Evaluation of land use/land cover changes in Mekelle City, Ethiopia using Remote Sensing and GIS (original) (raw)
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Journal of Geographic Information System
The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in fast-growing urban areas. We have developed a methodology to detect changes in land cover using satellite images for the years 1997, 2002, 2012 and 2017. The categories of five-class classification in the study area were built up area, plantation, waterbody, agricultural land and pastureland. The maps showed that between 1997 and 2017, the amount of urban or developed land increased from 8.12% to 52.4% of the total area, while agriculture land, plantation, waterbody and pastureland decreased from the 91.88% to 47.6% from the entire study area. The results showed that the urban (highly built-up) area increased dramatically. Inversely, pastureland, agricultural land, waterbody, and plantation decreased obviously from the period of 1997 to 2017. The remote sensing and GIS technique used in this study proved to be efficient; the time was shortened for the analysis of the city extension; and it was discovered that it was a useful tool to evaluate the effects of urbanization on the basis of the satellite image of the given years. The results quantify land use, coverage change patterns in Debre Tabor Town and demonstrate the potential of remote sensing, and GIS tools provide an accurate and cost-effective means to track land cover changes along time that can be used as management decisions and guidelines.
SN Applied Sciences
Mapping and quantifying the status of Land use/Land cover (LULC) changes and drivers of change are important for identifying vulnerable areas for change and designing sustainable ecosystem services. This study analyzed the status of LULC changes and key drivers of change for the last 30 years through a combination of remote sensing and GIS with the surveying of the local community understanding of LULC patterns and drivers in the Gubalafto district, Northeastern Ethiopia. Five major LULC types (cultivated and settlement, forest cover, grazing land, bush land and bare land) from Landsat images of 1986, 2000, and 2016 were mapped. The results demonstrated that cultivated and settlement constituted the most extensive type of LULC in the study area and increased by 9% extent. It also revealed that a substantial expansion of bush land and bare land areas during the past 30 years. On the other hand, LULC classes that has high environmental importance such as grazing land and forest cover ...
African Journal of Environmental Science and Technology, 2008
Recently, forest land grant for investment which is often misquoted as bare land is posing a challenge to biodiversity conservation efforts in the Majang Zone of Gambella Region, Ethiopia. On the other hand, Majang zone has always been known for dense forest cover and rich biodiversity; but recently threatened due to plantation investment. In order to tackle such prevailing problems, timely information about past and existing land-use/cover scenarios is needed. This study therefore aim to drive reliable information about land-use/cover trends for the last 30 years using Remote Sensing techniques. Landsat Thematic Mapper (TM) for year 1987 and Landsat 8 Operational Land Imager (OLI) for year 2016 were used for image classification. By applying all the approaches and algorithms recommended for image classification, six major land-use/cover classes were identified. The landscape ever covered with dense forest was dramatically updated to new land-use/cover. The 1987 land-use/cover map put forest as the major land cover accounted for 86.73%. However, findings from recent satellite image uncovered new land-use/cover class-plantation accounted for16.16 % that comes out of almost none existent land use pattern in 1987. The result also showed that agricultural land and settlement expanded at alarming rate (3.4 and 0.13 hectare) per year respectively but, the forest cover is the most altered part decreasing by 0.32 hectare per year. Thus, it is important to take urgent action against further conversion of forest to other land cover class, which might have negative impacts in advance on the remaining natural forest.
2019
Population pressure, lack of awareness and weak management are considered as the real reasons for the deforestation and degradation of natural resources in Ethiopia. Land use land cover (LULC) classification has been widely studied in remote sensing and GIS for the purpose of agricultural, ecological and hydrological processes. This study applied supervised classification method with maximum likelihood classification algorithm in ArcGIS 10.1 software to identify land use land cover changes observed in Abaya Chamo sub-basin, Ethiopia by using Landsat 4-5TM and Landsat-8 OLI/ TIRS images for the years 1995, 2000 and 2017. The LULC classification of the sub-basin was classified into seven major classes. It was found that barren soil, farmland, Lake Abaya and vegetation area had been increased within two decades and the annual rate of change was 0.08%, 0.45%, 0.25% and 0.37% respectively, but grass and shrubland, and woodland area has been decreased by an annual rate of change of 0.48% ...
—Urbanization has a pivotal role to play on land use land cover changes and ecological degradation, in return with some socioeconomic benefits. Hence, it is important to have frequent update on urban information to secure urban land use sustainability in order to minimize its impacts on urban ecology. The aim of this study is to use geospatial techniques for assessment of land use land cover change detection of Adama city, Ethiopia. Four datasets of landsat 5 and 7 thematic mapper (TM) were used to identify LULC from 1984 to 2014 over a period of 30 years using maximum likelihood technique and subsequently analysed within a GIS environment. The study area has been categorized into five different LULC classes, namely, urban, agriculture, shrub and bushes, barren area and hilly area. Results shows that during the last thirty years, urban area has increased by 31.73% (i.e., 42.66 km 2), while agriculture area have decreased by 24.53% (i.e., 32.98 km 2). Further, it is observed that during this period, population in the area has increasing at an average rate of 5%. Correlating population and urban growth, it is found that by the year 2030 the whole area would be fully converted into urban area.
