scholarly journals A study of spatial and temporal distribution of land utilization pattern in Mopka village using RS & GIS

2015 ◽  
Vol 5 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Soni Prasoon ◽  
Singh Pushpraj
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Anthropogenic Activities ◽  
Natural Habitat ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Land Utilization ◽  
Land Use Pattern ◽  
Barren Land

Remote Sensing and GIS is a very good modality for retrospection and the strategy for better exploitation of sustainable land use system. The present study was conducted in the Bilaspur district for analyzing the spatial distribution of Land Use Change. During last decades the increasing population of Bilaspur city, affect the land use pattern of Mopka Village. The anthropogenic activities were affecting the agricultural land along with barren land. For the development of civic amenities the land of the above village was used. The main objective of the present study is to analyses the land use/land cover distribution in Mopka village, Bilaspur district in between last 12 years and to identify the main forces behind the changes. The objectives of present studies are, to create a land use land cover maps of Mopka village using satellite imagery. To analysis the temporal changes of village area in between the year 2000 and 2012, the primary, secondary and satellite data were used. The results of the present study show that the decadeial changes due to population growth and increasing demand of infrastructure were destroying the natural resources, natural habitat and soil structure of area.Int. J. Agril. Res. Innov. & Tech. 5 (1): 1-9, June, 2015

scholarly journals Land use Land Cover Monitoring and Change Detection of Tinsukia, India

2020 ◽  
Vol 9 (6) ◽  
pp. 502-506
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Land Surface ◽  
Agricultural Land ◽  
Anthropogenic Activities ◽  
Land Use Land Cover ◽  
Potential Threat ◽  
Lulc Change ◽  
Barren Land

This study is driven towards land use land cover (LULC) mapping and LULC change detection in Tinsukia district, India. LULC mapping and change detection provides land planner and environmental scientists a better understanding of the land surface processes occurring in a given landscape so that they can come up with a strategy for sustainable development keeping degradation of natural environment from anthropogenic activities at bay. This study utilized remote sensing data products and software’s for LULC mapping and LULC change. Landsat data has been utilized in ENVI for the classification of LULC and LULC change detection during the period 1991-2020. The LULC classification was achieved through Maximum Likelihood Classification (MLC) which is a widely preferred classificatory method. Image change detection was achieved through ENVI thematic change workflow. On top of that ArcGIS version 10.2 was used for preparing all map layouts. Results reveal that the study area has undergone significant changes in its LULC pattern. Substantial increases were recorded in agricultural area (862.4 sq. km to 1186 sq. km), built up area (473.4 sq. km to 699.5 sq. km) and waterbodies (81 sq. km to 146.7 sq. km). A declining trend was evident in degraded vegetation (772.2 sq. km to 274.3 sq. km) and barren land (798.8 sq. km to 641 sq. km). In the short study period, the study area already seems to be changing in its LULC pattern due to anthropogenic activities. The steady increases to the agricultural land and built up area (BUA) is a potential threat to the LULC balance and it may have manifold impacts to LULC dynamics in the future if proper land utilization policy is not adopted.

scholarly journals Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

2021 ◽  
Vol 13 (16) ◽  
pp. 3337
Author(s):  
Shaker Ul Din ◽  
Hugo Wai Leung Mak
Keyword(s):  
Land Use ◽  
Support Vector Machine ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

Land Use/Land Cover Dynamic Monitoring and Analysis Using Remote Sensing and GIS Techniques: Case Study of Qingpu District, Shanghai

2012 ◽  
Vol 518-523 ◽  
pp. 5704-5709
Author(s):  
Yi Lin ◽  
Bing Liu ◽  
Feng Xie ◽  
Wen Wei Ren
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Dynamic Monitoring ◽  
Land Use Land Cover ◽  
Ecological Value ◽  
Barren Land

This paper illustrates almost twenty years (1986～2007) of Land use/land cover change (LULCC) in Qingpu-one district of Shanghai. Qingpu District is an area of Upper Huangpu Catchment for fresh water supply with considerable ecological value, but it is also experiencing urban sprawl from development. To reveal the trends underlie LULCC, we propose a novel procedure to quantify different land use/land covers and implement it in the case study. In this procedure, we first collect historical remote-sensing data and co-registered or corrected them to the same spatial resolution and radioactive level. Based upon preliminary interpretation or investigation, land use/land cover types in study area can be included in 5 categories, i.e. Water, Agricultural Land, Urban or Built-up Land, Forest Land, and Barren Land or others. Moreover, data is clipped via boundary of study area for reducing computation load, followed by FPCR-ISODATA classification to divide the data into k groups (k>the number of land types). After postprocessing, e.g., merge the same connoted subgroups and correct misclassified units accompany with validation and verification, the detailed land use/land cover results can be achieved accurately. The quantitative and regression analysis indicate that during the past twenty years the area of agricultural land of Qingpu decreased coupled with urban or built-up area increased linearly. The water area had the minimum change during the decades. Forests had the smallest average proportion (9.6%) of the total area. It occupied so small proportion of land that we can only find points of it in the maps. Barren land can be an indicator for monitoring uncompleted redevelopment or transition of land.

scholarly journals Land-Use/Land Cover Changes Contribute to Land Surface Temperature: A Case Study of the Upper Indus Basin of Pakistan

