SpiderFab: Process for On-Orbit Construction of Kilometer-Scale Apertures

The SpiderFab effort has investigated the value proposition and feasibility of radically changing the way we build and deploy spacecraft by enabling space systems to fabricate and integrate key components on-orbit. In this Phase II effort, we have focused on developing and demonstrating tools and processes to enable robotic systems to manufacture and assemble high performance structural elements that will serve as the support structures for components such as antennas and solar arrays. Through testing of these technologies in the laboratory environment,these efforts have established the technical feasibility of the key capabilities required for in-space manufacture of large apertures such as antennas, solar arrays, and optical systems,maturing prototype technical solutions for these capabilities to TRL-4. The SpiderFab effort has resulted in successful post-NIAC transition of the technology, first to SBIR-funded development of a technology for in-space manufacture (ISM) of truss structures, and then to a NASA/STMD Tipping Point Technologies funded effort to prepare a flight demonstration of ISM of a structure for a GEO communications satellite

Fachzeitschrift für Hydrographie und Geoinformation

Second International Issu

SMAP L-Band Microwave Radiometer: Instrument Design and First Year on Orbit

The Soil Moisture Active Passive (SMAP) L-band microwave radiometer is a conical scanning instrument designed to measure soil moisture with 4 percent volumetric accuracy at 40-kilometer spatial resolution. SMAP is NASA's first Earth Systematic Mission developed in response to its first Earth science decadal survey. Here, the design is reviewed and the results of its first year on orbit are presented. Unique features of radiometer include a large 6-meter rotating reflector, fully polarimetric radiometer receiver with internal calibration, and radio-frequency interference detection and filtering hardware. The radiometer electronics are thermally controlled to achieve good radiometric stability. Analyses of on-orbit results indicate the electrical and thermal characteristics of the electronics and internal calibration sources are very stable and promote excellent gain stability. Radiometer NEdT (Noise Equivalent differential Temperature) less than 1 degree Kelvin for 17-millisecond samples. The gain spectrum exhibits low noise at frequencies greater than 1 megahertz and 1 divided by f (pink) noise rising at longer time scales fully captured by the internal calibration scheme. Results from sky observations and global swath imagery of all four Stokes antenna temperatures indicate the instrument is operating as expected

Multi-Sensor Imaging and Space-Ground Cross-Validation for 2010 Flood along Indus River, Pakistan

Flood monitoring was conducted using multi-sensor data from space-borne optical, and microwave sensors; with cross-validation by ground-based rain gauges and streamflow stations along the Indus River; Pakistan. First; the optical imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) was processed to delineate the extent of the 2010 flood along Indus River; Pakistan. Moreover; the all-weather all-time capability of higher resolution imagery from the Advanced Synthetic Aperture Radar (ASAR) is used to monitor flooding in the lower Indus river basin. Then a proxy for river discharge from the Advanced Microwave Scanning Radiometer (AMSR-E) aboard NASA’s Aqua satellite and rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) are used to study streamflow time series and precipitation patterns. The AMSR-E detected water surface signal was cross-validated with ground-based river discharge observations at multiple streamflow stations along the main Indus River. A high correlation was found; as indicated by a Pearson correlation coefficient of above 0.8 for the discharge gauge stations located in the southwest of Indus River basin. It is concluded that remote-sensing data integrated from multispectral and microwave sensors could be used to supplement stream gauges in sparsely gauged large basins to monitor and detect floods.JRC.G.2-Global security and crisis managemen

An Earth System Data Record for Land Surface Freeze/Thaw State. Algorithm Theoretical Basis Document (ATBD), Version 1

This document represents and Algorithm Theoretical Basis Document (ATBD) for developing an Earth System Data Record (ESDR) quantifying global vegetated land surface freeze/thaw state (F/T) dynamics. The freeze/thaw ESDR (FT_ESDR) will be developed using multi-frequency satellite passive and active microwave remote sensing time series spanning multiple missions and sensors, including passive microwave radiometery from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and radar scatterometry from SeaWinds-on-QuikSCAT. These records are global in extent and provide a contiguous time series extending from 1979 onward with some overlap between missions

Optimization of Soil Hydraulic Model Parameters Using Synthetic Aperture Radar Data: An Integrated Multidisciplinary Approach

