The Red Edge in Arid Region Vegetation: 340-1060 nm Spectra
This paper describes the detection of narrow spectral features in vegetation and the reports of the detection of the
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This paper describes the detection of narrow spectral features in vegetation and the reports of the detection of the
In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March–April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial–temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.
Two recent field campaigns offer unique new opportunities to survey coupled aerosol and cloud processes operating within cold-air outbreaks (CAOs). NASA's 2019-2023 Aerosol Cloud meTeorology Interactions oVer the western Atlantic Experiment (ACTIVATE) project provided airborne in situ and remote sensing observations in multiple CAOs off the central US Eastern Seaboard. Contemporaneously, DOE's 2019-2020 Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) provided continuous ground-based in situ and remote sensing measurements during hundreds of hours of CAO conditions at two sites flanking the Norwegian Sea. Here we highlight lessons learned from contrasting sets of aerosol-aware Lagrangian large-eddy simulation case studies derived from each campaign, as well as outstanding uncertainties. Cases simulated include all of the most extensively sampled CAO flights during ACTIVATE, and a wide range of CAO strengths and mesoscale structures during COMBLE. Each case study is also suitable for simulation with large-scale models in single-column model mode or with a limited-domain approach using periodic boundary conditions. We seek to address the central question: what microphysical process pathways control the Lagrangian evolution of surface and top-of-atmosphere radiative fluxes under ACTIVATE and COMBLE conditions? Many science team members, co-investigators, and collaborators will be gratefully acknowledged in association with their contributions to making this work possible.
Due to their fast evolution and large natural variability in macro- and microphysical properties, the accurate representation of boundary layer clouds in current climate models remains a challenge. One of the regions with large intermodel spread in the Coupled Model Intercomparison Project Phase 6 ensemble is the western North Atlantic Ocean. Here, statistically representative in situ measurements can help to develop and constrain the parameterization of clouds in global models. To this end, we performed comprehensive measurements of boundary layer clouds, aerosol, trace gases, and radiation in the western North Atlantic Ocean during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. In total, 174 research flights with 574 flight hours for cloud and precipitation measurements were performed with the HU-25 Falcon during three winter (February–March 2020, January–April 2021, and November 2021–March 2022) and three summer seasons (August–September 2020, May–June 2021, and May–June 2022). Here we present a statistical evaluation of 16 140 individual cloud events probed by the fast cloud droplet probe and the two-dimensional stereo cloud probe during 155 research flights in a representative and repetitive flight strategy allowing for robust statistical data analyses. We show that the vertical profiles of distributions of the liquid water content and the cloud droplet effective diameter (ED) increase with altitude in the marine boundary layer. Due to higher updraft speeds, higher cloud droplet number concentrations (N liquid ) were measured in winter compared to summer despite lower cloud condensation nucleus abundance. Flight cloud cover derived from statistical analysis of in situ data is reduced in summer and shows large variability. This seasonal contrast in cloud coverage is consistent with a dominance of a synoptic pattern in winter that favors conditions for the formation of stratiform clouds at the western edge of cyclones (post-cyclonic). In contrast, a dominant summer anticyclone is concomitant with the occurrence of shallow cumulus clouds and lower cloud coverage. The evaluation of boundary layer clouds and precipitation in the N liquid ED phase space sheds light on liquid, mixed-phase, and ice cloud properties and helps to categorize the cloud data. Ice and liquid precipitation, often masked in cloud statistics by a high abundance of liquid clouds, is often observed throughout the cloud. The ACTIVATE in situ cloud measurements provide a wealth of cloud information useful for assessing airborne and satellite remote-sensing products, for global climate and weather model evaluations, and for dedicated process studies that address precipitation and aerosol–cloud interactions.
Scanning holographic lidar receivers are currently in use in two operational lidar systems, PHASERS (Prototype Holographic Atmospheric Scanner for Environmental Remote Sensing) and now HARLIE (Holographic Airborne Rotating Lidar Instrument Experiment). These systems are based on volume phase holograms made in dichromated gelatin (DCG) sandwiched between 2 layers of high quality float glass. They have demonstrated the practical application of this technology to compact scanning lidar systems at 532 and 1064 nm wavelengths, the ability to withstand moderately high laser power and energy loading, sufficient optical quality for most direct detection systems, overall efficiencies rivaling conventional receivers, and the stability to last several years under typical lidar system environments. Their size and weight are approximately half of similar performing scanning systems using reflective optics. The cost of holographic systems will eventually be lower than the reflective optical systems depending on their degree of commercialization. There are a number of applications that require or can greatly benefit from a scanning capability. Several of these are airborne systems, which either use focal plane scanning, as in the Laser Vegetation Imaging System or use primary aperture scanning, as in the Airborne Oceanographic Lidar or the Large Aperture Scanning Airborne Lidar. The latter class requires a large clear aperture opening or window in the aircraft. This type of system can greatly benefit from the use of scanning transmission holograms of the HARLIE type because the clear aperture required is only about 25% larger than the collecting aperture as opposed to 200-300% larger for scan angles of 45 degrees off nadir.
