Evaluation of Capacity of Salandi Reservoir Using Remote Sensing Data Along With Qgis Software

2018 ◽  
Vol 6 (8) ◽  
pp. 339
Author(s):  
Rupali Dhal ◽  
D. P. Satapathy
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Project Work ◽  
Space Technology ◽  
Reservoir Water ◽  
Sediment Distribution ◽  
Sensing Data ◽  
Spread Area ◽  
Water Spread

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.

Application of geoinformation technologies for arranging a satellite monitoring system

2019 ◽  
Vol 943 (1) ◽  
pp. 110-118
Author(s):  
A.A. Kadochnikov
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Web Gis ◽  
Nature Management ◽  
Satellite Monitoring ◽  
Technological Support ◽  
Sensing Data ◽  
Territorial Planning ◽  
Operational Information

Today, remote sensing data are an important source of operational information about the environment for thematic GIS, this data can be used for the development of water, forestry and agriculture management, in the ecology and nature management, with territorial planning, etc. To solve the problem of ensuring the effective use of the space activities’results in the Krasnoyarsk Territory a United Regional Remote Sensing Center was created. On the basis of the Center, a new satellite receiving complex of FRC KSC SB RAS was put into operation. It is currently receiving satellite data from TERRA, AQUA, Suomi NPP and FENG-YUN satellites. Within the framework in cooperation with the Siberian Regional Center for Remote Sensing the Earth, an archive of satellite data from domestic Resource-P and Meteor-M2 satellites was created. The work considers some features of softwaredevelopment and technological support tools for loading, processing and publishing remote sensing data. The product is created in the service-oriented paradigm based on geoportal technologies and interactive web-cartography. The focus in this article is paid to the peculiarities of implementing the software components of the web GIS, the efficient processing and presentation of geospatial data.

scholarly journals Risk management support through India Remote Sensing Satellites

2014 ◽  
Vol XL-8 ◽  
pp. 1-6
Author(s):  
N. Aparna ◽  
A. V. Ramani ◽  
R. Nagaraja
Keyword(s):  
Remote Sensing ◽  
Risk Management ◽  
Satellite Data ◽  
Global Climate ◽  
Remote Sensing Data ◽  
Temporal Variations ◽  
Geographical Information ◽  
Indian Remote Sensing ◽  
Management Support ◽  
Sensing Data

Remote Sensing along with Geographical Information System (GIS) has been proven as a very important tools for the monitoring of the Earth resources and the detection of its temporal variations. A variety of operational National applications in the fields of Crop yield estimation , flood monitoring, forest fire detection, landslide and land cover variations were shown in the last 25 years using the Remote Sensing data. The technology has proven very useful for risk management like by mapping of flood inundated areas identifying of escape routes and for identifying the locations of temporary housing or a-posteriori evaluation of damaged areas etc. The demand and need for Remote Sensing satellite data for such applications has increased tremendously. This can be attributed to the technology adaptation and also the happening of disasters due to the global climate changes or the urbanization. However, the real-time utilization of remote sensing data for emergency situations is still a difficult task because of the lack of a dedicated system (constellation) of satellites providing a day-to-day revisit of any area on the globe. The need of the day is to provide satellite data with the shortest delay. Tasking the satellite to product dissemination to the user is to be done in few hours. Indian Remote Sensing satellites with a range of resolutions from 1 km to 1 m has been supporting disasters both National & International. In this paper, an attempt has been made to describe the expected performance and limitations of the Indian Remote Sensing Satellites available for risk management applications, as well as an analysis of future systems Cartosat-2D, 2E ,Resourcesat-2R &RISAT-1A. This paper also attempts to describe the criteria of satellite selection for programming for the purpose of risk management with a special emphasis on planning RISAT-1(SAR sensor).

Remote Sensing Prospecting Deposit Model Using Aster Data: A Case Study from Southern Part of Taxkorgan Tajik Autonomous County, China

2015 ◽  
Vol 733 ◽  
pp. 124-129
Author(s):  
Hui Zhi Wu ◽  
Qi Gang Jiang ◽  
Chao Jun Bai
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Mineral Exploration ◽  
Information Source ◽  
Remote Sensing Data ◽  
Screening Methods ◽  
Data Sets ◽  
Sensing Data ◽  
Work Area ◽  
Geological Conditions

