Добірка наукової літератури з теми "Water Remote sensing"

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Статті в журналах з теми "Water Remote sensing"

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Moore, Gerald K. "Remote sensing in hydrology, remote sensing applications." Journal of Hydrology 131, no. 1-4 (February 1992): 388–89. http://dx.doi.org/10.1016/0022-1694(92)90228-n.

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KYO, Masanori. "Under water remote sensing." Journal of the Visualization Society of Japan 10, no. 37 (1990): 81–87. http://dx.doi.org/10.3154/jvs.10.81.

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3

Tang, Qiuhong, Huilin Gao, Hui Lu, and Dennis P. Lettenmaier. "Remote sensing: hydrology." Progress in Physical Geography: Earth and Environment 33, no. 4 (August 2009): 490–509. http://dx.doi.org/10.1177/0309133309346650.

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Satellite remote sensing is a viable source of observations of land surface hydrologic fluxes and state variables, particularly in regions where in situ networks are sparse. Over the last 10 years, the study of land surface hydrology using remote sensing techniques has advanced greatly with the launch of NASA’s Earth Observing System (EOS) and other research satellite platforms, and with the development of more sophisticated retrieval algorithms. Most of the constituent variables in the land surface water balance (eg, precipitation, evapotranspiration, snow and ice, soil moisture, and terrestrial water storage variations) are now observable at varying spatial and temporal resolutions and accuracy via remote sensing. We evaluate the current status of estimates of each of these variables, as well as river discharge, the direct estimation of which is not yet possible. Although most of the constituent variables are observable by remote sensing, attempts to close the surface water budget from remote sensing alone have generally been unsuccessful, suggesting that current generation sensors and platforms are not yet able to provide hydrologically consistent observations of the land surface water budget at any spatial scale.
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Mayani, Kaushikkumar R., and V. M. Patel V. M. Patel. "Relevance of Remote Sensing and GIS in Water Resoureces Engineering." Indian Journal of Applied Research 1, no. 11 (October 1, 2011): 50–51. http://dx.doi.org/10.15373/2249555x/aug2012/17.

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Trochim, E. D., A. Prakash, D. L. Kane, and V. E. Romanovsky. "Remote sensing of water tracks." Earth and Space Science 3, no. 3 (March 2016): 106–22. http://dx.doi.org/10.1002/2015ea000112.

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Zhang, Yunlin, Claudia Giardino, and Linhai Li. "Water Optics and Water Colour Remote Sensing." Remote Sensing 9, no. 8 (August 9, 2017): 818. http://dx.doi.org/10.3390/rs9080818.

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Menenti, M., and G. J. A. Nieuwenhuis. "Remote sensing in the water management practice." Netherlands Journal of Agricultural Science 34, no. 3 (August 1, 1986): 317–28. http://dx.doi.org/10.18174/njas.v34i3.16785.

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In this examination of the use of remote sensing in water management 3 case studies are presented. The first concerned water management in the eastern Netherlands and remote sensing was used to provide evapotranspiration values. The description of the hydrological conditions was markedly improved by combining remote sensing and hydrological model calculations. A case study in Argentina using Greenness Vegetation Index showed how remote sensing can be used to give data on irrigated area and crop type. In the third case study, remote sensing was used to investigate groundwater losses in a desert area in Libya. The use of theoretical and experimental research in remote sensing, remote sensing applications in the Netherlands and remote sensing applications in developing countries are discussed. (Abstract retrieved from CAB Abstracts by CABI’s permission)
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He, Ping, Xueya Chen, Yuanxing Cai, Yue Zhou, and Yan Chen. "Research Progress of Remote Sensing Technology in Lake Water Environment Monitoring in China." International Journal of Engineering and Technology 14, no. 2 (May 2022): 15–18. http://dx.doi.org/10.7763/ijet.2022.v14.1195.

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This paper analyzes the research progress of remote sensing technology in lake water environment monitoring in China in recent years, including the research progress of suspended matter concentration in water, the research progress of bloom characteristics and the research status of chlorophyll concentration A.Although great progress has been made in lake water environment monitoring, the use of remote sensing to capture the spectral characteristics of water remains to be strengthened. It is necessary to improve the lake remote sensing algorithm for long time series and large range.
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Sriharsha, Mr K. V., and Dr N. V. Rao. "Water Management Using Remote Sensing Techniques." CVR Journal of Science & Technology 4, no. 1 (June 1, 2013): 87–92. http://dx.doi.org/10.32377/cvrjst0417.

