scholarly journals Change Detection in Landuse/ Landcover of Abeokuta Metropolitan Area, Nigeria Using Multi-Temporal Landsat Remote Sensing

2019 ◽  
Vol 51 (2) ◽  
pp. 217
Author(s):  
Adebayo Oluwasegun Hezekiah ◽  
Otun. W. O ◽  
Daniel, I. Samuel
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Planning ◽  
Water Body ◽  
Land Use Land Cover ◽  
Land Utilization ◽  
Erdas Imagine ◽  
Multi Temporal ◽  
Landsat Satellite

This research paper examined the changes in land use/ land cover of Abeokuta, Nigeria between 1984 and 2015 using Multi-Temporal Landsat Remote Sensing paired with Geographic Information System (GIS) techniques. The evaluation of the trend, rate and magnitude changes was the objectives of this study.  Five Landsat satellite images of different dates,  i.e., Landsat Thematic Mapper (TM) of 1984, 2001, 2006, 2011 and 2015 with spatial resolution ranging from 15, 30 and 60metres were obtained from National Aeronautics Space Administration(NASA),United State Geological Survey Website and  GIS facility of Sioux Falls Website  and quantify the changes  over a period of thirty-one (31) years. Supervised classification methodology was applied to the acquired multi-band raster imageries using maximum livelihood technique in ERDAS Imagine 9.3. The images of the study area were classified into three (3) classes namely; vegetation, water body and built-up area and were overlay with vector maps of the study area generated in ArcGIS 10. The results show that for the period of 31years (1984-2015), vegetation which covered 76.20% of the total area has decreased to 39.29%, water body decreases from 6.63% to 1.89% while the built –up area which initially was 17.14% as at 1984 increased to 58.82%. The study, however, recommended that there is a need for a timely Land use/ Land cover mapping of the entire Abeokuta and its environs in order to reduce the effects of undiscrimate land utilization in the area. This will also facilitate necessary Land use planning and forestall the rising sprawl not only in Abeokuta but also in other urban centres.

scholarly journals A Spatio-temporal Study of Land Use Land Cover Change Detection Using GIS and Remote Sensing Techniques

2021 ◽  
Vol 12 (1) ◽  
pp. 026-031
Author(s):  
Snehalata Chaware ◽  
◽  
Nitin Patil ◽  
Gajanan Satpute ◽  
M. R. Meshram ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Planning ◽  
Water Body ◽  
Temporal Dynamics ◽  
Kappa Coefficient ◽  
Population Pressure ◽  
Land Use Land Cover ◽  
Spatio Temporal

Land resources in India are under severe pressure and it is widely believed that marginal lands are being brought under cultivation. The extent of such changes needs to be known for better land use planning decisions. The present study illustrates the spatio-temporal dynamics of land use land cover of Nagjhari watershed in Bhatkuli block of Amravati, Maharashtra. Multi-temporal high resolution of Sentinel and Landsat satellite data were used to identify the significant positive and negative Land use land cover changes over a decade of 2007 to 2017. From 2007 to 2017, the ‘habitation’ class increased by 34% due to increasing population pressure. There was a decrease in ‘wasteland’ by 10.3%, while the area under ‘agriculture’ decreased by approximately 4.7% because of the increased area under ‘habitation’ and ‘water body’ at Nagjhari watershed. The biggest change occurred in land use class ‘water body’ increased sharply from 2013-17 by 62.7 per cent due to consequence of state policy of watershed development that was implemented after 2014. The forest class recorded maximum loss (18.3%) due to increasing population maximum land converted into habitation. The study shows overall classification accuracy as 85.46% and kappa coefficient (K) of 0.85. Kappa coefficient indicated that land use land cover assessment from remote sensing data show the best accuracy. These finding will help in deciding land use policy for future and its impact on land management of the watershed.

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.

scholarly journals Observing land-use/land-cover dynamics in semi-arid environment: Evidence from Damaturu Town and its surrounding lands, Yobe State, Nigeria

2020 ◽  
Vol 4 (2) ◽  
pp. 55-78
Author(s):  
Modibbo Babagana-Kyari ◽  
Babagana Boso
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Arid Environment ◽  
Land Use Land Cover ◽  
Temporal Aspects ◽  
Erdas Imagine ◽  
Annual Change Rate ◽  
Multi Temporal ◽  
Spatio Temporal ◽  
Supervised Image Classification

The fragile Sudano-Sahelian ecological zone of Nigeria has been classified as a hotspot of land cover change (LCC) that has been suffering from serious anthropogenic and biophysical stresses. Damaturu, being the fastest growing town situated in the region happened to be a victim of this negative development. The purpose of this study is to remotely observe and assess the prevailing land-use/land-cover (LULC) dynamics of Damaturu town and its delicate surrounding lands from the year 1987-2017 study periods. To achieve this, a supervised image classification technique with Maximum Likelihood Classifier (MLC) algorithm was used in ERDAS Imagine version 15 software to classify the three epochs multi-temporal and multi-spectral Landsat imageries (TM 1987, ETM+7 2000 and OLI 2017). The classified LULC maps and their resulting statistics were then used to assess the spatio-temporal aspects of the observed changes by placing the results within the wider context of previous related literature and evidences. Findings revealed that the built-up area has been expanding since 1987 with an annual change rate of 4.5% between 1987-2000, and 5.3% during 2000-2017 respectively. The growth of the town is being accompanied by massive farmlands expansion and vegetal cover (trees and shrubs) lost making the surrounding arable lands seriously disturbed. Thus, if the observed trends continue, the entire studied region will be subjected to severe environmental hazard such as desertification. Overall, the study provides valuable information required for sustainable  environmental management.

