Analysis of Land Use Land Cover Changes Using Remote Sensing Data and Geographical Information Systems (GIS) at an Urban Set up of Damaturu, Nigeria

Change detection is useful in many applications related to land use and land cover change (LULCC), such as shifting cultivation and landscape changes. Land degradation and desertification. Remote sensing technology has been used for the detection of the changes in land use land cover in Damaturu town Nigeria. The main objectives of this research is to derive the land use/cover change map of Damaturu town from 1986 to 2017 and to quantify land use/ land cover change in the study area. Methodology employed while carry the research includes three satellites images for the year 1986, 1998 and 2017 were downloaded from USGS websites and used for detecting the land cover changes. Ground truth points were collected using google images and used for verification of image classifications. The accuracy of images classification was checked using ground truth point which showed the overall accuracy of 84.6% and a kappa coefficient of 0.89 which indicated that the method of classification was accurate. In the process of the research work, an increased was recorded in the built-up area which rose from 7.2% to 22.0%, open space increased from 10.8 to 22.8%, vegetation from 4.0% to 9.7%, water bodies from 0.0% to 0.1% while agricultural land decreased from 78% to 45.4% due to increase in interest of building as a result of the expansion of the town. The study arrived at the conclusion that there has been a significant land use change due to increase in population and development interest in built up areas which resulted in increased of amount of agricultural land being converted to build up areas over the period of 31 years.

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Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS

Sustainability ◽

10.3390/su12093925 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3925 ◽

Cited By ~ 2

Author(s):

Sonam Wangyel Wang ◽

Belay Manjur Gebru ◽

Munkhnasan Lamchin ◽

Rijan Bhakta Kayastha ◽

Woo-Kyun Lee

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Agricultural Land ◽

Water Bodies ◽

Geographical Information ◽

Land Cover Changes ◽

Rapid Urbanization ◽

Urbanized Areas

Understanding land use and land cover changes has become a necessity in managing and monitoring natural resources and development especially urban planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. Our study used remote sensing and geographical information system to detect and predict land use and land cover changes in one of the world’s most vulnerable and rapidly growing city of Kathmandu in Nepal. We found that over a period of 20 years (from 1990 to 2010), the Kathmandu district has lost 9.28% of its forests, 9.80% of its agricultural land and 77% of its water bodies. Significant amounts of these losses have been absorbed by the expanding urbanized areas, which has gained 52.47% of land. Predictions of land use and land cover change trends for 2030 show worsening trends with forest, agriculture and water bodies to decrease by an additional 14.43%, 16.67% and 25.83%, respectively. The highest gain in 2030 is predicted for urbanized areas at 18.55%. Rapid urbanization—coupled with lack of proper planning and high rural-urban migration—is the key driver of these changes. These changes are associated with loss of ecosystem services which will negatively impact human wellbeing in the city. We recommend city planners to mainstream ecosystem-based adaptation and mitigation into urban plans supported by strong policy and funds.

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Land Use - Land Cover Change Analysis of Karur Town - A GIS Approach

International Journal of Scientific Research in Science and Technology ◽

10.32628/ijsrst218373 ◽

2021 ◽

pp. 360-366

Author(s):

S. Ravichandran ◽

I. K. Manonmani

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Supervised Classification ◽

Agricultural Land ◽

Geographical Information ◽

Land Use Land Cover ◽

Change Analysis ◽

Barren Land

Land use / Land cover change is one of the most sensitive factors that show the interactions between human activities and the ecological environment. This research study demonstrated the importance of geographical information system and remote sensing technologies in spatial temporal data analysis and also this paper shows a GIS and remote sensing approach for modeling of spatial - temporal pattern of land use and land cover change (LULC) in a fastest growing towns / industrial region of Karur town. QGIS 3.10 version and Arc GIS 10.2 software platforms were utilized in the study for Image processing, LULC mapping and change detection analysis. USGS Earth explorer Landsat series satellite imageries were acquired and LULC maps were prepared for the years 1991, 2000, 2010 and 2020. Supervised classification with maximum likelihood algorithm is adopted for LULC classification. The LULC classes are Built upland, Agricultural land, Barren land and Water body based on NRSA Level – I supervised classification. The Built-up area has drastically increased from 1991 to 2020. It has increased more than double. It was 17 percent in 1991 and increased to 40 percent in 2020. This clearly shows Karur town is the becoming more and more urbanized.

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Role of a Mine in Changing Its Surroundings—Land Use and Land Cover and Impact on the Natural Environment in Barapukuria, Bangladesh

Sustainability ◽

10.3390/su132413602 ◽

2021 ◽

Vol 13 (24) ◽

pp. 13602

Author(s):

Hossain Mohammad Arifeen ◽

Md. Shahariar Chowdhury ◽

Haoran Zhang ◽

Tanita Suepa ◽

Nowshad Amin ◽

...

Keyword(s):

Remote Sensing ◽

Land Use ◽

Information System ◽

Land Cover ◽

Geographical Information System ◽

Agricultural Land ◽

Research Work ◽

Geographical Information ◽

Landsat 8 ◽

The Impact

Land use and land cover (LULC) change is considered among the most discussed issues associated with development nowadays. It is necessary to provide factual and up-to-date information to policymakers to fulfil the increasing population’s food, work, and habitation needs while ensuring environmental sustainability. Geographical Information System (GIS) and Remote sensing can perform such work adequately. This study aims to assess land use and land cover changes concerning the Barapukuria coal mine and its adjacent areas in Bangladesh by applying remote sensing and GIS (geographical information system) techniques. This research work used time-series satellite images from the Landsat 7 ETM+ satellite between 1999 and 2009 and the Landsat 8 OLI/TIRS satellite for 2019. Supervised classification maximum likelihood classifier matrix was implemented using ERDAS Imagine 2018. The images were categorised into four definite classes: settlement, agricultural land, forest land, and waterbody. Analytical results clearly indicated that settlements and agricultural land had increasing and decreasing trends over the past 20 years, respectively. Settlements increased from 22% to 34% between 1999 and 2019. However, agricultural land reduced from 69% to 59% in the same period. Settlements grew by more than 50% during this period. The research had an overall accuracy of 70%, while the kappa coefficient was more than 0.60. There were land subsidence issues because of mining activities, leading to 1.003 km2 area being depressed and 1500 houses cracked. This research depicts the present LULC scenario and the impact of the coalfield area. It is expected to reduce the burden on policymakers to prepare a proper and effective mines development policy in Bangladesh and meet sustainable development goal (SDG) 15 (Life on land).

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Using GIS, Remote Sensing, and Machine Learning to Highlight the Correlation between the Land-Use/Land-Cover Changes and Flash-Flood Potential

Remote Sensing ◽

10.3390/rs12091422 ◽

2020 ◽

Vol 12 (9) ◽

pp. 1422 ◽

Cited By ~ 4

Author(s):

Romulus Costache ◽

Quoc Bao Pham ◽

Ema Corodescu-Roșca ◽

Cătălin Cîmpianu ◽

Haoyuan Hong ◽

...

Keyword(s):

Machine Learning ◽

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Flash Flood ◽

Machine Learning Techniques ◽

Land Cover Changes ◽

Land Use Land Cover ◽

Runoff Potential

The aim of the present study was to explore the correlation between the land-use/land cover change and the flash-flood potential changes in Zăbala catchment (Romania) between 1989 and 2019. In this regard, the efficiency of GIS, remote sensing and machine learning techniques in detecting spatial patterns of the relationship between the two variables was tested. The paper elaborated upon an answer to the increase in flash flooding frequency across the study area and across the earth due to the occurred land-use/land-cover changes, as well as due to the present climate change, which determined the multiplication of extreme meteorological phenomena. In order to reach the above-mentioned purpose, two land-uses/land-covers (for 1989 and 2019) were obtained using Landsat image processing and were included in a relative evolution indicator (total relative difference-synthetic dynamic land-use index), aggregated at a grid-cell level of 1 km2. The assessment of runoff potential was made with a multilayer perceptron (MLP) neural network, which was trained for 1989 and 2019 with the help of 10 flash-flood predictors, 127 flash-flood locations, and 127 non-flash-flood locations. For the year 1989, the high and very high surface runoff potential covered around 34% of the study area, while for 2019, the same values accounted for approximately 46%. The MLP models performed very well, the area under curve (AUC) values being higher than 0.837. Finally, the land-use/land-cover change indicator, as well as the relative evolution of the flash flood potential index, was included in a geographically weighted regression (GWR). The results of the GWR highlights that high values of the Pearson coefficient (r) occupied around 17.4% of the study area. Therefore, in these areas of the Zăbala river catchment, the land-use/land-cover changes were highly correlated with the changes that occurred in flash-flood potential.

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

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3386.078219 ◽

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.

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A Review Paper on Monitoring Environmental Consequences of Land Cover Dynamics with The Help of Geo-informatics Technologies

Geosfera Indonesia ◽

10.19184/geosi.v5i3.18284 ◽

2020 ◽

Vol 5 (3) ◽

pp. 364

Author(s):

Ziyad Ahmed Abdo ◽

Satya Prakash

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Environmental Problems ◽

Land Cover Changes ◽

World Population ◽

Land Use Land Cover ◽

Environmental Consequences ◽

Land Cover Dynamics

Land cover dynamics is a challenging and vigorous process that associates natural and human systems that have undeviating effects on atmosphere, water and soil which lead to many environmental problems worldwide. Urbanization is one of a major land cover change that is highly correlated with many environmental problems that need emphasis. This paper aimed to review and present level and effect of land use land cover changes, urbanization, factors affecting land cover change and application of geographic information system & remote sensing in monitoring land cover changes. Over the past 300 years, about 1.2 million kilometer square of forests and 5.6 million kilometer square of pasture and rangeland were replaced by other uses worldwide, while cultivated land increased by 12 million km2. In 1950, only 30 percent of the world population lived in urban settings, the fraction raised to 55% by 2018. This led to about roughly 60% of the ecosystem services are being destroyed or used in unsustainable ways worldwide. Population expansion, change of technology, high land value, corruption, lack of awareness, migration of people and political pressure are among major driving force of land cover changes. Geo-informatics technology specially GIS and Remote Sensing is found to be an excellent tool for study of land cover change that enables observation across large area of earth’s surface with low cost, better efficient and high accuracy. Therefore monitoring, analyzing and evaluation of land cover dynamics with the help of geo-informatics is decisive for improved management & characterizing land cover alteration processes, and determining its environmental consequences. Keywords : land use; land cover change; urbanization; GIS & remote sensing; environment Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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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

10.5194/nhess-2020-255 ◽

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.

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