It is widely recognized that Synthetic Aperture Radar (SAR) data are a very valuable source of information for the modeling of the interactions between the land surface and the atmosphere. During the last couple of decades, most of the research on the use of SAR data in hydrologic applications has been focused on the retrieval of land and biogeophysical parameters (e.g., soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such its, for example, hydraulic conductivity, values, through remote sensing. This is due to the fact that no direct relationships between the remote-sensing observations, more specifically radar backscatter values, and the parameter values can be derived. However, land surface models can provide these relationships. The objective of this paper is to retrieve a number of soil physical model parameters through a combination of remote sensing anti land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure basest on the Extended Kalman Filter equations. In fact, the land surface model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing

Global Reach: A View of International Cooperation in NASA's Earth Science Enterprise

Improving life on Earth and understanding and protecting our home planet are foremost in the Vision and Mission of the National Aeronautics and Space Administration (NASA). NASA's Earth Science Enterprise end eavors to use the unique vantage point of space to study the Earth sy stem and improve the prediction of Earth system change. NASA and its international partners study Earth's land, atmosphere, ice, oceans, a nd biota and seek to provide objective scientific knowledge to decisi onmakers and scientists worldwide. This book describes NASA's extensi ve cooperation with its international partners

Surface Soil Moisture Retrievals from Remote Sensing:Current Status, Products & Future Trends

Advances in Earth Observation (EO) technology, particularly over the last two decades, have shown that soil moisture content (SMC) can be measured to some degree or other by all regions of the electromagnetic spectrum, and a variety of techniques have been proposed to facilitate this purpose. In this review we provide a synthesis of the efforts made during the last 20 years or so towards the estimation of surface SMC exploiting EO imagery, with a particular emphasis on retrievals from microwave sensors. Rather than replicating previous overview works, we provide a comprehensive and critical exploration of all the major approaches employed for retrieving SMC in a range of different global ecosystems. In this framework, we consider the newest techniques developed within optical and thermal infrared remote sensing, active and passive microwave domains, as well as assimilation or synergistic approaches. Future trends and prospects of EO for the accurate determination of SMC from space are subject to key challenges, some of which are identified and discussed within. It is evident from this review that there is potential for more accurate estimation of SMC exploiting EO technology, particularly so, by exploring the use of synergistic approaches between a variety of EO instruments. Given the importance of SMC in Earth’s land surface interactions and to a large range of applications, one can appreciate that its accurate estimation is critical in addressing key scientific and practical challenges in today’s world such as food security, sustainable planning and management of water resources. The launch of new, more sophisticated satellites strengthens the development of innovative research approaches and scientific inventions that will result in a range of pioneering and ground-breaking advancements in the retrievals of soil moisture from space

Global evaluation of SMAP/Sentinel-1 soil moisture products

MAP/Sentinel-1 soil moisture is the latest SMAP (Soil Moisture Active Passive) product derived from synergistic utilization of the radiometry observations of SMAP and radar backscattering data of Sentinel-1. This product is the first and only global soil moisture (SM) map at 1 km and 3 km spatial resolutions. In this paper, we evaluated the SMAP/Sentinel-1 SM product from different viewpoints to better understand its quality, advantages, and likely limitations. A comparative analysis of this product and in situ measurements, for the time period March 2015 to January 2022, from 35 dense and sparse SM networks and 561 stations distributed around the world was carried out. We examined the effects of land cover, vegetation fraction, water bodies, urban areas, soil characteristics, and seasonal climatic conditions on the performance of active–passive SMAP/Sentinel-1 in estimating the SM. We also compared the performance metrics of enhanced SMAP (9 km) and SMAP/Sentinel-1 products (3 km) to analyze the effects of the active–passive disaggregation algorithm on various features of the SMAP SM maps. Results showed satisfactory agreement between SMAP/Sentinel-1 and in situ SM measurements for most sites (r values between 0.19 and 0.95 and ub-RMSE between 0.03 and 0.17), especially for dense sites without representativeness errors. Thanks to the vegetation effect correction applied in the active–passive algorithm, the SMAP/Sentinel-1 product had the highest correlation with the reference data in grasslands and croplands. Results also showed that the accuracy of the SMAP/Sentinel-1 SM product in different networks is independent of the presence of water bodies, urban areas, and soil types.Peer ReviewedPostprint (published version

Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltration-runoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weather-related satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards. <P style='line-height: 20px;'> Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques. <P style='line-height: 20px;'> Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (<I>SWVI</I>), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past. <P style='line-height: 20px;'> In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the <I>SWVI</I> was able to identify the presence of a sort of 'early' signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability