Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/84035
Title: Modelling woody vegetation in Sudano-Sahelian zone of Nigeria using remote sensing
Authors: Usman, Muhammad
Degree: Ph.D.
Issue Date: 2018
Abstract: Rural areas surrounding Nigeria's second largest city, Kano, in the northern Nigeria, have some of the highest rural population densities in the world, and these have been increasing rapidly in recent decades, with as yet, no signs of stabilising. The subsistence nature of livelihoods in this semi-arid region bordering the African Sahel zone, where rainfall is known to be highly variable, introduces considerable risk for crop and woody vegetation productivity. A scenario of recent high rural and urban population growth in and around the city of Kano, set in context of predicted temperature increase and greater rainfall variability due to climate change, may give cause for concern. As almost all rural, and the vast majority of urban households still use wood fuel for cooking, lighting and heating (although Nigeria is the world's 6th largest oil producer), a return to the rainfall amounts of the drought decades of the 1970s and 80s could cause widespread economic and social distress. There are many accounts of rainfall trends in the northern Nigeria, many observing severe declines, and others a decline in recent decades followed by a return to normal. Almost all studies report great spatial variation in rainfall amounts and trends, with large differences in nearby areas, or conflicting results for the same regions. Furthermore, these reported statistics appear in many cases to be conflicting with farmers' perceptions of rainfall trends and its effects on their lives and livelihood. This study evaluates the available sources of rainfall data over recent decades in the northern Nigeria, using both climate station data and satellite-based rainfall products, as satellite rainfall variables are spatially superior to point-based ground stations. These rainfall data are first compared with satellite-based vegetation indices NDVI products such as GIMMS 3g and MODIS, extending back several decades to the early 1980s. They are also compared with several satellite-based rainfall products such as ARC, CHIRPS, TARCAT and TRMM, covering the same decades. The second part of the study evaluates climatic impacts on the rural landscape and thus on the agricultural economy, specifically on farmland trees, which are used by farmers for fuelwood for own use as well as for sale to supplement farm incomes. This part of the study focuses on the "Kano Close Settled Zone", due to its high rural population density as a case study example for savanna Africa. It evaluates high resolution remotely sensed images for tree inventory and changes in woody biomass, in terms of tree density and species composition, in the intensively farmed parklands surrounding Kano City. The objective is to observe trends in the woody vegetation surrounding Kano City from the 1960s onwards, which may be related to climatic trends.
The last part of the study evaluates the use of Geographic Object Based Image Analysis (GEOBIA) for delineation of tree crown cover in the agroforestry landscape of the Kano Close-Settled Zone (KCSZ) using high resolution WorldView-2 image and modelling of above ground biomass (AGB) using tree crown cover. Results of the study indicate a recovery of rainfall across northern Nigeria in the past three decades, although not back to 1960s levels. This recovery is observed from both ground station and CHIRPS satellite data, to be due to a longer rainy season, with higher rainfall amounts toward the end of the growing season in August to October. Vegetation indices from AVHRR GIMMS 3g and MODIS satellite products across the West African Sahel and Sudan zones confirm this recovery in terms of increased biomass. To evaluate the impacts of rainfall trends on the rural landscape and economy at local level, trends in farmland tree stocks around Kano, were determined from field data and high resolution images including archived aerial photographs and recent satellite images. Field survey was conducted in 1981 and 2016, and the images covered the 1960s pre-drought period, the 1970s to 80s drought period, and recent period of 2013-15. Contrary to other work on woody vegetation in West Africa, mostly from the Sahel Zone, a substantial increase in tree densities was observed since the 1960s and continuing through the drought decades, with at least a doubling of farmland tree densities at the present time. This observed increase is surprising in view of high population growth and reports of increased temperatures due to global warming. This increase in tree densities around Kano is attributed to continued reliance on wood as the main energy source, by a still rapidly growing population, with a more than doubling of Kano city's population in the 15 years up to the last population census in 2006. This growth would not have been possible without a parallel increase in the main energy source. Observations of a decline in a wide range of traditional tree species and replacement by fewer fast-growing and drought-tolerant species parallel recent reports from other parts of West Africa. The overall finding of the study is that trends in farmland tree stocks are less related to long term climatic trends, than to the Nigerian socio-economy, as farmers make decisions about the numbers and species of trees on their farms according to their own domestic needs and from sale of wood. The continued overwhelming dependence on biomass for fuel by a still rapidly growing population across northern Nigeria may be a cause for concern. Return to the drought conditions of previous decades coupled with tree death due to climate change may have serious consequences for rural households for whom the longevity of woody vegetation offers security against rainfall variability and crop failure.
Subjects: Hong Kong Polytechnic University -- Dissertations
Vegetation and climate -- Remote sensing
Vegetation and climate -- Nigeria
Vegetation mapping -- Remote sensing
Plants -- Remote sensing
Pages: 122 pages : color illustrations
Appears in Collections:Thesis

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