traditional comfort zone, while most of Mexicos ecosystems and species are at lower risk of severe climate change impacts. Integrating species richness data with the climate change severity analyses identifies critical areas that may require specific interventions to facilitate the adaptation of species to climate change. The information generated points not only to the utility of current protected areas, but is also useful in guiding the development of new protected areas and biological corridors, for the reduction of the potential impacts of future climate change.

SERVIR: Connecting Earth Observation Satellite Data to Local Science Applications

With four international centers or “hubs,” a joint NASA/USAID initiative known as SERVIR is well positioned to fast-track the application of Earth Observation (EO) satellite data into decision-making contexts across the globe. This chapter describes the SERVIR program and how it helps developing countries use EO data to address environmental issues. The focus is on SERVIR applications in Land-Cover and Land-Use Change (LCLUC) and emissions in Asia. These projects and applications, developed in collaboration with SERVIR hubs in Nepal and Thailand, are helping decision-makers in these regions monitor and manage forest resources, understand land cover dynamics, and inform greenhouse gas inventories.

Land Cover Mapping for Green House Gas Inventories in Eastern and Southern Africa Using Landsat and High Resolution Imagery: Approach and Lessons Learnt

Africa is rich in natural resources including minerals, natural habitats and vegetation (African Bank 2007). However, these resources are under sustained pressure from a population that is growing at a faster rate than anywhere else on the globe (African Institute for Policy Development 2012). Substantial changes in land cover have been observed at national and local scales on the continent by various studies in the recent past. The rapidly growing population increases demand for food and land for settlement, a challenge that is further compounded by climate change. The effects of climate change make the African populace vulnerable to unpredictable weather patterns, floods, droughts and rising sea levels that threaten low coastal towns. This chapter addresses the pressing challenges of environmental management and sustainability in Eastern Africa.