Pub Date : 2021-05-31DOI: 10.46610/JORSGT.2021.V07I02.001
B. Pasuluri, Radhika Mahankali, J. Manga, C. Rajeshwari
A brief overview of recent trends in Surface Plasmon Resonance (SPR) technology especially for gas sensing is presented. Some novel sensors (metallic grating, MIM, optical fiber) are discussed along with the development of plasmonic nanostructure based on zinc oxide (ZnO) for enhancing sensing application.
{"title":"A STUDY ON ENHANCED GAS SENSING APPLICATION THROUGH SPR SENSORS AND PLASMONIC ZNO NANOSTRUCTURE","authors":"B. Pasuluri, Radhika Mahankali, J. Manga, C. Rajeshwari","doi":"10.46610/JORSGT.2021.V07I02.001","DOIUrl":"https://doi.org/10.46610/JORSGT.2021.V07I02.001","url":null,"abstract":"A brief overview of recent trends in Surface Plasmon Resonance (SPR) technology especially for gas sensing is presented. Some novel sensors (metallic grating, MIM, optical fiber) are discussed along with the development of plasmonic nanostructure based on zinc oxide (ZnO) for enhancing sensing application.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130400638","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}
C. Armenta-Déu, Félix Jesús de-Segura-Muñoz, Francisco Javier Domínguez-Bravo
In this work, we develop a new modelling process to optimize the PV installation layout on industrial building rooftops; the model searches for maximizing the number of installed PV panels in a defined spot area, characterized by its shape, size, tilt and orientation. The study focuses on areas of latitude between tropics, but is useful for other latitudes. The method is applied to an industrial conglomerate of reference, made up of 34 industries, whose geographical characteristics have been provided by the GIS technique. The proposed model reduces the area of the spot to a very small size (5m x 5m), thanks to the use of the GIS tools, thus increasing the precision of results and making the solution more reliable. The accuracy of the method is over 98.5%. The model takes into account not only the shape and size of the PV panel but also the tilt angle. The model predicts the number of panels as a function of the tilt angle of the panel and the azimuth of the rooftop. The modelling process has allowed obtaining the surface coverage factor of the PV layout for panels facing to the Equator in rooftops with a specific azimuth. The results of the modelling shows that coverage factor increases with the rooftop’s azimuth, having a minimum value of 75% for a rooftop azimuth of 45o and a maximum of 92% for angles of 5o and 85o.
在这项工作中，我们开发了一种新的建模过程来优化工业建筑屋顶上的光伏安装布局;该模型在确定的点区域内搜索安装PV板的数量最大化，其特征是其形状、大小、倾斜和方向。这项研究主要集中在热带之间的纬度地区，但对其他纬度地区也有用。该方法应用于一个由34个行业组成的工业集团，该工业集团的地理特征已由GIS技术提供。由于使用了GIS工具，所提出的模型将现场面积减小到非常小的尺寸(5m x 5m)，从而提高了结果的精度，使解决方案更加可靠。该方法的准确度在98.5%以上。该模型不仅考虑了光伏板的形状和尺寸，还考虑了倾斜角度。该模型预测面板的数量作为面板倾斜角和屋顶方位角的函数。建模过程允许获得面向赤道的面板在特定方位的屋顶上的PV布局的表面覆盖系数。建模结果表明，覆盖系数随屋顶方位角的增加而增加，当屋顶方位角为45度时，覆盖系数最小值为75%，当屋顶方位角为50度和850度时，覆盖系数最大值为92%。
{"title":"Rooftop layout optimization for PV installation using GIS","authors":"C. Armenta-Déu, Félix Jesús de-Segura-Muñoz, Francisco Javier Domínguez-Bravo","doi":"10.37591/.v12i1.1084","DOIUrl":"https://doi.org/10.37591/.v12i1.1084","url":null,"abstract":"In this work, we develop a new modelling process to optimize the PV installation layout on industrial building rooftops; the model searches for maximizing the number of installed PV panels in a defined spot area, characterized by its shape, size, tilt and orientation. The study focuses on areas of latitude between tropics, but is useful for other latitudes. The method is applied to an industrial conglomerate of reference, made up of 34 industries, whose geographical characteristics have been provided by the GIS technique. The proposed model reduces the area of the spot to a very small size (5m x 5m), thanks to the use of the GIS tools, thus increasing the precision of results and making the solution more reliable. The accuracy of the method is over 98.5%. The model takes into account not only the shape and size of the PV panel but also the tilt angle. The model predicts the number of panels as a function of the tilt angle of the panel and the azimuth of the rooftop. The modelling process has allowed obtaining the surface coverage factor of the PV layout for panels facing to the Equator in rooftops with a specific azimuth. The results of the modelling shows that coverage factor increases with the rooftop’s azimuth, having a minimum value of 75% for a rooftop azimuth of 45o and a maximum of 92% for angles of 5o and 85o.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132210111","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}
C. Armenta-Déu, Félix Jesús Segura-Muñoz, Francisco José Domínguez-Bravo
Present work studies the energy supply from photovoltaic (PV) installations in industrial conglomerates using the rooftops as a surface to install the PV panels. The study is based on a modelling procedure that takes into account the specific characteristics of the rooftop, shape, size, azimuth and inclination, using GIS tools to identify these parameters for every single rooftop. Modelling has been developed modifying the tilt angle of the PV panel for vertical and horizontal PV panel layout and analyzing which one of the two configurations generates more energy. The study has been extended for tilt angles from the horizontal plane to the latitude of the location. The methodology uses a previous study in determining the optimum number of PV panels that can be placed on the rooftop. Shading effects have been taken into account for energy supply calculation, resulting in a variation with the tilt angle of the PV panel that depends on the range of the tilt angle; three ranges have been identified, low (0≤β/ϕ≤0.3), medium (0.3≤β/ϕ≤0.8)and high (0.8≤β/ϕ≤1). Maximum variation, 1.6%, has been observed in the low range, while for the high range energy supply does not seem there is no blocking to depend on the tilt angle. The results show that the modelling matches theoretical predictions within accuracy higher than 99.4%. Modelling has also been developed for two different configurations of the PV panel positioning, vertical and horizontal. Tests have been applied to the largest and smallest rooftop; the similar trend in the evolution and the close values of the energy supply with tilt angle proves that the methodology can be applied to any of the industrial building rooftops. The results of the modelling show that there is no much difference between the two configurations; however, horizontal configuration works better for larger areas while vertical one is more suitable for smaller areas. Additional row has been added to the layout provided the shadow is out of rooftop bounds. The increase of the energy is not very relevant, barely 1% for the vertical configuration and 0.2% for the horizontal one.
{"title":"Application of GIS tools to the improvement of energy supply in PV rooftop installations","authors":"C. Armenta-Déu, Félix Jesús Segura-Muñoz, Francisco José Domínguez-Bravo","doi":"10.37591/.v12i1.1088","DOIUrl":"https://doi.org/10.37591/.v12i1.1088","url":null,"abstract":"Present work studies the energy supply from photovoltaic (PV) installations in industrial conglomerates using the rooftops as a surface to install the PV panels. The study is based on a modelling procedure that takes into account the specific characteristics of the rooftop, shape, size, azimuth and inclination, using GIS tools to identify these parameters for every single rooftop. Modelling has been developed modifying the tilt angle of the PV panel for vertical and horizontal PV panel layout and analyzing which one of the two configurations generates more energy. The study has been extended for tilt angles from the horizontal plane to the latitude of the location. The methodology uses a previous study in determining the optimum number of PV panels that can be placed on the rooftop. Shading effects have been taken into account for energy supply calculation, resulting in a variation with the tilt angle of the PV panel that depends on the range of the tilt angle; three ranges have been identified, low (0≤β/ϕ≤0.3), medium (0.3≤β/ϕ≤0.8)and high (0.8≤β/ϕ≤1). Maximum variation, 1.6%, has been observed in