Project

Land change in Africa’s emerging cities.

Goal: There is a dearth of knowledge about changing land systems in urbanizing regions, particularly small and mid-sized cities (SMCs). Yet projected urban growth is expected to occur mostly in SMCs. This research seeks to link patterns with processes to better understand the patterns and factors driving land change and interactions in SMCs. This contributes to understanding the environment impacts of peri-urbanization and generates projections of future LULC as input for modelling soil loss, runoff, soil C stock, etc.

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Felicia Akinyemi
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Agricultural land area is increasing globally despite the loss of productive agricultural lands in some world regions. We examine the case of Africa where the knowledge about major agricultural land transitions and the impacts on the quality of land is still very limited. A comprehensive assessment of change in agricultural landscapes was conducted at the African continental scale. We identify influencing factors and model the quality of land associated with agricultural land gains and losses between 2000 and 2018. Land quality was established based on spatially-explicit analysis of varying Net Primary Productivity, soil organic carbon content, crop suit-ability and percent yield change for major crops of global importance grown across Africa such as maize, rice, soybean, wheat, and alfalfa. Distance to settlements was important in explaining agricultural land dynamics. Most land areas that transitioned to cropland in Africa were associated with large distances away from major roads. Poor access to major roads suggests the remoteness of gained croplands. Land quality was better in gained croplands than in those lost, whereas gained grasslands were of lesser quality compared to areas of grassland loss. Five typologies of African countries were developed based on net yield and amount of land cultivated per crop in cropland change areas. Type 1 typifies net yield increase and cultivated land decrease, while type 2 is characterized by yield increase consequent upon cropland expansion. Net yield and land remain unchanged in type 3, while in type 4 cultivated land increased but yield decreased as in 40% of African countries for maize, and in type 5, both yield and land area decreased. This study thus provides evidence about the quality of land in gained and lost agricultural areas and generalizable insights on their dynamics across Africa.
Felicia Akinyemi
added 2 research items
Land use-land cover (LULC) association with land surface temperature (LST) is well known. Knowledge about land change effects on LST in urbanizing African drylands is very limited. We examined LST and vegetation variations in semi-arid Gaborone (Botswana's capital) using MODIS daytime and night-time LST (DNLST), and Normalized Difference Vegetation Index between 2000 and 2018. Significant land transitions were identified in the land cover change map using Change Vector Analysis of Landsat-based biophysical indices of vegetation, water and bare soil. Artificial surface and tree-covered areas were net gaining categories, whereas cropland and grassland were net losing categories. Detailed profiling of DNLST trends and breakpoints was conducted in five relatively homogenous sites representing land cover/transitions. Increasing NDVI and DNLST trends found were significant. Per class, LST change at daytime and night-time are as follows: built-up areas (1.8 K, 2.2 K), Gaborone dam (5.7 K, 0.2 K), settlement expansion areas (4.6 K, 2.2 K), and rural settlement (2.0 K, 1.5 K). The cooling effect of irrigation on daytime LST was higher than night-time LST as daytime LST trend as low as −0.4 K was found in areas of irrigated croplands. Validation with synoptic station temperature data and dam water levels provides empirical evidence that MODIS gave credible DNLST estimates in this urbanizing dryland area. Our results also suggest the role of climate variability in urbanizing drylands alongside land cover change in controlling the LST. Regardless, coupling DNLST and land cover changes can provide useful information for spatial planning of drylands to create smart cities that are resilient to climate change.
Achieving land degradation neutrality (LDN) has been proposed to stem the loss of land resources globally. To date, LDN operationalization at country level has remained a challenge both from a policy and science perspective. Using an approach incorporating cloud‐based geospatial computing with machine learning, national level datasets of land cover, land productivity dynamics, soil organic carbon stocks were developed using the example of Botswana. LDN and proportion of degraded land were assessed. Between 2000 and 2015, grassland lost 17% of its original size, the highest level of loss for any land category; land productivity decline was highest in artificial surface areas (11%), whereas 36% of croplands show early signs of decline. With the use of national metrics (NM), areas under degradation were found to be 32.6% compared to 51.4% surface area when global default datasets (DD) are used. Estimates of degraded land computed with NM and DD were validated in Palapye, an agro‐pastoral region in eastern Botswana, where Composite Land Degradation Index (CLDI) field‐based data exists. Comparing land degradation (LD) in the three datasets (NM, DD, and CLDI), NM estimates were closest to the field data. The extra efforts put into developing national level data for LD assessment in this study is, thus, well‐justified. Beyond demonstrating remote sensing viability for LD assessment, the study developed procedures for generating and validating national level datasets. Using these procedures, LD monitoring will be enhanced in Botswana and elsewhere since these remote sensing datasets can be updated using freely available satellite datasets. This article is protected by copyright. All rights reserved.
Robert Gilmore Pontius
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I invite you and your colleagues to take my free online workshop sponsored by the Global Land Programme entitled METRICS THAT MAKE A DIFFERENCE: How to Analyze Change and Error with Applications to Land Change Simulation To learn about the workshop and to register, visit http://www.glp.taipei.ntu.edu.tw/events/online-workshop-20200701/
 