2022 ◽  
Vol 14 (2) ◽  
pp. 934
Author(s):  
Akhtar Rehman ◽  
Jun Qin ◽  
Amjad Pervez ◽  
Muhammad Sadiq Khan ◽  
Siddique Ullah ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Sustainable Land Use ◽  
Indus Basin ◽  
Land Use Land Cover ◽  
Rapid Urbanization ◽  
Barren Land

Land-use/land cover (LULC) changes have an impact on land surface temperature (LST) at the local, regional, and global scales. To simulate the LULC and LST changes of the environmentally important area of northern Pakistan, this research focused on spatio-temporal LULC and associated LST changes since 1987 and made predictions to 2047. We classified LULC from Landsat TM and ETM data, using the maximum probability supervised categorization approach. LST was retrieved using the Radiative Transfer Equation (RTE) methodology. Furthermore, we simulated LULC using the integrated approaches of Cellular Automata (CA) and Weighted Evidence (WE) and used a regression model to predict LST. The built-up areas and vegetation have increased by 2.1% and 11% due to a decline in the barren land by −8.5% during the last 30 years. The LULC is expected to increase, particularly the built-up and vegetation classes by 2.74% and 13.66%, respectively, and the barren land would decline by −4.2% by 2047. Consequently, the higher LST classes (i.e., 27 °C to <30 °C and ≥30 °C) soared up by about 25.18% and 34.26%, respectively, during the study period, which would further expand to 30.19% and 14.97% by 2047. The lower LST class (i.e., 12 °C to <21 °C) indicated a downtrend of about −41.29% and would further decrease to −3.13% in the next 30 years. The study findings are useful for planning and management, especially for climatologists, land-use planners, and researchers in sustainable land use with rapid urbanization.

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 Drivers and Implications of Land Use/Land Cover Dynamics in Finchaa Catchment, Northwestern Ethiopia

Land ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 113 ◽  
Author(s):  
Wakjira Takala Dibaba ◽  
Tamene Adugna Demissie ◽  
Konrad Miegel
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Management Practice ◽  
Supply And Demand ◽  
Sustainable Land Use ◽  
Water Bodies ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Grazing Land

Understanding the trajectories and extents of land use/land cover change (LULCC) is important to generate and provide helpful information to policymakers and development practitioners about the magnitude and trends of LULCC. This study presents the contributing factors of LULCC, the extent and implications of these changes for sustainable land use in the Finchaa catchment. Data from Landsat images 1987, 2002, and 2017 were used to develop the land use maps and quantify the changes. A supervised classification with the maximum likelihood classifier was used to classify the images. Key informant interviews and focused group discussions with transect walks were used for the socio-economic survey. Over the past three decades, agricultural land, commercial farm, built-up, and water bodies have increased while forestland, rangeland, grazing land, and swampy areas have decreased. Intensive agriculture without proper management practice has been a common problem of the catchment. Increased cultivation of steep slopes has increased the risk of erosion and sedimentation of nearby water bodies. Multiple factors, such as biophysical, socio-economic, institutional, technological, and demographic, contributed to the observed LULCC in the study area. A decline in agricultural yield, loss of biodiversity, extended aridity and drought, land and soil degradation, and decline of water resources are the major consequences of LULCC in the Finchaa catchment. The socio-economic developments and population growth have amplified the prolonged discrepancy between supply and demand for land and water in the catchment. More comprehensive and integrated watershed management policies will be indispensable to manage the risks.

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 Spatial Allocation Based on Physiological Needs and Land Suitability Using the Combination of Ecological Footprint and SVM (Case Study: Java Island, Indonesia)

2021 ◽  
Vol 10 (4) ◽  
pp. 259
Author(s):  
Sitarani Safitri ◽  
Ketut Wikantika ◽  
Akhmad Riqqi ◽  
Albertus Deliar ◽  
Irawan Sumarto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Ecological Footprint ◽  
Agricultural Land ◽  
Land Suitability ◽  
Sustainable Land Use ◽  
Public Works ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Spatial Allocation

Indonesia currently has 269 million people or 3.49% of the world’s total population and is ranked as the fourth most populous country in the world. Analysis by the Ministry of Public Works and Public Housing of Indonesia in 2010 shows that Java’s biocapacity is already experiencing a deficit. Therefore, optimization needs to be done to reduce deficits. This study aims to optimize and assess spatial allocation accuracy based on land-use/land cover suitability. In this study, the ecological footprint (EF) is utilized as a spatial allocation assessment based on physiological needs. The concept of land suitability aims for optimal and sustainable land use. Moreover, the land suitability model was conducted using the support vector machine (SVM). SVM is used to find the best hyperplane by maximizing the distance between classes. A hyperplane is a function that can be used to separate land-use/land cover types. The land suitability model’s overall-accuracy model was 86.46%, with a kappa coefficient value of 0.812. The final results show that agricultural land, plantations, and pastureland are still experiencing deficits, but there is some reduction. The deficit reduction for agricultural land reached 510,588.49 ha, 18,986.14 ha for plantations, and 1015.94 ha for pastures. The results indicate that the SVM algorithm is efficient in mapping the land-use suitability and optimizing spatial allocation.

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

scholarly journals Spatiotemporal Influence of Land Use/Land Cover Change Dynamics on Surface Urban Heat Island: A Case Study of Abuja Metropolis, Nigeria

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Heat Islands ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.

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