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 Assessment of Change in the Built-Up Index of Uyo Metropolis and Its Environs Using Remote Sensing

2019 ◽  
Vol 4 (6) ◽  
pp. 84-89 ◽  
Author(s):  
Aniekan Effiong Eyoh ◽  
Akwaowo Ekpa
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Quantitative Analysis ◽  
Land Cover ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Land Use Land Cover ◽  
Positive Growth ◽  
Bare Land ◽  
Erdas Imagine

The research was aim at assessing the change in the Built-up Index of Uyo metropolis and its environs from 1986 to 2018, using remote sensing data. To achieve this, a quantitative analysis of changes in land use/land cover within the study area was undertaken using remote sensing dataset of Landsat TM, ETM+ and OLI sensor images of 1986, 2000 and 2018 respectively. Supervised classification, using the maximum likelihood algorithm, was used to classify the study area into four major land use/land cover types; built-up land, bare land/agricultural land, primary swamp vegetation and secondary vegetation. Image processing was carried out using ERDAS IMAGINE and ArcGIS software. The Normalised Difference Built-up Index (NDBI) was calculated to obtain the built-up index for the study area in 1986, 2000 and 2018 as -0.20 to +0.45, -0.13 to +0.55 and -0.19 to +0.63 respectively. The result of the quantitative analysis of changes in land use/land cover indicated that Built-up Land had been on a constant and steady positive growth from 6.76% in 1986 to 11.29% in 2000 and 44.04% in 2018.

scholarly journals Classification of Land Use/Land Cover Changes Using GIS and Remote Sensing Technique in Lake Kenyir Basin, Terengganu, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 12 ◽  
Author(s):  
Mohd Khairul Amri Kamarudin ◽  
Kabir Abdulkadir Gidado ◽  
Mohd Ekhwan Toriman ◽  
Hafizan Juahir ◽  
Roslan Umar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Geographical Information ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technique ◽  
Multi Temporal ◽  
Vegetation Water

Geographical information system (GIS) techniques and Remote Sensing (RS) data are fundamental in the study of land use (LU) and land cover (LC) changes and classification. The aim of this study is to map and classify the LU and LC change of Lake Kenyir Basin within 40 years’ period (1976 to 2016). Multi-temporal Landsat images used are MSS 1976, 1989, ETM+ 2001 and OLI 8 2016. Supervised Classification on Maximum Likelihood Algorithm method was used in ArcGIS 10.3. The result shows three classes of LU and LC via vegetation, water body and built up area. Vegetation, which is the dominant LC found to be 100%, 88.83%, 86.15%, 81.91% in 1976, 1989, 2001 and 2016 respectively. While water body accounts for 0%, 11.17%, 12.36% and 13.62% in the years 1976, 1989, 2001 and 2016 respectively and built-up area 1.49% and 4.47 in 2001 and 2016 respectively. The predominant LC changes in the study are the water body and vegetation, the earlier increasing rapidly at the expense of the later. Therefore, proper monitoring, policies that integrate conservation of the environment are strongly recommended. 

scholarly journals Impact of Land Use Land Cover Change on Coastal Tourism in Kundapura, Karnataka, Using Multi-temporal Remotely Sensed Data and GIS Techniques

2018 ◽  
Vol 13 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Shekar Naik ◽  
H Gangadhara Bhat ◽  
T N Sreedhara
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Agricultural Land ◽  
Coastal Development ◽  
Land Use Land Cover ◽  
Coastal Tourism ◽  
Remotely Sensed Data ◽  
Erdas Imagine ◽  
Multi Temporal

The present study is an attempt to examine the Land Use Land Cover changes in parts of Kundapura Taluk in Karnataka for the period 2006 and 2016 and its impact on coastal tourism. IRS satellite images of 2006 and 2016 have been used and processed using ERDAS Imagine and ArcGIS. The result indicated tremendous changes, particularly in mixed urban and agricultural land and proved that RS/GIS has advantages over conventional techniques. The result obtained, based on the multi-dated satellite data study, will assist in decision making and help to take appropriate measures to monitor and regulate coastal development in order to achieve sustainable and integrated coastal development.

scholarly journals Urban Growth Assessment of Chennai District by Remote Sensing and Gis Techniques

2020 ◽  
Vol 8 (6) ◽  
pp. 5119-5125
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Satellite Images ◽  
Remote Sensing And Gis ◽  
Land Use Land Cover ◽  
Gis Techniques ◽  
Land Cover Map ◽  
Landsat Satellite

Urban growth of Chennai district is exponential and heading towards extreme urbanisation. Hence this necessitates the study of urban growth in Chennai district. The recent advancement in Remote sensing and GIS has an excellent ability to derive various data from the satellite images obtained .This helps us to map, monitor and picturise various aspects of development with respect to their demands. The basic principle of remote sensing is followed as the methodology. By following the methodology correctly and by proper processing of the data acquired from the satellite images, the exact requirements of information can be obtained. The Change in the urban growth of the Chennai district for three decades from 1989 to 2019 have been found by using remote sensing and GIS techniques. The satellite images of various years are obtained from Landsat satellite from the USGS Earth Explorer .The Land use characteristics of Chennai district of each year can be obtained by preparing the land use land cover map of Chennai district by the use of landsat satellite images. The two software namely ArcGIS and ERDAS Imagine are used to create the Land use land cover map. From the Land use land cover map of Chennai district, the change detection and statistical analysis of three decades are done and these analysis clearly shows that the urban growth of Chennai district is constantly increasing and there is a huge decrease in other natural features such as vegetation, water body and barren land. By performing urban trend analysis the urban growth of Chennai district for the upcoming years are predicted to prove the urban agglomeration in Chennai district.

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