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Mishra, Deepak, Eurico D’Sa, and Sachidananda Mishra. "Preface: Remote Sensing of Water Resources." Remote Sensing 8, no. 2 (February 4, 2016): 115. http://dx.doi.org/10.3390/rs8020115.

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Дисертації з теми "Water Remote sensing"

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Moon, Alex. "Remote sensing of bathing water quality." Thesis, Middlesex University, 2003. http://eprints.mdx.ac.uk/13422/.

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The European Union (EU) has openly solicited advice on the development of EU bathing water quality policy and made calls for the development of remotely sensed operational real world solutions. This research demonstrates a new approach to estimating water quality using remote sensing and specifically to monitoring bathing water quality by using remote sensing to "flag" failing areas for manual survey. This method meets the environmental demands of the EU, the tourist industry, the water industry and environmental monitoring agencies throughout the world. The results show the genuine potential for a remotely sensed monitoring system that could, with further research, lead to an efficient and effective method of monitoring bathing water quality. These findings are particularly important given the imminent changes in EU Bathing Water policy, an expected increase in monitoring costs (currently estimated by the EU to be 15 million euros for 2001 (EU, 2002)) and the widespread availability of airborne sensors and satellites. Simultaneous water quality and spectral data were collected at Southend-on-Sea pier with a Natural Environment Research Council (NERC) loaned spectroradiometer and water sampling equipment. Simultaneous data enabled the accurate analysis of the relationship between water quality and reflectance, avoiding the normal delays experienced with flown or satellite data. The thesis successfully proposes and investigates a remotely sensed flagging system for bathing water quality monitoring using both statistical and visual analysis to identify optimum wavelengths which identify threshold levels of E.coli, suspended sediments, low pH, nitrates, chlorophyll, faecal coliform and temperature. The findings demonstrate that remote sensing could be used to monitor several of the water quality parameters that are relevant to the EU Bathing Water Directives and, in particular, the monitoring of effluent in bathing waters through the successful identification of high E.coli counts. Through the creation and integration of a localised water quality model, it demonstrates that it is possible to predict when water quality parameters exceed a threshold level through direct remote sensing or through the use of remotely sensed indirect water quality parameters. The success rate of remotely sensed "flagging" of samples above a threshold level was tested and used to yield a "predictor" rating for each parameter. Finally, a spectral physical model was constructed that identifies the parameters, wavelengths and secondary parameters that could be used to flag failing water quality areas. This model could be used to improve monitoring coverage and reduce overall costs. The application of the model, which was based on Case 2 coastal water, to other types of coastal area is suggested as needing further research before it could be widely exploited. Remote sensing information could lead to a greater understanding of the coastal environment and offers potential near real time monitoring, allowing for the first time reactive management of coastal water quality in failing water quality areas. This would provide a solution to many of the issues raised by the EU regarding the current bathing water quality directives and provides the remote sensing community with a practical solution to a real world problem.
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Qi, Jiaguo 1959. "Spectral properties of paddy rice with variable water depth." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277119.

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An experiment was conducted to determine whether the water depth (above soil) and soil type would have any influence on the multispectral reflectances of paddy rice, and their calculated vegetation index values. The results showed that, when vegetation cover was low (below 600 grams of dry biomass per square meter), the near infrared (NIR) reflectances decreased very little with water depth. The same was true for red reflectances, but to a lesser degree. Overall the changes were not significant at 0.05 level of significance when the water depth was increased from 2.5 centimeters to 10 centimeters. When the vegetation cover became higher most NIR and red reflectances did not show a significant decrease with the increase of the water depth, and sometimes they even increased slightly up to a water depth of 6.4 cm. Nevertheless both rice cover and water depth as well as soils played an important role in the reflectance pattern in red and NIR bands. Some index values increased and some decreased depending on water depth and rice cover. Statistical analysis of the data showed that rice multispectral responses were mainly controlled by vegetation and minimally influenced by soil and water depths.
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Taylor, Frances M. "Remote sensing of water leaks from rural aqueducts." Thesis, University of Edinburgh, 2003. http://hdl.handle.net/1842/27514.

