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NASA NTRSDate not supplied

Next-generation wildlife tracking devices and integrated sensors for measuring species-environment interactions and advancing conservation

Global land use and climate change have magnified the importance of collecting accurate animal movement and environmental data to improve our ability to model species interactions with the environment and promote effective conservation. Advanced animal tracking devices that couple cutting-edge technologies with our expanding need for ecological information is critical. In addition to further optimizing device size to monitor small, sensitive species, new paradigms for collecting, storing, and transmitting data about animals and their environments will propel wildlife tracking devices forward. Advanced telemetry capabilities will increase our ability to pair location and sensor data from tagged wildlife with remote sensing data. The USGS Western Ecological Research Center, NASA Ames Research Center, and collaborators have been developing new wildlife tracking devices and integrated environmental sensors to address these challenges. We describe a new, miniaturized solar GPS-enabled Globalstar satellite transmitter with accelerometer capability that is 20% lighter and 25% less expensive than existing commercially available tags. We also introduce a novel peer-to-peer, solar-powered network tag that uses long-range, low-power, wireless platform technology. Concurrently, we began adapting a carbon nanotube (CNT) sensor to detect dimethyl sulfide (DMS), a trace gas relevant to marine ecology and climate studies. CNT sensors offer a small, lightweight, and low-power technology that can detect changes in resistance across carbon nanotubes coated with adsorbent selected to specifically bind with a variety of reactive trace gasses. We flew a prototype sensor in a small UAS and sampled an apparent increase in DMS concentration consistent with a well-defined marine frontal boundary. Currently we are integrating project components to create a hybridized architecture of networked peer-to-peer and satellite tags with integrated CNT and additional on-board and remote sensors to advance animal tracking and to provide information for next generation wildlife conservation.

Ian G. Brosnan↗
NASA NTRS1981

Space Shuttle - A new era in terrestrial remote sensing

The Space Shuttle will carry its first scientific cargo into orbit on its second test flight. The seven experiments to be conducted during this flight - investigations related to continental geology, atmospheric chemistry, meteorology, marine biology, and plant physiology - will demonstrate the potential usefulness of the Shuttle for research in the earth and life sciences.

Taranik, J. V.↗
NASA NTRS1993

Milankovitch insulation forcing and cyclic formation of large-scale glacial, fluvial, and eolian landforms in central Alaska

Continuous marine and ice-core proxy climate records indicate that the Earth's orbital geometry modulates long-term changes. Until recently, little direct evidence has been available to demonstrate correlations between Milankovitch cycles and large-scale terrestrial landforms produced during worldwide glaciations. In central Alaska large areas of loess and sand fill valleys and basins near major outwash streams. The streams themselves are bordered by sets of outwash terraces, and the terraces grade up valley into sets of moraines. The discovery of the Stampede tephra (approximately 175,000 yr ago) reworked within push moraines of the Lignite Creek glaciation suggests that this event correlates with the glaciation of marine isotope stage 6. A new occurrence of the Old Crow tephra (approximately 140,000 yr ago) on the surface of the oldest outwash terrace of the Tanana River, correlated with Delta glaciation, suggests this event also occurred at this time. The penultimate Healy glaciation apparently correlates with marine isotope stage 4, while radiocarbon dates indicate the latest Pleistocene moraines correlate with marine isotope stage 2. Recognition of the importance of orbital forcing to the cyclical formation of glacial landforms and landscapes can help in interpretations of remotely sensed glacial and proglacial land forms.

Beget, J. E.↗
NASA NTRS2012

Estimating Marine Aerosol Particle Volume and Number from Maritime Aerosol Network Data

As well as spectral aerosol optical depth (AOD), aerosol composition and concentration (number, volume, or mass) are of interest for a variety of applications. However, remote sensing of these quantities is more difficult than for AOD, as it is more sensitive to assumptions relating to aerosol composition. This study uses spectral AOD measured on Maritime Aerosol Network (MAN) cruises, with the additional constraint of a microphysical model for unpolluted maritime aerosol based on analysis of Aerosol Robotic Network (AERONET) inversions, to estimate these quantities over open ocean. When the MAN data are subset to those likely to be comprised of maritime aerosol, number and volume concentrations obtained are physically reasonable. Attempts to estimate surface concentration from columnar abundance, however, are shown to be limited by uncertainties in vertical distribution. Columnar AOD at 550 nm and aerosol number for unpolluted maritime cases are also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) data, for both the present Collection 5.1 and forthcoming Collection 6. MODIS provides a best-fitting retrieval solution, as well as the average for several different solutions, with different aerosol microphysical models. The average solution MODIS dataset agrees more closely with MAN than the best solution dataset. Terra tends to retrieve lower aerosol number than MAN, and Aqua higher, linked with differences in the aerosol models commonly chosen. Collection 6 AOD is likely to agree more closely with MAN over open ocean than Collection 5.1. In situations where spectral AOD is measured accurately, and aerosol microphysical properties are reasonably well-constrained, estimates of aerosol number and volume using MAN or similar data would provide for a greater variety of potential comparisons with aerosol properties derived from satellite or chemistry transport model data.

