Journal of Remote Sensing & GIS最新文献_第6页

Monitoring and Analysis of Displacement Using InSAR Techniques for Gulaba Landslide Site 古拉坝滑坡场地InSAR位移监测与分析

Journal of Remote Sensing & GIS Pub Date : 2018-09-06 DOI: 10.37591/.V9I2.65

A. Virk, Amanpreet Singh, S. Mittal

{"title":"Monitoring and Analysis of Displacement Using InSAR Techniques for Gulaba Landslide Site","authors":"A. Virk, Amanpreet Singh, S. Mittal","doi":"10.37591/.V9I2.65","DOIUrl":"https://doi.org/10.37591/.V9I2.65","url":null,"abstract":"Interferometric Synthetic Aperture Radar (InSAR) is a powerful remote sensing technique which provides high spatial resolution images with continuous temporal coverage of the earth surface data for monitoring of long-term landslide displacement. In the current study over Gulaba Camp in Manalito Marhi (Himachal Pradesh, India) region, a novel approach to monitor the landslide using the ascending and descending InSAR data sets is being implemented. 30 ascending and 23 descending Sentinel-1 Interferometric Wide Swath images spanning the period of 26 months are acquired and processed to identify active landslide sites which have been verified with the ground observations. The combination of the results of ascending and descending path enabled to provide cumulative displacement of 60–100 mm/year over the study period with a velocity of 20–45 mm/year. This study demonstrated multi-temporal InSAR is a useful technique in assessment and monitoring of the landslide and concluded that combining ascending and descending path data has greatly improved the result. Keywords: Landslide, multi-temporal InSAR, baseline, natural hazard Cite this Article Amardeep Singh Virk, Amanpreet Singh, Mittal SK. Monitoring and Analysis of Displacement Using InSAR Techniques for Gulaba Landslide Site. Journal of Remote Sensing & GIS. 2018; 9(2): 37–46p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133795745","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}

引用次数: 4

Ocean Surface Target Feature Extraction from Fused Multi-Polarized Bands of Sentinel-1 Data 基于Sentinel-1数据融合多极化波段的海洋表面目标特征提取

Journal of Remote Sensing & GIS Pub Date : 2018-07-19 DOI: 10.37591/.V9I2.123

T. T. Sreeranju, S. Lekshmi, P. Naresh

引用次数: 0

Detecting Land Use and Land Cover and Land Surface Temperature Change in Lilongwe City, Malawi 马拉维利隆圭市土地利用、土地覆盖和地表温度变化监测

Journal of Remote Sensing & GIS Pub Date : 2018-07-19 DOI: 10.37591/.V9I2.126

S. Gondwe, Richard Muchena, Jerome Boys

{"title":"Detecting Land Use and Land Cover and Land Surface Temperature Change in Lilongwe City, Malawi","authors":"S. Gondwe, Richard Muchena, Jerome Boys","doi":"10.37591/.V9I2.126","DOIUrl":"https://doi.org/10.37591/.V9I2.126","url":null,"abstract":"In south east Africa, Lilongwe city had an observed rapid population growth over the past decade and a half. The same city also had recently observed increased temperatures and adverse weather conditions such as occassional heavy storms which caused severe flooding in January 2017 and December 2017. It was therefore thought wise to do a land use and land cover (LULC) study of the city over time to detect land cover changes and its effect on land surface temperatures (LST). Landsat imagery was acquired for the year(s) 2008, 2013 and 2017 and it was classified to detect LULC changes for these given years. A significant (P<0.05) expansion of the city was detected especially between 2008 and 2013. The LST was derived from modelling NDVIs, from which emmisivity was calculated and then the LST was estimated. There was an inverse regression (r2=0.65) with a high correlation (r=0.806) between NDVI and LST. With urbanization, the natural and agricultural land was converted into settlements resulting in lower NDVIs and higher land surface temperatures. It was concluded that urbanization, amongst others can therefore definitely contribute to global warming. Keywords: Malawi, land cover, land use, emissivity, normalized vegetation index, land surface temperature Cite this Article Gondwe Steven VC, Richard Muchena, Jerome Boys. Detecting Land Use and Land Cover and Land Surface Temperature Change in Lilongwe City, Malawi. Journal of Remote Sensing & GIS. 2018; 9(2): 17–26p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134390155","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}

引用次数: 4

Monitoring of Tehri Hydroelectric Plant Induced Land Use Land Cover Change Detection in Garhwal District of Uttarakhand 北阿坎德邦加尔瓦尔地区特赫里水电站诱发土地利用的土地覆盖变化监测

