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 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 On the Feasibility of Monitoring Soil Moisture Using Active Microwave Remote Sensing written by Percy P. Batlivala and published by . This book was released on 1977 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Microwave Remote Sensing of Soil Moisture written by Jiangyuan Zeng and published by Mdpi AG. This book was released on 2023-11-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reprint focuses on the most advanced theories, models, algorithms, and products related to microwave remote sensing of soil moisture. Over the past few decades, significant efforts have been made to develop models, retrieval algorithms, downscaling methods, and validation strategies related to microwave remote sensing of soil moisture. Following the turn of the century, a series of microwave-based satellites/sensors have been successfully launched, and satellite soil moisture products have become increasingly abundant, greatly promoting the various applications of satellite soil moisture datasets. Despite numerous studies and achievements in this field, great challenges remain, such as the spatial resolution, retrieval accuracy, and validation strategies related to satellite soil moisture datasets. This reprint covers research progress on the following topics: (1) downscaling passive microwave-based soil moisture products, (2) estimating soil moisture from active microwave observations, (3) presenting some new algorithms (freeze-thaw state detection algorithm) and models (soil dielectric models) related to microwave remote sensing of soil moisture, (4) evaluating microwave-based soil moisture products, and (5) reviewing the state-of-the-art techniques and algorithms used to estimate and improve the quality of soil moisture estimations.

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 Microwave Scattering and Emission Models and Their Applications written by Adrian K. Fung and published by Artech House Remote Sensing Li. This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "An excellent reference book. Treatment is thorough in terms of starting from some fundamental assumptions and working through the details so the reader may understand both the mathematical derivation and the physical basis for the resulting phase distribution functions (PDFs). [Fung's] discussion of the dependence of the PDF on the scattering parameters and the range of possible values is extremely helpful, and the illustration of the terrain scattering PDF is quite clear."

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 On the Feasibility of Monitoring Soil Moisture Using Active Microwave Remote Sensing written by Percy P. Batlivala and published by . This book was released on 1977 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Soil Moisture Remote Sensing Using Active Microwaves and Land Surface Modeling written by Rogier van der Velde and published by . This book was released on 2010 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Active Microwave Remote Sensing of Soil Moisture written by Brian Barrett and published by . This book was released on 2006 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Passive and Active Microwave Remote Sensing of Soil Moisture written by John Dennis Bolten and published by . This book was released on 2001 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Active and Passive Microwave Remote Sensing of Soil Moisture written by Rajat Bindlish and published by . This book was released on 2000 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book In Situ Measurement and Remote Sensing of Soil Moisture Using Time Domain Reflectometry Thermal Infrared and Active Microwaves written by Michael P. Wüthrich Treubig and published by . This book was released on 1998 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Statistical analysis and combination of active and passive microwave remote sensing methods for soil moisture retrieval written by Kathrina Rötzer and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Towards Medium resolution Soil Moisture Retrieval from Active and Passive Microwave Observations written by Xiaoling Wu and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Surface soil moisture is essential to global water cycle monitoring, weather forecasting, prediction of drought and flood, and modelling of evaporation. The European Space Agency (ESA) launched the Soil Moisture and Ocean Salinity (SMOS) satellite in 2009, as the first-ever soil moisture dedicated satellite. It uses the passive microwave (radiometer) remote sensing technology due to the direct relationship with soil moisture, but due to technical limitations the spatial resolution is approximately 40 km. This places limitations on hydro-meteorological applications such as regional weather forecasting, flood prediction, and agricultural activities that have a resolution requirement of better than 10 km. Active microwave (radar) remote sensing provides a much higher spatial resolution capability (better than 3 km), but it is less sensitive to changes in soil moisture due to the confounding effects of vegetation and surface roughness. Consequently, NASA has developed the Soil Moisture Active Passive (SMAP) mission, scheduled for launch in January 2015, which will merge passive and active observations to overcome their individual limitations, thus providing a soil moisture product with resolution better than 10 km at a target accuracy of 0.04 cm3/cm3. The rationale behind this mission is to use fine resolution (3 km) radar observations to disaggregate the coarse resolution (36 km) radiometer observations into a medium-resolution (9 km) product. The downscaling algorithms for this purpose have so far undergone only limited testing with experimental data sets, and have therefore been tested mostly using synthetic data and a limited number of suitable experimental data sets mostly in the continental United States. Consequently, this thesis presents an extensive evaluation of soil moisture downscaling algorithms with an experimental data set collected from the Soil Moisture Active Passive Experiment (SMAPEx) field campaigns in south-eastern Australia. This research affords a unique opportunity to undertake a comprehensive assessment of the various downscaling approaches proposed, having applicability to the forthcoming SMAP mission. In particular, each approach is comprehensively assessed using a consistent data set collected over a diverse landscape exhibiting a range of conditions, and then inter-compared with the results from the others. A particular focus is placed on the SMAP baseline algorithm as this is currently the preferred algorithm and scheduled for implementation by NASA immediately upon launch. A preliminary study on the SMAP baseline algorithm was conducted by using existing satellite data; results from which suggested that a better representation of the SMAP data stream characteristics was required. Consequently, a study was undertaken on how to prepare the simulated SMAP data stream from the airborne data set collected from the SMAPEx field campaigns in Australia. These data were processed in terms of spatial aggregation, incidence angle normalization and azimuth effect analysis so as to be in line with the characteristics of the SMAP observations. Results indicated that data from SMAPEx could be reliably processed to represent the characteristics of the SMAP observations. The baseline algorithm was then tested using the simulated SMAP data set. Results showed that the baseline downscaling algorithm had the ability to fulfil the error requirement of medium resolution (9 km) brightness temperature product of SMAP over relatively homogenous area, but it had greater error than the requirement over the heterogeneous cropping area. Consequently, the baseline algorithm was assessed at higher resolutions in order to study the effect of land cover type and surface heterogeneity on the resulting downscaling accuracy. The medium resolution (9 km) brightness temperatures obtained from the baseline algorithm were then converted to a medium resolution soil moisture product, and results compared with other linear methods including the optional downscaling algorithm and a change detection method, and with a non-linear Bayesian merging method. The comparison of these different soil moisture downscaling algorithms suggested that the optional algorithm and the Bayesian merging method had a similar performance in retrieving medium resolution soil moisture products, with the lowest error and highest correlation between downscaled and reference soil moisture, amongst the downscaling algorithms tested. However, unless further improvements can be achieved with the Bayesian merging method the optional algorithm is recommended for application in SMAP due to its simplicity of approach and low computational requirement, thus making it simpler to apply in an operational context.

Download or read book Microwave Indices from Active and Passive Sensors for Remote Sensing Applications written by Emanuele Santi and published by MDPI. This book was released on 2019-10-21 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices.

Download or read book Remote Sensing of Soil Moisture 3 written by John Coyle and published by . This book was released on 1982 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: