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2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting
The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science
All fields of satellite, airborne and ground remote sensing.
To promote awareness, understanding, advancement and application of ocean engineering and marine technology. This includes all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.
1. Advanced Motion Control2. Haptics, Robotics and Human-Machine Systems3. Micro/Nano Motion Control Systems4. Intelligent Motion Control Systems5. Nonlinear, Adaptive and Robust Control Systems6. Motion Systems for Robot Intelligence and Humanoid Robotics7. CPG based Feedback Control, Morphological Control8. Actuators and Sensors in Motion System9. Motion Control of Aerial/Ground/Underwater Robots10. Advanced Dynamics and Motion Control11. Motion Control for Assistive and Rehabilitative Robots and Systems12. Intelligent and Advanced Traffic Controls13. Computer Vision in Motion Control14. Network and Communication Technologies in Motion Control15. Motion Control of Soft Robots16. Automation Technologies in Primary Industries17. Other Topics and Applications Involving Motion Dynamics and Control
EDM 2018 is a significant event aimed at development of scientific schools working on foreground areas of Russian science and technology. The main areas are research, design and implementation of micro/nanostructures, radio and telecommunication devices, power electronicand mechatronic systems which are now related to the development of scientific and technological progress. The conference aims to gather young specialists of the differentuniversities of Russia, CIS and other countries. Invited Russian and foreign specialists will report about the development of science and technologies, perspectives of further development of modern electronics. This conference is focused primarily on the discussion of the fundamental theoretical and technological problems of designing and implementing products of micro- and nanoelectronics, simulation methods, and engineering experiments and physical interpretation of the results of these experiments.
Experimental and theoretical advances in antennas including design and development, and in the propagation of electromagnetic waves including scattering, diffraction and interaction with continuous media; and applications pertinent to antennas and propagation, such as remote sensing, applied optics, and millimeter and submillimeter wave techniques.
Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.
EMC standards; measurement technology; undesired sources; cable/grounding; filters/shielding; equipment EMC; systems EMC; antennas and propagation; spectrum utilization; electromagnetic pulses; lightning; radiation hazards; and Walsh functions
It is expected that GRS Letters will apply to a wide range of remote sensing activities looking to publish shorter, high-impact papers. Topics covered will remain within the IEEE Geoscience and Remote Sensing Societys field of interest: the theory, concepts, and techniques of science and engineering as they apply to the sensing of the earth, oceans, atmosphere, and space; and ...
Theory, concepts, and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.
IEEE Transactions on Geoscience and Remote Sensing, 2005
A new physically based disaggregation method is developed to improve the spatial resolution of the surface soil moisture extracted from the Soil Moisture and Ocean Salinity (SMOS) data. The approach combines the 40-km resolution SMOS multiangular brightness temperatures and 1-km resolution auxiliary data composed of visible, near-infrared, and thermal infrared remote sensing data and all the surface variables involved in ...
IEEE Transactions on Geoscience and Remote Sensing, 2014
This study assesses the significance of conditioning the error modeling of The National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measurement Mission Microwave Imager rainfall algorithm (2A12) to near-surface soil moisture data derived from a land surface model. The term “conditioning” means the model parameters' dependence on soil wetness. The Oklahoma (OK) region is used as the study area due ...
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016
Soil moisture is a key state variable which plays a significant role in many hydrological processes. The Soil Moisture Active Passive (SMAP) mission was launched on 31 January 2015 which can provide global information of soil moisture. Among the released SMAP data sets, the Level 4 Surface and Root Zone Soil Moisture Analysis Product (L4_SM) can not only provide information ...
2007 IEEE International Geoscience and Remote Sensing Symposium, 2007
Water and energy fluxes at the interface between the land surface and atmosphere are strongly depending on the surface soil moisture content which is highly variable in space and time. The sensitivity of active and passive microwave remote sensing data to surface soil moisture content has been investigated in numerous studies. Recent satellite borne mission concepts, as e.g. the SMOS ...
IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), 2003
This paper presents an original methodology to retrieve surface (< 5 cm) soil moisture over low vegetated regions using the two active microwave instruments of ERS satellite. The developed algorithm takes advantage of the multi-angular configuration and high temporal resolution of the Wind Scatterometer (WSC) combined with the SAR high spatial resolution. High correlations (R/sup 2/ greater than 0.8) are ...
