scholarly journals Detection of Land Use Land Cover Changes Using Remote Sensing and GIS Techniques in a Secondary City in Bangladesh

2021 ◽  
Vol 4 (3) ◽  
pp. 132-146
Author(s):  
Md. Lutfor Rahman ◽  
Syed Hafizur Rahman
Keyword(s):  
Land Use ◽  
Land Cover ◽  
The United States ◽  
United States Geological Survey ◽  
Land Use Land Cover ◽  
Error Matrix ◽  
Barren Land ◽  
Landsat 7 ◽  
Landsat Satellite ◽  
Secondary City

This study aims at classifying land use land cover (LULC) patterns and detect changes in a 'secondary city' (Savar Upazila) in Bangladesh for 30 years i.e., from 1990 to 2020. Two distinct sets of Landsat satellite imagery, such as Landsat Thematic Mapper (TM) 1990 and Landsat 7 ETM+ 2020, were collected from the United States Geological Survey (USGS) website. Using ArcMap 10.3, the maximum likelihood algorithm was used to perform a supervised classification methodology. The error matrix and Kappa Kat were done to measure the mapping accuracy. Both images were classified into six separate classes: Cropland, Barren land, Built-up area, Vegetation, Waterbody, and Wetlands. From 1990 to 2020, Cropland, Barren land, Waterbody, and Wetlands have been decreased by 30.63%, 11.26%, 23.54%, and 21.89%, respectively. At the same time, the Built-up area and Vegetation have been increased by 161.16% and 5.77%, respectively. The research revealed that unplanned urbanization had been practiced in the secondary city indicated by the decreases in Cropland, Barren land, Wetland, and Waterbody, which also showed direct threats to food security and freshwater scarcity. An increase in Vegetation (mostly homestead vegetation) indicates some environment awareness programs that encourage people to maintain homestead and artificial gardens. The study argues for the sustainable planning of a secondary city for a developing country's future development.

scholarly journals Land Use/Land Cover Change Impact on Hydrological Process in the Upper Baro Basin, Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tewodros Getu Engida ◽  
Tewodros Assefa Nigussie ◽  
Abreham Berta Aneseyee ◽  
John Barnabas
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Swat Model ◽  
The United States ◽  
United States Geological Survey ◽  
Hydrological Process ◽  
Land Use Land Cover ◽  
Validation Period ◽  
The Impact

Understanding the hydrological process associated with Land Use/Land Cover (LU/LC) change is vital for decision-makers in improving human wellbeing. LU/LC change significantly affects the hydrology of the landscape, caused by anthropogenic activities. The scope of this study is to investigate the impact of LU/LC change on the hydrological process of Upper Baro Basin for the years 1987, 2002, and 2017. The Soil Water Assessment Tool (SWAT) model was used for the simulation of the streamflow. The required data for the SWAT model are soils obtained from the Food and Agriculture Organization; Digital Elevation Model (DEM) and LU/LC were obtained from the United States Geological Survey (USGS). The meteorological data such as Rainfall, Temperature, Sunshine, Humidity, and Wind Speeds were obtained from the Ethiopian National Meteorological Agency. Data on discharge were obtained from Ministry of Water, Irrigation and Electricity. Ecosystems are deemed vital. Landsat images were used to classify the LU/LC pattern using ERDAS Imagine 2014 software and the LU/LC were classified using the Maximum Likelihood Algorithm of Supervised Classification. The Sequential Uncertainty Fitting (SUFI-2) global sensitivity method within SWAT Calibration and Uncertainty Procedures (SWAT-CUP) was used to identify the most sensitive streamflow parameters. The calibration was carried out using observed streamflow data from 01 January 1990 to 31 December 2002 and a validation period from 01 January 2003 to 31 December 2009. LU/LC analysis shows that there was a drastic decrease of grassland by 15.64% and shrubland by 9.56% while an increase of agricultural land and settlement by 18.01% and 13.01%, respectively, for 30 years. The evaluation of the SWAT model presented that the annual surface runoff increased by 43.53 mm, groundwater flow declined by 27.58 mm, and lateral flow declined by 5.63 mm. The model results showed that the streamflow characteristics changed due to the LU/LC change during the study periods 1987–2017 such as change of flood frequency, increased peak flows, base flow, soil erosion, and annual mean discharge. Curve number, an available water capacity of the soil layer, and soil evaporation composition factor were the most sensitive parameters identified for the streamflow. Both the calibration and validation results disclosed a good agreement between measured and simulated streamflow. The performance of the model statistical test shows the coefficient of determination (R2) and Nash–Sutcliffe (NS) efficiency values 0.87 and 0.81 for calibration periods of 1990–2002 and 0.84 and 0.76 for the validation period of 2003 to 2009, respectively. Overall, LU/LC significantly affected the hydrological condition of the watershed. Therefore, different conservation strategies to maintain the stability and resilience of the ecosystem are vital.

scholarly journals Spatio-temporal analysis of land use/land cover change through overlay technique in Kinnaur district of Himachal pradesh, Western Himalaya

2020 ◽  
Author(s):  
Rajan Maurya ◽  
V. S. Negi ◽  
B. W. Pandey ◽  
B. W. Pandey
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Natural Resources ◽  
Electric Power ◽  
Well Being ◽  
The United States ◽  
Himachal Pradesh ◽  
United States Geological Survey ◽  
Land Use Land Cover

