2020
DOI: 10.3390/su12062377
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An Analysis of Urban Land Use/Land Cover Changes in Blantyre City, Southern Malawi (1994–2018)

Abstract: Rapid and unplanned urban growth has adverse environmental and social consequences. This is prominent in sub-Saharan Africa where the urbanisation rate is high and characterised by the proliferation of informal settlements. It is, therefore, crucial that urban land use/land cover (LULC) changes be investigated in order to enhance effective planning and sustainable growth. In this paper, the spatial and temporal LULC changes in Blantyre city were studied using the integration of remotely sensed Landsat imagerie… Show more

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Cited by 34 publications
(27 citation statements)
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“…Each pixel was categorised into one of the four developed LULC classes: built-up area (residential, commercial, and service; industrial and transport; as well as recreational urban areas); vegetated areas (arable land, meadows, pastures, areas covered with low vegetation, allotment gardens, fallow land, and bare soil); wooded areas (forests, parks, wooded and semi-natural areas); and surface water areas (rivers, canals, reservoirs). The assessment of classification accuracy was also performed to quantitatively determine how effectively the pixels are grouped into the correct feature classes [78]. For this purpose, the test fields were distributed evenly outside the areas of the training fields, supported by information from the analysis of accurate maps (e.g., multi-temporal aerial photography, orthophotomaps).…”
Section: Land Use and Land Cover Classification And Changes Between 2000 And 2020mentioning
confidence: 99%
See 1 more Smart Citation
“…Each pixel was categorised into one of the four developed LULC classes: built-up area (residential, commercial, and service; industrial and transport; as well as recreational urban areas); vegetated areas (arable land, meadows, pastures, areas covered with low vegetation, allotment gardens, fallow land, and bare soil); wooded areas (forests, parks, wooded and semi-natural areas); and surface water areas (rivers, canals, reservoirs). The assessment of classification accuracy was also performed to quantitatively determine how effectively the pixels are grouped into the correct feature classes [78]. For this purpose, the test fields were distributed evenly outside the areas of the training fields, supported by information from the analysis of accurate maps (e.g., multi-temporal aerial photography, orthophotomaps).…”
Section: Land Use and Land Cover Classification And Changes Between 2000 And 2020mentioning
confidence: 99%
“…On the basis of confusion matrix, it was possible to analyse parameters describing classification accuracy, such as overall accuracy, which is defined as accuracy between the classified map and the reference data as well as Kappa coefficient defining total classification error and the degree of conformity between the compared images. Kappa coefficient greater than 0.80 indicates excellent agreement; a value between 0.4-0.80 indicates moderate agreement, and a value less than 0.4 indicates poor agreement between classification categories [78]. Such analyses resulted in raster maps of LULC classification; also, magnitude of changes for the individual land cover class in each period were calculated.…”
Section: Land Use and Land Cover Classification And Changes Between 2000 And 2020mentioning
confidence: 99%
“…This trend will inevitably result in increased exposure to natural disasters, such as earthquakes and floods [2][3][4]. Additionally, owing to the unregulated and inadequately planned nature of urban growth in Malawi, informal settlements, typical of rural areas, will be expanded at the outskirts of major cities, such as Lilongwe and Blantyre [5]. Residential buildings are characterised by poor engineering and construction quality, and are therefore highly vulnerable to natural hazards [6].…”
Section: Introductionmentioning
confidence: 99%
“…It is actually a process of inputting various resources into the regional urban-rural spatial system to acquire all kinds of outputs, which is input and output efficiency relationship. To quantify the efficiency relationship needs to construct input index system and output index system, where urban-rural integration is a firstlevel input index, and there are three second-level output indexes-efficiency outputs of urban-rural ecological integration, economic integration, and social integration as discussed by Mawenda et al [5].…”
Section: Introductionmentioning
confidence: 99%
“…However, only Sun Town was able to properly develop, while the overall spatial structure of the county remains sluggish. The urban town system is triangle-shaped and includes only a small number of key towns, playing a limited role in driving development to other towns as discussed by Mawenda et al[5]. Evolution of Dynamic Construction Land.…”
mentioning
confidence: 99%