the low range, while for the high range energy supply does not seem there is no blocking to depend on the tilt angle. The results show that the modelling matches theoretical predictions within accuracy higher than 99.4%. Modelling has also been developed for two different configurations of the PV panel positioning, vertical and horizontal. Tests have been applied to the largest and smallest rooftop; the similar trend in the evolution and the close values of the energy supply with tilt angle proves that the methodology can be applied to any of the industrial building rooftops. The results of the modelling show that there is no much difference between the two configurations; however, horizontal configuration works better for larger areas while vertical one is more suitable for smaller areas. Additional row has been added to the layout provided the shadow is out of rooftop bounds. The increase of the energy is not very relevant, barely 1% for the vertical configuration and 0.2% for the horizontal one.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126926803","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 : 2021-03-24DOI: 10.46610/JORSGT.2021.V07I01.002
P. Phutane, Alok Kumar Tuddu, Snehal J. Waghmare, Nishigandha M. Jagtap
One of the major problems facing developing countries is the safety of vehicles from theft. Hence, we created a prototype model of a fingerprint-based protection system for Electric Bike by combining the Fingerprint sensor module R307 with the Arduino Uno as a solution to the aforementioned problem. This vehicle's biometric system captures an image of the owner's finger, converts it to binary, and stores it in a database. When the motorist places his or her finger on the fingerprint module R307, the device compares its image to the image stored in the database, and if the two are identical, the vehicle's ignition system will turn on. Our primary aim in creating the project is to give users direct access to the system, enabling them to get started quickly and with a clear process that allows us to fully comprehend the system.
{"title":"Ignition of Electric Bike Using Fingerprint Sensor","authors":"P. Phutane, Alok Kumar Tuddu, Snehal J. Waghmare, Nishigandha M. Jagtap","doi":"10.46610/JORSGT.2021.V07I01.002","DOIUrl":"https://doi.org/10.46610/JORSGT.2021.V07I01.002","url":null,"abstract":"One of the major problems facing developing countries is the safety of vehicles from theft. Hence, we created a prototype model of a fingerprint-based protection system for Electric Bike by combining the Fingerprint sensor module R307 with the Arduino Uno as a solution to the aforementioned problem. This vehicle's biometric system captures an image of the owner's finger, converts it to binary, and stores it in a database. When the motorist places his or her finger on the fingerprint module R307, the device compares its image to the image stored in the database, and if the two are identical, the vehicle's ignition system will turn on. Our primary aim in creating the project is to give users direct access to the system, enabling them to get started quickly and with a clear process that allows us to fully comprehend the system.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130325821","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}
Reservoirs are storage structures for water and are useful for irrigation, navigation, hydroelectric power, water supply for drinking, flood control, etc. But reservoir sedimentation is the gradual accumulation of the incoming sediment load from rivers and causes serious problem on the environment, flood management, economy and the long term efficiency of reservoirs also gets reduced. So, we have to aware of these critical complications and for that the causes of sedimentation, calculation of existing sedimentation volume, estimation of possibilities of sediment increment in future and remedial measures are some of considerable key parameters in reservoir sustainability. From the literature collection, some of important models and techniques are discussed for prediction of reservoir sedimentation in this review paper.