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The development of techniques for the detection of water leaks from underground pipelines is seen as a high profile activity by water companies and regulators. This is due to increasing water demands and problems with current leak detection methods. In this thesis optical reflectance and microwave backscatter were used to identify optimal indices for detecting water leaks amongst a variety of different land cover types at different growth stages. Ground-based surveys and modelling techniques were used to establish optimal wavelengths for detection. Results from these studies suggested that in the optical domain visible/middle infrared ratios show potential for leak detection for a wide range of leak types, under a variety of vegetation canopies at different growth stages. Given the sensitivity of L-band radar to moisture, and the ability to separate contributions from canopy and ground surface, it is possible to detect surface water beneath a range of vegetation canopies. The optimal leak detection indices were then used to idenitfy leaks on airborne image data. The available image data was L - band fully polarimetric E-SAR data, and 126 channel HYMAP hyperspectral airborne data which were acquired over an 8km section of the Vrynwy aqueduct (UK), which included a high concentration of leaks. Four of the five leaks were identifiable on the optical image data and none of the leaks were detectable on the microwave data. However the E-SAR data was obtained under unfavourable conditions. The results of both approaches are used to infer limits of detection in terms of season and meteorological conditions for a range of land covers. Preliminary findings suggest that leaks may be optimally detected when canopy height is low, surrounding soil is dry after a period of no rain, and the leak has been present for at least 2 days. The results from this work suggest that remote sensing is both an effective and feasible tool for leak identification.
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Beckett, Heath. "Remote sensing of water stress in fynbos vegetation." Bachelor's thesis, University of Cape Town, 2010. http://hdl.handle.net/11427/25902.

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I aim to determine whether or not remote sensing, through multispectral, satellite and digital photography, is a feasible and accurate method for determining drought stress in Fynbos vegetation. I hypothesize that (1) water stress in fynbos is detectable with the use of a remote sensing index, namely NDVI and (2) that the remotely sensed trends will correlate with ground truth measures of water stress.
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Drayton, Robert S. "The application of remote sensing to water resources." Thesis, Aston University, 1989. http://publications.aston.ac.uk/14269/.

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Techniques are developed for the visual interpretation of drainage features from satellite imagery. The process of interpretation is formalised by the introduction of objective criteria. Problems of assessing the accuracy of maps are recognized, and a method is developed for quantifying the correctness of an interpretation, in which the more important features are given an appropriate weight. A study was made of imagery from a variety of landscapes in Britain and overseas, from which maps of drainage networks were drawn. The accuracy of the mapping was assessed in absolute terms, and also in relation to the geomorphic parameters used in hydrologic models. Results are presented relating the accuracy of interpretation to image quality, subjectivity and the effects of topography. It is concluded that the visual interpretation of satellite imagery gives maps of sufficient accuracy for the preliminary assessment of water resources, and for the estimation of geomorphic parameters. An examination is made of the use of remotely sensed data in hydrologic models. It is proposed that the spectral properties of a scene are holistic, and are therefore more efficient than conventional catchment characteristics. Key hydrologic parameters were identified, and were estimated from streamflow records. The correlation between hydrologic variables and spectral characteristics was examined, and regression models for streamflow were developed, based solely on spectral data. Regression models were also developed using conventional catchment characteristics, whose values were estimated using satellite imagery. It was concluded that models based primarily on variables derived from remotely sensed data give results which are as good as, or better than, models using conventional map data. The holistic properties of remotely sensed data are realised only in undeveloped areas. In developed areas an assessment of current land-use is a more useful indication of hydrologic response.
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Hunter, Peter D. "Remote sensing in shallow lake ecology." Thesis, University of Stirling, 2007. http://hdl.handle.net/1893/365.

