Alexander Lotsch

Land cover mapping in support of LAI and FPAR retrievals from EOS-MODIS and MISR: classification methods and sensitivities to errors

Land cover maps are used widely to parameterize the biophysical properties of plant canopies in models that describe terrestrial biogeochemical processes. In this paper, we describe the use of supervised classification algorithms to generate land cover maps that characterize the vegetation types required for Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) retrievals from MODIS and MISR. As part of this analysis, we examine the sensitivity of remote sensing-based retrievals of LAI and FPAR to land cover information used to parameterize vegetation canopy radiative transfer models. Specifically, a decision tree classification algorithm is used to generate a land cover map of North America from Advanced Very High Resolution Radiometer (AVHRR) data with 1 km spatial resolution using a six-biome classification scheme. To do this, a time series of normalized difference vegetation index data from the AVHRR is used in association with extensive site-based training data compiled using Landsat Thematic Mapper (TM) and ancillary map sources. Accuracy assessment of the map produced via decision tree classification yields a cross-validated map accuracy of 73%. Results comparing LAI and FPAR retrievals using maps from different sources show that disagreement in land cover labels generally do not translate into strong disagreement in LAI and FPAR maps. Further, the main source of disagreement in LAI and FPAR maps can be attributed to specific biome classes that are characterized by a continuum of fractional cover and canopy structure.

Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Climate Change: New Dimensions in Disaster Risk, Exposure, Vulnerability, and Resilience

Executive Summary Disaster signifies extreme impacts suffered when hazardous physical events interact with vulnerable social conditions to severely alter the normal functioning of a community or a society (high confidence) . Social vulnerability and exposure are key determinants of disaster risk and help explain why non-extreme physical events and chronic hazards can also lead to extreme impacts and disasters, while some extreme events do not. Extreme impacts on human, ecological, or physical systems derive from individual extreme or non-extreme events, or a compounding of events or their impacts (for example, drought creating the conditions for wildfire, followed by heavy rain leading to landslides and soil erosion). [1.1.2.1, 1.1.2.3, 1.2.3.1, 1.3] Management strategies based on the reduction of everyday or chronic risk factors and on the reduction of risk associated with non-extreme events, as opposed to strategies based solely on the exceptional or extreme, provide a mechanism that facilitates the reduction of disaster risk and the preparation for and response to extremes and disasters (high confidence) . Effective adaptation to climate change requires an understanding of the diverse ways in which social processes and development pathways shape disaster risk. Disaster risk is often causally related to ongoing, chronic, or persistent environmental, economic, or social risk factors. [1.1.2.2, 1.1.3, 1.1.4.1, 1.3.2] Development practice, policy, and outcomes are critical to shaping disaster risk (high confidence) . Disaster risk may be increased by shortcomings in development. Reductions in the rate of depletion of ecosystem services, improvements in urban land use and territorial organization processes, the strengthening of rural livelihoods, and general and specific advances in urban and rural governance advance the composite agenda of poverty reduction, disaster risk reduction, and adaptation to climate change. [1.1.2.1, 1.1.2.2, 1.1.3, 1.3.2, 1.3.3]

Assessment of remotely sensed and statistical inventories of African agricultural fields

This paper critically examines different sources of remotely sensed and statistical inventories of African agricultural fields. Substantial discrepancies are found across alternative sources of information in both the extent and location of agricultural fields. In one‐third of the countries, the difference between lowest and highest field extent estimate exceeds 25% of the total country area, and the maximum difference at the continental level is 2.6 million km2. Much of the disagreement between land‐cover maps arises from areas of low cropping density. These inconsistencies have important implications when using these data directly, e.g. for the assessment of land cover changes, or indirectly in economic or physical models, and indicate a need to explicitly quantify uncertainties arising from the limitations in land‐cover data. They also highlight the need for development of regional land information systems for baseline development and informed policy decisions.

Spatio-temporal deconvolution of NDVI image sequences using independent component analysis

Independent component analysis (ICA) provides a powerful new method to spatially and temporally deconvolve image sequences into components that capture variability arising from independent physical sources. To do this, ICA uses information contained in higher order cross-moments of multivariate data. We use remotely sensed time series of the normalized difference vegetation index to illustrate the utility of this technique.