{"title":"Prediction of Reservoir Sedimentation: A Review","authors":"V. Murthy, B. Vijayasaradhi","doi":"10.37591/.V11I3.1068","DOIUrl":"https://doi.org/10.37591/.V11I3.1068","url":null,"abstract":"Reservoirs are storage structures for water and are useful for irrigation, navigation, hydroelectric power, water supply for drinking, flood control, etc. But reservoir sedimentation is the gradual accumulation of the incoming sediment load from rivers and causes serious problem on the environment, flood management, economy and the long term efficiency of reservoirs also gets reduced. So, we have to aware of these critical complications and for that the causes of sedimentation, calculation of existing sedimentation volume, estimation of possibilities of sediment increment in future and remedial measures are some of considerable key parameters in reservoir sustainability. From the literature collection, some of important models and techniques are discussed for prediction of reservoir sedimentation in this review paper.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"121 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128358904","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}
Information on crop acreage statistics and distribution of crops in different districts is required for planning and implementation of various government schemes. Further, information is also required on kharif fallow areas to enhance the cropping intensity. Therefore, in this context acreage assessment in different agriculture seasons i.e., kharif, rabi and zaid has been carried out in Jharkhand State using Landsat-8 OLI remote sensing data. Estimation was carried out for the year 2015–16, 2016–17 and 2017–18. Gross cropped area in the State varied from 19526 Sq.km. in the year 2015–16 to 24089 sq.km. in the year 2017–18. The Gross cropped area and Net Sown Area was highest in Ranchi and West Singhbhum districts in different years. District-wise analysis of kharif fallow showed highest area in West Singhbhum district. Further, suitability analysis for pulses and other appropriate crops needs to be carried out to convert the post fallow kharif areas to double crop areas and more than two crop areas to increase the cropping intensity.
{"title":"Crop Acreage Estimation in Jharkhand using Multi-temporal Satellite Data","authors":"N. Sharma, N. J. Kullu, Chandni Purty","doi":"10.37591/.V11I3.1065","DOIUrl":"https://doi.org/10.37591/.V11I3.1065","url":null,"abstract":"Information on crop acreage statistics and distribution of crops in different districts is required for planning and implementation of various government schemes. Further, information is also required on kharif fallow areas to enhance the cropping intensity. Therefore, in this context acreage assessment in different agriculture seasons i.e., kharif, rabi and zaid has been carried out in Jharkhand State using Landsat-8 OLI remote sensing data. Estimation was carried out for the year 2015–16, 2016–17 and 2017–18. Gross cropped area in the State varied from 19526 Sq.km. in the year 2015–16 to 24089 sq.km. in the year 2017–18. The Gross cropped area and Net Sown Area was highest in Ranchi and West Singhbhum districts in different years. District-wise analysis of kharif fallow showed highest area in West Singhbhum district. Further, suitability analysis for pulses and other appropriate crops needs to be carried out to convert the post fallow kharif areas to double crop areas and more than two crop areas to increase the cropping intensity.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130051913","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 all-time imaging ability of SAR systems which can penetrate cloud cover and free availability of Sentinel C-Band data are very useful in deriving critical spatial information for flood disaster management in tropical areas such as Malawi. This study shows how Sentinel-1 data has been used to map flood extents by utilizing VH and VV polarizations and enhance risk mapping during the years 2015 to 2020 in Nsanje district. Multi-dated Sentinel-1 images were acquired, pre-processed, and analyzed through Change Detection and Thresholding technique to interpret backscattered radiation thereby distinguishing flooded and non-flooded areas. The VV Polarization result shows that percentage of land that remained under flood water in Nsanje district was 3.97% in 2015, 5.91% in 2019 and 2.05% in 2020. On the other hand, VH Polarization result shows about 7.71% and 2.02% of land remained under flood water in 2019 and 2020 respectively.Sentinel-2 pre-flood image was used to determine major land cover classes in the district. MNDWI derived from Landsat 8 imagery of the same date as 2019 Sentinel-1 crisis imagery was used for flood extent validation. Overall Accuracy of flood extent delineation was 96% and 90% for VH and VV polarization respectively. Flooding frequency in specific areas was observed to determine physical vulnerability and hence figure out the risk to a possible repetition of flood disaster. Further, social data were used to aid a better understanding of the capacity to cope with a possible flood hazard in the study area.