2015
Urbanization has a pivotal role for land-use and land-cover changes and ecological degradation in return with some socioeconomic benefits. Hence, it is very important to have frequent urban information to secure urban land use sustainability so as to minimize its impacts on urban ecology. This study was aimed at to map and quantify Land-use/Land-cover change and spatio-temporal expansion process of Assela Town between 1985 and 2013. Integrated Remote Sensing (RS) and Geographical Information System (GIS) techniques were applied. The Land-use/Land-cover and urban expansion dynamics of the town was the result of remotely sensed multi-temporal satellite imageries interpretation traced back to 1985, 1993, 2001 and 2013 respectively. Land-use/Land-cover area changes detection and conversion to urban landscape comparison between each study period was computed. The supervised image classification method with maximum likelihood probability algorithm has been employed for the land -cover cla...
European Academic Research, 2021
In the last decades, Assela town has experienced drastic changes in its vast geographical expansion, and also by internal transformations. Subsequently, understanding and evaluating the spatiotemporal dynamics of urban growth and land use and land cover (LULC) shifts, and it is important to bring forth the right strategies and processes to track urban development in decision-making. The goal of this analysis was therefore to examine LULC changes that have taken place bewtween 1995 to 2021, forecast the long-term urban development in Assela town using geospatial techniques. For this study a three time series data Landsat 5 for 1995, Landsat 7 for 2008, and Landsat 8 for 2021 satellite images were used to extract LULC types. Four LULC classes were extracted using a Support Vector Machine (SVM) supervised classification approach for image classification. Agricultural land, paved surfaces, vegetation, and water bodies were the LULC classes. Maximum likelihood supervised classification of satellite imageries was applied for Image classification. The area in terms of LULC can be divided into following four classes: Paved surface, agriculture land, and vegetation and water bodies.
Wetlands are one of the crucial natural resources. They provide invaluable biodiversity resources, aid in water quality improvement, support ground water recharge, help in moderating climate change and support flood control. Environment is in the other hand, where we live and something, we are very familiar with our day to day life. Geographic Information Systems (GIS), Remote Sensing and Global Positioning System (GPS) were a useful tool for wetland and environmental change analysis and to improve on the classification accuracy. This study investigates population and environmental change of Jarmet wetland and its surrounding area change analysis over the period of 1972 to 2015. The purpose of this study was to show land use/ land cover change of Jarmet wetland and its surrounding environment over years as a response to population growth. For this purpose, multi-temporal satellite imageries (Landsat MSS 1972, TM1986, ETM+ 2000, 2005 and 2015 and SRTM 2000) were obtained and used for...
Evaluation of land use/land cover changes and land degradation in Dera District, Ethiopia were undertaken using two remotely sensed datasets (Landsat 5 TM of 1985 and Landsat 7 ETM + imagery 2011). Land use/land cover change detection and Normalized Difference Vegetation Index analysis was carried out on the two images. Global positioning system and topographical maps of scale 1:50,000 for ground verification and ERDAS Imagine 9.1 and ArcGIS 9.2 software for satellite image processing and analysis were used for the study. Field observations and focus group discussions were also conducted to obtain addition information. The result of this study showed that cultivated and degraded lands were increased by 25.79% and 398% respectively at the expense of forest, shrub and grazing lands. Normalized Difference Vegetation Index analysis has also indicated the increased of land degradation between 1985 and 2011 images which mainly aggravated by land use/land cover changes.
2015
This study examines the application of GIS and Remote Sensing in mapping Land Use and Land Cover change in Kilite Awulalo Woreda, Eastern Tigray Zone from 1972 to 2014. For this study, LANDSAT images of 1972 (Landsat-1 MSS); 1984 (Landsat-5 TM); 2000 (Landsat-7 ETM+) and 2014 (Landsat-8 OLI_TIRS) were used and analyzed using Arc GIS 10.1 and Erdas Imagine 13. Supervised classification scheme was used to classify the images. Under land use and land cover categories Agriculture land, Settlement land, Grazing land, Forest land, Bush land, Water bodies and Bare/stony land were studied. The result shows that Bush land was decreased from 1972 to 2014 which is 1972 (58007.88 hectare), 1984 (47900.79 hectare), 2000 (45000.1 hectare) and 2014 (40573.53 hectare) and forested land was decreased from the year 1984 (21706.65 hectare) to 2014 (11916.6 hectare). Agriculture and settlement area was increased from the year 1972 to 2014. Agriculture was increasing 13138.92, 20856.78, and 23000.09 to ...