Scientists within NASA s Applied Sciences Directorate have developed a well-characterized remote sensing Verification & Validation (V&V) site at the John C. Stennis Space Center (SSC). This site enables the in-flight characterization of satellite and airborne high spatial and moderate resolution remote sensing systems and their products. The smaller scale of the newer high resolution remote sensing systems allows scientists to characterize geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active lidar systems. SSC employs geodetic targets, edge targets, radiometric tarps, atmospheric monitoring equipment, and thermal calibration ponds to characterize remote sensing data products. The SSC Instrument Validation Lab is a key component of the V&V capability and is used to calibrate field instrumentation and to provide National Institute of Standards and Technology traceability. This poster presents a description of the SSC characterization capabilities and examples of calibration data.
A 36 GHz computer controlled airborne Surface Contour Radar (SCR) is described, which was developed by the Naval Research Laboratory and NASA. The system uses pulse-compression techniques and dual frequency carriers spaced far enough apart to be decorrelated on the sea surface. The continuous wave transmitter is biphase modulated, the return signal is autocorrelated, and the code length and clock rate are variable, providing selectable range resolutions of 0.15, 0.30, 0.61 and 1.52 m. The SCR generates a false-color coded elevation map of the sea surface below the aircraft in real time, and can routinely produce ocean directional wave spectra with off-line data processing.
This paper describes a program of airborne radiometric imaging at 90 GHz and 140 GHz. Using high sensitivity (below 1 K) and high angular resolution (0.5-1.0 degree), high quality images have been made. The following measurements are discussed: cloud and fog penetration at 90 GHz, discrimination between agricultural and urban areas, discrimination between different vegetation types, detection of vehicles on roads, detection and classification of airports and airplanes, ship detection and quantitative oil spill sensing. The application of information enhancement techniques with automatic and real time application aspects is also described, and results of applied techniques for contrast and contour enhancement are shown.
We highlight three emerging NASA optical technologies that enhance our ability to remotely sense, analyze, and explore ocean worlds–FluidCam and fluid lensing, MiDAR, and NeMO-Net. Fluid lensing is the first remote sensing technology capable of imaging through ocean waves without distortions in 3D at sub-cm resolutions. Fluid lensing and the purpose-built FluidCam CubeSat instruments have been used to provide refraction-corrected 3D multispectral imagery of shallow marine systems from unmanned aerial vehicles (UAVs). Results from repeat 2013 and 2016 airborne fluid lensing campaigns over coral reefs in American Samoa present a promising new tool for monitoring fine-scale ecological dynamics in shallow aquatic systems tens of square kilometers in area. MiDAR is a recently-patented active multispectral remote sensing and optical communications instrument which evolved from FluidCam. MiDAR is being tested on UAVs and autonomous underwater vehicles (AUVs) to remotely sense living and non-living structures in light-limited and analog planetary science environments. MiDAR illuminates targets with high-intensity narrowband structured optical radiation to measure an object’s spectral reflectance while simultaneously transmitting data. MiDAR is capable of remotely sensing reflectance at fine spatial and temporal scales, with a signal-to-noise ratio 10-10(exp 3) times higher than passive airborne and spaceborne remote sensing systems, enabling high-framerate multispectral sensing across the ultraviolet, visible, and near-infrared spectrum. Preliminary results from a 2018 mission to Guam show encouraging applications of MiDAR to imaging coral from airborne and underwater platforms whilst transmitting data across the air-water interface. Finally, we share NeMO-Net, the Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment. NeMO-Net is a machine learning technology under development that exploits high-resolution data from FluidCam and MiDAR for augmentation of low-resolution airborne and satellite remote sensing. NeMO-Net is intended to harmonize the growing diversity of 2D and 3D remote sensing with in situ data into a single open-source platform for assessing shallow marine ecosystems globally using active learning for citizen-science based training. Preliminary results from four-class Q17 coral classification have an accuracy of 94.4%. Together, these maturing technologies present promising scalable, practical, and cost-efficient innovations that address current observational and technological challenges in optical sensing of marine systems.
Dr. Ved Chirayath's seminar will highlight new sensing technologies and airborne platforms he is developing for Earth & Space Science as director of the NASA Silicon Valley Laboratory for Advanced Sensing. His talk will feature recent work on Fluid Lensing, the first remote sensing technology capable of imaging through ocean waves in 3D at sub-cm resolutions, MiDAR, a next-generation active hyperspectral remote sensing and optical communications instrument, airborne gas sensing of multipollutant combustion sources, and a plasma actuated unmanned aerial vehicle (UAV) that utilized high-voltage dielectric discharge devices to achieve the first plasma controlled flight in history.Fluid Lensing and the NASA FluidCam instrument have been used extensively to provide distortion-free 3D multispectral imagery from UAVs of shallow marine systems around the world. MiDAR is being deployed on aircraft and underwater remotely operated vehicles (ROVs) as a new method to remotely sense living and nonliving structures in extreme environments as an analog for future Ocean Worlds robotic exploration missions. Finally, Chirayath will present preliminary results from NeMO-Net, a supercomputer-based neural network that uses a citizen science video game for global multimodal coral reef benthic habitat mapping, fusing remote sensing data from Fluid Lensing, MiDAR, NASA's Earth Observing System, and commercial satellites, to better understand the present and past dynamics of shallow marine systems. Together, these maturing technologies present promising new ways in which to explore terrestrial, marine, and aerial systems on Earth, and, ultimately, aid in the search for extraterrestrial life within our solar system and beyond.
Airborne tests of multispectral scanners to determine usefulness of remote sensors in surveying river, coastal, and deep-sea phenomena
A site-specific ocean color remote sensing algorithm was developed and used to convert Multispectral Airborne Radiometer System (MARS) spectral radiance measurements to chlorophyll-a concentration profiles along aircraft tracklines in the Greenland Sea. The analysis is described and the results given in graphical or tabular form. Section 2 describes the salient characteristics and history of development of the MARS instrument. Section 3 describes the analyses of MARS flight segments over consolidated sea ice, resulting in a set of altitude dependent ratios used (over water) to estimate radiance reflected by the surface and atmosphere from total radiance measured. Section 4 presents optically weighted pigment concentrations calculated from profile data, and spectral reflectances measured in situ from the top meter of the water column; this data was analyzed to develop an algorithm relating chlorophyll-a concentrations to the ratio of radiance reflectances at 441 and 550 nm (with a selection of coefficients dependent upon whether significant gelvin presence is implied by a low ratio of reflectances at 410 and 550 nm). Section 5 describes the scaling adjustments which were derived to reconcile the MARS upwelled radiance ratios at 410:550 nm and 441:550 nm to in situ reflectance ratios measured simultaneously on the surface. Section 6 graphically presents the locations of MARS data tracklines and positions of the surface monitoring R/V. Section 7 presents stick-plots of MARS tracklines selected to illustrate two-dimensional spatial variability within the box covered by each day's flight. Section 8 presents curves of chlorophyll-a concentration profiles derived from MARS data along survey tracklines. Significant results are summarized in Section 1.
A unique radio-oceanographic remote sensing instrument was developed. The 36 GHz airborne Surface Contour Radar (SCR) remotely produces a real-time topographical map of the sea surface beneath the aircraft. It can routinely produce ocean directional wave spectra with off-line data processing. The transmitter is a coherent dual-frequency device that uses pulse compression to compensate for the limited available power at Ka band. The radar has selectable pulse widths of 1, 2, 4, and 10 nanoseconds. The transmitting antenna is a 58 lambda horn fed dielectric lens whose axis is parallel to the longitudinal axis of the aircraft. It illuminates an elliptical mirror which is oriented 45 deg to the lens' longitudinal axis to deflect the beam towards the region beneath the aircraft. The mirror is oscillated in a sinusoidal fashion through mechanical linkages driven to a variable speed motor to scan the transmitter beam (1.2 deg X 1.2 deg) with + or - 16 deg of the perpendicular to the aircraft wings in the plane perpendicular to the aircraft flight direction.
Abstract—Active optical (Laser/Lidar) measurement techniques are critical for the future National Aeronautics and Space Administration (NASA) Earth, Planetary Science, Exploration, and Aeronautics measurements. The latest science decadal surveys recommend a number of missions requiring active optical systems to meet the science measurement objectives and the aeronautics community continues to use Laser/Lidar technologies to meet the aeronautics measurement objectives. This presentation will provide an overview of NASA efforts in developing and maturing state-of-the-art advanced solid-state flight laser/lidar systems for airborne and space-borne remote sensing measurements. The presentation will also provide details of a strategic approach for active optical technologies and techniques to meet the NASA’s future Earth and Space Science measurement ments for space-based applications.
