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At least 163 records · Page 9

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NASA NTRS1975

Annual review of earth observations from space

An overview is given of the present state of satellites making observations of the earth. Satellite systems discussed include the NOAA series of Synchronous Meteorological Satellites (SMS) and sun-synchronous satellites, the two LANDSATS (formerly called ERTS), and the NIMBUS series. Examples are presented of the types of observations being made as well as their purposes. These include observations of synoptic and mesoscale atmospheric processes for daily weather forecasting, global atmospheric processes for long-range weather forecasting, planetary radiation budget and ocean circulation for monitoring climatic trends, earth dynamics and tectonic structure for mineral exploration and assessing earthquake hazards, atmospheric composition and water quality for environment monitoring, and thematic mapping for monitoring land use, managing crops and water resources, and assessing environmental impacts.

Nordberg, W.↗

NASA NTRS1978

Determination of spectral signatures of substances in natural waters

Optical remote sensing of water pollution offers the possibility of fast, large scale coverage at a relatively low cost. The possibility of using the spectral characteristics of the upwelling light from water for the purpose of ocean water quality monitoring was explained. The work was broken into several broad tasks as follows: (1) definition of a remotely measured spectral signature of water, (2) collection of field data and testing of the signature analysis, and (3) the possibility of using LANDSAT data for the identification of substances in water. An attempt to extract spectral signatures of acid waste and sediment was successful.

Klemas, V.↗

NASA NTRS1994

Precise mean sea level measurements using the Global Positioning System

This paper describes the results of a sea level measurement test conducted off La Jolla, California, in November of 1991. The purpose of this test was to determine accurate sea level measurements using a Global Positioning System (GPS) equipped buoy. These measurements were intended to be used as the sea level component for calibration of the ERS 1 satellite altimeter. Measurements were collected on November 25 and 28 when the ERS 1 satellite overflew the calibration area. Two different types of buoys were used. A waverider design was used on November 25 and a spar design on November 28. This provided the opportunity to examine how dynamic effects of the measurement platform might affect the sea level accuracy. The two buoys were deployed at locations approximately 1.2 km apart and about 15 km west of a reference GPS receiver located on the rooftop of the Institute of Geophysics and Planetary Physics at the Scripps Institute of Oceanography. GPS solutions were computed for 45 minutes on each day and used to produce two sea level time series. An estimate of the mean sea level at both locations was computed by subtracting tide gage data collected at the Scripps Pier from the GPS-determined sea level measurements and then filtering out the high-frequency components due to waves and buoy dynamics. In both cases the GPS estimate differed from Rapp's mean altimetric surface by 0.06 m. Thus, the gradient in the GPS measurements matched the gradient in Rapp's surface. These results suggest that accurate sea level can be determined using GPS on widely differing platforms as long as care is taken to determine the height of the GPS antenna phase center above water level. Application areas include measurement of absolute sea level, of temporal variations in sea level, and of sea level gradients (dominantly the geoid). Specific applications would include ocean altimeter calibration, monitoring of sea level in remote regions, and regional experiments requiring spatial and temporal resolution higher than that available from altimeter data.

Kelecy, Thomas M.↗

NASA NTRS1996

SWADE Data Guide

This is a guide to the data that was collected during the Surface Wave Dynamics Experiment (SWADE) carried out from October 1990 through March 1991. The area studied was the Mid-Atlantic bight. Buoys collected data continuously during this time. Included are three 3-meter discus buoys the National Data Buoy Center (NDBC) set in the area for this project, they then later added a fourth 3-meter discus and an experimental coastal buoy. Data from all of the NDBC buoys and stations from New England to Florida have been included in the data set; in addition, several other buoys monitored meteorological and ocean conditions for parts of the experiment. Several times during the project, there were intensive data collection periods. During the third of these, there were 7 aircraft and a ship collecting data. Maps of each mission from the platforms that have shared their data are included. The anonymous FTP site that has been established to make this data public is described.

Oberholtzer, David↗

NASA NTRS1996

The EOS CERES Global Cloud Mask

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Berendes, T. A.↗

NASA NTRS1993

A Look at a Day of Data from The TOPEX/POSEIDON GPS Receiver

Launched on 10 August, 1992, the Topex/Poseidon satellite is a joint project of NASA and the French space agency CNES. The purpose of this Earth orbiting altimetric satellite (for brevity, referred to as Topex) is to enable monitoring of the ocean topography to higher levels of accuracy than previously achieved. Essential to obtaining this greater level of accuracy is the use of improved navigational systems which can yield position estimates for Topex good to a few centimeters. One of the navigational systems utilized by Topex is the Global Positioning System (GPS) -- a network of navigational beacons that has become widely used in many areas beside spacecraft navigation...