Journal of Remote Sensing & GIS Pub Date : 2018-07-19 DOI: 10.37591/.V9I2.110

Disha Punetha, Archana Sharma, P. Panwar

{"title":"Monitoring of Tehri Hydroelectric Plant Induced Land Use Land Cover Change Detection in Garhwal District of Uttarakhand","authors":"Disha Punetha, Archana Sharma, P. Panwar","doi":"10.37591/.V9I2.110","DOIUrl":"https://doi.org/10.37591/.V9I2.110","url":null,"abstract":"The present study analyses the land use change caused by the construction of Tehri dam in Bhagirathi river. Geospatial techniques like Geographic Information System (GIS) and remote sensing have been used to make land use map using Landsat satellite image of 2000 and 2014. In Tehri district, change in land use and new developments (industrial, urban and commercial) were observed. Land use land cover change was done using two satellite images, classifying them via supervised classification and applying change detection in the classified images. Classified images had an overall accuracy of 88.57 and 88.31%. The results were validated using the ground truth points distributed all over the study. Seven main classes were identified in the study area as water, open forest, dense forest, river bed, agriculture, urban and others (which includes scrub and barren land). The increase was observed in built-up class from 2000–2014. The decrease was observed in the open, dense forest and river bed. The present study showed that the construction of the hydropower and associated construction activities had caused changes in the Tehri valley. Keywords: Change detection, land use, land cover, hydropower, Tehri, supervised classification Cite this Article Disha Punetha, Archana Sharma, Pooja Panwar. Monitoring of Tehri Hydroelectric Plant Induced Land Use Land Cover Change Detection in Garhwal District of Uttarakhand. Journal of Remote Sensing & GIS. 2018; 9(2): 1–9p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129593166","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}

引用次数: 0

Assessment of Different Methods for Soil Moisture Estimation: A Review 不同土壤水分估算方法的评价综述

Journal of Remote Sensing & GIS Pub Date : 2018-05-29 DOI: 10.37591/.V9I1.105

P. Sharma, D. Kumar, H. Srivastava, P. Patel

{"title":"Assessment of Different Methods for Soil Moisture Estimation: A Review","authors":"P. Sharma, D. Kumar, H. Srivastava, P. Patel","doi":"10.37591/.V9I1.105","DOIUrl":"https://doi.org/10.37591/.V9I1.105","url":null,"abstract":"Importance of precise soil moisture information is well understood in various fields like agriculture, hydrology, meteorology, environmental studies etc. Soil moisture is very dynamic, both temporally and spatially, therefore its continuous monitoring is necessary. There are various methods available to retrieve soil moisture status. All these methods have their own advantages and disadvantages and should be used with caution depending upon the requirements and demand of the project. In this paper, an attempt has been made to evaluate different soil moisture estimation methods right from conventional methods like gravimetric soil moisture techniques to most advanced tools like Synthetic Aperture Radar Polarimetric (PolSAR) techniques. All these methods have not only been assessed individually but have also been compared and evaluated for their relative advantages and limitations. It is expected that this paper will be very useful for the researchers and managers looking for soil moisture information at different scales and different accuracies based upon their objectives, resources and needs. Keywords: Soil moisture estimation, point measurement methods, optical, thermal, microwave remote sensing methods Cite this Article Pavan Kumar Sharma, Dheeraj Kumar, Hari Shanker Srivastava et al. Assessment of Different Methods for Soil Moisture Estimation: A Review. Journal of Remote Sensing & GIS. 2018; 9(1): 57–73p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124490130","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}

引用次数: 31

Application of SPOT Imagery for Landcover Mapping and Assessing Indicators of Erosion and Proportion of Bareground in Arid and Semi-arid Environment SPOT影像在干旱半干旱地区土地覆被制图及光秃秃土地侵蚀比例指标评估中的应用

Journal of Remote Sensing & GIS Pub Date : 2018-05-03 DOI: 10.4172/2469-4134.1000240

N. Fajji, L. Palamuleni, V. Mlambo

{"title":"Application of SPOT Imagery for Landcover Mapping and Assessing Indicators of Erosion and Proportion of Bareground in Arid and Semi-arid Environment","authors":"N. Fajji, L. Palamuleni, V. Mlambo","doi":"10.4172/2469-4134.1000240","DOIUrl":"https://doi.org/10.4172/2469-4134.1000240","url":null,"abstract":"Inappropriate land-use on a fragile ecological condition have greater impact on the natural state of rangelands making land degradation a common phenomenon. Usage of remote sensing has become an ideal choice for monitoring these natural resources. SPOT 5 imagery was used, in this study for characterizing land cover classes and mapping vegetation distribution in the North West Province, South Africa by employing the maximum likelihood classification technique. Regression technique was also used to assess relationship between rainfall distribution and proportion of bare ground. Water body, bare ground, indicators of erosion, built-up area, grass and shrubs were the LULC classes in the image classification. Except for indicators of erosion, all the land-cover classes were classified with higher accuracies (in average, >0.78 overall accuracies and 0.70 for Kappa). However, SPOT 5 imagery yielded low overall accuracy (< 0.3) for indicators of erosion. Strong coefficient of determination (r²=0.80) was detected between average rainfall and proportion of bare ground indicating that rainfall is the most important factor in controlling the spatial distribution of vegetation in the study sites.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131420181","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}

引用次数: 1

Pseudo-Invariant Feature Selection for Crosssensor Optical Satellite Images 交叉传感器光学卫星图像的伪不变特征选择

Journal of Remote Sensing & GIS Pub Date : 2018-05-02 DOI: 10.4172/2469-4134.1000239

Lino Garda Denaro, B. Lin, M. A. Syariz, Lalu Muhamad Jaelani, C. Lin

{"title":"Pseudo-Invariant Feature Selection for Crosssensor Optical Satellite Images","authors":"Lino Garda Denaro, B. Lin, M. A. Syariz, Lalu Muhamad Jaelani, C. Lin","doi":"10.4172/2469-4134.1000239","DOIUrl":"https://doi.org/10.4172/2469-4134.1000239","url":null,"abstract":"Processing of multitemporal satellite images generally suffers from uncertainties caused by differences in illumination and observation angles, as well as variation in atmospheric conditions. Moreover, satellite images acquired from different sensors contain not only the uncertainties but disparate relative spectral response. Given that radiometric calibration and correction of satellite images are difficult without ground measurements during data acquisition, this study addresses pseudo-invariant feature selection for relative radiometric normalization (RRN) that minimizes the radiometric differences among images caused by atmospheric and spectral band inconsistencies during data acquisition. The key to a successful RRN is the selection of pseudo-invariant features (PIFs) among bitemporal images. To select PIFs, multivariate alteration detection (MAD) algorithm is adopted with kernel canonical correlation analysis (KCCA) instead of canonical correlation analysis (CCA). KCCA, which assumes that the relation between at-sensor radiance is spatially nonlinear, can obtain more appropriate PIFs for cross-sensor images than that of CCA, which assumes that the relation between the at-sensor radiances of bitemporal image is spatially linear. In addition, a regularization term is added to the optimization of KCCA to avoid trivial solutions and overfitting. Qualitative and quantitative analyses on bitemporal images acquired by Landsat-7 Enhanced Thematic Mapper Plus and Landsat-8 Operational and Imager sensors were conducted to evaluate the proposed method. The experimental results demonstrate the superiority of the proposed KCCA based MAD to the CCA-based MAD in terms of PIF selection, particularly for images containing significant cloud","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129437193","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}

引用次数: 1

Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing 基于热遥感的大海得拉巴城市热岛季节分析

Journal of Remote Sensing & GIS Pub Date : 2018-04-10 DOI: 10.37591/.V9I1.61

N. Sridhar, V. Bhole

{"title":"Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing","authors":"N. Sridhar, V. Bhole","doi":"10.37591/.V9I1.61","DOIUrl":"https://doi.org/10.37591/.V9I1.61","url":null,"abstract":"Urban areas are characterized by densely built-up area. Due to urbanization and consequent urban growth, green spaces, water bodies and other land use changes are resulting in several environmental issues and concerns. One such urban environmental issue is the emergence of Urban Heat Island. An Urban Heat Island (UHI) is the characteristics of elevated temperaturere of both atmosphere and land surface in urban areas as compared with the un-urbanized surrounding or rural areas. In this work, the Land Surface Temperature (LST) of mega city of Hyderabad is extracted with the help of remote sensing data. For the present study, Moderate-resolution Imaging Spectroradiometer ( MODIS) data pertaining to the year 2015 is used. The main objective this study is to identify and map Urban Heat Island. Seasonal variations in the Land Surface Temperature (LST) are analyzed for the month of May and December. It is seen from the analysis of Land Surface Temperature (LST) that, the urban areas have recorded higher temperature as compared to its rural counterpart. It is also seen that emergence of Urban Heat Island is very conspicuous during the night time. The temperature variation between urban-rural surroundings varies between 29.11 and 21.69°C in the month of May (summer) whereas it ranged between 23.71 and 16.14°C in the month of December (winter). The variations in the night temperature is maximum during summer season. Keywords: Urbanization, remote sensing, land surface temperature, urban heat island Cite this Article Sridhar N, Vijaya Bhole. Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing. Journal of Remote Sensing & GIS. 2018; 9(1): 49–56p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115255861","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}

引用次数: 0

MSW Landfill Site Selection for Hyderabad City Using GIS and AHP 基于GIS和AHP的海得拉巴市生活垃圾填埋场选址

Journal of Remote Sensing & GIS Pub Date : 2018-04-10 DOI: 10.37591/.V9I1.81

T. S. Rao, I. N. Babu, N. Chandana

{"title":"MSW Landfill Site Selection for Hyderabad City Using GIS and AHP","authors":"T. S. Rao, I. N. Babu, N. Chandana","doi":"10.37591/.V9I1.81","DOIUrl":"https://doi.org/10.37591/.V9I1.81","url":null,"abstract":"One of the significant difficulties in most of massive urban areas is lack of land for waste disposal. According to UN world population prospects, about 54% of the population resides in urban areas which are anticipated to rise to 66% by 2050. India is estimated to add 404 million urban dwellers by 2050. The substantial increase in the population growth has lead to the immense generation of waste. 5000 TPD of municipal solid waste is being generated from Greater Hyderabad Municipal Corporation (GHMC). In many places, the solid waste generated is dumped unscientifically onto the open lands. So there is a need for optimized potential site selection for disposal of waste. This paper mainly focuses on selection of potential site for the disposal of municipal solid waste generated from GHMC area using Geographic Information System (GIS) and Analytical Hierarchy Process (AHP). In AHP, weights were allocated to each criteria based on relative importance with respect to each other and ratings are assigned depending on its magnitude of impact. Various factors are considered in the siting process were categorized into environmental and economic criteria. Road networks and slope were clustered under economic basis and water bodies, sensitive sites, groundwater levels and land use were clustered under environmental basis. For all criterions, thematic maps were generated and then combined with AHP using GIS for site selection. Keywords: Landfill site selection, GIS, AHPs Cite this Article T. Srinivasa Rao, I. Naga Babu, Chandana N. MSW Landfill Site Selection for Hyderabad City Using GIS and AHP. Journal of Remote Sensing & GIS. 2018; 9(1): 15–25p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133262911","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}

引用次数: 1

Integration of Remote Sensing and GIS Techniques for Flood Monitoring and Damage Assessment: A Case Study of Naogaon District, Bangladesh 遥感与GIS技术在洪水监测与灾害评估中的整合——以孟加拉国Naogaon地区为例

Journal of Remote Sensing & GIS Pub Date : 2018-03-30 DOI: 10.4172/2469-4134.1000236

Abdullah-Al- Faisal, A. Kafy, Sumita Roy

{"title":"Integration of Remote Sensing and GIS Techniques for Flood Monitoring and Damage Assessment: A Case Study of Naogaon District, Bangladesh","authors":"Abdullah-Al- Faisal, A. Kafy, Sumita Roy","doi":"10.4172/2469-4134.1000236","DOIUrl":"https://doi.org/10.4172/2469-4134.1000236","url":null,"abstract":"Recording of hydrological parameters of a flood with conventional means often fails due to an extreme event especially in developing countries like Bangladesh. Flood water causes a lot of property damage almost every year and it demands to be controlled for economic growth by water management. The objective of the study is to analyze the damages according to different land uses like urban area (Built-up) or agricultural lands, flood height and thus the percentages of loss in different land use in various corresponding year. Naogaon District has been chosen as the study area for this analysis. Remote Sensing data has been used in this context as remote sensing technology along with Geographic Information System (GIS) has become a key tool for flood monitoring in recent years. Satellite images which have been collected from Landsat 4-5 Thematic Mapper for the year 2004, 2007 and 2012 and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images for the year 2017. In each year images of different times (March and September) of Naogaon district have been analyzed with Geographical Information System (GIS) and ERDAS Imagine software. The analysis demonstrate the variation of land use changes in before and after flood occurrence month from 2004 to 2017 depends on this change. The analysis also describe the relation of the flood in that four observation years as well as the percentages of loss association with the flood spread, flood height, and land uses. The study helps to find out the losses and related relations of flood and thus the importance of water management. The study demonstrates an encouragement to further flood water management studies.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117130618","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}

引用次数: 17