Download or read book Algorithms to Estimate Soil Moisture Storage from Microwave Measurements written by Bruce J. Blanchard and published by . This book was released on 1979 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Inversion Algorithms for the Microwave Remote Sensing of Soil Moisture written by Gary Duke Hancock and published by . This book was released on 1982 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Retrieval of Soil Moisture Using Microwave Spaceborne written by Jyoti Sharma and published by A.K. Publications. This book was released on 2023-02-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Retrieval of soil moisture using microwave spaceborne refers to the measurement and estimation of the amount of water present in the soil using satellite-borne microwave radiometers. The microwave radiometry technology works by measuring the microwave radiation emitted by the soil surface, which is related to the soil moisture content. The data collected by these radiometers is then processed using algorithms to estimate the soil moisture content. Soil moisture information is crucial for a variety of applications, including weather prediction, drought monitoring, irrigation planning, vegetation monitoring, and water resource management. The ability to obtain soil moisture measurements on a large scale through spaceborne technology provides a powerful tool for improving our understanding of land surface processes and the water cycle. Spaceborne soil moisture retrieval has proven to be an effective method for monitoring soil moisture over large areas and has provided valuable information for numerous studies in hydrology, agriculture, and climate modeling. However, the accuracy of these estimates is dependent on several factors, including the calibration of the radiometer, the development of robust algorithms, and the availability of ground validation data. Ongoing research is focused on improving the accuracy of soil moisture retrieval from spaceborne microwave radiometers and increasing our understanding of the relationships between soil moisture and other land surface variables. Xray systems in medical science, laser scanning for atmospheric constituents, and sonar sounding of sea level. Remote sensing utilizes electromagnetic radiation as an information carrier from the target to the sensing device. It involves the interaction of electromagnetic radiations to the targeting object. The radiations, reflected, transmitted, or emitted by the object are captured by the sensors to find the target information. These sensors can be mounted on different platforms such as automotive vehicles, aircraft, rockets, hot air balloons, drones, space shuttles, and satellites. Remote sensing is part of countless possible innovations due to the roaming of the satellites around our Earth. Satellites play a crucial role in developing various technologies such as global mapping, GPS, urban planning, etc. The primary applications of remote sensing are the study of Earth's surface, Earth's atmosphere, LU/LC management, climate change monitoring, agriculture, drought, etc.
Download or read book Estimation of Soil Moisture Using Active Microwave Remote Sensing written by Vinod Ramnath and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The method for developing a soil moisture inversion algorithm using Radar data can be approached in two ways: the multiple-incident angle approach and the change detection method. This thesis discusses how these two methods can be used to predict surface soil moisture. In the multiple incident angle approach, surface roughness can be mapped, if multiple incident angle viewing is possible and if the surface roughness is assumed constant during data acquisitions. A backpropagation neural network (NN) is trained with the data set generated by the Integral Equation Method (IEM) model. The training data set includes possible combinations of backscatter obtained as a result of variation in dielectric constant within the period of data acquisitions. The inputs to the network are backscatter acquired at different incident angles. The outputs are correlation length and root mean square height (rms). Once the roughness is mapped using these outputs, dielectric constant can be determined. Three different data sets, (backscatter acquired from multiple-frequencies, multiple-polarizations, and multiple-incident angles) are used to train the NN. The performance of the NN trained by the different data sets is compared. The next approach is the application of the change detection concept. In this approach, the relative change in dielectric constant over two different periods is determined from Radarsat data using a simplified algorithm. The vegetation backscatter contribution can be removed with the aid of multi-spectral data provided by Landsat. A method is proposed that minimizes the effect of incident angle on Radar backscatter by normalizing the acquired SAR images to a reference angle. A quantitative comparison of some of the existing soil moisture estimation algorithms is also made.
