Agroenvironmental transformation in the Sahel: Another kind of “Green Revolution"

millions fed, food security, Sahel, Zai, Stone bunds, Agroforestry, Soil management,

Land degradation in the Limpopo Province, South Africa

Student Number : 9511039F - MSc Dissertation - School of Animal, Plant and Environmental Sciences - Faculty of ScienceAn estimated 91 % of South Africa’s total land area is considered dryland and susceptible to desertification. In response, South Africa has prepared a National Action Programme to combat land degradation, and this requires assessment and monitoring to be conducted in a systematic, cost effective, objective, timely and geographically-accurate way. Despite a perception-based assessment of land degradation conducted in 1999, and a land-cover mapping exercise conducted for 2000/2001, there are few national scientifically rigorous degradation monitoring activities being undertaken, due largely to a lack of objective, quantitative methods for use in large-scale assessments. This study therefore tests a satellitederived index of degradation for the Limpopo Province in South Africa, which is perceived to be one of the most degraded provinces in the country. The long-term average maximum normalized difference vegetation index (NDVI), calculated from a time series (1985-2004) of NOAA AVHRR satellite images, as a proxy for vegetation productivity, was related to water balance datasets of mean annual precipitation (MAP) and growth days index (GDI), using both linear and non-linear functions. Although the linear regressions were highly significant (p<0.005), a non-linear four parameter Gompertz curve was shown to fit the data more accurately. The curve explained only a little of the variance in the data in the relationship between NDVI and GDI, and so GDI was excluded from further analysis. All pixels that fell below a range of threshold standard deviations less than the fitted curve were deemed to represent degraded areas, where productivity was less than the predicted value. The results were compared qualitatively to existing spatial datasets. A large proportion of the degraded areas that were mapped using the approach outlined above occurred on areas of untransformed savanna and dryland cultivation. However the optical properties of dark igneous derived soils with high proportions of smectitic minerals and therefore low reflectance, were shown to lower NDVI values substantially. Overall, there was an acceptable agreement between the mapped degradation and the validation datasets. While further refinement of the methodology is necessary, including a rigorous field-based resource condition assessment for validation purposes, and research into the biophysical effects on the NDVI values, the methodology shows promise for regional assessment in South Africa

Economics of Land Degradation and Improvement – A Global Assessment for Sustainable Development

environmental economics; biodiversity; sustainable developmen

Earth resources: A continuing bibliography with indexes (issue 60)

This bibliography lists 485 reports, articles, and other documents introduced into the NASA scientific and technical information system between October 1 and December 31, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors

Earth resources: A continuing bibliography with indexes (issue 59)

This bibliography lists 518 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors

Remote Sensing in Mangroves

The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the worl

Desertification

IPCC SPECIAL REPORT ON CLIMATE CHANGE AND LAND (SRCCL) Chapter 3: Climate Change and Land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystem

Disaggregating Tree And Grass Phenology In Tropical Savannas

Savannas are mixed tree-grass systems and as one of the world’s largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation. The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency method was better for extracting the green tree phenology, but the original decomposition method was better for retrieval of understory grass phenology. Both methods, however, were less accurate than in the Cerrado than in Australia due to intermingling and intergrading of grass and small woody components. Since African savanna trees are predominantly deciduous, the frequency method was combined with the linear unmixing of fractional cover to attempt to separate the relatively similar phenology of deciduous trees and seasonal grasses. The results for Africa revealed limitations associated with both methods. There was spatial and seasonal variation in the spectral indices used to unmix fractional cover resulting in poor validation for NPV in particular. The frequency analysis revealed significant phase variation indicative of different phenology, but these could not be clearly ascribed to separate grass and tree components. Overall findings indicate that site-specific variation and vegetation structure and composition, along with MODIS pixel resolution, and the simple vegetation index approach used was not robust across the different savanna biomes. The approach showed generally better performance for estimating PV fraction, and separating green phenology, but there were major inconsistencies, errors and biases in estimation of NPV and BS outside of the Australian savanna environment