Land use and land cover changes involve the transformation of the landscape. For example, the encroachment on the wetlands leads to increased incidences of floods. In addition, the freehold land tenure system in Kampala has accelerated the loss of land for cultivation in Kampala (Maxwell, 1994). Policy should focus on ensuring the farmers have secured land tenure to minimise rapid conversion of agricultural land to urban uses. Policymakers should target waste management policies, curb charcoal burning by encouraging the use of clean energy, and protect the wetlands.
96 3.6 Limitations of study
The supervised Landsat image classification to obtain land use and land cover (LULC) changes used in this chapter to produce LULC transition matrices have been generally found to produce relatively reliable landscape transformations. However, the accuracy of the LULC classification output is largely dependent on the satellite image quality and the resolution Landsat images used. The Landsat image quality is affected by atmospheric condition during the time of its capture, for instance, cloud cover has a great effect on the image quality.
Ideally, multi-temporal image assessment for comparison purposes would require using cloud- free images obtained on the same day of the month for the initial and latter year would lower the differences that can result from seasonal variability (rainy or dry). In this study, obtaining cloud-free images on the same day of the month for the initial and latter analysis year was a challenge. Therefore, images with up to 10% cloud cover were used which can potentially lower the out quality. Secondly, obtaining images on the same day of the month in both years was another challenge, for instance, the images used for Kampala LULC classification were captured between November and February. This also has a potential effect on the image output especially. Likewise, for Mbarara images were obtained between February and May. Fortunately, in Kampala, November to February generally lie in the same season and Mbarara February to May have similar weather condition, this minimised the impact, nevertheless lowered overall comparison.
The image resolution of 30m enables to capture LULC changes per 900 sq metre area which can more accurately be applied in peri-urban areas where it is more likely to find relatively uniform
97
land use over 900m. However, in an urban setup where standard plot size in Kampala and Mbarara measures 16 by 30.5 m (488 sq metres), LULC changes on these plots which are dominant as urban intensification continues in some cases cannot be captured.
The determining the principal signals of inter-category transition to identify the random or systematic landscape transition is that it only considers relative proportions of other categories at the initial time. This approach as aforementioned is based on an assumption that a given land use category should gain more from categories which were dominant in the landscape and again less from categories which comprised a small proportion of the landscape. However, this approach does not consider the relative positions of the categories, during urban growth, the proximity of the land category relative to urban built-up is very important. For example, a built- up category can gain more from a category nearest even if its relative proportion in the landscape at the initial time was less. This is one of the major limitations of using this approach in assessing systematic and random signals of LULC transition in an urban area.
In addition, the swapping change considers what a given category loses/gains to/from other categories, however, the limitation is that it only assess the quantity and does not consider the quality land gained or lost for a given category in the landscape. This is more so when we consider agricultural land, the lost land maybe or different productive as compared to what is gained in another part of the landscape as soil productivity is heterogeneous.
98 3.7 Conclusion
This paper has provided an account of urban growth in Uganda using Kampala and Mbarara regional centre as case studies. The built-up area in Kampala expanded by about 8 times between 1989 and 2015 while Mbarara increased by about 5 times between 2002 and 2016. Rapid urban growth not only leads to a loss of agricultural land, it also forces changes from savannah to grazing lands farther away from the city centre.
Significantly urban growth in both cities has led to the loss of agricultural land which indicates that the built-up area growth rate in both cities is usurping agricultural land. This is compensated by gains in agricultural land through the process of swapping with other categories, for example, savannahs and wetlands usually in peri-urban areas and surrounding rural areas. Thus, the loss of agricultural land is predominantly near the city centres and along the highways caused by their easy accessibility which acts as an attraction to urban development. This has led to systematic transition between agricultural land and built-up. Because of the absence of strict regulations to urban development and existence of a number of formal and informal land tenure systems in Uganda, as in most of the African countries, urban growth will continue to encroach into agricultural land.
In order to understand the implications of urban growth for agricultural production, there is the need to assess the quality of agricultural land lost to urban expansion in both cities. It is also necessary to examine the productivity of the new agricultural land vis-à-vis the lost land to understand the exact consequences of urban growth on agricultural production. Although
99
Kampala and Mbarara were chosen as case studies, the observable features of urban growth in these centres are extensible to most cities and urban centres in SSA. Therefore, this study is an impetus to further studies on the quality of urban and peri-urban agricultural land and its lost urban expansion and most importantly the overall impacts on urban food security in SSA.
The peri-urban zones closer to urban centres experience the immediate impacts of land demands from urban growth while the zone far from the city usually continues handling agricultural and natural resource products (Simon et al., 2004). Urban growth and development in smaller cities or peri-urban communities is increasingly an important component of land use change not only in the SSA but also in the rest of the developing countries (Nagendra et al., 2004). The rapidly changing conditions in smaller urban areas need to be monitored carefully if sustainable development is to be achieved as more and more agricultural land is expected to be converted to built-up (Vierich and Stoop, 1990, Yunlong and Smit, 1994, RUAF, 2010). Henderson (2002) observed that rapid growth of cities in Africa would negatively affect the quality of life in urban centres as a result of increased pressure on resources.
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Abstract
Most of the urban growth in developing countries is occurring on productive soils. Yet there is a lack of detailed baseline soil information that can facilitate the assessment of the impact of urbanisation on the loss of quality soils. The current soil maps in most African countries are rather old with little details. The biggest hindrance to updating and improving the soil information in such a setting is the high costs of the required detailed soil survey, in addition to complication caused by the loss of natural soils to urban development (Urbanisation leads to continuous alteration of the soil which makes it difficult to classify it classify). Therefore, this