Airborne Wind Shear Detection and Warning Systems. Second Combined Manufacturers' and Technologists' Conference, part 1

The Second Combined Manufacturers' and Technologists' Conference hosted jointly by NASA Langley (LaRC) and the Federal Aviation Administration (FAA) was held in Williamsburg, Virginia, on October 18 to 20, 1988. The purpose of the meeting was to transfer significant, ongoing results gained during the second year of the joint NASA/FAA Airborne Wind Shear Program to the technical industry and to pose problems of current concern to the combined group. It also provided a forum for manufacturers to review forward-look technology concepts and for technologists to gain an understanding of the problems encountered by the manufacturers during the development of airborne equipment and the FAA certification requirements

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Mapping forest structure in Mississippi using LiDAR remote sensing

This study aimed at evaluating the agreement of spaceborne Light Detection and Ranging (lidar) ICESat-2 canopy height with Airborne Laser Scanning (ALS) derived canopy height to inform about the performance of ICESat-2 canopy height metrics and understand its uncertainties and utilities. The agreement was assessed for different forest types, physiographic regions, a range of percent canopy cover, and diverse disturbance histories. Results of this study suggest that best agreements are found using strong beam data collected at night for canopy height retrieval using ICESat-2. The ICESat-2 showed great potential for estimating canopy heights, particularly in evergreen forests with high canopy cover. Statistical models were developed using fixed-effects and mixed-effects modeling approaches to predict ALS canopy height metrics using ICESat-2 parameters and other attributes. Overall, ICESat-2 showed good agreement with ALS canopy height and showed its predictive ability to characterize canopy height. The outcome of this study will help the scientific community understand the capabilities and limitations of ICESat-2 canopy heights; the study also provides a new approach to obtain wall-to-wall ALS standard canopy height maps at landscape level

Development of a Multimode Instrument for Remote Measurements of Unsaturated Soil Properties

The hydromechanical behavior of soil is governed by parameters that include the moisture content, soil matric potential, texture, and the mineralogical composition of the soil. Remote characterization of these and other key properties of the soil offers advantages over conventional in situ or laboratory-based measurements: information may be acquired rapidly over large, or inaccessible areas; samples do not need to be collected; and the measurements are non-destructive. A field-deployable, ground-based remote sensor, designated the Soil Observation Laser Absorption Spectrometer (SOLAS), was developed to infer parameters of bare soils and other natural surfaces over intermediate (100 m) and long (1,000 m) ranges. The SOLAS methodology combines hyperspectral remote sensing with differential absorption and laser ranging measurements. A transmitter propagates coherent, near-infrared light at on-line (823.20 nm) and off-line (847.00 nm) wavelengths. Backscattered light is received through a 203-mm diameter telescope aperture and is divided into two channels to enable simultaneous measurements of spectral reflectance, differential absorption, and range to the target. The spectral reflectance is measured on 2151 continuous bands that range from visible (380 nm) to shortwave infrared (2500 nm) wavelengths. A pair of photodetectors receive the laser backscatter in the 820–850 nm range. Atmospheric water vapor is inferred using a differential absorption technique in conjunction with an avalanche photodetector, while range to the target is based on a frequency-modulated, self-chirped, homodyne detection scheme. The design, fabrication, and testing of the SOLAS is described herein. The receiver was optimized for the desired backscatter measurements and assessed through a series of trials that were conducted in both indoor and outdoor settings. Spectral reflectance measurements collected at proximal range compared well with measurements collected at intermediate ranges, demonstrating the utility of the receiver. Additionally, the noise characteristics of the spectral measurements were determined across the full range of the detected wavelengths. Continued development of the SOLAS instrument will enable range-resolved and water vapor-corrected reflectance measurements over longer ranges. Anticipated applications for the SOLAS technology include rapid monitoring of earth construction projects, geohazard assessment, or ground-thruthing for current and future satellite-based multi- and hyperspectral data

Gazing at the Solar System: Capturing the Evolution of Dunes, Faults, Volcanoes, and Ice from Space