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Shallow lakes are an important ecological and socio-economic resource. However, the impact of human pressures, both at the lake and catchment scale, has precipitated a decline in the ecological status of many shallow lakes, both in the UK, and throughout Europe. There is now, as direct consequence, unprecedented interest in the assessment and monitoring of ecological status and trajectory in shallow lakes, not least in response to the European Union Water Framework Directive (2000/60/EC). In this context, the spatially-resolving and panoramic data provided by remote sensing platforms may be of immense value in the construction of effective and efficient strategies for the assessment and monitoring of ecological status in shallow lakes and, moreover, in providing new, spatially-explicit, insights into the function of these ecosystems and how they respond to change. This thesis examined the use of remote sensing data for the assessment of (i) phytoplankton abundance and species composition and (ii) aquatic vegetation distribution and ecophysiological status in shallow lakes with a view to establishing the credence of such an approach and its value in limnological research and monitoring activities. High resolution in-situ and airborne remote sensing data was collected during a 2-year sampling campaign in the shallow lakes of the Norfolk Broads. It was demonstrated that semi-empirical algorithms could be formulated and used to provide accurate and robust estimations of the concentration of chlorophyll-a, even in these optically-complex waters. It was further shown that it was possible to differentiate and quantify the abundance of cyanobacteria using the biomarker pigment C-phycocyanin. The subsequent calibration of the imagery obtained from the airborne reconnaissance missions permitted the construction of diurnal and seasonal regional-scale time-series of phytoplankton dynamics in the Norfolk Broads. This approach was able to deliver unique spatial insights into the migratory behaviour of a potentially-toxic cyanobacterial bloom. It was further shown that remote sensing can be used to map the distribution of aquatic plants in shallow lakes, importantly including the extent of submerged vegetation, which is central to the assessment of ecological status. This research theme was subsequently extended in an exploration of the use of remote sensing for assessing the ecophysiological response of wetland plants to nutrient enrichment. It was shown that remote sensing metrics could be constructed for the quantification of plant vigour. The extrapolation of these techniques enabled spatial heterogeneity in the ecophysiological response of Phragmites australis to lake nutrient enrichment to be characterised and assisted the formulation of a mechanistic explanation for the variation in reedswamp performance in these shallow lakes. It is therefore argued that the spatially synoptic data provided by remote sensing has much to offer the assessment, monitoring and policing of ecological status in shallow lakes and, in particular, for facilitating the development of pan-European scale lake surveillance capabilities for the Water Framework Directive (2000/60/EC). It is also suggested that remote sensing can make a valuable contribution to furthering ecological understanding and, most significantly, in enabling ecosystem processes and functions to be examined at the lake-scale.
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Beltrán-Abaunza, José M. "Remote sensing in optically complex waters : water quality assessment using MERIS data." Doctoral thesis, Stockholms universitet, Institutionen för ekologi, miljö och botanik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-123724.

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This PhD study focusses on the use of MEdium Resolution Imaging Spectrometer (MERIS) data for reliable and quantitative water-quality assessment of optically-complex waters (lake, brackish and coastal waters). The thesis is divided into two parts: A. intercalibration of reflectance measurements in different optically-complex water bodies (Paper I), and validation of various satellite processing algorithms for the coastal zone (Paper II). B. Applications: the use of MERIS data in integrated coastal zone management mostly using Himmerfjärden bay as an example. Himmerfjärden bay is one of the most frequently monitored coastal areas in the world and it is also the recipient of a large urban sewage treatment plant, where a number of full-scale nutrient management experiments have been conducted to evaluate the ecological changes due to changes in nutrient schemes in the sewage plant. Paper I describes the development and assessment of a new hyperspectral handheld radiometer for in situ sampling and validation of remote sensing reflectance.  The instrument is assessed in comparison with readily available radiometers that are commonly used in validation. Paper II has a focus on the validation of level 2 reflectance and water products derived from MERIS data. It highlights the importance of calibration and validation activities, and the current accuracy and limitations of satellite products in the coastal zone.  Bio-optical in situ data is highlighted as one of the key components for assessing the reliability of current and future satellite missions. Besides suspended particulate matter (SPM), the standard MERIS products have shown to be insufficient to assure data quality retrieval for Baltic Sea waters. Alternative processors and methods such as those assessed and developed in this thesis therefore will have to be put in place in order to secure the success of future operational missions, such as Sentinel-3. The two presented manuscripts in the applied part B of the thesis (paper III and IV), showed examples on the combined use of in situ measurements with optical remote sensing to support water quality monitoring programs by using turbidity and suspended particulate matter as coastal indicators (manuscript III). The article also provides  a new turbidity algorithm for the Baltic Sea and a robust and cost-efficient method for research and management.  A novel approach to improve the quality of the satellite-derived products in the coastal zone was demonstrated in manuscript IV. The analysis included, the correction for adjacency effects from land and an improved pixel quality screening.  The thesis provides the first detailed spatio-temporal description of the evolution of phytoplankton blooms in Himmerfjärden bay  using quality-assured MERIS data, thus forwarding our understanding of ecological processes in in Swedish coastal waters. It must be noted that monitoring from space is not a trivial matter in these optically-complex waters dominated by the absorption of coloured dissolved organic matter (CDOM). These types of coastal waters are especially challenging for quantitative assessment from space due to their low reflectance.  Papers III and IV thus also provide tools for a more versatile use in other coastal waters that are not as optically-complex as the highly absorbing Baltic Sea waters. The benefits of the increased spatial-temporal data coverage by optical remote sensing were presented, and also compared to in situ sampling methods (using chlorophyll-a as indicator).

Research funders:

European Space Agency (ESA, contract no.21524/08/I-OL)

NordForsk funding: Nord AquaRemS Ref. no. 80106

NordForsk funding:  NordBaltRemS Ref.no. 42041

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.