In the modern era of globalisation demand of natural resources is very high for the well-being of human; high demand results in the degradation of natural resources, uneven pattern of development and changes in naturally available resources. Changes in land use land cover (LULC) is a dynamic process, which varies with time and space. It is the main component in the planning and management of natural resources, and analysing the changes in the environment. There are many remote sensing and GIS-based model used by the researcher in the world to identify the land use pattern. Here, Digital change detection model is used to determine the changes in Land use and Land cover with geo-referenced multi-temporal remote sensing data. This present study is an attempt to identify the spatial-temporal variation of LULC in the Kinnaur district of Himachal Pradesh, based on the secondary data. Landsat imageries are collected from the United States Geological Survey (USGS) for a different period like Landsat TM, Landsat ETM +, and Landsat OLI. Kinnaur district has witnessed many hydro-electric power projects, dam, tunnel and road construction, which has changed the pattern of land use in a few decades. It is indispensable to have a sustainable development mechanism for the fragile ecosystem. It includes the initiative of local government and Corporate Social Responsibility (CSR), government agencies and global partners to improve the degraded land condition.Keywords: Natural Resources, Land Use/ Land Cover, Kinnaur, Hydro-electric Power Projects.

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.

Spatial features of land use/land cover change in the United States

2003 ◽  
Vol 13 (1) ◽  
pp. 63-70 ◽  
Author(s):  
Zhiqiang Gao ◽  
Jiyuan Liu ◽  
Xiangzheng Deng
Keyword(s):  
United States ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
The United States ◽  
Land Use Land Cover ◽  
Spatial Features

scholarly journals Land Use/Land Cover Mapping of Sambar Watershed by Using Remote Sensing and GIS

2021 ◽  
Vol 10 (9) ◽  
pp. 578-585
Author(s):  
B. Varpe Shriniwas D. Payal Sandip
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing And Gis ◽  
Rapid Expansion ◽  
Water Bodies ◽  
Land Cover Mapping ◽  
Fallow Land ◽  
Land Use Land Cover ◽  
Barren Land

In the present study, an effort has been made to study in detail of Land Use/Land Cover Mapping for Sambar watershed by using Remote Sensing and GIS technique was carried out during the year of 2020-2021 in Parbhani district. In this research the Remote Sensing and Geographical Information system technique was used for identifying the land use/land cover classes with the help of ArcGIS 10.8 software. The Sambar watershed is located in 19º35ʹ78.78˝ N and 76º87ʹ88.44˝ E in the Parbhani district of Marathwada region in Maharashtra. It is covered a total area 97.01 km2. The land use/land cover map and its classes were identified by the Supervised Classification Method in ArcGIS 10.8 software by using the Landsat 8 satellite image. Total six classes are identified namely as Agricultural area, Forest area, Urban area, Barren land, Water bodies and Fallow land. The Agricultural lands are well distributed throughout the watershed area and it covers 4135 ha. (43 per cent). Forest occupies 502 ha area and sharing about 5 per cent of the total land use land cover of the study area. The Urban land occupies 390 ha. area (4 per cent) and there was a rapid expansion of settlement area. Barren land occupies 3392 ha. area (35 per cent). A water bodies occupy 630 ha. area (6 per cent) and the Fallow land occupies 650 ha (7 per cent) but well-developed dendritic drainage pattern and good water availability is in the Sambar watershed.

scholarly journals Land cover classification using landsat-8 optical data and supervised classifiers

2018 ◽  
Vol 7 (2.17) ◽  
pp. 101
Author(s):  
K V. Ramana Rao ◽  
Prof P. Rajesh Kumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Classification ◽  
Optical Data ◽  
Landsat 8 ◽  
Barren Land ◽  
Detection Techniques ◽  
Time Periods ◽  
Classification Information ◽  
Landsat Satellite

Land use and land cover information of an area has got importance in various aspects mainly because of various development activities that are taking place in every part of the world. Various satellite sensors are providing the required data collected by remote sensing techniques in the form of images using which the land use land cover information can be analyzed.  Constistency of Landsat satellite is illustrated with two time periods such as Operational Land Imager (OLI) of 2013 and consecutive 2014 procured by earth explorer with quantified changes for the same period in visakhapatnam of hudhud cyclone. Since this city is consisting of mainly urban, vegetation, few water bodies, some area of agriculture and barren,five classes have been chosen from the study area. The results indicate that due to the hudhud event some changes took place.  vegetation and built-up land have been increased by An increase of 19.1% (6.3 km2) and 11% (5.36 km2) has been observed in the case of vegetation and built up area  where as a decrease of 1.2% (4.06 km2), 6.1% (1.70 km2) and 1.2% (0.72 km2) has been observed in the case of  agriculture, barren land, and water body respectively. With the help of available satellite imagery belonging to the same area and of different time periods along with the  change detection techniques landscape dynamics have been analyzed. Using various classification algorithms along with the data available from the satellite sensor the land use and land cover classification information of the study area has been obtained. The maximum likelihood algorithm provided better results compared to other classification techniques and the accuracy achieved with this algorithm is 99.930% (overall accuracy) and 0.999 (Kappa coefficient).  

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