Journal of Remote Sensing & GIS最新文献

{"title":"GIS Based Assessment of Soil Erosion Using Universal Soil Loss Equation (USLE) in Wular Catchment of Kashmir","authors":"Z. Hassan, M. I. Malik, T. A. Kanth","doi":"10.37591/.V8I3.2","DOIUrl":"https://doi.org/10.37591/.V8I3.2","url":null,"abstract":"The Universal Soil Loss Equation (USLE) has been assessed in the present study using Remote Sensing and GIS in order to estimate the potential Soil Loss at watershed level in Wular Catchment. Wular Catchment has an area of 1200.36 km 2 and lies between 34 o 12′24″ and 34 o 36′26″ N latitude and 74 o 26′41″ and 74 o 56′02″E longitude. Its altitudinal range is from 1580 meters near Wular Lake to about 4500 meters in Harmukh range. Maps of the R, K, LS, C and P factors were derived from the precipitation data, soil map, digital elevation model (DEM), land use and field survey respectively. It emerges from the study that about 6% of the area has severe erosion with a soil loss more than 900 t ha −1 yr −1 . The watersheds of 1EE2a, 1EM2a and 1EE1c have the highest percentage share of 19.91%, 17.30% and 14.88% respectively under severe erosion. This is the most susceptible zone to soil erosion primarily due to very steep slope gradient and slope length. The study clearly demonstrates the importance of vegetation cover for watershed management. The Study has proposed soil and water conservation measures in accordance with the spatial distribution of soil loss in the Catchment. Keywords: USLE; Soil Loss; Wular Catchment; Soil Erosion; Rainfall; Erosivity Cite this Article Zahoor-ul-Hassan, M. Imran Malik, T.A. Kanth. GIS Based Assessment of Soil Erosion Using Universal Soil Loss Equation (USLE) in Wular Catchment of Kashmir. Journal of Remote Sensing & GIS . 2017; 8(3): 56–66p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121634046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Composite Suitability Index (CSI) Method for Ground Water Potential Identification: A Case Study for Bangalore Urban and Rural District, Karnataka","authors":"S. Revathy, S. Babu, R. Raikar","doi":"10.37591/.V8I3.37","DOIUrl":"https://doi.org/10.37591/.V8I3.37","url":null,"abstract":"Usage of groundwater for domestic and industrial purposes poses a main intimidation to the rapidly depleting groundwater resources of India. The present work emphasizes the viability of remote sensing and geographic information system (GIS) applications in groundwater studies, especially in the identification of groundwater potential zones in Bangalore urban and rural districts, Karnataka, India, using composite suitability index (CSI) method. The CSI technique is used to determine the weights of different themes and their modules for recognizing the groundwater prospective zone. Each class or unit of every thematic layer was assigned a knowledge based ranking, depending on its significance. Then all thematic layers were overlaid through overlay process/method in Arc GIS environment. Five categories of groundwater potential zones, namely, good, good-moderate, moderate, moderate-poor and poor were identified and delineated. The obtained ground water potential zone map will be used to furtherance the urban and rural water supply plan in the Bangalore urban and rural areas. Keywords: Groundwater potential identification, composite suitability index, GIS and remote sensing Cite this Article Revathy SS, Suresh Babu S, Raikar RV. Composite Suitability Index (CSI) Method for Ground Water Potential Identification: A Case Study for Bangalore Urban and Rural District, Karnataka. Journal of Remote Sensing & GIS. 2017; 8(3): 8–16p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129418768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prioritization, Characterization and Geo-spatial Location of River Training Structures for Vrishabhavathi River using GIS Techniques","authors":"K. Gajalakshmi, A. M. Joshi, A. Sneha","doi":"10.37591/.V8I3.40","DOIUrl":"https://doi.org/10.37591/.V8I3.40","url":null,"abstract":"Bengaluru drainage characteristics of natural catchments have drastically altered due to unplanned urbanization, increasing volume and rate of surface runoff. The frequent blockage of drainage system due to indiscriminate disposal of solid waste, encroachment of wetlands and increasing volume of flow makes coping up and worsening the present drainage systems. These problems of urban floods can be prevented by taking necessary precautions in places where these urban floods could occur. Remote sensing and geographical information system plays a major role in recognizing the flood prone area. Using Arc-GIS software and Google Earth images, critical bed characteristics are identified. In order to analyse physico-chemical characteristics of ground water along the banks of the river, eight water samples were collected and tested. A temporal analysis on surface water of Vrishabhavathi reservoir was made. The geo-spatial location of varying ground water quality and flood prone areas was identified by weighted overlay analysis through GIS application. Bad river bed characteristics, poor ground water quality, flood prone areas and variation in surface water quality were identified in the study. This work is concluded by suggesting corrective measures that can be carried out in these identified locations to avoid urban floods. Keywords: GIS, river bed characteristics, physico-chemical characteristics, ground water quality, river training, geo-spatial location, flood prone areas Cite this Article Gajalakshmi K, Joshi Ashwin M, Sneha AR. Prioritization, Characterization and Geo-spatial Location of River Training Structures for Vrishabhavathi River using GIS Techniques. Journal of Remote Sensing & GIS . 