SEARCH · Search NASA

Results for “remote data collection”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

NASA NTRS2021

Tonlé Sap Food Security and Agriculture II: Evaluating Changes in Ecosystem Vitality and Freshwater Healthin the Tonlé Sap Basin using Remotely Sensed Data

The Tonlé Sap Lake and river basin in central Cambodia provide critical ecosystem services to the region, including fisheries, agricultural irrigation, hydropower, and biodiverse habitats. Deforestation, increased pumping for farming, and effects of climate change such as droughts and forest fires threaten the health of the lake and food security in the region. This project built upon the previous term through a partnership with Conservation International (CI), the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority to assess ecosystem vitality and implement CI’s Freshwater Health Index (FHI) tool, in an effort to prioritize resource expenditure and highlight areas of concern. Due to the COVID-19 pandemic and related travel restrictions, partners had not been able to readily collect in situ data for the past year, which make up the majority of FHI inputs. To help fill this data gap, we developed a methodology for using Gravity Recovery and Climate Experiment (GRACE) satellite data to calculate groundwater storage depletion, and a Python Application Programming Interface for processing and formatting remotely-sensed data for the Soil and Water Assessment Tool (SWAT) model. We then used SWAT to model nutrient flows and of phosphorous, nitrogen and suspended sediments amounts in the basin from October 2000 to December 2020. These outputs served as inputs for the FHI and provided policy makers with robust monitoring information to aid decision-making in the area and safeguard the lake’s vital fisheries and biodiversity.

Justine Spore↗

NASA NTRS1984

Remotely sensed sea surface temperature variability off California during a 'Santa Ana' clearing

Multichannel atmospheric correction equations for the NOAA 6 proposed by Bernstein (1982) and by McClain (1981) are evaluated by using satellite and in situ data collected over and in the Southern California Bight. The temporal and spatial variation of sea surface temperature over small scales is estimated from the data, and the effect of this variation in matching satellite and in situ data sets is discussed. Changes in the temperature fields between images are examined for diurnal variation and for surface advection of horizontal temperature gradients.

Lynn, R. J.↗

NASA NTRS2008

Wireless Sensor Network Handles Image Data

To relay data from remote locations for NASA s Earth sciences research, Goddard Space Flight Center contributed to the development of "microservers" (wireless sensor network nodes), which are now used commercially as a quick and affordable means to capture and distribute geographical information, including rich sets of aerial and street-level imagery. NASA began this work out of a necessity for real-time recovery of remote sensor data. These microservers work much like a wireless office network, relaying information between devices. The key difference, however, is that instead of linking workstations within one office, the interconnected microservers operate miles away from one another. This attribute traces back to the technology s original use: The microservers were originally designed for seismology on remote glaciers and ice streams in Alaska, Greenland, and Antarctica-acquiring, storing, and relaying data wirelessly between ground sensors. The microservers boast three key attributes. First, a researcher in the field can establish a "managed network" of microservers and rapidly see the data streams (recovered wirelessly) on a field computer. This rapid feedback permits the researcher to reconfigure the network for different purposes over the course of a field campaign. Second, through careful power management, the microservers can dwell unsupervised in the field for up to 2 years, collecting tremendous amounts of data at a research location. The third attribute is the exciting potential to deploy a microserver network that works in synchrony with robotic explorers (e.g., providing ground truth validation for satellites, supporting rovers as they traverse the local environment). Managed networks of remote microservers that relay data unsupervised for up to 2 years can drastically reduce the costs of field instrumentation and data rec

Source record↗

NASA NTRS1993

C-band radar backscatter of sea ice in the Weddell Sea, Antarctica during the austral winter of 1992