HIV/AIDS, Climate Change and Disaster Management: Challenges for Institutions in Malawi

Southern African institutions involved in disaster management face two major new threats: the HIV/AIDS pandemic (eroding organizational capacity and increasing vulnerability of the population), and climate change (higher risk of extreme events and disasters). Analyzing the combined effects of these two threats on six disaster-related institutions in Malawi, the authors find evidence of a growing gap between demand for their services and capacity to satisfy that demand. HIV/AIDS leads to staff attrition, high vacancy rates, absenteeism, increased workload and other negative effects enhanced by human resources policies and financial limitations. Many necessary tasks cannot be carried out adequately with constraints such as the 42 percent vacancy rate in the Department of Poverty and Disaster Management Affairs, or the reduction of rainfall stations operated by the Meteorological Service from over 800 in 1988 to just 135 in 2006. The authors highlight implications of declining organizational capacity for climate change adaptation, and formulate recommendations.

Sensitivity of Cropping Patterns in Africa to Transient Climate Change

The detailed analysis of current cropping areas in Africa presented here reveals significant climate sensitivities of cropland density and distribution across a variety of agro-ecosystems. Based on empirical climate-cropland relationships, cropland density responds positively to increases in precipitation in semi-arid and arid zones of the sub-tropics and warmer temperatures in higher elevations. As a result, marginal increases in seasonal precipitation lead to denser cropping areas in arid and semi-arid regions. Warmer temperatures, on the other hand, tend to decrease the probability of cropping in most parts of Africa (the opposite is true for increases in rainfall and decreases in temperatures relative to current conditions). Despite discrepancies and uncertainties in climate model output, the analysis suggests that cropland area in Africa is likely to decrease significantly in response to transient changes in climate. The continent is expected to have lost on average 4.1 percent of its cropland by 2039, and 18.4 percent is likely to have disappeared by the end of the century. In some regions of Africa the losses in cropland area are likely to occur at a much faster rate, with northern and eastern Africa losing up to 15 percent of their current cropland area within the next 30 years or so. Gains in cropland area in western and southern Africa due to projected increases in precipitation during the earlier portions of the century will be offset by losses later on. In conjunction with existing challenges in the agricultural sector in Africa, these findings demand sound policies to manage existing agricultural lands and the productivity of cropping systems.

Investigating the Impact of Climate Change on the Robustness of Index-Based Microinsurance in Malawi

This analysis explores the potential impact of climate change on the viability of the Malawi weather insurance program making use of scenarios of climate change-induced variations in rainfall patterns. The analysis is important from a methodological and policy perspective. By combining catastrophe insurance modeling with climate modeling, the methodology demonstrates the feasibility, albeit with large uncertainties, of estimating the effects of climate change on the near and long-term future of microinsurance schemes serving the poor. By providing a model-based estimate of the incremental role of climate change, along with the associated uncertainties, this methodology can quantitatively demonstrate the need for financial assistance to protect micro-insurance pools against climate-change induced insolvency. This is of major concern to donors, nongovernmental organizations, and others supporting these innovative systems; those actually at-risk; and insurers. A quantitative estimate of the additional burden that climate change imposes on weather insurance for poor regions is of interest to organizations funding adaptation.

Mainstreaming Climate Adaptation into Development Assistance in Mozambique : Institutional Barriers and Opportunities

Based on a literature review and expert interviews, this paper analyzes the most important climate impacts on development goals and explores relevant institutions in the context of mainstreaming climate adaptation into development assistance in Mozambique. Climate variability and change can significantly hinder progress toward attaining the Millennium Development Goals and poverty aggravates the countrys climate vulnerability. Because Mozambique is one of the major recipients of official development assistance in the world, there is a clear interest in ensuring that the risks of climate impacts are incorporated into the countrys development investments. A screening of donor activities at the sub-national level shows that a high share of development assistance is invested in climate-sensitive sectors, partly in areas that are particularly exposed to droughts, floods, and cyclones. The authors find that Mozambique has a supportive legislative environment and donors have a high awareness of climate risks. However, limited individual, organizational, networking, and financial capacity constrain mainstreaming initiatives. Given strong limitations at the national level, bilateral and multilateral donors can play a key role in fostering institutional capacity in Mozambique.