Download or read book Introduction to Satellite Remote Sensing written by William Emery and published by Elsevier. This book was released on 2017-08-30 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Satellite Remote Sensing: Atmosphere, Ocean and Land Applications is the first reference book to cover ocean applications, atmospheric applications, and land applications of remote sensing. Applications of remote sensing data are finding increasing application in fields as diverse as wildlife ecology and coastal recreation management. The technology engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. The book opens with an introduction to the history of remote sensing, starting from when the phrase was first coined. It goes on to discuss the basic concepts of the various systems, including atmospheric and ocean, then closes with a detailed section on land applications. Due to the cross disciplinary nature of the authors' experience and the content covered, this is a must have reference book for all practitioners and students requiring an introduction to the field of remote sensing. - Provides study questions at the end of each chapter to aid learning - Covers all satellite remote sensing technologies, allowing readers to use the text as instructional material - Includes the most recent technologies and their applications, allowing the reader to stay up-to-date - Delves into laser sensing (LIDAR) and commercial satellites (DigitalGlobe) - Presents examples of specific satellite missions, including those in which new technology has been introduced
Download or read book Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing written by and published by . This book was released on 1983 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book NOAA Technical Memorandum NESS written by United States. National Oceanic and Atmospheric Administration and published by . This book was released on 1980 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monitoring and Predicting Agricultural Drought written by Vijendra K. Boken and published by Oxford University Press. This book was released on 2005-04-14 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agricultural droughts affect whole societies, leading to higher food costs, threatened economies, and even famine. In order to mitigate such effects, researchers must first be able to monitor them, and then predict them; however no book currently focuses on accurate monitoring or prediction of these devastating kinds of droughts. To fill this void, the editors of Monitoring and Predicting Agricultural Drought have assembled a team of expert contributors from all continents to make a global study, describing biometeorological models and monitoring methods for agricultural droughts. These models and methods note the relationships between precipitation, soil moisture, and crop yields, using data gathered from conventional and remote sensing techniques. The coverage of the book includes probabilistic models and techniques used in America, Europe and the former USSR, Africa, Asia, and Australia, and it concludes with coverage of climate change and resultant shifts in agricultural productivity, drought early warning systems, and famine mitigation. This will be an essential collection for those who must advise governments or international organizations on the current scope, likelihood, and impact of agricultural droughts. Sponsored by the World Meterological Organization
Download or read book Soil Moisture Estimation by Microwave Remote Sensing for Assimilation Into WATClass written by Damian Chi-Ho Kwok and published by . This book was released on 2007 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis examines the feasibility of assimilating space borne remotely-sensed microwave data into WATClass using the ensemble Kalman filter. WATClass is a meso-scale gridded hydrological model used to track water and energy budgets of watersheds by way of real-time remotely sensed data. By incorporating remotely-sensed soil moisture estimates into the model, the model's soil moisture estimates can be improved, thus increasing the accuracy of the entire model. Due to the differences in scale between the remotely sensed data and WATClass, and the need of ground calibration for accurate soil moisture estimation from current satellite-borne active microwave remote sensing platforms, the spatial variability of soil moisture must be determined in order to characterise the dependency between the remotely-sensed estimates and the model data and subsequently to assimilate the remotely-sensed data into the model. Two sets of data - 1996-1997 Grand River watershed data and 2002-2003 Roseau River watershed data - are used to determine the spatial variability. The results of this spatial analysis however are found to contain too much error due to the small sample size. It is therefore recommended that a larger set of data with more samples both spatially and temporally be taken. The proposed algorithm is tested with simulated data in a simulation of WATClass. Using nominal values for the estimated errors and other model parameters, the assimilation of remotely sensed data is found to reduce the absolute RMS error in soil moisture from 0.095 to approximately 0.071. The sensitivities of the improvement in soil moisture estimates by using the proposed algorithm to several different parameters are examined.
Download or read book Estimation of Soil Moisture in the Southern United States in 2003 Using Multi satellite Remote Sensing Measurements written by Melissa Soriano and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil moisture is a critical parameter for predicting and detecting floods and droughts, as well as indicating crop and vegetation health. Current indicators utilize surrogate or modeled measures of soil moisture. Actual observed soil moisture measurements have the potential to improve understanding of floods, droughts, and crop health. In this study, ground soil moisture daily average values were compared to estimates obtained from two microwave sensors, the EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) and the Tropical Rainfall Measurement Mission Microwave Scanning Radiometer (TMI), as well as one optical sensor, the EOS Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). The study areas were the Little Washita River Experimental Watershed in Oklahoma and the Little River Experimental Watershed in Georgia. This research compared AMSR-E, TMI, and MODIS data to ground data from the Little Washita Berg station and also compared AMSR-E and TMI data to ground data from the Little River Soil Climate Analysis Network station. AMSR-E and TMI performed better in Little Washita than in Little River during the crop-covered season. This may be due to the vegetation type, distribution, and density at Little River. AMSR-E exhibited a smaller range of variability than the TMI or in-situ measurements at both study sites for all time periods. In the crop-covered season of June, July, and August of 2003, MODIS soil moisture retrieval at the Little Washita site correlated better (R^2 = 0.772) with the in-situ measurements than AMSR-E or TMI soil moisture retrievals. The spatial resolution of MODIS (1 km) is finer than the spatial resolution of AMSR-E (~25 km) or TMI. Spatial resolution is an important factor because topography, soil properties, and vegetation cover may vary significantly over satellite footprints. Both microwave sensors are limited by their coarse spatial resolution. However, optical measurements are limited to cloud-free conditions. Future work includes research on algorithms which combine optical and microwave measurements to provide the advantages of each.
Download or read book ESTIMATION OF SOIL MOISTURE USING ACTIVE MICROWAVE REMOTE SENSING written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The method for developing a soil moisture inversion algorithm using Radar data can be approached in two ways: the multiple-incident angle approach and the change detection method. This thesis discusses how these two methods can be used to predict surface soil moisture. In the multiple incident angle approach, surface roughness can be mapped, if multiple incident angle viewing is possible and if the surface roughness is assumed constant during data acquisitions. A backpropagation neural network (NN) is trained with the data set generated by the Integral Equation Method (IEM) model. The training data set includes possible combinations of backscatter obtained as a result of variation in dielectric constant within the period of data acquisitions. The inputs to the network are backscatter acquired at different incident angles. The outputs are correlation length and root mean square height (rms). Once the roughness is mapped using these outputs, dielectric constant can be determined. Three different data sets, (backscatter acquired from multiple-frequencies, multiple-polarizations, and multiple-incident angles) are used to train the NN. The performance of the NN trained by the different data sets is compared. The next approach is the application of the change detection concept. In this approach, the relative change in dielectric constant over two different periods is determined from Radarsat data using a simplified algorithm. The vegetation backscatter contribution can be removed with the aid of multi-spectral data provided by Landsat. A method is proposed that minimizes the effect of incident angle on Radar backscatter by normalizing the acquired SAR images to a reference angle. A quantitative comparison of some of the existing soil moisture estimation algorithms is also made.
Download or read book ESTAR written by C. T. Swift and published by . This book was released on 1993 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spatial Modelling of the Terrestrial Environment written by Richard E.J. Kelly and published by John Wiley & Sons. This book was released on 2004-10-22 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding and predicting the behaviour of natural and human environmental systems is crucial for the effective management of the Earth’s limited resources. Recently, great advances have been made through spatial modelling. This book provides a snapshot of the latest research in modelling technologies and methodologies within five environmental fields; the cryosphere, hydrology, geomorphology, vegetation interfaces and urban environments. Spatial Modelling of the Terrestrial Environment deals with the use of remote sensing, numerical models and GIS in addressing important natural and human environmental sciences issues, focusing on the theory and application of modelling remotely sensed data within the context of environmental processes. Extensive case material exemplifies the latest research and modelling paradigms presented in the book.
Download or read book Data Assimilation for the Earth System written by Richard Swinbank and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology. Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites. This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.
Download or read book Land Surface Atmosphere Interactions for Climate Modeling written by E.F. Wood and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is well known that the interactions between land surfaces and the atmosphere, and the resulting exchanges in water and energy have a tremendous affect on climate. The inadequate representation of land-atmosphere interactions is a major weakness in current climate models, and is providing the motivation for the HAPEX and ISLSCP experiments as well as the proposed Global Energy and Water Experiment (GEWEX) and the Earth Observing System (EOS) mission. The inadequate representation reflects the recognition that the well-known phys ical relationships, which are well described at small scales, result in different relationships when represented at the scales used in climate models. Understanding this transition in the mathematical relationships with increased space-time scales appears to be very difficult, and has led to different approaches; at one extreme, the famous "bucket" model where the land-surface is a simple one layer storage without vegetation; the other extreme may be Seller's Simple Biosphere Model (Sib) where one big leaf covers the climate model grid. Given the heterogeneous nature of landforms, soils and vegetation within a climate model grid, the development of new land surface parameterizations, and their verification through large scale experiments is perceived to be a challenging area of research for the hydrology and meteorology communities. This book evolved from a workshop held at Princeton University to explore the status of land surface parameterizations within climate models, and how observa tional data can be used to assess these parameterizations and improve models.
Download or read book Satellite Soil Moisture Retrieval written by Prashant K. Srivastava and published by Elsevier. This book was released on 2016-04-29 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: Satellite Soil Moisture Retrieval: Techniques and Applications offers readers a better understanding of the scientific underpinnings, development, and application of soil moisture retrieval techniques and their applications for environmental modeling and management, bringing together a collection of recent developments and rigorous applications of soil moisture retrieval techniques from optical and infrared datasets, such as the universal triangle method, vegetation indices based approaches, empirical models, and microwave techniques, particularly by utilizing earth observation datasets such as IRS III, MODIS, Landsat7, Landsat8, SMOS, AMSR-e, AMSR2 and the upcoming SMAP. Through its coverage of a wide variety of soil moisture retrieval applications, including drought, flood, irrigation scheduling, weather forecasting, climate change, precipitation forecasting, and several others, this is the first book to promote synergistic and multidisciplinary activities among scientists and users working in the hydrometeorological sciences. - Demystifies soil moisture retrieval and prediction - Links soil moisture retrieval techniques with new satellite missions for earth and environmental science oriented problems - Written to be accessible to a wider range of professionals with a common interest in geo-spatial techniques, remote sensing, sustainable water resource development, and earth and environmental issues
Download or read book Estimation of Soil Moisture with the Combined L Band Radar and Radiometer Measurements written by and published by . This book was released on 2005 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study demonstrates a technique of estimating soil moisture using the combined passive/active L-band microwave measurements. It shows 1) evaluation of the small albedo assumption for using dual polarization passive measurements, 2) development of a synthesized technique to estimate soil moisture, and 3) evaluation with ground soil moisture measurements from the SMEX02 experiment data.