This work uses multiple types of remote sensing data to develop a model-based mineral exploration method. Data used include Worldview-2 satellite data as the main information source supplemented by QuickBird satellite data to assist in geological interpretations and ASTER satellite data to extract remote sensing anomalies. We have enhanced the spectral and spatial resolution of the remote sensing data using ENVI software. Human-computer interaction methods have been used to confirm the geological conditions. We have interpreted 24 distinct lithologic units, including various types of metamorphic and sedimentary rocks. A total of 471 remote sensing anomalies were delineated, consisting of 173 hydroxyl anomalies and 298 iron-staining anomalies. Geological background screening methods were applied to identify 98 remote sensing anomalies, of which 29 were recommended for further study. Based on the interpretation of anomalies extracted from the ASTER and other geological remote sensing data sets, we have established a typical-deposit prospecting model. In the model, we delineated remote sensing prospecting targets by considering: remote sensing anomalies, geologic bodies and structures, geophysical anomalies and geochemical anomalies. Using this model, we divided the work area into two zones based on types of mineral generation. Seven prospecting targets (one A class, three B class and three C class) were identified. Trenching and block sorting methods were conducted for field verification, and resulted in the discovery of two copper and two iron occurrences with commercial potential.

Design and Development of EOS/MODIS Satellite Data Automatic Download Robot

2013 ◽  
Vol 423-426 ◽  
pp. 2737-2741
Author(s):  
Dan Yang Cao ◽  
Kang Ning Xu ◽  
Zhi Yan Wang ◽  
Ji Wu Ma
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Design And Development ◽  
Sensing Data ◽  
Reliable Performance ◽  
Eos Modis

With the development and advancement of technology, remote sensing data of MODIS satellite become more precise, loved and applied by relevant researchers widely. This software enables remote sensing data of EOS/MODIS satellite's automated ordering and address of FTP resource's accessing, providing convenience for users. Currently, the software with stable and reliable performance, is robust, fully automated, and can provide services to all kinds of users of remote sensing data of MODIS satellite.

scholarly journals Remote radiological assessment in the marine environment: A pilot study based on Cs-137 measurements and satellite observations in the Aegean Sea

2019 ◽  
Vol 24 ◽  
pp. 191
Author(s):  
G. Mavrokefalou ◽  
H. Florou ◽  
O. Sykioti
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Satellite Data ◽  
Sea Water ◽  
Remote Sensing Data ◽  
Aegean Sea ◽  
137Cs Activity ◽  
Sea Surface ◽  
Sensing Data ◽  
Activity Concentrations

A program concept has been developed to utilize sea parameters like sea surface temperature (SST), ocean colour (OC) and sea surface salinity (SSS), in order to explore their potential relations with 137Cs activity concentrations in sea water. These relations are expected to lead to the creation of an innovative tool based on remote sensing data and in real time 137Cs measurements, for the remote radioactivity detection of the Greek marine ecosystem both for routine control and emergency recordings. The presented results are a preliminary effort of the tool’s development. Remote sensing data have been acquired from MIRAS and MODIS instruments on-board ESA-SMOS and NASA-TERRA/AQUA satellites respectively. Satellite data comprise of SST and OC measurements. The ERL’s data of 137Cs activity concentrations (204 measurements) in seawater have been used for the period March 2012 to February 2015. Therefore, a) map analyses in a GIS including interpolation and integration of 83 real time measurements corrected with the effective half live of 7.2 y according to the monthly data of satelites and spatial linear regression have been implemented for the Aegean Sea, b) additional temporal analyses using linear and polynomial regression have been performed for the area of Souda- Crete, for which the most frequent measurements of 137Cs activity concentration in sea water have been measured in ERL. In this study, the first derived results on the correlation between SST measurements with 137Cs activity concentrations are presented, whereas the respective correlation with OC is being under invstigation. Further investigations include multivariate polynomial analyses into the Geographic Information System (GIS) platform with more extensive sampling and satellite data from new systems, whereas comparative correlations of 137Cs with seawater parameters derived by conventional means will be performed.

scholarly journals MULTI-SOURCED, REMOTE SENSING DATA IN LEVEES MONITORING: CASE STUDY OF SAFEDAM PROJECT

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 101-108
Author(s):  
K. Bakuła ◽  
D. Zelaya Wziątek ◽  
B. Weintrit ◽  
M. Jędryka ◽  
T. Ryfa ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Flood Hazard ◽  
Multicriteria Analysis ◽  
Remote Sensing Data ◽  
Monitoring And Evaluation ◽  
Source Information ◽  
Sensing Data ◽  
Data Usage ◽  
Levee Failure