A C-band ship-based scatterometer was used to measure the backscatter coefficient of sea ice in the Weddell Sea during June and July 1992. These are the first microwave scatterometer data ever to be collected in the Antarctic sea ice cover during the austral winter. The instrument was a frequency-modulated continuous-wave (FM-CW) radar altimeter modified by the University of Kansas Radar Systems and Remote Sensing Laboratory to perform backscatter measurements. Measurements were taken as part of a Jet Propulsion Laboratory experiment aboard the German ice research vessel F.S. Polarstern. Backscatter measurements were performed at incidence angles ranging from 17 to 65 degrees with VV and HV polarization as the Polarstern travelled from east to west across the central Weddell Sea. Backscatter measurements were made of several different types of ice sea including pancake, dark nilas, white nilas, grey, first-year and second-year ice. Periodic external calibrations were performed with the aid of a Luneberg Lens to enable absolute values of backscatter to be derived from the data. At each radar measurement location, in-situ measurements were made of snow and sea ice. Physical and chemical analyses of ice core and snow samples, together with high magnification photography of snow crystallography provide important information with which to develop physical models of the scattering systems. Meteorological information and oceanographic conditions were also recorded throughout the experiment. Many of the stations were chosen to coincide with periods of near-simultaneous or coincident imaging by the ERS-1 satellite Synthetic Aperture Radar (SAR). This enabled spaceborne imaging by the C-band SAR of areas of sea ice in which backscatter measurements were taken. This provides a valuable tool for interpretation of satellite SAR imagery from Antarctic sea ice in terms of the physical properties of the sea ice and snow. Preliminary results of the backscatter from the various ice types and their relation to the physical properties of sea ice are presented.

Hosseinmostafa, R.↗

NASA NTRS1973

Study of the marine environment of the northern Gulf of California

The author has identified the following significant results. Results of studies of the oceanography of the northern Gulf of California (Mexico) are reported. A remote, instrumented buoy measuring and telemetering oceanographic data by ERTS-1 satellite was designed, constructed, deployed, and tested. Regular cruises by a research ship on a pattern of 47 oceanographic stations collected data which are analyzed and referenced to analysis of ERTS-1 satellite imagery. A thermal dynamic model of current patterns in the northern Gulf of California is proposed. Findings are examined in relation to the model.

Hendrickson, J. R.↗

NASA NTRS1981

Crew optimized Shuttle/experiment pointing

The extensive participation of the Shuttle crewmembers (Commander, Pilot, Mission Specialist, and Payload Specialist) in Shuttle/experiment pointing is required to accomplish and enhance payload pointing operations and to optimize associated data collection. For payloads requiring extensive pointing operations, the degree of mission success which can be achieved by the involvement of the crew can not be matched by a combination of remote ground operations and automation. The importance of the use of the crew's manipulative skills, scientific judgment, and flexibility in the alteration of preplanned time lines was clearly demonstrated during the Skylab Apollo Telescope Mount solar experiment operations. The payload pointing operations associated with the Spacelab Instrument Pointing System and the Annular Suspension and Pointing System Gimbal System will also extensively use these crew capabilities. Crew operations will also play a potentially important role in the use of advanced pointing systems to accurately point experiments which have an extensive interaction with the surrounding environment, such as laser experiments.

Holt, A. C.↗

NASA NTRS2006

C3 System Performance Simulation and User Manual. Getting Started: Guidelines for Users

This document is a User's Manual describing the C3 Simulation capabilities. The subject work was designed to simulate the communications involved in the flight of a Remotely Operated Aircraft (ROA) using the Opnet software. Opnet provides a comprehensive development environment supporting the modeling of communication networks and distributed systems. It has tools for model design, simulation, data collection, and data analysis. Opnet models are hierarchical -- consisting of a project which contains node models which in turn contain process models. Nodes can be fixed, mobile, or satellite. Links between nodes can be physical or wireless. Communications are packet based. The model is very generic in its current form. Attributes such as frequency and bandwidth can easily be modified to better reflect a specific platform. The model is not fully developed at this stage -- there are still more enhancements to be added. Current issues are documented throughout this guide.

Source record↗

NASA NTRS2019

Flood Mapping of Recent Major Hurricane Events with Synthetic Aperture Radar, Commercial Imaging, and Aerial Observations

Floodwater mapping is an important remote sensing process that is used for disaster response, recovery, and damage assessment practices. Developing a system to read in Synthetic Aperture Radar (SAR) data and perform land cover classification will allow for the production of near real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of the situation. SAR is a unique remote sensing tool. Data in this project was obtained by NASA Jet Propulsion Laboratory’s Uninhabited Aerial Vehicle SAR (UAVSAR), an L-band radar mounted to a Gulfstream III jet. Data collected by UAVSAR is similar to what will be available from the NASA-Indian Space Research Organization (NISAR) mission starting in early 2022. Using Python and ArcGIS applications, a model was developed using training samples taken from NOAA post-event aerial photography and UAVSAR data gathered in the aftermath of Hurricane Florence in September 2018.

