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At least 1,801 records · Page 100

Effective use of principal component analysis with high resolution remote sensing data to delineate hydrothermal alteration and carbonate rocks

Methods of applying principal component (PC) analysis to high resolution remote sensing imagery were examined. Using Airborne Imaging Spectrometer (AIS) data, PC analysis was found to be useful for removing the effects of albedo and noise and for isolating the significant information on argillic alteration, zeolite, and carbonate minerals. An effective technique for using PC analysis using an input the first 16 AIS bands, 7 intermediate bands, and the last 16 AIS bands from the 32 flat field corrected bands between 2048 and 2337 nm. Most of the significant mineralogical information resided in the second PC. PC color composites and density sliced images provided a good mineralogical separation when applied to a AIS data set. Although computer intensive, the advantage of PC analysis is that it employs algorithms which already exist on most image processing systems.

Feldman, Sandra C.↗

The use of four-photon Raman spectroscopy for the remote sensing of natural objects

The results of the laboratory simulation of optical Kerr effect/Raman spectroscopy for the purpose of remote sensing are presented. The experimental setup is described, and measurements of the vibrational spectra of various liquids obtained. Attention is paid to the possibility of using the proposed method to detect trace hydrocarbons in water, and the spectrum of petroleum is obtained. Full-scale measurements using a laser spectrometer were made on the Black Sea.

Bunkin, A. F.↗

Image processing methods used to simulate flight over remotely sensed data

It has been demonstrated that image processing techniques can provide an effective means of simulating flight over remotely sensed data (Hussey et al. 1986). This paper explains the methods used to simulate and animate three-dimensional surfaces from two-dimensional imagery. The preprocessing techniques used on the input data, the selection of the animation sequence, the generation of the animation frames, and the recording of the animation is covered. The software used for all steps is discussed.

Mortensen, H. B.↗

Neural network approaches versus statistical methods in classification of multisource remote sensing data

Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

Benediktsson, Jon A.↗

Soil moisture variability within remote sensing pixels

The effects of topography and the level of soil moisture on the variability of soil moisture within remote sensing pixels were assessed during the First ISLSCP Field Experiment (FIFE) during 1987 and 1989. Soil moisture data from flat, sloped, and valley-shaped pixels were obtained over a wide range of moisture conditions. Relative elevation data were obtained for each study area to create digital elevation models with which to quantify topographic variability. Within-pixel soil moisture variability was shown to increase with increased topographic heterogeneity. The flat pixel had significantly lower standard deviations and fewer outlier points than the slope and valley pixels. Most pixel means had a positive skewness, indicating that most pixels will have areas of markedly higher than average soil moisture.

Charpentier, Michael A.↗

Effects of water-emission anisotropy on multispectral remote sensing at thermal wavelengths of ocean temperature and of cirrus clouds

The impact of water-emission anisotropy on remotedly sensed long-wave data has been studied. Water emission is formulated from a calm body for a facile computation of radiative transfer in the atmosphere. The error stemming from the blackbody assumption are calculated for cases of a purely absorbing or a purely scattering atmosphere taking the optical properties of the atmosphere as known. For an absorbing atmosphere, the errors in the sea-surface temperature (SST) are found to be always reduced and be the same whether measurements are made from space or at any level of the atmosphere. The inferred optical thickness tau of an absorbing layer can be in error under the blackbody assumption by a delta tau of 0.01-0.08, while the inferred optical thickness of a scattering layer can be in error by a larger amount, delta tau of 0.03-0.13. It is concluded that the error delta tau depends only weakly on the actual optical thickness and the viewing angle, but is rather sensitive to the wavelength of the measurement.

Otterman, J.↗

Remote Sensing of Multi-Level Wind Fields with High-Energy Airborne Scanning Coherent Doppler Lidar

The atmospheric lidar remote sensing groups of NOAA Environmental Technology Laboratory, NASA Marshall Space Flight Center, and Jet Propulsion Laboratory have developed and flown a scanning, 1 Joule per pulse, CO2 coherent Doppler lidar capable of mapping a three-dimensional volume of atmospheric winds and aerosol backscatter in the troposphere and lower stratosphere. Applications include the study of severe and non-severe atmospheric flows, intercomparisons with other sensors, and the simulation of prospective satellite Doppler lidar wind profilers. Examples of wind measurements are given for the marine boundary layer and near the coastline of the western United States.

Rothermel, Jeffry↗

Barium Nitrate Raman Laser Development for Remote Sensing of Ozone

In order to understand the impact of anthropogenic emissions upon the earth's environment, scientists require remote sensing techniques which are capable of providing range-resolved measurements of clouds, aerosols, and the concentrations of several chemical constituents of the atmosphere. The differential absorption lidar (DIAL) technique is a very promising method to measure concentration profiles of chemical species such as ozone and water vapor as well as detect the presence of aerosols and clouds. If a suitable DIAL system could be deployed in space, it would provide a global data set of tremendous value. Such systems, however, need to be compact, reliable, and very efficient. In order to measure atmospheric gases with the DIAL technique, the laser transmitter must generate suitable on-line and off-line wavelength pulse pairs. The on-line pulse is resonant with an absorption feature of the species of interest. The off-line pulse is tuned so that it encounters significantly less absorption. The relative backscattered power for the two pulses enables the range-resolved concentration to be computed. Preliminary experiments at NASA LaRC suggested that the solid state Raman shifting material, Ba(NO3)2, could be utilized to produce these pulse pairs. A Raman oscillator pumped at 532 nm by a frequency-doubled Nd:YAG laser can create first Stokes laser output at 563 nm and second Stokes output at 599 nm. With frequency doublers, UV output at 281 nm and 299 nm can be subsequently obtained. This all-solid state system has the potential to be very efficient, compact, and reliable. Raman shifting in Ba(NO3)2, has previously been performed in both the visible and the infrared. The first Raman oscillator in the visible region was investigated in 1986 with the configurations of plane-plane and unstable telescopic resonators. However, most of the recent research has focused on the development of infrared sources for eye-safe lidar applications.