Sayer, A. M.↗
NASA NTRS2018

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
NASA NTRS1977

Literature review of the remote sensing of natural resources

Abstracts of 596 documents related to remote sensors or the remote sensing of natural resources by satellite, aircraft, or ground-based stations are presented. Topics covered include general theory, geology and hydrology, agriculture and forestry, marine sciences, urban land use, and instrumentation. Recent documents not yet cited in any of the seven information sources used for the compilation are summarized. An author/key word index is provided.

Fears, C. B.↗
NASA NTRS1981

Determining economic benefits of satellite data in short-range forecasting

The chances of enhanced short term weather predictions and economic benefits from the use of GOES satellite data were examined. Results for a meteorological consulting firm before and after the introduction of GOES data were chosen as the method, and monetary benefits were selected as the measure. Services were provided for use by road and street departments, commodities dealers, and marine clients of the consulting firm. The Man-computer Interactive Data Access Program (McIDAS) was employed to furnish 1/2 hour visual or IR imagery for remote access. The commodities clients reconnected the GOES real-time imagery once the study was completed, while the consulting firm, which was personnel and not equipment intensive, did not. Further development of the flexibility of access to the GOES data and improvements in the projected grids are indicated.

Suchman, D.↗
NASA NTRS2009

Towards an Autonomous Space In-Situ Marine Sensorweb

We describe ongoing efforts to integrate and coordinate space and marine assets to enable autonomous response to dynamic ocean phenomena such as algal blooms, eddies, and currents. Thus far we have focused on the use of remote sensing assets (e.g. satellites) but future plans include expansions to use a range of in-situ sensors such as gliders, autonomous underwater vehicles, and buoys/moorings.

Chien, S.↗
NASA NTRS2020

Current and Future Remote Sensing of Harmful Algal Blooms in the Chesapeake Bay to Support the Shellfish Industry

Harmful algal bloom (HAB) species in the Chesapeake Bay can negatively impact fish, shellfish, and human health via the production of toxins and the degradation of water quality. Due to the deleterious effects of HAB species on economically and environmentally important resources, such as oyster reef systems, Bay area resource managers are seeking ways to monitor HABs and water quality at large spatial and fine temporal scales. The use of satellite ocean color imagery has proven to be a beneficial tool for resource management in other locations around the world where high-biomass, nearly monospecific HABs occur. However, remotely monitoring HABs in the Chesapeake Bay is complicated by the presence of multiple, often co-occurring, species and optically-complex waters. Here we present a summary of common marine and estuarine HAB species found in the Chesapeake Bay, Alexandrium monilatum, Karlodinium veneficum, Margalefidinium polykrikoides, and Prorocentrum minimum, that have been detected from space using multispectral data products from the Ocean and Land Color Imager (OLCI) sensor on the Sentinel-3 satellites and identified based on historic phytoplankton data, in situ sampling, and ecological associations. We review how future hyperspectral instruments will improve discrimination of potentially harmful species from other phytoplankton communities and present a framework in which satellite data products could aid Chesapeake Bay resource managers with monitoring water quality and protecting shellfish resources.

Chesapeake Bay, satellite remote sensing, harmful ↗
NASA NTRS1984

Biological Oceanography

Within the framework of global biogeochemical cycles and ocean productivity, there are two areas that will be of particular interest to biological oceanography in the 1990s. The first is the mapping in space time of the biomass and productivity of phytoplankton in the world ocean. The second area is the coupling of biological and physical processes as it affects the distribution and growth rate of phytoplankton biomass. Certainly other areas will be of interest to biological oceanographers, but these two areas are amenable to observations from satellites. Temporal and spatial variability is a regular feature of marine ecosystems. The temporal and spatial variability of phytoplankton biomass and productivity which is ubiquitous at all time and space scales in the ocean must be characterized. Remote sensing from satellites addresses these problems with global observations of mesocale (2 to 20 days, 10 to 200 km) features over a long period of time.