Melancon, Alexander M.↗

NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗

NASA NTRS1988

Remote Sensing in Polarized Light

Preliminary analysis of polarized images of earth collected by hand-held cameras on Shuttle Missions 51A, 51G, 51I, and 61A indicate that information of the earth's surface and atmosphere exists in those data. To ensure that follow-on research in polarization is focused upon and that the experiments are properly designed to address specific questions, 26 scientists with past experience and interest in polarization observations met at the Lyndon B. Johnson Space Center on November 3 to 5, 1987. This conference report summarizes the discussions and provides the recommendations of the group for follow-on research.

Whitehead, Victor S.↗

NASA NTRS1991

Top/bottom multisensor remote sensing of Arctic sea ice

Results are presented on the Aircraft/Submarine Sea Ice Project experiment carried out in May 1987 to investigate concurrently the top and the bottom features of the Arctic sea-ice cover. Data were collected nearly simultaneously by instruments aboard two aircraft and a submarine, which included passive and active (SAR) microwave sensors, upward looking and sidescan sonars, a lidar profilometer, and an IR sensor. The results described fall into two classes of correlations: (1) quantitative correlations between profiles, such as ice draft (sonar), ice elevation (laser), SAR backscatter along the track line, and passive microwave brightness temperatures; and (2) qualitative and semiquantitative correlations between corresponding areas of imagery (i.e., passive microwave, AR, and sidescan sonar).

Comiso, J. C.↗

NASA NTRSDate not supplied

Emissions Characterization and Smoke Transport of A Prescribed Fire

Under the background of climate change, vast regions of the world will face a hotter and probably drier future that favors ignition and spread of wildfires. This poses additional challenges to the communities who are fighting the ever-larger wildfires. Fire and smoke models are valuable tools to fire managers and decision-makers to mitigate the impact of fires. Existing fire modeling systems bear large uncertainties due to the difficulty in collecting data to characterize fire behavior and smoke transport. More observations are urgently needed for improvement of fire modeling and reduction in model uncertainty. The coordinated prescribed burn experiment, such as the Fire and Smoke Model and Measurement Evaluation Experiment (FSMMEE), will allow the concurrent collection of critical measurements of fuel, fire behavior, smoke, and meteorology to better understand and model fires. In this preliminary investigation, we employed the data from the prescribed burn experiment at Langdon Mountain, Utah, in November 2019, to reconstruct the fire emissions and characterize the smoke transport. The NASA Unified Weather Research and Forecasting Model (NU-WRF) was utilized to assist in identifying the potential pre-fire remote sensing capabilities, such as fuel load, moisture, and fire radiative power, which are helpful to model development and advancement. Along the way, two sets of NU-WRF experiments would be done by applying either a default fire emissions inventory (i.e., NASA’s Quick Fire Emissions Dataset, QFED) or reconstructed fire emissions using the data collected from the prescribed fire. The results would help answer the questions such as “How do reconstructed emissions compare to QFED emissions and their impact on plume transport”.

NU-WRF↗

NASA NTRS2016

Amazon Forests Response to Droughts: A Perspective from the MAIAC Product

Amazon forests experienced two severe droughts at the beginning of the 21st century: one in 2005 and the other in 2010. How Amazon forests responded to these droughts is critical for the future of the Earth's climate system. It is only possible to assess Amazon forests' response to the droughts in large areal extent through satellite remote sensing. Here, we used the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) data to assess Amazon forests' response to droughts, and compared the results with those from the standard (Collection 5 and Collection 6) MODIS VI data. Overall, the MAIAC data reveal more realistic Amazon forests inter-annual greenness dynamics than the standard MODIS data. Our results from the MAIAC data suggest that: (1) the droughts decreased the greenness (i.e., photosynthetic activity) of Amazon forests; (2) the Amazon wet season precipitation reduction induced by El Niño events could also lead to reduced photosynthetic activity of Amazon forests; and (3) in the subsequent year after the water stresses, the greenness of Amazon forests recovered from the preceding decreases. However, as previous research shows droughts cause Amazon forests to reduce investment in tissue maintenance and defense, it is not clear whether the photosynthesis of Amazon forests will continue to recover after future water stresses, because of the accumulated damages caused by the droughts.

remote sensing↗

NASA NTRS1995

Smithsonian stratospheric far-infrared spectrometer and data reduction system

The Smithsonian far-infrared spectrometer (FIRS) is a remote sensing Fourier transform spectrometer that measures the mid- and far-infrared thermal emission spectrum of the stratosphere from balloon and aircraft platforms. The spectrometer has had nine successful balloon flights from 1987 to 1994, flying at float altitudes of 36 - 39 km and collecting 131 hours of midlatitude stratospheric limb spectra. The spectrometer also flew on a NASA CD-8 aircraft, as part of the second Airborne Arctic Stratospheric Expedition (AASE-2), collecting 140 hours of overhead spectra at latitudes ranging from the equator to the north pole. We present here a brief description of the instrument, a discussion of data reduction procedures, an estimation of both random and systematic errors, an outline of the procedure for retrieving mixing ratio profiles, and an explanation of the method of deriving temperature and pressure from the far- and mid-infrared spectra.

Johnson, D. G.↗

NASA NTRS1992

Radar interferometry studies of the earth's topography

Digital elevation models (DEMs) which have been acquired using the TOPSAR interferometric radar sensor are directly applicable to geological and geophysical studies. Attention is presently given to three illustrative examples of the use of DEMs: the correction of remote-sensing observations for local slope and topographic effects, topographic expressions of erosion and uplift in alluvial fans, and volcanology. The greatest advantages of TOPSAR over conventional photogrammetry include rapidity of data collection, high spatial and vertical resolution, and the ability to obtain contiguous data independent of cloud cover.

Evans, Diane L.↗

NASA NTRS2000

BOREAS Level-0 NS001 TMS Imagery: Digital Counts in BIL Format

For BOREAS, the NS001 TMS imagery, along with the other remotely sensed images, was collected in order to provide spatially extensive information over the primary study areas. This information includes detailed land cover and biophysical parameter maps such as fPAR and LAI. Data collections occurred over the study areas during the 1994 field campaigns.

Hall, Forrest G.↗

NASA NTRSDate not supplied

Preliminary SnowSAR Results from SnowEx 2017

SnowEx 2017 was the first in a multi-year series of airborne remote sensing campaigns, designed to address gaps in snow retrieval techniques in preparation for a future snow satellite mission. A variety of sensor types were flown to collect multi-sensor airborne data. In combination with detailed ground truth, this multi-sensor dataset enables critical trade studies to determine optimum sensor-plus-model combinations for different snow conditions and confounding factors. Up to half of terrestrial snow-covered areas are forested, and forests are a major confounding factor for global snow retrievals. Therefore, the main focus of SnowEx 2017 was evaluating the performance of the various sensing techniques to retrieve snow water equivalent (SWE) under steadily increasing amounts of forest cover. The primary site of Grand Mesa, Colorado, USA was selected for its natural gradients of forest density and SWE with a minimum of other factors. Radar retrievals of SWE relying on volume scattering have been studied for three decades, using a variety of frequencies, with varying degrees of success. The most recent volume scattering algorithms have focused on using 2 to 3 frequencies and both co- and cross-polarizations in the 9—18 GHz range (X through Ku bands). As such, one of the primary SnowEx 2017 airborne sensors was a dual-band (X & Ku) radar, the SnowSAR. Earlier versions of SnowSAR were used in 2011 and 2012 campaigns in Finland as well as a 2013 campaign in Canada. For SnowEx 2017, SnowSAR was installed on a P-3 aircraft from the US Naval Research Laboratory. Challenges associated with the aircraft, the installation, schedule, and flying weather all contrived to limit the amount of data collected. However, months of painstaking processing has yielded data that should be of value to the original objectives of SnowEx 2017. This paper will describe in detail the SnowSAR data that were collected, and provide quality assessments of the backscatter coefficient in terms of date, time, location, frequency, polarization, snow conditions, overlap with ground truth sites, forest density, etc. The challenges as well as potential remedies/caveats will be described in order to help guide users and maximize exploitation of this valuable data.

airborne sensors↗

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↗