{"title":"Mapping Flood Risk of Nsanje District in Malawi Using Sentinel-1 Data","authors":"S. Gondwe, Shital H. Shukla","doi":"10.37591/.V11I3.1066","DOIUrl":"https://doi.org/10.37591/.V11I3.1066","url":null,"abstract":"The all-time imaging ability of SAR systems which can penetrate cloud cover and free availability of Sentinel C-Band data are very useful in deriving critical spatial information for flood disaster management in tropical areas such as Malawi. This study shows how Sentinel-1 data has been used to map flood extents by utilizing VH and VV polarizations and enhance risk mapping during the years 2015 to 2020 in Nsanje district. Multi-dated Sentinel-1 images were acquired, pre-processed, and analyzed through Change Detection and Thresholding technique to interpret backscattered radiation thereby distinguishing flooded and non-flooded areas. The VV Polarization result shows that percentage of land that remained under flood water in Nsanje district was 3.97% in 2015, 5.91% in 2019 and 2.05% in 2020. On the other hand, VH Polarization result shows about 7.71% and 2.02% of land remained under flood water in 2019 and 2020 respectively.Sentinel-2 pre-flood image was used to determine major land cover classes in the district. MNDWI derived from Landsat 8 imagery of the same date as 2019 Sentinel-1 crisis imagery was used for flood extent validation. Overall Accuracy of flood extent delineation was 96% and 90% for VH and VV polarization respectively. Flooding frequency in specific areas was observed to determine physical vulnerability and hence figure out the risk to a possible repetition of flood disaster. Further, social data were used to aid a better understanding of the capacity to cope with a possible flood hazard in the study area.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115516212","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}
Developing Countries like India has more than half of the population engaged in fishery, agriculture etc. and agriculture drives the economy of the Nation. Traditional survey methods are tedious and time consuming, however, with advancement in Remote Sensing Technology data for Agriculture monitoring can be obtained at local and regional scale. The present study demonstrates the use of multi-year multi-date Sentinel-2 MSI data for winter crop monitoring in in Visnagar taluka Mahesansa district of Gujarat state. Multi-temporal Sentinel-2 data covering study area for the winter crop period from November-2018 to March-2019 was downloaded from https://earthexplorer.usgs.gov/ .The major objective of this study was to monitor site-specific crop growth in different villages of Visnagar Taluka by generating Normalized Difference Vegetation Index (NDVI) profiles of major winter crops. The spectral behavior of wheat, mustard, Fennel and castor crops during active growth stages was studied. The results indicated that different winter crops can be discriminated using the data during the early growth phases like flag-leaf emergence to flowering stages of these crops. Even it was observed that the spectral response of normal-sown and late-sown wheat crop have quite distinct spectral behavior as compared to other winter crops. In this study, the NDVI profiles of different winter crops indicated that Last week of January to first week of February, when all the winter crops were at grand growth stages of grain filling and grain-milk, pod formation (mustard & castor) stages have similar NDVI values, therefore during this period major winter crops in this region may not be possible to discriminate using single date satellite data.
{"title":"Spectral Response of Winter Crops Using Multi-temporal Sentinel-2 MSI Data in Visnagar Taluka, Gujarat State","authors":"Das Jay Sapan, Shital H. Shukla, M. Kalubarme","doi":"10.37591/.V11I3.1069","DOIUrl":"https://doi.org/10.37591/.V11I3.1069","url":null,"abstract":"Developing Countries like India has more than half of the population engaged in fishery, agriculture etc. and agriculture drives the economy of the Nation. Traditional survey methods are tedious and time consuming, however, with advancement in Remote Sensing Technology data for Agriculture monitoring can be obtained at local and regional scale. The present study demonstrates the use of multi-year multi-date Sentinel-2 MSI data for winter crop monitoring in in Visnagar taluka Mahesansa district of Gujarat state. Multi-temporal Sentinel-2 data covering study area for the winter crop period from November-2018 to March-2019 was downloaded from https://earthexplorer.usgs.gov/ .The major objective of this study was to monitor site-specific crop growth in different villages of Visnagar Taluka by generating Normalized Difference Vegetation Index (NDVI) profiles of major winter crops. The spectral behavior of wheat, mustard, Fennel and castor crops during active growth stages