Felicia Akinyemi
added a research item
This study's focus is on Palapye, a predominantly dryland agricultural but urbanising region in eastern Botswana. Maps of ten land use-land cover (LULC) categories at three time points (1986, 2000, and 2014) were produced based on the ISO 19144 land cover classification scheme. Land change intensities were examined at the time interval, category and transition levels using Intensity Analysis. A combination of multi-layer perceptron neural network and Markov chain analysis was used to project LULC to 2028 and investigate future changes. The rate of land change was faster during the second time interval (2000–2014) than during the first time interval (1986–2000) as the region transforms from an agrarian to a service economy. In the first time interval cropland was a net losing category, whereas it was a net gaining category during the second time interval. Cropland expanded into shrublands in the southwestern part of the study area. The built-up category was active in gains during the two time intervals as it targeted grasslands and shrublands. Built-up is also projected to gain an additional 272 km² by 2028. The bareland and paved/rocky materials categories were also active in gains during both time intervals. A loss of 26% of natural land cover over the study period was recorded due mainly to transition into croplands, built-up areas, and grassland. The policy implications of findings are discussed as this region is important for biodiversity, ecosystem services, food production, mining, and tourism.
Felicia Akinyemi
added 5 research items
The Nigerian government is reviving the agricultural sector to shift from its sole dependence on crude oil for foreign exchange earnings. Thus, the Cocoa Belt agro-ecological region of southwest Nigeria is important to the national economy. With the increasing demand for land to grow export crops and to meet other needs such as settlement expansion, land use is changing. Land-use data and mapping are essential inputs for the process of formulating, implementing, and monitoring policy with the aim of reducing the impact of land-cover/land-use LCLU change. Land-use types, their spatial extent and dynamics over a 25 year period are examined from multispectral images of the Landsat Thematic Mapper and Enhanced Thematic Mapper Plus. This study examines the main drivers of LCLU change and the environmental impact. Results show that forest conversion to agricultural lands is the main trend, and cultivation is the main cause of forest loss in the study area. The need to produce food for the teeming population, coupled with the government's policy to expand export crop production is resulting in the loss of native forest, including areas designated as forest reserves. Results underscore the need for deliberate land-use planning and management in this belt. This study reveals the situation of unplanned and rapid changes to land use in the context of a developing country where explicit policies to cater for such activities are absent.
Urban growth can have positive effects if well managed or negative impacts in instances of uncontrolled urban expansion. Often, land management regulations are employed in urban areas to ensure that land is efficiently planned and managed to achieve sustainable land management. This study examines the changing landscape of Kabuga town, Rwanda due to land use conversion. Data was obtained from 107 respondents and interviews with the local authorities in charge of urban planning. Variables examined include migration, the means of acquiring land, land use (initial use of land and current use of land) while driving factors of land use conversion were also identified. The challenges of urban growth in Kabuga and the implications for proper land management are examined. Results reveal that 6% of the population lived in Kabuga before 1994 and the remaining 94% are migrants; 55% came within the period 1994-2005, 29% came during 2006-2012 and 10% came after 2012 implying that residents are predominantly migrants. The analysis finds evidence of diminishing agricultural and forested land and vacant lands in favour of residential area and commercial activities due to influx of people. Major impacts of this changing environment in Kabuga town are overcrowding, pollution and loss of green spaces.
Land change in Kigali, Rwanda, is examined using Intensity Analysis, which measures the temporal stationarity of changes among categories. Maps for 1981, 2002 and 2014 were produced that show the land categories Built, Vegetated and Other, which is composed mainly of croplands and bare surfaces. Land change accelerated from the first time interval (1981–2002) to the second time interval (2002–2014), as increased human and economic activities drove land transformation. During the first interval, Vegetated showed net loss whereas Built showed net gain, in spite of a small transition directly from Vegetated to Built. During the second interval, Vegetated showed net gain whereas Built showed nearly equal amounts of gross loss and gross gain. The gain of Built targeted Other during both time intervals. A substantial portion of overall change during both time intervals consisted of simultaneous transitions from Vegetated to Other in some locations and from Other to Vegetated in other locations.
Felicia Akinyemi
added an update
Download ePrints for Akinyemi 2017 https://authors.elsevier.com/a/1VYZDWf-B0Tr0
Article title: Land change in the central Albertine rift: Insights from analysis and mapping of land use-land cover change in north-western Rwanda Article reference: JAPG1727 Journal title: Applied Geography
 
Felicia Akinyemi
added a project goal
There is a dearth of knowledge about changing land systems in urbanizing regions, particularly small and mid-sized cities (SMCs). Yet projected urban growth is expected to occur mostly in SMCs. This research seeks to link patterns with processes to better understand the patterns and factors driving land change and interactions in SMCs. This contributes to understanding the environment impacts of peri-urbanization and generates projections of future LULC as input for modelling soil loss, runoff, soil C stock, etc.