Jee, J. Rodney↗

NASA NTRS1993

A Look at a Day of Data from the Topex/Poseidon GPS Receiver

Launched on August 10, 1992, the Topex/Poseidon satellite is a joint project of NASA and the French space agency CNES. The pupose of this Earth orbiting altimetric satellite (for brevity, referred to as Topex) is to enable monitoring of the ocean topography to higher levels of accuracy than previously achieved.

robust regression spline graphics↗

NASA NTRSDate not supplied

Sunglint-aided Methane Retrieval: Using Sentinel-2 to Quantify Offshore Oil and Gas Emissions

The extraction, production, and transportation of oil and gas via activities such as intentional venting and fugitive emissions are leading contributors to anthropogenic methane emissions. Offshore operations comprise a significant percentage of all oil and gas operations, yet emission monitoring over the ocean is insufficient. Due to low surface reflectance over the ocean, remote sensing measurements offshore are limited. Therefore offshore contributions to the overall global methane budget are unknown. Regulators such as the Bureau of Ocean and Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) are unable to validate operator-reported methane emission estimates. The NASA DEVELOP Program partnered with BOEM, BSEE, and SkyTruth to identify potential offshore methane sources in the Gulf of Mexico. Drawing upon existing retrieval methods to detect and quantify onshore methane emissions (Varon et al., 2021), we selected sunglint scenes to detect methane plumes over the ocean in Sentinel-2 imagery. We detected two methane plumes at the Constitution complex in the Gulf of Mexico and off the coast of Pointe-Noire, Congo. If expanded, these methods could serve a vital role in validating operator reporting and quantifying climate impacts of offshore oil and gas operations - complementing those of next generation satellites.

Katherine Howell↗

NASA NTRSDate not supplied

Zarr stores in NASA's EOSDIS

Data hosted by the National Aeronautics and Space Administration (NASA) are expected to increase to over 600 PB by the end of the decade (see Figure 1). This rapid increase is, in part, driven by the launch of new, high-data-volume Earth observing missions, such as the NASA-Indian Space Research Organisation (ISRO) Synthetic Aperture Radar (NISAR), Surface Water and Ocean Topography (SWOT), Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Plankton, Aerosol, Cloud ocean Ecosystem (PACE) missions.

Owen Littlejohns↗

NASA NTRS2018

Mobile Device Application for Monitoring Cyanobacteria Harmful Algal Blooms Using Sentinel-3 Satellite Ocean and Land Colour Instruments

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes.

Harmful Algal Bloom↗

NASA NTRS2004

Continuous Monitoring of the Jason-l and TOPEX/POSEIDON Ocean Altimetry Missions from Dedicated Calibration Sites

We present calibration results from Jason-1 and TOPEX/POSEIDON overflights of the three dedicated verification sites: 1) a California offshore oil platform (Harvest); 2) the Mediterranean island of Corsica (Cape Senetosa), and 3) the Bass Strait off the coast of Tasmania. The high-accuracy of the Jason-1 measurement system is evident in the results from the dedicated calibration experiments. These experiments do indicate, however, that the Jason-1 sea-surface-height (SSH) measurements are biased high by approximately 12-15 cm. We discuss the implications of geographically correlated errors on the determination of the SSH bias.

satellite altimerty↗

NASA NTRS1973

Earth physics, overview

Satellite applications in earth and ocean dynamic studies are considered for: earthquake hazard assessment and alleviation; prediction of general ocean circulation, surface currents, and heat transport; monitoring of transient phenomena of the ocean surface, such as sea state and wave conditions, wind-surface interactions and storm searches; and refinement of the global geoid, the gravity and magnetic fields of the earth.