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Ali, Khalid A. "PREDICTION OF WATER QUALITY PARAMETERS FROM VIS-NIR RADIOMETRY: USING LAKE ERIE AS A NATURAL LABORATORY FOR ANALYSIS OF CASE 2 WATERS." Kent State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=kent1309980508.

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Koukouli, Mary Elizabeth. "Remote sensing of water vapour in Venus' middle atmosphere." Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:60216894-5d24-431a-99f0-cc8b0709cb30.

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The Pioneer Venus Orbiter Infrared Radiometer and Venera 15 Fourier Transform Spectrometer observations of thermal emission from Venus' middle atmosphere between 10°S and 50°N were used to determine global maps of temperature, cloud optical depth and water vapour abundance. The spectral regions observed include the strong 15 μtm carbon dioxide band and the 45 μm fundamental rotational water band. The main aim of this thesis is to reconcile the water vapour abundance results from these two sets of observations reported in previous studies. New radiative transfer and retrieval models have been developed for this purpose based on new correlated-k absorption tables calculated with up-to-date spectral line data. The H2SO4 cloud opacity and scattering properties have been recalculated from new refractive index data using Mie theory. For the first time these two sets of observations have been analysed using the same retrieval tools. From the Pioneer Venus Orbiter Infrared Radiometer observations we report a high abundance of water vapour in the early afternoon at the equatorial cloud-top region and a strong day-night variability in the cloud-top pressure. From the Venera 15 Fourier Transform Spectrometer observations we report medium local variability in water vapour abundance, with highest values in the near-equatorial region and slight decrease towards the polar region. It is found that serious constraints are placed on the validation of the retrievals by the lack of adequately accurate H2SO4 optical properties data in the shorter wavelengths and by the poor vertical resolution when sensing the complex but interesting cloud region which prohibits its rigorous modelling. The proposed European Space Agency Venus Express mission will carry a number of high resolution infrared and UV instruments that will shed new light to the interesting question of water vapour abundance in Venus' middle atmosphere.
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El-Sheikha, Dial-Deen Mohamed. "Remote sensing of water and nitrogen stress in broccoli." Diss., The University of Arizona, 2003. http://hdl.handle.net/10150/280349.

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Remote sensing is being used in agriculture for crop management. Ground based remote sensing data acquisition system was used for collection of high spatial and temporal resolution data for irrigated broccoli crop. The system was composed of a small cart that ran back and forth on a rail system that was mounted on a linear move irrigation system. The cart was equipped with a sensor that had 4 discrete wavelengths; 550 nm, 660 nm, 720 nm, and 810 nm, and an infrared thermometer, all had 10 nm bandwidth. A global positioning system was used to indicate the cart position. The study consisted of two parts; the first was to evaluate remotely sensed reflectance and indices in broccoli during the growing season, and determine whether remotely sensed indices or standard deviation of indices can distinguish between nitrogen and water stress in broccoli, and the second part of the study was to evaluate remotely sensed indices and standard deviation of remotely sensed indices in broccoli during daily changes in solar zenith angle. Results indicated that nitrogen was detected using Ratio Vegetation index, RVI, Normalized Difference Vegetation Index, NDVI, Canopy Chlorophyll Concentration Index, CCCI, and also using the reflectance in the Near-Infrared, NIR, bands. The Red reflectance band capability of showing stress was not as clear as the previous indices and bands reflectance. The Canopy Chlorophyll Concentration Index, CCCI, was the most successful index. The Crop Water Stress Index was able to detect water stress but it was highly affected by the solar zenith angle change along the day.
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Книги з теми "Water Remote sensing"

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Cazenave, A., N. Champollion, J. Benveniste, and J. Chen, eds. Remote Sensing and Water Resources. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32449-4.

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Bagheri, Sima. Hyperspectral Remote Sensing of Nearshore Water Quality. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-46949-2.

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Schultz, Gert A., and Edwin T. Engman, eds. Remote Sensing in Hydrology and Water Management. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59583-7.

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Lakshmi, Venkat, Douglas Alsdorf, Martha Anderson, Sylvain Biancamaria, Michael Cosh, Jared Entin, George Huffman, et al., eds. Remote Sensing of the Terrestrial Water Cycle. Hoboken, NJ: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118872086.

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Schultz, Gert A. Remote Sensing in Hydrology and Water Management. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000.

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Drayton, Robert Sutherland. The application of remote sensing to water resources. Birmingham: Aston University. Department of Civil Engineering, 1989.

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Huang He xia you he shi yao gan jian ce ji shu yan jiu: Remote sensing monitoring technology for river regime of Yellow river downstream. Beijing Shi: Zhongguo shui li shui dian chu ban she, 2012.