Gazing imaging holds promise for improved understanding of surface characteristics and processes of Earth and solar system bodies. Evolution of earthquake fault zones, migration of sand dunes, and retreat of ice masses can be understood by observing changing features over time. To gaze or stare means to look steadily, intently, and with fixed attention, offering the ability to probe the characteristics of a target deeply, allowing retrieval of 3D structure and changes on fine and coarse scales. Observing surface reflectance and 3D structure from multiple perspectives allows for a more complete view of a surface than conventional remote imaging. A gaze from low Earth orbit (LEO) could last several minutes allowing for video capture of dynamic processes. Repeat passes enable monitoring time scales of days to years. Numerous vantage points are available during a gaze (Figure 1). Features in the scene are projected into each image frame enabling the recovery of dense 3D structure. The recovery is robust to errors in the spacecraft position and attitude knowledge, because features are from different perspectives. The combination of a varying look angle and the solar illumination allows recovering texture and reflectance properties and permits the separation of atmospheric effects. Applications are numerous and diverse, including, for example, glacier and ice sheet flux, sand dune migration, geohazards from earthquakes, volcanoes, landslides, rivers and floods, animal migrations, ecosystem changes, geysers on Enceladus, or ice structure on Europa. The Keck Institute for Space Studies (KISS) hosted a workshop in June of 2014 to explore opportunities and challenges of gazing imaging. The goals of the workshop were to develop and discuss the broad scientific questions that can be addressed using spaceborne gazing, specific types of targets and applications, the resolution and spectral bands needed to achieve the science objectives, and possible instrument configurations for future missions. The workshop participants found that gazing imaging offers the ability to measure morphology, composition, and reflectance simultaneously and to measure their variability over time. Gazing imaging can be applied to better understand the consequences of climate change and natural hazards processes, through the study of continuous and episodic processes in both domains

Airborne laser sensors and integrated systems

The underlying principles and technologies enabling the design and operation of airborne laser sensors are introduced and a detailed review of state-of-the-art avionic systems for civil and military applications is presented. Airborne lasers including Light Detection and Ranging (LIDAR), Laser Range Finders (LRF), and Laser Weapon Systems (LWS) are extensively used today and new promising technologies are being explored. Most laser systems are active devices that operate in a manner very similar to microwave radars but at much higher frequencies (e.g., LIDAR and LRF). Other devices (e.g., laser target designators and beam-riders) are used to precisely direct Laser Guided Weapons (LGW) against ground targets. The integration of both functions is often encountered in modern military avionics navigation-attack systems. The beneficial effects of airborne lasers including the use of smaller components and remarkable angular resolution have resulted in a host of manned and unmanned aircraft applications. On the other hand, laser sensors performance are much more sensitive to the vagaries of the atmosphere and are thus generally restricted to shorter ranges than microwave systems. Hence it is of paramount importance to analyse the performance of laser sensors and systems in various weather and environmental conditions. Additionally, it is important to define airborne laser safety criteria, since several systems currently in service operate in the near infrared with considerable risk for the naked human eye. Therefore, appropriate methods for predicting and evaluating the performance of infrared laser sensors/systems are presented, taking into account laser safety issues. For aircraft experimental activities with laser systems, it is essential to define test requirements taking into account the specific conditions for operational employment of the systems in the intended scenarios and to verify the performance in realistic environments at the test ranges. To support the development of such requirements, useful guidelines are provided for test and evaluation of airborne laser systems including laboratory, ground and flight test activities

Deep Learning Methods for Remote Sensing

Remote sensing is a field where important physical characteristics of an area are exacted using emitted radiation generally captured by satellite cameras, sensors onboard aerial vehicles, etc. Captured data help researchers develop solutions to sense and detect various characteristics such as forest fires, flooding, changes in urban areas, crop diseases, soil moisture, etc. The recent impressive progress in artificial intelligence (AI) and deep learning has sparked innovations in technologies, algorithms, and approaches and led to results that were unachievable until recently in multiple areas, among them remote sensing. This book consists of sixteen peer-reviewed papers covering new advances in the use of AI for remote sensing