Vonbun, F. O.↗

NASA NTRS2005

A Range Compensating Feed Motion Concept for Spaceborne Radar

Tropical cyclones can cause major loss of both life and property, so that improvements in forecasting motion, intensity, and rainfall are needed. Such forecasting requires accurate measurements of the current state of the cyclone. Ground-based Doppler radars have long been used as an effective means of monitoring severe precipitating storms. Because of the oceanic nature of tropical cyclones, remote monitoring from space is desirable. Recently, the Precipitation Radar (PR) [1] aboard the Tropical Rainfall Measuring Mission (TRMM) [2] satellite has demonstrated an unprecedented capacity for 3-D imaging of precipitating storms. Nonetheless, due to the relatively long TRMM return cycle (less than once per day) the value of PR data has primarily been limited to the understanding of climatological properties of tropical cyclones [3]. The return cycle can be substantially reduced by sensing from a geostationary platform.

reflector antennas↗

NASA NTRS2013

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

Biological Oceanography↗

NASA NTRS2007

Solutions Network Formulation Report. The Potential Contribution of the Ocean Surface Topography Mission to the General NOAA Oil Monitoring Environment

Data collected by the OSTM could be used to provide a solution for the GNOME DST. GNOME, developed by NOAA?s Office of Response and Restoration Hazardous Materials Response Division, geospatially models oil spill trajectories using wind, current, river flow, and tidal data. Data collected by the OSTM would supply information about ocean currents and wind speeds. This Candidate Solution is in alignment with the Coastal Management, Water Management, Disaster Management, Public Health, Ecological Forecasting, and Homeland Security National Applications and will benefit society by improving the capabilities of emergency responders who evaluate an oil spill?s probable threat.

Hilbert, Kent↗

NASA NTRSDate not supplied

Global Ocean Studies from ICESat-2 Mission

The primary purpose of ICESat-2 mission is to monitor changes in the cryosphere. Fortunately, additional, and unrealized information from the penetration of laser light below ocean surface offers a new and exciting opportunity to study the ocean biology globally. The objective of this study is to provide the global ocean subsurface results (e.g., depolarization ratio and particulate backscattering coefficient) from ATLAS/ICESat-2 lidar measurements. The seasonal maps of ATLAS retrieved subsurface results exhibit all the major ocean plankton features anticipated from the earlier passive ocean color and CALIOP/CALIPSO lidar measurements. The ICESat-2 ATLAS lidar can continue to monitor global ocean phytoplankton properties after CALIOP/CALIPSO mission. Moreover, the ICESat-2 ocean subsurface results provide unique information to augment existing ocean color measurements by adding nighttime observations and the depth dimension with high horizontal and vertical resolutions.

ICESat2↗

NASA NTRS1998

Wavelet Analysis of SAR Images for Coastal Monitoring

The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.

Liu, Antony K.↗

NASA NTRS2012

Optical Characterisation of Suspended Particles in the Mackenzie River Plume (Canadian Arctic Ocean) and Implications for Ocean Colour Remote Sensing

Climate change significantly impacts Arctic shelf regions in terms of air temperature, ultraviolet radiation, melting of sea ice, precipitation, thawing of permafrost and coastal erosion. Direct consequences have been observed on the increasing Arctic river flow and a large amount of organic carbon sequestered in soils at high latitudes since the last glacial maximum can be expected to be delivered to the Arctic Ocean during the coming decade. Monitoring the fluxes and fate of this terrigenous organic carbon is problematic in such sparsely populated regions unless remote sensing techniques can be developed and proved to be operational. The main objective of this study is to develop an ocean colour algorithm to operationally monitor dynamics of suspended particulate matter (SPM) on the Mackenzie River continental shelf (Canadian Arctic Ocean) using satellite imagery. The water optical properties are documented across the study area and related to concentrations of SPM and particulate organic carbon (POC). Robust SPM and POC : SPM proxies are identified, such as the light backscattering and attenuation coefficients, and relationships are established between these optical and biogeochemical parameters. Following a semi-analytical approach, a regional SPM quantification relationship is obtained for the inversion of the water reflectance signal into SPM concentration. This relationship is reproduced based on independent field optical measurements. It is successfully applied to a selection of MODIS satellite data which allow estimating fluxes at the river mouth and monitoring the extension and dynamics of the Mackenzie River surface plume in 2009, 2010 and 2011. Good agreement is obtained with field observations representative of the whole water column in the river delta zone where terrigenous SPM is mainly constrained (out of short periods of maximum river outflow). Most of the seaward export of SPM is observed to occur within the west side of the river mouth. Future work will require the validation of the developed SPM regional algorithm based on match-ups with field measurements, then the routine application to ocean colour satellite data in order to better estimate the fluxes and fate of SPM and POC delivered by the Mackenzie River to the Arctic Ocean.

Mackenzie River plume↗