Impact of land-use and land-cover change on groundwater quality in the Lower Shiwalik hills: a remote sensing and GIS based approach

Singh, Sudhir Kumar; Singh, Chander Kumar; Mukherjee, Saumitra

doi:10.2478/v10085-010-0003-x

Cited by 82 publications

(29 citation statements)

References 16 publications

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“…Settlement increased from 4.9% to 14.11% from 1991 to 2014. Similar studies in Shiwalik hills also attributed land-use and land-cover change to the increase in population size and per-capita requirement of natural resources [31].…”

Section: -2014supporting

confidence: 53%

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

2015

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Satellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index values were used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

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Section: -2014supporting

confidence: 53%

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

2015

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“…Satellite datasets, like Landsat, IRS and IKONOS, provide valuable information that can be used as an input for many prediction studies. Many researchers have applied geospatial techniques for natural resource management and planning purposes (Singh et al 2010;Túri and Szabó 2008;Patel et al 2012;Singh et al 2013a;Srivastava et al 2013b). Cellular Automata (CA) is a popular technique which works on a uniform grid-based principle, and has been utilized in urban growth modeling for simulating spatial processes (Wu and Webster 2000;O'Sullivan 2001;Wu 2002).…”

Section: Introductionmentioning

confidence: 99%

Predicting Spatial and Decadal LULC Changes Through Cellular Automata Markov Chain Models Using Earth Observation Datasets and Geo-information

et al. 2015

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Remote sensing and GIS are important tools for studying land use/land cover (LULC) change and integrating the associated driving factors for deriving useful outputs. This study is based on utilization of Earth observation datasets over the highly urbanized Allahabad district in India. Allahabad district has experienced intense change in LULC in the last few decades. To monitor the changes, advanced techniques in remote sensing and GIS, such as Cellular Automata (CA)-Markov Chain Model (CAMCM) were used to identify the spatial and temporal changes that have occurred in LULC in this area. Two images, 1990 and 2000, were used for calibration and optimization of the Markovian algorithm, while 2010 was used for validating the predictions of CA-Markov using the ground based land cover image. After validating the model, plausible future LULC changes for 2020 were predicted using the CAMCM. Analysis of the LULC pattern maps, achieved through classification of multitemporal satellite datasets, indicated that the socio-economic and biophysical factors have greatly influenced the growth of agricultural lands and settlements in the area. The two urbanization indicators calculated in this study viz. Land Consumption Ratio (LCR) and Land Absorption Coefficient (LAC) were also used, which indicated a drastic change in the area in terms of urbanization. The predicted LULC scenario for year 2020 provides useful inputs to the LULC planners for effective and pragmatic management of the district and a direction for an effective land use policy making. Further suggestions for an effective policy making are also provided which can be used by government officials to protect this important land resource.

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“…Many studies have proved the use of EO data namely groundwater [27,46,48,51,52], river water quality [55], coastal water [22], lake and wetlands [5,47,53,59,60], land use/land cover mapping [45,46,48,50,51], land use change trajectories [56], land use/land cover modeling [28,49], urban land use dynamics [4], hydrological modeling [31], forest mapping [44], cyclone tracking [16], soil characterization [37], climate change [54], slope estimation [57], landscape ecology [47,53], ocean studies [35,36] and watershed management [67], watershed prioritization [68]. GIS processing has become a critical step in hydrologic modeling since it contributes to generate model parameters in a spatially distributed manner.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Surface Runoff from Semi-arid Ungauged Agricultural Watershed Using SCS-CN Method and Earth Observation Data Sets

Rawat

Singh

2017

Water Conserv Sci Eng

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In the present study, Soil Conservation ServiceCurve Number (SCS-CN) method, Earth Observation (EO) data sets and Geographic Information System (GIS) have been used in order to estimate the surface runoff from Jhagrabaria an agricultural watershed of Allahabad district, Uttar Pradesh (India). LANDSAT-7ETM+, NOAA data and hydrologic soil groups have been used to prepare land use/land cover, rainfall and soil map. The traditional SCS-CN method for calculating the composite CN is very tedious and time demanding process of the hydrologic modeling. Therefore, GIS is now being used in combination with the SCS-CN method. The outcome of work showed 79.35 (CN II ) of normal condition, of dry condition 61.76 (CN I ) and of wet condition 89.84 (CN III ), respectively. This investigation outline that ungauged watershed exhibits an annual average of 14 years runoff volume as 3.58 × 10 6 m 3 from an average annual rainfall of 14 years 110.77 cm and the average annual surface runoff of 14 years was 23.83 cm and annual average runoff coefficient of 14 years was 0.22. The correlation analysis suggests that the strong correlation as R 2 (0.91) was observed between satellite drive rainfall and runoff from SCS-CN method. The developed rainfall-runoff model for the region will be useful to understand the watershed and its runoff flow characteristics.

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Impact of land-use and land-cover change on groundwater quality in the Lower Shiwalik hills: a remote sensing and GIS based approach

Cited by 82 publications

References 16 publications

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

Exploring Land use and Land cover change in themining areas of Wa East District, Ghana usingSatellite Imagery

Predicting Spatial and Decadal LULC Changes Through Cellular Automata Markov Chain Models Using Earth Observation Datasets and Geo-information

Estimation of Surface Runoff from Semi-arid Ungauged Agricultural Watershed Using SCS-CN Method and Earth Observation Data Sets

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