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

2020 ◽  
Vol 12 (9) ◽  
pp. 3925 ◽  
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.

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

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Karagama Kolo Geidam ◽  
◽  
Nor Aizam Adnan ◽  
Baba Alhaji Umar ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Research Work ◽  
Ground Truth ◽  
Geographical Information ◽  
Land Cover Changes ◽  
Land Use Land Cover

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.

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

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.

scholarly journals Variations in ecosystem service value in response to land use/land cover changes in Central Asia over 1995-2035

2019 ◽  
Author(s):  
Jiangyue Li ◽  
Hongxing Chen ◽  
Chi Zhang ◽  
Tao Pan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Central Asia ◽  
Ecosystem Service ◽  
Water Bodies ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Ecosystem Service Value ◽  
Rapid Urbanization ◽  
Service Value

Acute farmland expansion and rapid urbanization in Central Asia have accelerated land use/land cover changes, which has significant effect onecosystemservice. However, the spatio-temporal changes in ecosystem service values in Central Asia are not well understood. Here, based on land use products with 300-m resolution for the years of 1995, 2005 and 2015 and transfer methodology, we predicted LUCC for 2025 and 2035 using CA-Markov, assessed changes in ecosystem service value in response to LUCC dynamics, and explored the elasticity for the response of ESV to LULC changes. We found significant expansions of cropland and urban and shrinking of water bodies and bare land during 1995-2035. Overall ESVs had an increasing trend from 1995-2035, which was mainly due to the increasing cropland and construction land. The combined valueofecosystemservices of cropland, grassland, water bodies accounted for over 90% of the total ESVs. However, LULC analysis showed that the area of water body reduced by 21.80% from 1995 to 2015 and continued to decrease by 21.14% from 2015 to 2035, indicating that approximately 63.37 billion US$ of ESVs lost in Central Asia. Biodiversity, food production and water regulation were major service functions, accounting for 80.52% of the total ESVs . Our results demonstrated that theeffective land-usepolicies should be made to control farmland expansion and protect water bodies, grassland and forestland for better sustainable ecosystem services.

scholarly journals An Assessment of Land Use and Land Cover Changes and Its Impact on the Surface Water Quality of the Crocodile River Catchment, South Africa

2021 ◽  
Author(s):  
Nde Samuel Che ◽  
Sammy Bett ◽  
Enyioma Chimaijem Okpara ◽  
Peter Oluwadamilare Olagbaju ◽  
Omolola Esther Fayemi ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Surface Water ◽  
Land Cover ◽  
Land Cover Change ◽  
Physicochemical Parameters ◽  
Anthropogenic Activities ◽  
Water Bodies ◽  
Land Cover Changes ◽  
River Catchment

The degradation of surface water by anthropogenic activities is a global phenomenon. Surface water in the upper Crocodile River has been deteriorating over the past few decades by increased anthropogenic land use and land cover changes as areas of non-point sources of contamination. This study aimed to assess the spatial variation of physicochemical parameters and potentially toxic elements (PTEs) contamination in the Crocodile River influenced by land use and land cover change. 12 surface water samplings were collected every quarter from April 2017 to July 2018 and were analyzed by inductive coupled plasma spectrometry-mass spectrometry (ICP-MS). Landsat and Spot images for the period of 1999–2009 - 2018 were used for land use and land cover change detection for the upper Crocodile River catchment. Supervised approach with maximum likelihood classifier was used for the classification and generation of LULC maps for the selected periods. The results of the surface water concentrations of PTEs in the river are presented in order of abundance from Mn in October 2017 (0.34 mg/L), followed by Cu in July 2017 (0,21 mg/L), Fe in April 2017 (0,07 mg/L), Al in July 2017 (0.07 mg/L), while Zn in April 2017, October 2017 and April 2018 (0.05 mg/L). The concentrations of PTEs from water analysis reveal that Al, (0.04 mg/L), Mn (0.19 mg/L) and Fe (0.14 mg/L) exceeded the stipulated permissible threshold limit of DWAF (< 0.005 mg/L, 0.18 mg/L and 0.1 mg/L) respectively for aquatic environments. The values for Mn (0.19 mg/L) exceeded the permissible threshold limit of the US-EPA of 0.05 compromising the water quality trait expected to be good. Seasonal analysis of the PTEs concentrations in the river was significant (p > 0.05) between the wet season and the dry season. The spatial distribution of physicochemical parameters and PTEs were strongly correlated (p > 0.05) being influenced by different land use type along the river. Analysis of change detection suggests that; grassland, cropland and water bodies exhibited an increase of 26 612, 17 578 and 1 411 ha respectively, with land cover change of 23.42%, 15.05% and 1.18% respectively spanning from 1999 to 2018. Bare land and built-up declined from 1999 to 2018, with a net change of - 42 938 and − 2 663 ha respectively witnessing a land cover change of −36.81% and − 2.29% respectively from 1999 to 2018. In terms of the area under each land use and land cover change category observed within the chosen period, most significant annual change was observed in cropland (2.2%) between 1999 to 2009. Water bodies also increased by 0.1% between 1999 to 2009 and 2009 to 2018 respectively. Built-up and grassland witness an annual change rate in land use and land cover change category only between 2009 to 2018 of 0.1% and 2.7% respectively. This underscores a massive transformation driven by anthropogenic activities given rise to environmental issues in the Crocodile River catchment.

