scholarly journals Land Use/Land Cover Changes of Ado-Ekiti LGA, Ekiti State, Nigeria Using Remote Sensing Techniques

2021 ◽  
pp. 32-42
Author(s):  
Ajagbe, Abeeb Babajide ◽  
Oguntade, Sodiq Solagbade ◽  
Abiade, Idunnu Temitope
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Local Government ◽  
Land Cover ◽  
Water Body ◽  
Local Government Area ◽  
Land Cover Changes ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Bare Surface

Land use assessment and land cover transition need remote sensing (RS) and geographic information systems (GIS). Land use/land cover changes of Ado-Ekiti Local Government Area, Ekiti State, Nigeria, were examined in this research. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI were acquired for 1985, 2000, and 2015 respectively. Image scene with path 190 and row 055 was used for the three Landsat Images. A supervised digital image classification approach was used in the study, which was carried out using the ArcMap 10.4 Software. Five land use/land cover categories were recognised and recorded as polygons, including Built-up Areas, Bare surface, water body, Dense Vegetation and Sparse Vegetation. The variations in the area covered by the various polygons were measured in hectares. This study revealed that between 1985 and 2015, there was a significant change in Built-up areas from 1694 hectares to 5656 hectares. However, there was a reduction in water body from 25 hectares in 1985 to 19 hectares in 2015; there was a severe reduction in the bare surface from 4641 hectares in 1985 to 2237 hectares in 2015. Generally, the findings show that the number of people building houses in the study area has grown over time, as many people reside in the outskirts of the Local Government Area, resulting in a decrease in the vegetation and bare surfaces. The maps created in this research will be useful to the Ekiti State Ministry of Land, Housing, Physical Planning, and Urban Development to develop strategies and government policies to benefit people living in the Ado-Ekiti Local Government Area of the State.

scholarly journals Classification of land use/land cover of Aniocha north local government area, Delta state using satellite imagery

2021 ◽  
Vol 10 (3) ◽  
pp. 207-216
Author(s):  
Ugbelase Vincent Nwacholundu ◽  
Igbokwe Joel Izuchukwu ◽  
Emengini Josephine Ebele ◽  
Ejikeme Joseph Onyedika ◽  
Igbokwe Esomchukwu Chinagorom
Keyword(s):  
Land Use ◽  
Local Government ◽  
Land Cover ◽  
Local Government Area ◽  
Thematic Mapper ◽  
Population Pressure ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Average Accuracy ◽  
Landsat 7

Remote Sensing (RS) and Geographic Information System (GIS) have been established as indispensable tools in the assessment of Land use / Land cover (LULC) change. RS and GIS are important for the monitoring, modelling and mapping of land use and land cover changes across a range of spatial and temporal scales, in order to assess the extent, direction, causes, and effects of the changes. Change detection has provided suitable and wide-ranging information to various decision support systems for natural resource management and sustainable development. The main objective of the study is to assess and evaluate the extent and direction of changes in LULC of Aniocha North Local Government Area (LGA), Delta State, Nigeria to explain the changes and identify some of their effects on both the livelihoods of the local people and the local environment, and also to explore some of the conservation measures designed to overcome problems associated with land use and land cover changes. Landsat 7 Enhanced Thematic Mapper (ETM+) of 2002 with 30 meters resolution and landsat 7 Enhanced Thematic Mapper (ETM) 2014satellite images as well as GIS techniques were used to monitor the changes and to generate maps of the LULC of the area in these periods. Supervised Land Use/Land Cover classification algorithm (Maximum likelihood with null class) was used in the analysis of classification. The classification result of LandSat ETM+ (2002) revealed that farmland accounted for 36.34% of the total LULC class, followed by savannah which accounted for 24.15%. Forest built up area, and waterbody constituted 20.42%, 16.46% and 2.62% respectively. Also, the result of LandSat ETM (2014) shows that forest accounted for 38.59% followed by farmland with 30.93%. Built up area covers 25.55% while savannah and river cover 2.86% and 2.08% respectively. The classification shows 83.26 % average accuracy and 79.16 % overall accuracy for 2002 while the 2014 accuracy assessment showed 95.06% average accuracy and 94.99% overall accuracy. Growing population pressure and its associated problems, such as the increasing demand for land and trees, poor institutional and socio-economic settings, and also unfavorable government policies, such as lack of land tenure security and poor infrastructure development, have been the major driving forces behind the LULC changes.

scholarly journals CLASSIFICATION AND ASSESSMENT OF THE LAND USE – LAND COVER CHANGES IN JODHPUR CITY USING REMOTE SENSING TECHNOLOGIES

2018 ◽  
Vol XLII-5 ◽  
pp. 767-771 ◽  
Author(s):  
M. A. Saharan ◽  
N. Vyas ◽  
S. L. Borana ◽  
S. K. Yadav
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Accuracy Assessment ◽  
Assessment Method ◽  
Land Cover Changes ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Rock Outcrops ◽  
Barren Land