NeuroGrid: Recording action potentials and large-scale network activity from the surface of the brain - IEEE Brain Workshop
Indoor Vertical Farms: Growing Food Without Sun, Soil or Pesticides
IMS 2011 Microapps - A Multi-Level Conductor Surface Roughness Model
Quantum Computation - ASC-2014 Plenary series - 4 of 13 - Tuesday 2014/8/12
IMPASS: Intelligent Mobility Platform with Active Spoke System
Life Sciences: Surface Enhanced Raman Spectroscopy, and more
3D Body-Mapping for Severely Burned Patients - Julia Loegering - IEEE EMBS at NIH, 2019
IEEE Magnetics Distinguished Lecture - Yoshichika Otani
Making Orthogonal Transitions with Climbing Mini-Whegs
BSIM Spice Model Enables FinFET and UTB IC Design
Microwave PCB Structure Selection Microstrip vs. Grounded Coplanar Waveguide: MicroApps 2015 - Rogers Corporation
Silicon THz: an Opportunity for Innovation
Perpendicular magnetic anisotropy: From ultralow power spintronics to cancer therapy
Lighting the Way: Optical Sensors in the Life Sciences
ASC-2014 SQUIDs 50th Anniversary: 4 of 6 - Keiji Enpuku
IROS TV 2019-STAR LAB at the University of Surrey Space Technology for Autonomous systems & Robotics
ISEC 2013 Special Gordon Donaldson Session: Remembering Gordon Donaldson - 5 of 7 - SQUID Instrumentation for Early Cancer Diagnostics
Robotics History: Narratives and Networks Oral Histories: Larry Matthies
Demonstrations of Gravity-Independent Mobility and Drilling on Natural Rock using Microspines
A new physically based disaggregation method is developed to improve the spatial resolution of the surface soil moisture extracted from the Soil Moisture and Ocean Salinity (SMOS) data. The approach combines the 40-km resolution SMOS multiangular brightness temperatures and 1-km resolution auxiliary data composed of visible, near-infrared, and thermal infrared remote sensing data and all the surface variables involved in the modeling of land surface-atmosphere interaction available at this scale (soil texture, atmospheric forcing, etc.). The method successively estimates a relative spatial distribution of soil moisture with fine-scale auxiliary data, and normalizes this distribution at SMOS resolution with SMOS data. The main assumption relies on the relationship between the radiometric soil temperature inverted from the thermal infrared and the microwave soil moisture. Based on synthetic data generated with a land surface model, it is shown that the radiometric soil temperature can be used as a tracer of the spatial variability of the 0-5 cm soil moisture. A sensitivity analysis shows that the algorithm remains stable for big uncertainties in auxiliary data and that the uncertainty in SMOS observation seems to be the limiting factor. Finally, a simple application to the SGP97/AVHRR data illustrates the usefulness of the approach.
This study assesses the significance of conditioning the error modeling of The National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measurement Mission Microwave Imager rainfall algorithm (2A12) to near-surface soil moisture data derived from a land surface model. The term “conditioning” means the model parameters' dependence on soil wetness. The Oklahoma (OK) region is used as the study area due to its relatively low vegetation and smooth terrain and the availability of high-quality in situ hydrometeorological data from the Mesonet network. The study period includes two warm seasons (March to October) from 2009 and 2010. The National Oceanic and Atmospheric Administration/National Severe Storms Laboratory ground radar- based National Mosaic and Quantitative Precipitation Estimation system (NMQ/Q2) is used as high-resolution (5-min/1-km) reference rainfall. The surface wetness conditions (wet, dry, and normal) were determined from surface soil moisture fields simulated by the NASA Catchment Land Surface Model forced with Q2 rainfall fields. A 2-D satellite rainfall error model, SREM2D, is used to provide the ensemble error representation of 2A12 rainfall using two different parameter calibration approaches: conditioning the SREM2D parameters to the surface soil wetness categories versus not. The statistical analysis of model-generated ensembles and associated error metrics show better performance when surface wetness information is used in SREM2D. In terms of quantification, the ensemble rainfall from the conditional SREM2D parameter calibration shows better reference rainfall encapsulation. The conditioning of SREM2D to soil wetness can apply to rainfall rate estimates from other microwave sensors on board low Earth orbiting satellites and is valuable for the forthcoming missions on precipitation (Global Precipitation Measurement) and soil moisture (Soil Moisture Active Passive).
Soil moisture is a key state variable which plays a significant role in many hydrological processes. The Soil Moisture Active Passive (SMAP) mission was launched on 31 January 2015 which can provide global information of soil moisture. Among the released SMAP data sets, the Level 4 Surface and Root Zone Soil Moisture Analysis Product (L4_SM) can not only provide information on surface soil moisture (top 5 cm of the soil column), but also provide estimates of root zone soil moisture (top 1 m of the soil column) which is very important for several key applications targeted by SMAP. However, since this product has been released only for a short time, its accuracy and reliability has not been validated so far. In this study, we evaluated the L4_SM soil moisture analysis product against in-situ soil moisture measurements collected from the Little Washita Watershed network located in southwest Oklahoma in the Great Plains region of the United States. The results show that both the surface and root zone soil moisture estimates in the L4_SM product are in good agreement with the in-situ measurements, and the RMSE is 0.027 m3/m3 and 0.032 m3/m3 for the surface and root zone soil moisture respectively which both have exceeded the RMSE requirement of 0.04 m3/m3 for this product.
Water and energy fluxes at the interface between the land surface and atmosphere are strongly depending on the surface soil moisture content which is highly variable in space and time. The sensitivity of active and passive microwave remote sensing data to surface soil moisture content has been investigated in numerous studies. Recent satellite borne mission concepts, as e.g. the SMOS mission, are dedicated to provide global soil moisture information with a temporal frequency of 1-3 days to capture the high temporal dynamics of surface soil moisture. Passive satellite microwave sensors have spatial resolutions in the order of tens of kilometres. The paper investigates the impact of land surface heterogeneity on soil moisture retrievals from L-band passive microwave data at different spatial scales between 1 km and 40 km. The impact of sensor noise and quality of ancillary information is explicitly considered. A synthetic study is conducted where brightness temperature observations are generated using simulated land surface conditions. The soil moisture retrieval uncertainties resulting from the heterogeneity within the image pixels as well as the uncertainties in the a priori knowledge of surface temperature data and due to sensor noise, is investigated.
This paper presents an original methodology to retrieve surface (< 5 cm) soil moisture over low vegetated regions using the two active microwave instruments of ERS satellite. The developed algorithm takes advantage of the multi-angular configuration and high temporal resolution of the Wind Scatterometer (WSC) combined with the SAR high spatial resolution. High correlations (R/sup 2/ greater than 0.8) are observed for three studied watersheds in France with an rms error smaller than 4% between real and retrieved moistures.
]Studies on character and variation of surface moisture become more and more important in land surface process and hydrological modeling. Several methods have been proposed to estimate dry/wet conditions of land surface. However, there are some limitations in these methods. We developed an empirical method of detecting surface moisture condition using surface temperature and vegetation index derived from NOAA/AVHRR data. The results show that vegetation index and surface temperature are important parameters to describe characters of dry/wet condition of land surface. It is obvious that the use of remotely sensed data is potentially of great interest in such context. Therefore, to monitor surface moisture is an important subject of remote sensing. Using this method the surface moisture is detected in the Northwestern Loess plateau of China. The distribution characters of the surface moisture is analyzed as well
Surface soil moisture products generated by recent L-band radiometer missions have significant potential for enhancing hydrologic stream flow prediction. Here, we objectively evaluate this potential using data sets generated by both the ESA SMOS and NASA SMAP satellite missions. Evaluation is based on their ability to improve the representation of both 1) pre-storm antecedent soil moisture conditions and 2) within-storm rainfall accumulation depths. Results demonstrate that SMOS and SMAP surface soil moisture products can significantly improve both key aspects of a hydrologic prediction system.
Thermal inert in method is one of the main approaches for drought monitoring by using remotely sensed data. The method is widely used in the China North Plain which is relatively flat. In our study, we tried to apply the approach to the agricultural areas of Shaanxi Province in the Northwest China with terrain and climate varies. The results showed that apparent thermal inertia can be used to monitor the drought occurrence. Considering the effects of terrains, vegetation coverage and soil types, the more homogeneous the land surface is, the better correlation between the apparent thermal inertia mid surface soil moisture is
Water and energy fluxes at the interface between the land surface and atmosphere are affected by the surface water content of the soil, which is highly variable in space and time. Recent satellite mission concepts, as e.g. the Soil Moisture and Ocean Salinity Mission (SMOS), are dedicated to provide global soil moisture information with a temporal frequency of a few days to capture the high temporal dynamics of surface soil moisture. As passive microwave sensors have a spatial resolution in the order of tens of kilometers, the application of the data in mesoscale flood forecasting or water balance models is hampered due to the different spatial scales. The paper investigates the potential of using prior information on spatially persistent soil moisture fields to disaggregate SMOS scale soil moisture products. The approach is based on a ten-year soil moisture climatology, derived from a state-of-the-art land surface scheme. The developed approach shows a generally good performance for large parts of the test site, where soil moisture can be disaggregated with an accuracy better than the 4 vol.% benchmark of the SMOS mission.
In this study, the spatial pattern and correlation of surface moisture content over the Jinghe River Basin, was investigated by using in-situ measurements and remotely sensed data. First of all, the spatial pattern of the soil moisture content was retrieved from the MODIS imagery based on a statistical relationship between the Temperature Vegetation Dryness Index (TVDI) and in- situ soil moisture measurements over the basin, then the geo-statistic analysis methods and semi-variogram function were applied on the derived soil moisture for investigating the spatial correlations of soil moisture content. It was found that the magnitude of the field measured soil moisture content was correlated with the adjacent pixels especially for the samples from the same land use type. The correlation length, which is increasing with the topographical attribute, can be detected and validated from the statistical characteristics of in-situ soil moisture measurements and remotely sensed data.
This guide provides information of special relevance to the planning, design, testing, installation, operation and maintenance of gas-insulated substations(GIS) and equipment. This guide is intended to supplement IEEE Std C37-122- 1993(R2002). In general, this guide is applicable to all GIS above 52 kV. However the importance of the topics covered varies with application category. For example, issues related to advanced ...