scholarly journals Analysis of Spatiotemporal Land Use and Land Cover Changes using Remote Sensing and GIS: A Review

2018 ◽  
Vol 7 (4.34) ◽  
pp. 159
Author(s):  
Kabir Abdulkadir Gidado ◽  
Mohd Khairul Amri Kamarudin ◽  
Nik Ahmad Firdausaq ◽  
Aliyu Muhammad Nalado ◽  
Ahmad Shakir Mohd Saudi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Accuracy Assessment ◽  
Geographical Information ◽  
Lulc Changes ◽  
Detection Analysis ◽  
Socio Economic Factors

The land-use and land-cover (LULC) pattern of an area is an outcome of natural and socio-economic factors and their use spatially by man; this LULC varies from the forest, water body, agricultural land and so on. Remote Sensing (RS) and Geographical Information System (GIS) studies have predominantly focused on providing the technical knowledge of, where, and the type of LULC change that has occurred and its impacts on man and the environment. Knowledge about LULC changes is essential for understanding the relationships and interfaces between humans and the natural environment. The purpose of this article is to review the previous studies of the spatiotemporal LULC changes. However, thirty (30) articles were reviewed from 2011 to 2017. However, these articles studied the LULC, classification, changes and change detection analysis, using different methods and software of RS and G.I.S. The finding shows that these articles have overall accuracy assessment ranges from 75% to 95% validations. Also, supervised classification in Maximum Likelihood Algorithm method was mostly employed for the LULC classification. Moreover, these reviewed articles confirmed that LULC changes are imminent as a result of both natural and human factors which lead to increase and decrease of one LULC cover to another. Therefore proper monitoring of LULC changes when applied help the relevant government bodies, agencies and environmental managers utilise the environment to the fullest.  

scholarly journals Perubahan Tutupan Lahan Setelah 14 Tahun Bencana Tsunami (Studi Kasus di Kecamatan Baitussalam)

2020 ◽  
Vol 4 (1) ◽  
pp. 699-707
Author(s):  
Nadya Faizah ◽  
Muhammad Rusdi ◽  
Sugianto Sugianto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Land Cover Changes

Abstrak. Perubahan tutupan lahan mengakibatkan beberapa penggunaan lahan menjadi berubah, terutama pada lahan pertanian yang berubah menjadi non-pertanian. Perubahan penggunaan lahan saat ini sudah sering terjadi di beberapa daerah terutama pada lahan pertanian yang berubah menjadi lahan non-pertanian. Pasca Tsunami daerah yang terkena bencana dilakukan rehabilitasi dan rekontruksi, semua aktivitas tersebut berdampak kepada perubahan tutupan lahan. Perubahan tutupan lahan diperoleh dari overlay dengan kaedah union mulai dari tahun 2004 hingga tahun 2018. Hasil analisis menunjukkan bahwa perubahan tutupan lahan selama kurun waktu 14 tahun pasca Tsunami terbesar terjadi pada pemukiman, yaitu mengalami peningkatan sebesar 550,14 ha (76,96%). sedangkan Perubahan tutupan lahan terkecil yaitu semak belukar sebesar 66,41 ha (5,06%).Land Cover Changes after 14 years of the Tsunami Case Study at Kecamatan BaitussalamAbstract. Changes in land cover have caused some land use to change, especially on agricultural land that has turned into non-agricultural land. Post-tsunami areas affected by rehabilitation and reconstruction, all of these activities have an impact on land cover change. Changes in land cover were obtained from overlays with the unification method from 2004 to 2018. The results of the analysis showed that changes in land cover for 14 years after the Tsunami occurred mostly in settlements, which increased by 550.14 ha (76.96%). while the smallest land cover change is shrubs covering an area of 66.41 ha (5.06%).

