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Part III The use of remote sensing for the spatial assessment of ecological vulnerability in NW-Namibia. Example of global environmental change in Southern Africa:. Change in Global Plant Productivity 1982 – 1999 -> Productivity Increase -> Productivity decrease.
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Part III The use of remote sensing for the spatial assessment of ecological vulnerability in NW-Namibia
Example of global environmental change in Southern Africa: Change in Global Plant Productivity 1982 – 1999 -> Productivity Increase -> Productivity decrease (Source: NASA Earth Observatory News, 6/03)
Ecological, socioeconomic and political drivers ... • OVAMBO: • Small scale farms • Mixed farming • Subsistence • High population • pressure • HIMBA/HERERO: • Pastoralism • Cattle rangeland • Riverine gardens • ... ANG. Etosha N.P. BOT. • COMM. FARM.: • - Large scale • rangeland farms • Low population • pressure ecological gradients RSA ... on VULNERABILITYin NW-Namibia
multiple factor approach to access vulnerability The vulnerability of a specific region is defined as: “…the expected damage as resulting from the expected environmental perturbations in view of the expected transformation and adaptation processes.” “…the expected damage as resulting from the expected environmental perturbations in view of the expected transformation and adaptation processes.” “…the expected damage as resulting from the expected environmental perturbations in view of the expected transformation and adaptation processes.” (Corell, Cramer & Schellnhuber, 2001) - environmental perturbations - transformation and adaptation processes
Importance of Data integration: • Qualitative findings • (e.g. trough stakeholder dialog) • Quantitative information, • projection of different indicators • Numerical modells for VULNERABILITY: • V = f ( E, S, AC ), but presently there is no applicable, sofisticated equation for vulnerability • Fuzzy Logic decision tree using qualitative and quantitative variables are needed • Modelling with qualitative differential equations is possible if understandable patterns occur • State of the Practice:graphical combination using visual interpretation techniques (e.g. blend-technique)
Vulnerability index (necessity and demand): • (spatial) comparisions of regions • temporal course (for the next 5, 10, 50, ... years) • comparision of scenarios • scales: low, medium, high • mono- & multicausal-analysis: combination of indicators • simplification, but access to detailed information at all time • sectoral und user specific • utilisation through scientists and decision makers
WINDHOEK N Walvis Bay ca. 350 km Outjo ca. 400 km Opuwo Biomass modelling withMODIS 1km DGM (GTOPO30, USGS) overlaid with Terra MODIS Scene from 20.02.2001 (Combination: R:3 G:4 B:1, 500m Pixel)
global models 1000 km desertification salinization 100 km degradation 10 km fire regional models NOAA 1 km MODIS locale models 100 m LANDSAT vegetation 10 m crops measurements/ observation arial photographs 1 m 1 min 10 min 1 hour 1 day 10 days 1 month 1 year 10 years spatial scale temporal scale
= Reflectance at Channel 2 (IR) = Reflectance at Channel 1 (Red) 1. Vegetation dynamic observed by NOAA-NDVI: • spatial resolution: 1 x 1 km² • daily global coverage • time series since 1970 • vegetation monitoring • using the NDVI:
Mixed Forest Woody Savannah Savannah Closed Shrub land Open Shrub land Grassland Barren Land 2. Land cover changes with MODIS & NOAA IGBP Global Land Cover scheme (Hansen et al. 2000) Water
phenologic metrics 2. Land cover changes with MODIS & NOAA
3. Assessment of Degradation using high-resolution data • LANDSAT ETM+ • Ground res: 30 m; • 7 spectral bands; • Date: 6/5/2000; • Band Comb: 5,3,2
Opuwo degradated land affected by degradation 3. Assessment of Degradation using high-resolution data
LANDSAT ETM+ (2000) 4. Strategies against Drought: Monitoring of Agriculture Areas
4. Strategies against Drought: Monitoring of Agriculture Areas • diversification of subsistence • as monitored by • quantifying of garden areas and harvest • changes of garden areas over time through • comparison with older aerial photographs.
Human Dimension Vegetation Dynamics and Biomass Cattle and Grazing Degradation Land Use & ~ Cover Change Modelling scheme for the assessment of ecological vulnerability in NW Namibia Regional Biosphere Model
Human Dimension Developing of a ‚Vulnerability-Index‘ Spatial and temporal explicit Output (e.g.) Vegetation Dynamics and Biomass Biomass Cattle and Grazing Desertification Land Cover Change Stocking Pasture Balance Land Cover Change Drought Prediction Possibilities of handling options in crisis situations
During the workshop discussions, we will focus on identifying the following: • key processes that influence vulnerability; • key indicators of vulnerability; • intersections and interactions among different stressors; • the common denominators of vulnerability; and • potential policy interventions to reduce vulnerability. • Questions related to vulnerability case studies: • 1 To what extent is human security presently at risk in your case study region? • 2.Which stressors currently threaten human security in this region? • Are these stressors endogenous or exogenous to the region? • 3. How do these stressors interact and thereby either reinforce each other or • reduce the cumulative risk? • 4. How might future societal and environmental changes influence future human • security in the region? Is either the nature of the threats or the relative importance • of various stressors expected to change? • 5. What factors shape the capacity of this region to adapt to these potential future changes?
Cooperation: PIK (Germany) Gent (Belgium) Utrecht (The Netherlands) Santa Barbara (USA) Sioux Falls (USA) Land Use and Land Cover Change (LUCC) PI ENVISAT PI SRTM
Ecological, socioeconic and political drivers ... NPP increase HIMBA -Pastoralism ANG. • XY • small scale • Mixture farming • Subsistence • High population • dynamic x x BOT. Etosha N.P. NAMIB YZ Large scale Rangeland farms Cash crop Low population pressure NPP decrease ecological gradients RSA ... on vulnerability in NW-Namibia
Arial photo, 1975 4. Strategies against Drought: Monitoring of Agriculture Areas