<p><strong>Abstract.</strong> Land Use – Land Cover (LULC) classification mapping is an important tool for management of natural resources of an area. The remote sensing technology in recent times has been used in monitoring the changing patterns of land use-land cover. The aim of the study is to monitor the LULC changes in Jodhpur city over the period 1990–2018. Satellite imagery of Landsat 8 OLI (June, 2018) &amp;amp; Landsat TM (Oct, 1990) were used for classification analysis. Supervised classification-maximum likelihood algorithm is used in ENVI software to detect land use land cover changes. Five LULC categories were used, namely- urban area, mining area, vegetation, water bodies and other area (Rock outcrops and barren land). The LULC classified maps of two different periods i.e. 2018 and 1990 were generated on 1<span class="thinspace"></span>:<span class="thinspace"></span>50,000 scale. The accuracy assessment method was used to measure the accuracy of classified maps. This study shall be of good assistance to the town planners of Jodhpur city for the purpose of the sustainable development as per the master plan 2031.</p>

scholarly journals Land use/Land cover Changes in Sangamner City by using Remote Sensing and GIS

2019 ◽  
Vol 8 (2) ◽  
pp. 4614-4621
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Urban Expansion ◽  
Geographical Information ◽  
Space Distribution ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
The Town

This paper examines that, with the help of Remotes Sensing (RS) and Geographical Information system (GIS) Land use/Land cover of the town area from period 1975 to 2017 are classified into different classes. The town information is extracted from Toposheet and Remote Sensing Landsat-7 ETM+ images of 1975 to 2017. There are five expansion types are considered during 42 years, including water body, built-up area, forest, Agriculture and exposed Rock. By analyzing the data from the year 1975 to 2017 we found that the natural feature area such as water body, the forest is decreasing continuously and the area of town that is built-up area increase partially etc. Shannon’s Entropy approach identifies the degree of special concentration and dispersion growth, its value is close to 1 which indicates that space distribution is evenly dispersed. According to get the value of statistical Kappa Coefficient which lies in between 0.75 to 0.89 we say that there is accuracy in the requirement of research. Also, in addition to that population for the next three-decade help to define the built-up area of the city, the method used to forecast the population are Arithmetic increase method, Geometric increase method, Incremental increase method, Decreasing rate of growth method and Simple graphical method, this method gives a forecast of urban expansion from the year 2021 to 2041. The Land use/ Land cover changes classification is useful for proper planning, utilization and management of resources. Land use/Land cover changes are contributed to creating community spirit and a properly balanced population structure.

scholarly journals Land use and land cover change analysis of District Charsadda, Pakistan along Kabul River in 2010 flood: using an advance geographic information system and remote sensing techniques

2020 ◽  
Author(s):  
Misbah Fida ◽  
Irshad Hussain ◽  
Wang Tao ◽  
Abdur Rashid ◽  
Syed Amir Ali Shah
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Agricultural Land ◽  
Geographic Information ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Remote Sensing Techniques ◽  
Kabul River

Abstract. The objective of this research study was to quantify land use and land cover changes before and after the 2010 flood at District Charsadda, Pakistan. The land use and land cover changes were evaluated with the help of advanced geographic information systems (GIS) and remote sensing techniques (RST). Moreover, some remedial measures were taken to develop land use/land cover of the area to overcome future problems. Land use and land cover changes were measured by using satellite images. Two instances were compared, i.e. pre-flood and post-flood, to analyze the change in land use/land cover of District Charsadda within 5 Km along the Kabul River. Comparative analysis of pre and post-flood imageries shows drastic changes over the water body, built-up area, agriculture land, and bare land during flood instances. The study area is rural and agricultural land is dominant in the area. We evaluated the percentage of different land uses/land covers within our study area, as agricultural land was about 68.5 %, barren land was about 22.5 %, and the water body was 8.8 % before the flood. After inundation, the water body raised to 16.4 %, bare soil increased to 26.30 %, agriculture land degraded up to 57 %, and settlements (villages) along River Kabul were badly damaged and finished by this flood. Approximately, four villages of District Nowshera, six villages of District Peshawar, and twenty-seven villages of Charsadda District were badly damaged during the 2010 flood.

scholarly journals Land Use/Land Cover Changes in a Disturbed River Watershed Kenya

2019 ◽  
Vol 3 (2) ◽  
pp. 29
Author(s):  
Zachary Gichuru Mainuri ◽  
John M. Mironga ◽  
Samuel M. Mwonga
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing Image ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Human Needs ◽  
Observation Systems ◽  
Erdas Imagine ◽  
Remote Sensing Image Processing

Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Two land use/land cover (LULC) classes were established as forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where shrub land reduced by -19%, and forestry reduced by -72%. In 2000 – 2014 shrub land reduced by-45%, and forestry reduced by -64%. Forestry and shrub land were found to be consistently reducing.

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