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8

Rango, Albert. Current operational applications of remote sensing in hydrology. Geneva, Switzerland: Secretariat of the World Meteorological Organization, 1999.

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9

Arst, Kh I︠U︡. Optical properties and remote sensing of multicomponental water bodies. Berlin: Springer, 2002.

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Optical properties and remote sensing of multicomponental water bodies. Berlin: Springer, 2003.

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Частини книг з теми "Water Remote sensing"

1

Maliva, Robert, and Thomas Missimer. "Remote Sensing." In Arid Lands Water Evaluation and Management, 435–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29104-3_18.

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Engman, E. T., and R. J. Gurney. "Water quality." In Remote Sensing in Hydrology, 175–92. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-0407-1_9.

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Oki, Taikan, and Pat J. F. Yeh. "Water Resources." In Encyclopedia of Remote Sensing, 903–9. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_193.

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Fetzer, Eric. "Water Vapor." In Encyclopedia of Remote Sensing, 909–11. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_194.

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Durand, Michael. "Surface Water." In Encyclopedia of Remote Sensing, 816–19. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_197.

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Shaban, Amin. "Fundamentals of Satellite Remote Sensing." In Springer Water, 1–14. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15549-9_1.

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7

Weng, Fuzhong. "Cloud Liquid Water." In Encyclopedia of Remote Sensing, 68–70. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_18.

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8

Oki, Taikan, and Pat J. F. Yeh. "Water and Energy Cycles." In Encyclopedia of Remote Sensing, 895–903. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_192.

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9

Engman, E. T., and R. J. Gurney. "Water resources management and monitoring." In Remote Sensing in Hydrology, 193–210. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-0407-1_10.

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Wang, Yeqiao, Shuhua Qi, and Jian Xu. "Multitemporal Remote Sensing for Inland Water Bodies and Wetland Monitoring." In Multitemporal Remote Sensing, 357–71. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47037-5_17.

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Тези доповідей конференцій з теми "Water Remote sensing"

1

Toll, David L., Kristi Arsenault, Paul Houser, Jared Entin, Brian Cosgrove, Christa Peters-Lidard, and Matthew Rodell. "Terrestrial water and energy systems for water resource applications." In Remote Sensing, edited by Roland Meynart, Steven P. Neeck, Haruhisa Shimoda, Joan B. Lurie, and Michelle L. Aten. SPIE, 2004. http://dx.doi.org/10.1117/12.514325.

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2

Tonizzo, A., T. Harmel, A. Ibrahim, S. Hlaing, I. Ioannou, A. Gilerson, J. Chowdhary, B. Gross, F. Moshary, and S. Ahmed. "Sensitivity of the above water polarized reflectance to the water composition." In Remote Sensing, edited by Charles R. Bostater, Jr., Stelios P. Mertikas, Xavier Neyt, and Miguel Velez-Reyes. SPIE, 2010. http://dx.doi.org/10.1117/12.865510.

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3

Bostater, Jr., Charles R., James Jones, Heather Frystacky, Mate Kovacs, and Oszkar Jozsa. "Image analysis for water surface and subsurface feature detection in shallow waters." In Remote Sensing, edited by Charles R. Bostater, Jr., Stelios P. Mertikas, Xavier Neyt, and Miguel Velez-Reyes. SPIE, 2010. http://dx.doi.org/10.1117/12.870728.

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4

Bostater, Jr., Charles R., and Luce Bassetti. "Influence of water waves on hyperspectral remote sensing of subsurface water features." In Remote Sensing, edited by Charles R. Bostater, Jr. and Rosalia Santoleri. SPIE, 2004. http://dx.doi.org/10.1117/12.565273.

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5

Dinoev, T., P. Ristori, Y. Arshinov, S. Bobrovnikov, I. Serikov, B. Calpini, H. van den Bergh, and V. Simeonov. "Meteorological water vapor Raman lidar: advances." In Remote Sensing, edited by Upendra N. Singh. SPIE, 2006. http://dx.doi.org/10.1117/12.692451.

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6

Bostater, Charles R. "Multiresolution earth remote sensing approach." In Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2018, edited by Charles R. Bostater, Stelios P. Mertikas, and Xavier Neyt. SPIE, 2018. http://dx.doi.org/10.1117/12.2515670.