scholarly journals Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

2021 ◽  
Vol 12 (2) ◽  
pp. 635-670
Author(s):  
Wolfgang A. Obermeier ◽  
Julia E. M. S. Nabel ◽  
Tammas Loughran ◽  
Kerstin Hartung ◽  
Ana Bastos ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Conditions ◽  
Agricultural Land ◽  
Environmental Changes ◽  
Land Cover Changes ◽  
Environmental Forcing ◽  
The Impact ◽  
Global Carbon

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).

Application of Remote Sensing and GIS to Detect Land Use and Land Cover Changes in Jos East Local Government Area, Plateau State, Nigeria.

2021 ◽  
Vol 1 (1) ◽  
pp. 1-8
Author(s):  
Solomon Wuyep zitta
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Digital Camera ◽  
Land Cover Changes ◽  
Remotely Sensed Data ◽  
Plateau State ◽  
Ground Truthing ◽  
Land Management System

This study examines the potentials of Remote Sensing techniques and GIS in land resources management with particular reference to detect land use and land cover changes in Jos East L.G.A, between 1995 to 2015. In this study, administrative maps, remotely sensed data (Landsat and Nigeriasat-1 satellite imageries) and GIS techniques were used in the image analysis. All these were done using Ilwis 3.3 Academic, ERDAS 9.3, IDIRISI 17.0 and ArcGIS 10.1. Digital camera was also used for ground truthing. The results were presented using classified imageries. Between the years 1995 to 2015, there was consistent change in the land use land cover of Jos east with different LULC categories. Throughout the study years, vegetation was observed to have the highest percentage of the total land coverage with 57544.28 ha (63%) in 1995, decreasing to 50322.96 ha (50%) in 2005, and 34969.95 (39%) in the year 2015. While agricultural/farm land was gradually increasing throughout the study period with 21271.05 ha (23%) in 1995, 27017.37 ha (27%) in 2005 and 25406.19 ha (28%) in 2015. Findings also showed that build-up-areas/settlement development increased consistently from 1451.97ha (2%) in 1995, 3290.49 ha (3%) in 2005 to 5817.96 (6%) in 2015. It was concluded that agriculture in the study area is increasing while large areas of vegetation is drastically reducing and being converted to farmlands and settlements. It is recommended that government should put up a reliable land management system in form of restrictions on premature conversion of agricultural land, there should be policies that control threat to the vegetation cover. Government should take cognizance of the land use and land cover at a regular interval to ascertain the changes that are taking place in the study area.

scholarly journals Land use/land cover change assessment of Mohana watershed (Far-Western Nepal) using GIS and remote sensing

2021 ◽  
Vol 6 (3) ◽  
pp. 320-328
Author(s):  
Suraj Prasad Bist ◽  
Rabindra Adhikari ◽  
Raju Raj Regmi ◽  
Rajan Subedi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Water Bodies ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land ◽  
Gis And Remote Sensing

The present study was conducted in the Mohana watershed of Far-western Nepal to assess land use land cover change. The study has used ArcGIS and three Landsat images - Landsat TM (1999), Landsat ETM+ (2009), and Landsat OLI (2019) – to analyze land use the land cover change of the watershed. The change matrix technique was used for change detection analysis. The study area was classified into five classes; forest, agriculture, built-up, water bodies, and barren lands. The study has found that among the five identified classes forest and build-up increased positively from 45.40 % to 51.51 % - forest cover and 11.26 % to 19. 85 % - build-up respectively. Similarly, agricultural land and water bodies initially increased but after 2009 both land cover areas decreased to 23.79 % and 0.73 % from 31.38 % and 0.97 % in 2009 respectively. Barren land decreased from 15.37% to 4.12% over the last 20 years. This study might support land-use planners and policymakers to adopt the best suitable land use management option for the Mohana watershed.

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

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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