2017; 8(3): 33–45p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124068744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale geoscene analysis using VHR remote sensing images: application to urban functional mapping","authors":"S. Du","doi":"10.4172/2469-4134-C1-007","DOIUrl":"https://doi.org/10.4172/2469-4134-C1-007","url":null,"abstract":"","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"323 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121072835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of a Pipeline Route in a Karst Terrain, Florida, USA","authors":"C. Denizman, Eric Parrish","doi":"10.4172/2469-4134.1000210","DOIUrl":"https://doi.org/10.4172/2469-4134.1000210","url":null,"abstract":"A pipeline, known as Sabal Trail Pipeline, for natural gas transport has been proposed to extend from Alabama to Florida, passing through a very fragile and mostly uncovered karst terrain in Florida. There is considerable concern as to the structural integrity of the pipeline as well as its potential impacts on the environment, particularly on groundwater quality of the Floridan aquifer. Using Geographic Information Systems, this study examines the extent of karst in the proposed trail route and suggest two new alternative routes with significantly less karst development. Mean depression density within 5 km of the proposed Sabal Trail route is 5.2 depressions per km2, with a spatial coverage of 12.2%. Depressions within the alternative route have significantly lower density -2.1 depressions per km2 and much smaller spatial coverage; 5.7%. The routes were also compared with respect to intersected land cover categories.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115685862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drought Analysis for Agricultural Impact Through Geoinformatic Based Indices, A Case Study of Bankur District, West Bengal, India","authors":"Kartic Bera, Jatisankar Bandyopadhyay","doi":"10.4172/2469-4134.1000209","DOIUrl":"https://doi.org/10.4172/2469-4134.1000209","url":null,"abstract":"Erotic and subnormal rainfall distribution or high demand of water causes the drought. According to the National Commission on Agriculture has categorized three types of drought. One of them is hydrological drought, due to the drought rural community are affected by availability of surface water, sub-surface water and ground water. This is why we can say that hydrological or agricultural drought is the silent natural threat or hazard of rural economy. Also, it impacts on crop area, crop production, environment by abnormal weather condition. In West Bengal, the few districts are drought prone. Bankura is one of them. In this paper, remote sensing based methodology prepared for identify and take management stratagem according to state label or district label. Prevention and preparedness means pre-disaster activities designed to increase the level of readiness and improvement of operational and institutional capabilities for responding to a drought.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117006256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GIS Applications for Assessing Spatial Distribution of Boreholes and Hand Dug Wells in Boroboro Community, Atiba Local Government, Oyo State","authors":"O. E. Awodumi, Opeyemi Stephen Akeasa","doi":"10.4172/2469-4134.1000208","DOIUrl":"https://doi.org/10.4172/2469-4134.1000208","url":null,"abstract":"Shortage of water supply and quality has become a major global concern as a result of rapid population growth; industrial activities, agricultural expansion and currently climate change. As urbanization increases, so thus, human consumption and demand for water continue increases. Boroboro community is a sub-urban settlement which has a major challenge in supply of water because of limited number of boreholes and hand–dug wells as well as effect of season variation in the community. This research is aimed at mapping and assessing the spatial distribution of boreholes and hand-dug wells in Boroboro community using Geographical Information Systems (GIS). The spatial distribution of the boreholes and hand dug wells were determined using hand-held GPS. The data generated was analyzed using ArcGIS 10.3 software and the buffering of the boreholes and hand-dug wellswere overlaid to know those who have access to both the boreholes and the hand dug well. The result shows as the community expands, the distance to the existing and available boreholes and hand dug wells increases. It is recommended government should assist in the provision of potable water through sitting of hand dug wells and boreholes with good depth in the study area.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121071463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on Spatiotemporal Variability of Water Quality Parameters in Florida Bay Using Remote Sensing","authors":"M. Gholizadeh, A. Melesse","doi":"10.4172/2469-4134.1000207","DOIUrl":"https://doi.org/10.4172/2469-4134.1000207","url":null,"abstract":"In this study, the bio-physical parameters associated with water quality of Florida Bay were investigated based on atmospherically corrected data. The principal objective of this study was to monitor and assess the spatial and temporal changes of four water quality parameters: turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen (TN), using the application of integrated remote sensing, GIS data, and statistical techniques. For this purpose, two dates of Landsat Thematic Mapper (TM) data in 2000 (February 13), 2007 (January 31), and one date of Landsat Operational Land Imager (OLI) in 