We present NeMO-Net, the Srst open-source deep convolutional neural network (CNN) and interactive learning and training software aimed at assessing the present and past dynamics of coral reef ecosystems through habitat mapping into 10 biological and physical classes. Shallow marine systems, particularly coral reefs, are under significant pressures due to climate change, ocean acidification, and other anthropogenic pressures, leading to rapid, often devastating changes, in these fragile and diverse ecosystems. Historically, remote sensing of shallow marine habitats has been limited to meter-scale imagery due to the optical effects of ocean wave distortion, refraction, and optical attenuation. NeMO-Net combines 3D cm-scale distortion-free imagery captured using NASA FluidCam and Fluid lensing remote sensing technology with low resolution airborne and spaceborne datasets of varying spatial resolutions, spectral spaces, calibrations, and temporal cadence in a supercomputer-based machine learning framework. NeMO-Net augments and improves the benthic habitat classification accuracy of low-resolution datasets across large geographic ad temporal scales using high-resolution training data from FluidCam.NeMO-Net uses fully convolutional networks based upon ResNet and ReSneNet to perform semantic segmentation of remote sensing imagery of shallow marine systems captured by drones, aircraft, and satellites, including WorldView and Sentinel. Deep Laplacian Pyramid Super-Resolution Networks (LapSRN) alongside Domain Adversarial Neural Networks (DANNs) are used to reconstruct high resolution information from low resolution imagery, and to recognize domain-invariant features across datasets from multiple platforms to achieve high classification accuracies, overcoming inter-sensor spatial, spectral and temporal variations.Finally, we share our online active learning and citizen science platform, which allows users to provide interactive training data for NeMO-Net in 2D and 3D, integrated within a deep learning framework. We present results from the PaciSc Islands including Fiji, Guam and Peros Banhos 1 1 2 1 3 1 where 24-class classification accuracy exceeds 91%.
STRIVES Entry: 20230013683, Abstract—Active optical (Laser/Lidar) measurement techniques are critical for the future National Aeronautics and Space Administration (NASA) Earth, Planetary Science, Exploration, and Aeronautics measurements. The latest science decadal surveys recommend several missions requiring active optical systems to meet the science measurement objectives and the aeronautics community continues to use Laser/Lidar technologies to meet the aeronautics measurement objectives. This presentation will provide an overview of NASA efforts in developing and maturing state-of-the-art advanced solid-state flight laser/lidar systems for airborne and space-borne remote sensing measurements. The presentation will also provide details of a strategic approach for active optical technologies and techniques to meet the NASA’s future Earth and Space Science measurements/missions needs and requirements for space-based applications.
NASA's Ames Research Center is performing an AVIRIS demonstration project in conjunction with the U. S. Environmental Protection Agency (Region 3). NASA and EPA scientists have jointly defined a Study Area in eastern Virginia to include portions of the Chesapeake Bay, southern Delmarva Peninsula, and the mouths of the York and James Rivers. Several environmental issues have been identified for study. These include, by priority: 1) water constituent analysis in the Chesapeake Bay, 2) mapping of submerged aquatic vegetation in the Bay, 3) detection of vegetation stress related to Superfund sites at the Yorktown Naval Weapons Station, and 4) wetland species analysis in the York River vicinity. In support of this project, three lines of AVIRIS data were collected during the Wallops Island deployment on 17 August 1997. The remote sensing payload included AVIRIS, MODIS Airborne Simulator and an RC-10 color infrared film camera. The AVIRIS data were delivered to Ames from the JPL AVIRIS Data Facility, on 29 September 1997. Quicklook images indicate nominal data acquisition, and at the current time an atmospheric correction is being applied. Water constituent analysis of the Bay is our highest priority based on EPA interest and available collateral data, both from the surface and from other remote sensing instruments. Constituents of interest include suspended sediments, chlorophyll-a and accessory pigments, Analysis steps will include: verification of data quality, location of study sites in imagery, incorporation of relevant field data from EPA and other Chesapeake Bay cooperators, processing of imagery to show phenomenon of interest, verification of results with cooperators. By 1st quarter CY98 we plan to circulate initial results to NASA and EPA management for review. In the longer term we will finalize documentation, prepare results for publication, and complete any needed technology transfer to EPA remote sensing personnel.