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.
{"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}
The introduction of new generation high-resolution SAR imagery helps in the effective monitoring of land and ocean surfaces. The SAR imagery acquired are often degraded by speckle noise which makes it difficult for quality interpretation mainly in ocean domain. Speckle reduction techniques are applied to these images to reduce the noise prior to other image processing tasks. In this paper, three different speckle reduction methods are applied both in VV and VH polarized bands of Sentinel 1A data. The filtered images are fused with different combinations using stationary wavelet transform. The performance measures of fused images are analyzed and features such as ship parameters and wave characteristics are extracted from the best-fused image. Keywords: SAR, speckle noise, filtering, fusion, radar cross section, ocean wave spectra Cite this Article Sreeranju TT, Lekshmi S, Praveen Naresh. Ocean Surface Target Feature Extraction from Fused Multi-Polarized Bands of Sentinel-1 Data. Journal of Remote Sensing & GIS. 2018; 9(2): 10–16p.
{"title":"Ocean Surface Target Feature Extraction from Fused Multi-Polarized Bands of Sentinel-1 Data","authors":"T. T. Sreeranju, S. Lekshmi, P. Naresh","doi":"10.37591/.V9I2.123","DOIUrl":"https://doi.org/10.37591/.V9I2.123","url":null,"abstract":"The introduction of new generation high-resolution SAR imagery helps in the effective monitoring of land and ocean surfaces. The SAR imagery acquired are often degraded by speckle noise which makes it difficult for quality interpretation mainly in ocean domain. Speckle reduction techniques are applied to these images to reduce the noise prior to other image processing tasks. In this paper, three different speckle reduction methods are applied both in VV and VH polarized bands of Sentinel 1A data. The filtered images are fused with different combinations using stationary wavelet transform. The performance measures of fused images are analyzed and features such as ship parameters and wave characteristics are extracted from the best-fused image. Keywords: SAR, speckle noise, filtering, fusion, radar cross section, ocean wave spectra Cite this Article Sreeranju TT, Lekshmi S, Praveen Naresh. Ocean Surface Target Feature Extraction from Fused Multi-Polarized Bands of Sentinel-1 Data. Journal of Remote Sensing & GIS. 2018; 9(2): 10–16p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"8 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":"126793582","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}
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.
{"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}
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.
{"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}
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.
{"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}
Pub Date : 2018-05-03DOI: 10.4172/2469-4134.1000240
N. Fajji, L. Palamuleni, V. Mlambo
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.
{"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}
Pub Date : 2018-05-02DOI: 10.4172/2469-4134.1000239
Lino Garda Denaro, B. Lin, M. A. Syariz, Lalu Muhamad Jaelani, C. Lin
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
多时相卫星图像的处理通常受到光照和观测角度差异以及大气条件变化所造成的不确定性的影响。此外，从不同传感器获得的卫星图像不仅包含不确定性，而且相对光谱响应也不同。考虑到在数据采集过程中，如果没有地面测量，卫星图像的辐射定标和校正是困难的，本研究解决了相对辐射归一化(RRN)的伪不变特征选择，以最大限度地减少数据采集过程中大气和光谱波段不一致造成的图像之间的辐射差异。在双时图像中选取伪不变特征(pif)是RRN成功的关键。采用多元变化检测(MAD)算法，采用核典型相关分析(KCCA)代替典型相关分析(CCA)来选择pif。假设at-sensor radiance之间的关系是空间非线性的KCCA比假设双时间图像at-sensor radiance之间的关系是空间线性的CCA能够获得更合适的跨传感器图像pif。此外，在KCCA的优化过程中增加了正则化项，避免了平凡解和过拟合。对Landsat-7 Enhanced Thematic Mapper Plus和Landsat-8 Operational and Imager传感器获取的双时相图像进行定性和定量分析，以评估所提出的方法。实验结果表明，基于KCCA的MAD在PIF选择方面优于基于cca的MAD，特别是对于包含显著云的图像
{"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}
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.
城市地区的特点是密集的建成区。由于城市化和随之而来的城市增长，绿地、水体和其他土地利用的变化导致了一些环境问题和关注。其中一个城市环境问题就是城市热岛的出现。城市热岛(Urban Heat Island, UHI)是指城市地区的大气和地表温度与未城市化的周边地区或农村地区相比升高的特征。本文利用遥感数据提取了海得拉巴特大城市的地表温度(LST)。在本研究中，使用了2015年的中分辨率成像光谱仪(MODIS)数据。本研究的主要目的是识别和绘制城市热岛。分析了5月和12月地表温度的季节变化。从陆地表面温度(LST)的分析中可以看出，城市地区的温度高于农村地区。城市热岛在夜间的出现也非常明显。5月(夏季)城乡温差在29.11 ~ 21.69°C之间，12月(冬季)城乡温差在23.71 ~ 16.14°C之间。夏季夜间气温变化最大。关键词:城市化遥感地表温度城市热岛基于热遥感的大海得拉巴城市热岛季节分析遥感与地理信息系统学报。2018;9 (1): 49-56p。
{"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}
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.
在大多数大城市地区，一个重大困难是缺乏处理废物的土地。根据联合国世界人口展望，大约54%的人口居住在城市地区，预计到2050年将上升到66%。到2050年，印度预计将增加4.04亿城市居民。人口增长的大幅增加导致了大量废物的产生。大海得拉巴市政公司(GHMC)每天产生5000吨城市固体废物。在许多地方，产生的固体废物被不科学地倾倒在开阔的土地上。因此，有必要优化潜在的废物处置选址。本文主要利用地理信息系统(GIS)和层次分析法(AHP)对GHMC地区城市生活垃圾的潜在处置场地进行了选择。在AHP中，根据相对于彼此的重要性为每个标准分配权重，并根据其影响的大小分配评级。在选址过程中考虑的各种因素被分为环境和经济标准。路网和边坡在经济基础上聚类，水体、敏感场地、地下水位和土地利用在环境基础上聚类。对于所有标准，生成专题地图，然后使用GIS将其与AHP相结合进行选址。T. Srinivasa Rao, I. Naga Babu, Chandana N.基于GIS和AHP的海得拉巴市生活垃圾填埋场选址遥感与地理信息系统学报。2018;9 (1): 15-25p。
{"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}
Pub Date : 2018-03-30DOI: 10.4172/2469-4134.1000236
Abdullah-Al- Faisal, A. Kafy, Sumita Roy
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.
{"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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：