2015 (January 5) in the dry season, and two dates of TM data in 2000 (August 7), 2007 (September 28), and one date of OLI data in 2015 (September 2) in the wet season of the subtropical climate of South Florida, were used to assess temporal and spatial patterns and dimensions of studied parameters in Florida Bay, USA. The simultaneous observed data of four studied parameters were obtained from 20 monitoring stations and were used for the development and validation of the models. The optical bands in the region from blue to near infrared and all the possible band ratios were used to explore the relation between the reflectance of waterbody and observed data. The predictive models to estimate chl-a and turbidity concentrations were developed through the use of stepwise multiple linear regression (MLR) and gave high coefficients of determination in dry season (R2=0.86 for chl-a and R2=0.84 for turbidity) and moderate coefficients of determination in wet season (R2=0.66 for chl-a and R2=0.63 for turbidity). Values for total phosphate and TN were correlated with chl-a and turbidity concentration and some bands and their ratios. Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI, and ground data and showed a high coefficient of determination in dry season (R2=0.74 for total phosphate and R2=0.82 for TN) and in wet season (R2=0.69 for total phosphate and R2=0.82 for TN). The MLR models showed a good trustiness to monitor and predict the spatiotemporal variations of the studied water quality parameters in Florida Bay.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114478960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of Optimum Route Alignment in Landslide Areas: A Case Study from Sri Lanka","authors":"Nayana Padmani Wak, Sudath Ra","doi":"10.4172/2469-4134.1000206","DOIUrl":"https://doi.org/10.4172/2469-4134.1000206","url":null,"abstract":"In Sri Lanka road network, especially in hilly terrain is affected by landslide in every rainy season. Therefore, the maintenance cost of the Road Development Authority is increasing and roads have to be closed for traffic due to landslides. Hence developing a methodology to identify an optimum route alignment in landslide areas is essential in the planning of roads. To identify the optimum route alignment for Beragala-Koslanda landslide area, geo-informatics approach was used considering engineering factors simultaneously in the present study. 1:10,000 scale topographic map, 30 m resolution downloaded USGS DEM, 1: 100,000 geology map and 1: 50,000 landslide hazard zone map were used as basic input data for the analysis. Using the basic input data, seven layers (Landslide hazard zone, Land use and management, Slope, Drainage density, Populated area, Sensitivity area and Lithology) were extracted and further they were weighted and ranked using Spatial Multi Criteria Analysis (SMCA) according to the values given by experts in the field of geology and highway engineering. The least cost path for the area was identified by using the least cost path algorithm in Arc GIS 10.2. Field verification was conducted with the participation of civil engineers and GPS (Global Positioning System) were used to go through the identified path. Finally, 15.414 km length alternative route was identified from Beragala to Koslanda landslide area. The final result obtained in this study supports other researches in the application of GIS and SMCA in complex planning. Possibilities of applying GIS and SMCA in identifying the route alignment avoiding landslide risk areas, was proved in this study.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131367298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GIS-RUSLE Interphase Modelling of Soil Erosion Hazard and Estimation of Sediment Yield for River Nzoia Basin in Kenya","authors":"Akali Ngaywa Moses","doi":"10.4172/2469-4134.1000205","DOIUrl":"https://doi.org/10.4172/2469-4134.1000205","url":null,"abstract":"River Nzoia basin is predisposed to degradation attributed to poor anthropogenic land use practices, soil erosion and sedimentation. The objective of this study was to model soil erosion hazard and estimate sediment yield for river Nzoia basin. Database of the basin comprised of 90 m DEM, LandSat imagery, rainfall, and soil data. Simulated RUSLE model factors (R, K, LS, and C) were multiplied using the raster calculator in ArcGIS 10.1. This generated the soil erosion hazard map for river Nzoia basin with an average annual soil loss rate of 0.51 and a maximum of 8.84 Mton ha-1 yr-1. This translates into a mean annual soil loss of 6.579 × 105 Mtonyr-1. Sediment Delivery Ratio (SDR) of 0.121 revealed that 87.9% of the soil eroded by water in the basin is deposited before reaching the basin outlet. Average annual sediment yield estimated was 0.06 Mtonyr-1. Soil erosion modeling results showed that river Nzoia basin is experiencing varying erosion rates spatially. The interplay among the RUSLE factors strongly influence average annual soil loss rates. Areas experiencing high soil loss rates are closely linked to annual cropland, deforested and high elevation points. Low rates of soil loss are attributable to soil conservation practices and protected areas such as game parks. Thus, there is a close coupling between soil loss and land use category in river Nzoia basin. Sustainable land use practices should be embraced to support conservation programmes to mitigate soil erosion, prevent sedimentation and reduce sediment yield in the river channel.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"312 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132968676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}