Abbott, M. R.↗
NASA NTRS1989

New approaches to the measurement of chlorophyll, related pigments and productivity in the sea

In the 1984 SBIR Call for Proposals, NASA solicited new methods to measure primary production and chlorophyll in the ocean. Biospherical Instruments Inc. responded to this call with a proposal first to study a variety of approaches to this problem. A second phase of research was then funded to pursue instrumentation to measure the sunlight stimulated naturally occurring fluorescence of chlorophyll in marine phytoplankton. The monitoring of global productivity, global fisheries resources, application of above surface-to-underwater optical communications systems, submarine detection applications, correlation, and calibration of remote sensing systems are but some of the reasons for developing inexpensive sensors to measure chlorophyll and productivity. Normally, productivity measurements are manpower and cost intensive and, with the exception of a very few expensive multiship research experiments, provide no contemporaneous data. We feel that the patented, simple sensors that we have designed will provide a cost effective method for large scale, synoptic, optical measurements in the ocean. This document is the final project report for a NASA sponsored SBIR Phase 2 effort to develop new methods for the measurements of primary production in the ocean. This project has been successfully completed, a U.S. patent was issued covering the methodology and sensors, and the first production run of instrumentation developed under this contract has sold out and been delivered.

Booth, C. R.↗
NASA NTRS1977

Interpretations of optical observations of Mercury and the moon

Optical, thermal and radar remote-sensing measurements indicate that Mercury is covered with a relatively thick layer of soil similar in texture and thickness to lunar regolith. Photometric limb profiles measured by Mariner 10 imply that the small-scale slopes on Mercury are about half those on the moon, probably because of differing gravity. The differential photometric functions of Mercury and the moon have a latitudinal dependence which can be completely accounted for by shadowing in craters. The lack of polar darkening on Mercury in spite of the presence of a magnetic field implies that the dominant soil-darkening process on Mercury, and by extension, on the moon is not dependent on the solar wind, but probably is deposition of material evaporated by meteorite impacts. Recent measurements of Mercury's spectral reflectivity in the IR and vacuum UV are both consistent with the surface rocks of Mercury being lower in FeO than those of the moon. Based on laboratory experiments the average FeO content on the surface of Mercury is estimated to be between 3 and 6%.

Hapke, B.↗
NASA NTRS1980

Clamshell door system

Space shuttle system opens, closes, and latches bay doors. System includes remotely controlled "zipper latch" that accomodates misalignment. Opening, closing, and latching follow specific sequences, and are monitored from cockpit. Entire system could be modified for commercial jetliners and marine vessels with underwater access doors.

Helble, D. R.↗
NASA NTRS1992

Satellite-derived surface latent heat fluxes in a rapidly intensifying marine cyclone

The aim of this article is to estimate surface latent heat fluxes in the vicinity of a rapidly deepening cyclone before and during its period of most rapid intensification. This is done with a bulk parameterization scheme and remotely sensed input data. A method for estimating the difference in specific humidity between the surface and a 10-m height is investigated using the Special Sensor Microwave/Imager-observed integrated water vapor field and a sea surface temperature analysis. The surface latent heat flux fields generally have estimated errors below 40 percent south of 40 deg N and outside the region of high integrated water vapor values associated with frontal bands. The method of estimating surface latent heat fluxes for the case study was found to be usable in most regions of the northwest Atlantic Ocean except for those locations directly adjacent to coastlines in instances of offshore flow and in the vicinity of surface fronts.

Miller, Douglas K.↗
NASA NTRS1992

Soluble species in the Arctic summer troposphere - Acidic gases, aerosols, and precipitation

The large-scale spatial distribution from 0.15-to 6 km altitude in the North American Arctic troposphere of several soluble acidic gases and major aerosol species during the summertime is reported. The distribution is found to be compositionally consistent on a large spatial scale. The summertime troposphere is an acidic environment, with HCOOH and CH3COOH the principal acidic gases while acidic sulfate aerosols dominate the particulate phase. There appears to be a surface source of NH3 over the pack ice which may originate from decay of dead marine organisms on the ice surface, evolution from surface ocean waters in open ice leads, or release from rotting sea ice. At low altitude over the pack ice this NH34 appears to partially neutralize aerosol acidity. Over sub-Arctic tundra in southeastern Alaska, inputs of marine biogenic sulfur from the Bering Sea appear to be an important source of boundary layer aerosol SO4(2-). The rainwater acidity over the tundra is typical of remote regions.

Talbot, R. W.↗
NASA NTRS1970

Remote sensing and the pelagic fisheries environment off Oregon

Remote sensing oceanography at Oregon State University is part of a multidisciplinary research program: (1) to learn more about nearshore oceanographic processes and how they affect the production of marine life and the availability of albacore tuna; and (2) to provide fishermen with information in near real time that will be useful in scouting for albacore concentrations.

Pearcy, W. G.↗
NASA NTRS1975

Information needs: Perceived and real for state decisionmakers

Remote sensing techniques provide important information for land and water use planning organizations in order to assess coastal developments and their impact on water resources, sediment transport, erosion, and marine biology. Political expediency requires pertinent data acquisition and data dissemination to local populations for coastal zone management decision making.

Schwartz, A. R.↗