Matthias Lüdeke

The use of satellite NDVI data for the validation of global vegetation phenology models: application to the Frankfurt Biosphere Model

Abstract An algorithm based on a three-spline function fitted to measured NDVI courses (normalized difference vegetation index) was developed to analyze a given NDVI annual course with respect to leaf shooting and leaf abscission times of deciduous vegetation. In contrast to algorithms which are based on modified second derivatives of the NDVI time course to detect shooting or abscission, the proposed algorithm takes into account the whole annual time course and is therefore less sensitive to noise in the NDVI-signal. In the present study this algorithm was used to validate the phenology results for the deciduous vegetation of a global equilibrium run of the prognostic Frankfurt Biosphere Model (FBM, spatial resolution 0.5° × 0.5°) driven by a climatology which represents a mean seasonality of the driving variables. The mean value of the area-weighted frequency distribution of the difference between the shooting date deduced from NDVI and the shooting date calculated by the FBM for the deciduous vegetation types is −4 days, indicating that in the global mean the FBM predicts leaf shooting less than one week too late. A 75% fraction of the area under consideration shows predicted shooting dates lying within a range of ± 30 days compared to the satellite-derived dates. The distribution has its maximum at a difference of 0 days (i.e. the FBM exactly fits the NDVI deduced shooting day for these areas). This result supports the general assumption that at least in global scale models phenology can be successfully deduced from carbon flux balance considerations.

A new method for analysing socio-ecological patterns of vulnerability

This paper presents a method for the analysis of socio-ecological patterns of vulnerability of people being at risk of losing their livelihoods as a consequence of global environmental change. This method fills a gap in methodologies for vulnerability analysis by providing generalizations of the factors that shape vulnerability in specific socio-ecological systems and showing their spatial occurrence. The proposed method consists of four steps that include both quantitative and qualitative analyses. To start, the socio-ecological system exposed to global environmental changes that will be studied needs to be determined. This could, for example, be farmers in drylands, urban populations in coastal areas and forest-dependent people in the tropics. Next, the core dimensions that shape vulnerability in the socio-ecological system of interest need to be defined. Subsequently, a set of spatially explicit indicators that reflect these core dimensions is selected. Cluster analysis is used for grouping the indicator data. The clusters found, referred to as vulnerability profiles, describe different typical groupings of conditions and processes that create vulnerability in the socio-ecological system under study, and their spatial distribution is provided. Interpretation and verification of these profiles is the last step in the analysis. We illustrate the application of this method by analysing the patterns of vulnerability of (smallholder) farmers in drylands. We identify eight distinct vulnerability profiles in drylands that together provide a global overview of different processes taking place and sub-national detail of their distribution. By overlaying the spatial distribution of these profiles with specific outcome indicators such as conflict occurrence or migration, the method can also be used to understand these phenomena better. Analysis of vulnerability profiles will in a next step be used as a basis for identifying responses to reduce vulnerability, for example, to facilitate the transfer of best practices to reduce vulnerability between different places.

Embodied crop calories in animal products

Increases in animal products consumption and the associated environmental consequences have been a matter of scientific debate for decades. Consequences of such increases include rises in greenhouse gas emissions, growth of consumptive water use, and perturbation of global nutrients cycles. These consequences vary spatially depending on livestock types, their densities and their production system. In this letter, we investigate the spatial distribution of embodied crop calories in animal products. On a global scale, about 40% of the global crop calories are used as livestock feed (we refer to this ratio as crop balance for livestock) and about 4?kcal of crop products are used to generate 1?kcal of animal products (embodied crop calories of around 4). However, these values vary greatly around the world. In some regions, more than 100% of the crops produced is required to feed livestock requiring national or international trade to meet the deficit in livestock feed. Embodied crop calories vary between less than 1 for 20% of the livestock raising areas worldwide and greater than 10 for another 20% of the regions. Low values of embodied crop calories are related to production systems for ruminants based on fodder and forage, while large values are usually associated with production systems for non-ruminants fed on crop products. Additionally, we project the future feed demand considering three scenarios: (a)?population growth, (b)?population growth and changes in human dietary patterns and (c)?changes in population, dietary patterns and feed conversion efficiency. When considering dietary changes, we project the global feed demand to be almost doubled (1.8?2.3 times) by 2050 compared to 2000, which would force us to produce almost equal or even more crops to raise our livestock than to directly nourish ourselves in the future. Feed demand is expected to increase over proportionally in Africa, South-Eastern Asia and Southern Asia, putting additional stress on these regions.

Integration of case studies on Global Change by means of qualitative differential equations

We present a novel methodology to integrate qualitative knowledge from different case studies on Global Change related issues into a single framework. The method is based on the concept of qualitative differential equations (QDEs) which represents a mathematically well-defined approach to investigate classes of ordinary differential equations (ODEs) used in conventional modeling exercises. These classes are defined by common qualitative features, e.g., monotonicity, signs, etc. Using the QSIM-algorithm it is possible to derive the set of possible solutions of all ODEs in the class. By this one can formulate a common, qualitatively specified cause–effect scheme valid for all case studies. The scheme is validated by testing it against the actually observed histories in the study regions with respect to their reconstruction by the corresponding QDE. The method is outlined theoretically and exemplary applied to the problem of land-use changes due to smallholder agriculture in developing countries. It is shown that the seven case-studies used can be described by a single cause–effect scheme which thus constitutes a pattern of Global Change. As a generally valid prerequisite for sustainability of this kind of land-use the presence of wage labor is shown to represent a decisive factor.

Defining the bull's eye: satellite imagery-assisted slum population assessment in Hyderabad, India

Abstract This paper presents an approach to qualitative and spatial assessment of slum population numbers in Hyderabad, India using circle-based population data from the Census of India and results of the analysis of high resolution QuickBird satellite image data (2003) derived from automatic line detection and lacunarity algorithm. This approach provides plausible and spatially explicit aggregate statistics of slum population numbers within the city. This work suggests that both over- and underreporting of slum population numbers does occur in Hyderabad, and provides an improved view on the slum distribution patterns within this urban agglomeration.

Armed conflict distribution in global drylands through the lens of a typology of socio-ecological vulnerability

Motivated by an inconclusive debate over implications of resource scarcity for violent conflict, and common reliance on national data and linear models, we investigate the relationship between socio-ecological vulnerability and armed conflict in global drylands on a subnational level. Our study emanates from a global typology of smallholder farmers’ vulnerability to environmental and socioeconomic stresses in drylands. This typology is composed of eight typical value combinations of variables indicating environmental scarcities, resource overuse, and poverty-related factors in a widely subnational spatial resolution. We investigate the relationships between the spatial distribution of these combinations, or vulnerability profiles, and geocoded armed conflicts, and find that conflicts are heterogeneously distributed according to these profiles. Four profiles distributed across low- and middle-income countries comprise all drylands conflicts. Comparing models for conflict incidence using logit regression and receiver operator characteristic analysis based on (1) the set of all seven indicators as independent variables and (2) a single, only vulnerability profile-based variable proves that the nonlinear typology-based variable is the better explanans for conflict incidence. Inspection of the profiles’ value combinations makes this understandable: A systematic explanation of conflict incidence and absence across all degrees of natural resource endowments is only reached through varying importance of poverty and resource overuse depending on the level of endowment. These are nonlinear interactions between the explaining variables. Conflict does not generally increase with resource scarcity or overuse. Comparison with conflict case studies showed both good agreement with our results and promise in expanding the set of indicators. Based on our findings and supporting literature, we argue that part of the debate over implications of resource scarcity for violent conflict in drylands may be resolved by acknowledging and accounting for nonlinear processes.

Bridging Qualitative and Quantitative Methods in Foresight

There is a long-lasting and controversial discourse on the role of quantitative and qualitative data and methods in science, at least since the “Newtonian turn” in physics in the seventeenth century. After this successful step in the mathematical formalization of a large branch of physics, nowadays called “classical mechanics”, it was used as a kind of paradigmatic case by many theorists of science. Thereby, standards for scientific processes and theory structures were imposed on realms of science dealing with dramatically different subjects and having different purposes than classical mechanics. This was controversially discussed within the debate on positivism, but it still has a strong influence on our understanding of science.

Assessment of climate change - induced vulnerability to floods in Hyderabad, India, using remote sensing data

The frequency and intensity of extreme rainfall events over Hyderabad, India, are often the cause of devastating floods in its urban and peri-urban areas. This paper introduces a quantitative approach to assessing urban vulnerability to floods in Hyderabad, identifying informal settlements via high resolution satellite photography and through the development of a flood model for urban and peri-urban areas.