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7

Santini, F., R. M. Cavalli, A. Palombo, and S. Pignatti. "Optical model for the water characterization of the highly turbid water of the Winam Gulf (Victoria Lake)." In Remote Sensing, edited by Charles R. Bostater, Jr., Stelios P. Mertikas, Xavier Neyt, and Miguel Vélez-Reyes. SPIE, 2007. http://dx.doi.org/10.1117/12.739061.

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8

Migliorini, Stefano, Stefano Nativi, and Dino Giuli. "Water vapor and cloud liquid water effective profile retrievals over the sea using TRMM microwave imager (TMI)." In Remote Sensing, edited by Jaqueline E. Russell. SPIE, 1999. http://dx.doi.org/10.1117/12.373058.

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Ioannou, Ioannis, Alexander Gilerson, Michael Ondrusek, Soe Hlaing, Robert Foster, Ahmed El-Habashi, Kaveh Bastani, and Samir Ahmed. "Remote estimation of in water constituents in coastal waters using neural networks." In SPIE Remote Sensing, edited by Charles R. Bostater, Stelios P. Mertikas, and Xavier Neyt. SPIE, 2014. http://dx.doi.org/10.1117/12.2067772.

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10

Bazzani, Marco, Giovanna Cecchi, Luca Pantani, and Valentina Raimondi. "Lidar measurement of light attenuation in water." In Remote Sensing, edited by Giovanna Cecchi and Eugenio Zilioli. SPIE, 1998. http://dx.doi.org/10.1117/12.332728.

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Звіти організацій з теми "Water Remote sensing"

1

Mobley, Curtis D. Algorithm Comparison for Shallow-Water Remote Sensing. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada541078.

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2

Aldridge, David Franklin, Lewis Clark Bartel, Nedra Bonal, and Bruce Phillip Engler. Geophysical remote sensing of water reservoirs suitable for desalinization. Office of Scientific and Technical Information (OSTI), December 2009. http://dx.doi.org/10.2172/986593.

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3

Alföldi, T. Remote Sensing as a Tool for Water Resource Engineers. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1987. http://dx.doi.org/10.4095/217451.

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4

Champagne, C., K. Staenz, A. Bannari, H. P. White, J. C. Deguise, and H. McNairn. Estimation of Plant Water Content of Agricultural Canopies Using Hyperspectral Remote Sensing. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2002. http://dx.doi.org/10.4095/219955.

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5

Tufillaro, Nicholas. Correlation of Remote Sensing Water Quality Maps with an in situ Sensor Network. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1862416.

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6

Xu, Min, Hongxing Liu, Richard Beck, Molly Reif, Erich Emery, and Jade Young. Regional analysis of lake and reservoir water quality with multispectral satellite remote sensing images. Engineer Research and Development Center (U.S.), December 2019. http://dx.doi.org/10.21079/11681/34933.

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7

Friedman, Shmuel, Jon Wraith, and Dani Or. Geometrical Considerations and Interfacial Processes Affecting Electromagnetic Measurement of Soil Water Content by TDR and Remote Sensing Methods. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7580679.bard.