was studied. The results indicated that different winter crops can be discriminated using the data during the early growth phases like flag-leaf emergence to flowering stages of these crops. Even it was observed that the spectral response of normal-sown and late-sown wheat crop have quite distinct spectral behavior as compared to other winter crops. In this study, the NDVI profiles of different winter crops indicated that Last week of January to first week of February, when all the winter crops were at grand growth stages of grain filling and grain-milk, pod formation (mustard & castor) stages have similar NDVI values, therefore during this period major winter crops in this region may not be possible to discriminate using single date satellite data.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122323874","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}
Sylhet Sadar suffers from excessive rainfall causing the enormous soil loss in this area. C-factor is one of the most important parameter of the Universal Soil Loss Equation (USLE) and revised version of USLE for estimating soil loss. The current study was conducted for determining the crop management factor (C) using remote sensing (RS) and geographical information system (GIS) tools. Satellite images (Landsat 7 ETM+ of 2000, 2010 and Landsat 8 OLI-TIRS of 2020) of the study area were analyzed using ArcGIS 10.5 and ENVI 5.1 software to generate maps for land use and land cover (LULC), normalized differential vegetative index (NDVI) and crop management factor (C). Results showed that the percentage of each LULC classes from 2000 to 2020 was changed over time. There was rapid growth in crop land, water bodies and settlement areas between 2000 and 2020 while the same period observed lessening in vegetation coverage. The relationship between C-factor and vegetation indices such as NDVI was identified. As NDVI and C-factor values are correlated, both lowest and highest NDVI (-0.506–0.629) and C-factor value (0.185–0.753) was found at the same year (2000). By the next 20 years in 2020, the highest NDVI value reduced to 0.373 and lowest C-factor value increased to 0.314 indicates that vegetation coverage of the study area is decreasing. To ensure proper soil management it is therefore imperative to encourage forest regeneration activities, tree planting exercises, crop rotation, conservation tillage practices and shrub growth schemes.
{"title":"Mapping of Crop Management Factor (C) for Sylhet Sadar using Remote Sensing and GIS","authors":"A. G. Polash, M. Islam","doi":"10.37591/.V11I3.1067","DOIUrl":"https://doi.org/10.37591/.V11I3.1067","url":null,"abstract":"Sylhet Sadar suffers from excessive rainfall causing the enormous soil loss in this area. C-factor is one of the most important parameter of the Universal Soil Loss Equation (USLE) and revised version of USLE for estimating soil loss. The current study was conducted for determining the crop management factor (C) using remote sensing (RS) and geographical information system (GIS) tools. Satellite images (Landsat 7 ETM+ of 2000, 2010 and Landsat 8 OLI-TIRS of 2020) of the study area were analyzed using ArcGIS 10.5 and ENVI 5.1 software to generate maps for land use and land cover (LULC), normalized differential vegetative index (NDVI) and crop management factor (C). Results showed that the percentage of each LULC classes from 2000 to 2020 was changed over time. There was rapid growth in crop land, water bodies and settlement areas between 2000 and 2020 while the same period observed lessening in vegetation coverage. The relationship between C-factor and vegetation indices such as NDVI was identified. As NDVI and C-factor values are correlated, both lowest and highest NDVI (-0.506–0.629) and C-factor value (0.185–0.753) was found at the same year (2000). By the next 20 years in 2020, the highest NDVI value reduced to 0.373 and lowest C-factor value increased to 0.314 indicates that vegetation coverage of the study area is decreasing. To ensure proper soil management it is therefore imperative to encourage forest regeneration activities, tree planting exercises, crop rotation, conservation tillage practices and shrub growth schemes.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115840481","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 : 2020-11-19DOI: 10.46610/jorsgt.2020.v06i03.003
S. Soundarya, M. Nandhini, E. Ramakohila, R. Gowsalya
{"title":"A Review of Hyper Spectral Imaging Techniques for The Quality Assessment of Fish","authors":"S. Soundarya, M. Nandhini, E. Ramakohila, R. Gowsalya","doi":"10.46610/jorsgt.2020.v06i03.003","DOIUrl":"https://doi.org/10.46610/jorsgt.2020.v06i03.003","url":null,"abstract":"","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124800629","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}
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