Detecting land use and land cover change for a 28-year period using multi-temporal Landsat satellite images in the Jukskei River catchment, Gauteng, South Africa
{"title":"Detecting land use and land cover change for a 28-year period using multi-temporal Landsat satellite images in the Jukskei River catchment, Gauteng, South Africa","authors":"T. Mawasha, W. Britz","doi":"10.4314/sajg.v11i1.2","DOIUrl":null,"url":null,"abstract":"The Jukskei River catchment is one of the urban catchments in the central part of Gauteng province covering a large part of City of Johannesburg Metropolitan Municipality and small part of Tshwane and Ekurhuleni Metropolitan Municipalities that have witnessed tremendous land use/land cover (LULC) change over time. Jukskei River catchment is one of the fastest growing catchments in terms of population and change in LULC over time. Therefore, it is very important to detect the nature and extent of these changes in order to identify the direction and future expansion of LULC within the catchment area. To accomplish that, multi-temporal satellite remotely sensed data acquired from Landsat-5 Thematic Mapper (TM) 1987, Landsat-5 Thematic Mapper (TM) 2001 and Landsat-8 Operational Land imager (OLI) 2015 were used to detect LULC change in Jukskei River catchment area. The Jukskei River catchment was classified into four major LULC classes including: Built-up area, bare surface, sparse vegetation and intact vegetation. The analysis of the results revealed that for the past 28 years (i.e., 1987-2015), built-up and bare surface areas have increased by 56.2% (42713.1 ha) and 8,2% (6225.1 ha) while intact and sparse vegetation have decreased by 9.8% (7455.0 ha) and 25.8% (19659.6 ha), respectively. The overall accuracies for 1987, 2001, and 2015, were 85.9%, 87.5%, and 92.5% respectively, with Kappa Index of Agreement (KIA) of 81.3%, 83.3%, and 90% which indicates the accuracy of classified images with the reference images. The results revealed by this study can be used for decision-making activities and policy development regarding land use management within the catchment.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v11i1.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 3
Abstract
The Jukskei River catchment is one of the urban catchments in the central part of Gauteng province covering a large part of City of Johannesburg Metropolitan Municipality and small part of Tshwane and Ekurhuleni Metropolitan Municipalities that have witnessed tremendous land use/land cover (LULC) change over time. Jukskei River catchment is one of the fastest growing catchments in terms of population and change in LULC over time. Therefore, it is very important to detect the nature and extent of these changes in order to identify the direction and future expansion of LULC within the catchment area. To accomplish that, multi-temporal satellite remotely sensed data acquired from Landsat-5 Thematic Mapper (TM) 1987, Landsat-5 Thematic Mapper (TM) 2001 and Landsat-8 Operational Land imager (OLI) 2015 were used to detect LULC change in Jukskei River catchment area. The Jukskei River catchment was classified into four major LULC classes including: Built-up area, bare surface, sparse vegetation and intact vegetation. The analysis of the results revealed that for the past 28 years (i.e., 1987-2015), built-up and bare surface areas have increased by 56.2% (42713.1 ha) and 8,2% (6225.1 ha) while intact and sparse vegetation have decreased by 9.8% (7455.0 ha) and 25.8% (19659.6 ha), respectively. The overall accuracies for 1987, 2001, and 2015, were 85.9%, 87.5%, and 92.5% respectively, with Kappa Index of Agreement (KIA) of 81.3%, 83.3%, and 90% which indicates the accuracy of classified images with the reference images. The results revealed by this study can be used for decision-making activities and policy development regarding land use management within the catchment.