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Анотація:
Time Domain Reflectometry (TDR) and other in-situ and remote sensing dielectric methods for determining the soil water content had become standard in both research and practice in the last two decades. Limitations of existing dielectric methods in some soils, and introduction of new agricultural measurement devices or approaches based on soil dielectric properties mandate improved understanding of the relationship between the measured effective permittivity (dielectric constant) and the soil water content. Mounting evidence indicates that consideration must be given not only to the volume fractions of soil constituents, as most mixing models assume, but also to soil attributes and ambient temperature in order to reduce errors in interpreting measured effective permittivities. The major objective of the present research project was to investigate the effects of the soil geometrical attributes and interfacial processes (bound water) on the effective permittivity of the soil, and to develop a theoretical frame for improved, soil-specific effective permittivity- water content calibration curves, which are based on easily attainable soil properties. After initializing the experimental investigation of the effective permittivity - water content relationship, we realized that the first step for water content determination by the Time Domain Reflectometry (TDR) method, namely, the TDR measurement of the soil effective permittivity still requires standardization and improvement, and we also made more efforts than originally planned towards this objective. The findings of the BARD project, related to these two consequential steps involved in TDR measurement of the soil water content, are expected to improve the accuracy of soil water content determination by existing in-situ and remote sensing dielectric methods and to help evaluate new water content sensors based on soil electrical properties. A more precise water content determination is expected to result in reduced irrigation levels, a matter which is beneficial first to American and Israeli farmers, and also to hydrologists and environmentalists dealing with production and assessment of contamination hazards of this progressively more precious natural resource. The improved understanding of the way the soil geometrical attributes affect its effective permittivity is expected to contribute to our understanding and predicting capability of other, related soil transport properties such as electrical and thermal conductivity, and diffusion coefficients of solutes and gas molecules. In addition, to the originally planned research activities we also investigated other related problems and made many contributions of short and longer terms benefits. These efforts include: Developing a method and a special TDR probe for using TDR systems to determine also the soil's matric potential; Developing a methodology for utilizing the thermodielectric effect, namely, the variation of the soil's effective permittivity with temperature, to evaluate its specific surface area; Developing a simple method for characterizing particle shape by measuring the repose angle of a granular material avalanching in water; Measurements and characterization of the pore scale, saturation degree - dependent anisotropy factor for electrical and hydraulic conductivities; Studying the dielectric properties of cereal grains towards improved determination of their water content. A reliable evaluation of the soil textural attributes (e.g. the specific surface area mentioned above) and its water content is essential for intensive irrigation and fertilization processes and within extensive precision agriculture management. The findings of the present research project are expected to improve the determination of cereal grain water content by on-line dielectric methods. A precise evaluation of grain water content is essential for pricing and evaluation of drying-before-storage requirements, issues involving energy savings and commercial aspects of major economic importance to the American agriculture. The results and methodologies developed within the above mentioned side studies are expected to be beneficial to also other industrial and environmental practices requiring the water content determination and characterization of granular materials.
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Agassi, Menahem, Michael J. Singer, Eyal Ben-Dor, Naftaly Goldshleger, Donald Rundquist, Dan Blumberg, and Yoram Benyamini. Developing Remote Sensing Based-Techniques for the Evaluation of Soil Infiltration Rate and Surface Roughness. United States Department of Agriculture, November 2001. http://dx.doi.org/10.32747/2001.7586479.bard.

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The objective of this one-year project was to show whether a significant correlation can be established between the decreasing infiltration rate of the soil, during simulated rainstorm, and a following increase in the reflectance of the crusting soil. The project was supposed to be conducted under laboratory conditions, using at least three types of soils from each country. The general goal of this work was to develop a method for measuring the soil infiltration rate in-situ, solely from the reflectance readings, using a spectrometer. Loss of rain and irrigation water from cultivated fields is a matter of great concern, especially in arid, semi-arid regions, e.g. much of Israel and vast area in US, where water is a limiting factor for crop production. A major reason for runoff of rain and overhead irrigation water is the structural crust that is generated over a bare soils surface during rainfall or overhead irrigation events and reduces its infiltration rate (IR), considerably. IR data is essential for predicting the amount of percolating rainwater and runoff. Available information on in situ infiltration rate and crust strength is necessary for the farmers to consider: when it is necessary to cultivate for breaking the soil crust, crust strength and seedlings emergence, precision farming, etc. To date, soil IR is measured in the laboratory and in small-scale field plots, using rainfall simulators. This method is tedious and consumes considerable resources. Therefore, an available, non-destructive-in situ methods for soil IR and soil crusting levels evaluations, are essential for the verification of infiltration and runoff models and the evaluation of the amount of available water in the soil. In this research, soil samples from the US and Israel were subjected to simulated rainstorms of increasing levels of cumulative energies, during which IR (crusting levels) were measured. The soils from the US were studied simultaneously in the US and in Israel in order to compare the effect of the methodology on the results. The soil surface reflectance was remotely measured, using laboratory and portable spectrometers in the VIS-NIR and SWIR spectral region (0.4-2.5mm). A correlation coefficient spectra in which the wavelength, consisting of the higher correlation, was selected to hold the highest linear correlation between the spectroscopy and the infiltration rate. There does not appear to be a single wavelength that will be best for all soils. The results with the six soils in both countries indeed showed that there is a significant correlation between the infiltration rate of crusted soils and their reflectance values. Regarding the wavelength with the highest correlation for each soil, it is likely that either a combined analysis with more then one wavelength or several "best" wavelengths will be found that will provide useful data on soil surface condition and infiltration rate. The product of this work will serve as a model for predicting infiltration rate and crusting levels solely from the reflectance readings. Developing the aforementioned methodologies will allow increased utilization of rain and irrigation water, reduced runoff, floods and soil erosion hazards, reduced seedlings emergence problems and increased plants stand and yields.
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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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Анотація:
To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.
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10

Shimabukuro, Fred I. A Method for Remote Sensing of Precipitable Water Vapor and Liquid in the Atmosphere Using a 22-GHz Radiometer. Fort Belvoir, VA: Defense Technical Information Center, August 1987. http://dx.doi.org/10.21236/ada184204.

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