<p><strong>Abstract.</strong> In the following study, the authors present the development of a created levee monitoring system &amp;ndash; a supplement to the existing programs of flood protection providing flood hazard and risk maps in Poland. The system integrates multi-source information about levees, acquiring and analysing various types of remote sensing data, such as the photogrammetric and LiDAR data obtained from Unmanned Aerial Vehicles, optical and radar satellite data. These datasets are used in order to assess the levee failure risk resulting from their condition starting from a general inspection using satellite data and concluding with UAV data usage in a detailed semiautomatic inventory. Finally, the weakest parts of a levee can be defined to create reliable flood hazard maps in case of levee failure, thus facilitating the constant monitoring of the water level between water gauges. The presented system is an example of a multisource data integration, which by the complementation of each system, provides a powerful tool for levee monitoring and evaluation. In this paper, the authors present a scope of the preventative configuration of the SAFEDAM system and the possible products of remote sensing data processing as the result of a hierarchical methodology of remote sensing data usage, thus leading to a multicriteria analysis defining the danger associated with the risk of levee failure.</p>

scholarly journals Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

2017 ◽  
Vol 21 (12) ◽  
pp. 6235-6251 ◽  
Author(s):  
Guiomar Ruiz-Pérez ◽  
Julian Koch ◽  
Salvatore Manfreda ◽  
Kelly Caylor ◽  
Félix Francés
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Vegetation Dynamics ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Sub Saharan Africa ◽  
Automatic Calibration ◽  
Calibration And Validation ◽  
Sensing Data ◽  
Spatio Temporal

Abstract. Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment – the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

scholarly journals DROUGHT AND FINE FUEL MOISTURE CODE EVALUATION: AN EARLY WARNING SYSTEM FOR FOREST/LAND FIRE USING REMOTE SENSING APPROACH

2014 ◽  
Vol 9 (2) ◽  
Author(s):  
Yenni Vetrita ◽  
Indah Prasasti ◽  
Nanik Suryo Haryani ◽  
M Priyatna ◽  
M Rokhis Khomarudin
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Early Warning ◽  
Warning System ◽  
Remote Sensing Data ◽  
Observation Data ◽  
Fuel Moisture ◽  
Forest Land ◽  
Sensing Data ◽  
Two Parameters

This study evaluated two parameters of fire danger rating system (FDRS) using remote sensing data i.e. drought code (DC) and fine fuel moisture code (FFMC) as an early warning program for forest/land fire in Indonesia. Using the reference DC and FFMC from observation data, we calculated the accuracy, bias, and error. The results showed that FFMC from satellite data had a fairly good correlation with FFMC observations (r=0.68, bias=7.6, and RMSE=15.7), while DC from satellite data had a better correlation with FFMC observations (r=0.88, bias=49.91, and RMSE=80.22). Both FFMC and DC from satellite and observation were comparable. Nevertheless, FFMC and DC satellite data showed an overestimation values than that observation data, particularly during dry season. This study also indicated that DC and FFMC could describe fire occurrence within a period of 3 months before fire occur, particularly for DC. These results demonstrated that remote sensing data can be used for monitoring and early warning fire in Indonesia.

scholarly journals Application of Remote Sensing, GIS, and GPS Technology on Environment and Earth's Natural Resources Management An Introduction

2007 ◽  
Vol 6 (1) ◽  
pp. 96-117
Author(s):  
N. Nandini ◽  
Aboud S. Jumbe ◽  
Sucharita Tandon ◽  
Sunita N.
Keyword(s):  
Remote Sensing ◽  
Natural Resources ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Crop Monitoring ◽  
Sensing Data ◽  
Data Generator ◽  
Information Updates ◽  
Thematic Information ◽  
Meteorological Satellite

Remote sensing data have been used to derive thematic information of various natural resources and environment.The type and level of information extracted depends on the expertise of the analyst and what he/she is looking for in the data.An application in remote sensing is the practical use to which a series of aerial satellite images are put. The application of remote sensing or earth observation techniques to atmospheric, Earth and environmental sciences can vary according to the final user's requirements.The utilization of remote sensing data can be broadly classified into three categories as a baseline data generator for a variety of environmental resources; as a tool to monitor change detection, Environmental monitoring, and for mapping purposes. Different environmental applications require different frequencies of information updates for monitoring to be effective. Environment phenomena such as weather systems, natural hazards, and other rarely extreme events such as tsunamis; pollution or oceanographic events are very dynamic and rapidly develop over minutes and hours. Therefore for satellite data to be useful in their analysis imaging frequency and data delivery has to be atleast several times a day. At present only low spatial resolution meteorological satellite data can meet this need. Other applications such as crop monitoring require better spatial detail but rates of change occur only over a matter of weeks and therefore image updates need not be more frequent than weekly or monthly. This data can be processed, refined, and managed with the use of advanced tools such as Geographic Information System(GIS) and Geographic Positioning System(GPS).

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