ASSESSMENT OF HYDROPHYSICAL CONDITIONS FOR VISTULA LAGOON BY FIELD DATA AND REMOTE SENSING DATA

2018 ◽  
Author(s):  
Д. Домнин ◽  
D. Domnin ◽  
В. Пилипчук ◽  
V. Pilipchuk
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Field Data ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Measured Data ◽  
Vistula Lagoon ◽  
Large Array ◽  
Data Files ◽  
Time Description

In the study, a large array of data (more than 15 thousand records and 180 full-scale measurements with satellite data files) for the period 1994–2012 (by ABIORAS) was systematized. Comparative analysis of the literary and fullscale satellite data has been executed. Based mainly on the stock of field measurements were made modern space-time description of the water masses in the lagoon (temperature, salinity). The discrepancy between the intra-variation in temperature between the periods 1966–1976 and 1994–2004 were identified. The paper contains a comparison and the subsequent correlation of field and satellite data, defined regularity of temperature exceeding of satellite data over the measured data. Lagoon area is divided into districts.

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.

Satellite Remote Sensing and the Management of Natural Resources

2019 ◽  
Author(s):  
Nathalie Pettorelli
Keyword(s):  
Remote Sensing ◽  
Resource Management ◽  
Natural Resource Management ◽  
Natural Resource ◽  
Satellite Data ◽  
Satellite Remote Sensing ◽  
Habitat Restoration ◽  
Remote Sensing Data ◽  
Ecological Knowledge ◽  
Postgraduate Students

This book intends to familiarise prospective users in the environmental community with satellite remote sensing technology and its applications, introducing terminology and principles behind satellite remote sensing data and analyses. It provides a detailed overview of the possible applications of satellite data in natural resource management, demonstrating how ecological knowledge and satellite-based information can be effectively combined to address a wide array of current natural resource management needs. Topics considered include the use of satellite data to monitor the various dimensions of biodiversity; the use of this technology to track pressures on biodiversity such as invasive species, pollution, and illegal fishing; the utility of satellite remote sensing to inform the management of protected areas, translocation, and habitat restoration; and the contribution of satellite remote sensing towards the monitoring of ecosystem services and wellbeing. The intended audience is ecologists and environmental scientists; the book is targeted as a handbook and is therefore also suitable for advanced undergraduate and postgraduate students in the biological and ecological sciences, as well as policy makers and specialists in the fields of conservation biology, biodiversity monitoring, and natural resource management. The book assumes no prior technical knowledge of satellite remote sensing systems and products. It is written so as to generate interest in the ecological, environmental management, and remote sensing communities, highlighting issues associated with the emergence of truly synergistic approaches between these disciplines.

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).

scholarly journals Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

2014 ◽  
Vol 11 (23) ◽  
pp. 6827-6840 ◽  
Author(s):  
M. Réjou-Méchain ◽  
H. C. Muller-Landau ◽  
M. Detto ◽  
S. C. Thomas ◽  
T. Le Toan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Spatial Scales ◽  
Forest Biomass ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Forest Degradation ◽  
Forest Carbon ◽  
Mitigation Strategies ◽  
Large Plot

Abstract. Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha–1) at spatial scales ranging from 5 to 250 m (0.025–6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20–400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

scholarly journals Thermal Infrared Hyperspectral Imaging for Mineralogy Mapping of a Mine Face

2018 ◽  
Vol 10 (10) ◽  
pp. 1518 ◽  
Author(s):  
Stephane Boubanga-Tombet ◽  
Alexandrine Huot ◽  
Iwan Vitins ◽  
Stefan Heuberger ◽  
Christophe Veuve ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Resolution ◽  
Remote Sensing Data ◽  
Field Measurements ◽  
Thermal Infrared ◽  
Field Studies ◽  
Hyperspectral Data ◽  
Spectral Bands ◽  
Remote Sensing Systems ◽  
Viewing Perspective

Remote sensing systems are largely used in geology for regional mapping of mineralogy and lithology mainly from airborne or spaceborne platforms. Earth observers such as Landsat, ASTER or SPOT are equipped with multispectral sensors, but suffer from relatively poor spectral resolution. By comparison, the existing airborne and spaceborne hyperspectral systems are capable of acquiring imagery from relatively narrow spectral bands, beneficial for detailed analysis of geological remote sensing data. However, for vertical exposures, those platforms are inadequate options since their poor spatial resolutions (metres to tens of metres) and NADIR viewing perspective are unsuitable for detailed field studies. Here, we have demonstrated that field-based approaches that incorporate thermal infrared hyperspectral technology with about a 40-nm bandwidth spectral resolution and tens of centimetres of spatial resolution allow for efficient mapping of the mineralogy and lithology of vertical cliff sections. We used the Telops lightweight and compact passive thermal infrared hyperspectral research instrument for field measurements in the Jura Cement carbonate quarry, Switzerland. The obtained hyperspectral data were analysed using temperature emissivity separation algorithms to isolate the different contributions of self-emission and reflection associated with different carbonate minerals. The mineralogical maps derived from measurements were found to be consistent with the expected carbonate results of the quarry mineralogy. Our proposed approach highlights the benefits of this type of field-based lightweight hyperspectral instruments for routine field applications such as in mining, engineering, forestry or archaeology.

scholarly journals Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes

2013 ◽  
Vol 10 (10) ◽  
pp. 6279-6307 ◽  
Author(s):  
E. Boegh ◽  
R. Houborg ◽  
J. Bienkowski ◽  
C. F. Braban ◽  
T. Dalgaard ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Field Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Leaf Nitrogen ◽  
Agricultural Landscapes ◽  
Nitrogen Pools ◽  
Spectral Vegetation Indices

Abstract. Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

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