McCray, Christopher L.↗

Time-Series Analysis of Remotely-Sensed SeaWiFS Chlorophyll in River-Influenced Coastal Regions

The availability of a nearly-continuous record of remotely-sensed chlorophyll a data (chl a) from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission, now longer than ten years, enables examination of time-series trends for multiple global locations. Innovative data analysis technology available on the World Wide Web facilitates such analyses. In coastal regions influenced by river outflows, chl a is not always indicative of actual trends in phytoplankton chlorophyll due to the interference of colored dissolved organic matter and suspended sediments; significant chl a timeseries trends for coastal regions influenced by river outflows may nonetheless be indicative of important alterations of the hydrologic and coastal environment. Chl a time-series analysis of nine marine regions influenced by river outflows demonstrates the simplicity and usefulness of this technique. The analyses indicate that coastal time-series are significantly influenced by unusual flood events. Major river systems in regions with relatively low human impact did not exhibit significant trends. Most river systems with demonstrated human impact exhibited significant negative trends, with the noteworthy exception of the Pearl River in China, which has a positive trend.

Acker, James G.↗

Data Access Services that Make Remote Sensing Data Easier to Use

This slide presentation reviews some of the processes that NASA uses to make the remote sensing data easy to use over the World Wide Web. This work involves much research into data formats, geolocation structures and quality indicators, often to be followed by coding a preprocessing program. Only then are the data usable within the analysis tool of choice. The Goddard Earth Sciences Data and Information Services Center is deploying a variety of data access services that are designed to dramatically shorten the time consumed in the data preparation step. On-the-fly conversion to the standard network Common Data Form (netCDF) format with Climate-Forecast (CF) conventions imposes a standard coordinate system framework that makes data instantly readable through several tools, such as the Integrated Data Viewer, Gridded Analysis and Display System, Panoply and Ferret. A similar benefit is achieved by serving data through the Open Source Project for a Network Data Access Protocol (OPeNDAP), which also provides subsetting. The Data Quality Screening Service goes a step further in filtering out data points based on quality control flags, based on science team recommendations or user-specified criteria. Further still is the Giovanni online analysis system which goes beyond handling formatting and quality to provide visualization and basic statistics of the data. This general approach of automating the preparation steps has the important added benefit of enabling use of the data by non-human users (i.e., computer programs), which often make sub-optimal use of the available data due to the need to hard-code data preparation on the client side.

Lynnes, Christopher↗

Sensitivity of Multiangle, Multispectral Polarimetric Remote Sensing Over Open Oceans to Water-Leaving Radiance: Analyses of RSP Data Acquired During the MILAGRO Campaign

For remote sensing of aerosol over the ocean, there is a contribution from light scattered underwater. The brightness and spectrum of this light depends on the biomass content of the ocean, such that variations in the color of the ocean can be observed even from space. Rayleigh scattering by pure sea water, and Rayleigh-Gans type scattering by plankton, causes this light to be polarized with a distinctive angular distribution. To study the contribution of this underwater light polarization to multiangle, multispectral observations of polarized reflectance over ocean, we previously developed a hydrosol model for use in underwater light scattering computations that produces realistic variations of the ocean color and the underwater light polarization signature of pure sea water. In this work we review this hydrosol model, include a correction for the spectrum of the particulate scattering coefficient and backscattering efficiency, and discuss its sensitivity to variations in colored dissolved organic matter (CDOM) and in the scattering function of marine particulates. We then apply this model to measurements of total and polarized reflectance that were acquired over open ocean during the MILAGRO field campaign by the airborne Research Scanning Polarimeter (RSP). Analyses show that our hydrosol model faithfully reproduces the water-leaving contributions to RSP reflectance, and that the sensitivity of these contributions to Chlorophyll a concentration [Chl] in the ocean varies with the azimuth, height, and wavelength of observations. We also show that the impact of variations in CDOM on the polarized reflectance observed by the RSP at low altitude is comparable to or much less than the standard error of this reflectance whereas their effects in total reflectance may be substantial (i.e. up to >30%). Finally, we extend our study of polarized reflectance variations with [Chl] and CDOM to include results for simulated spaceborne observations.

Chowdhary, Jacek↗

Making an Informed Decision on Freshwater Management by Integrating Remote Sensing Data with Traditional Data

The US National Research Council (NRC) recommended that: "The U.S. government, working in concert with the private sector, academe, the public, and its international partners, should renew its investment in Earth-observing systems and restore its leadership in Earth science and applications." in response to the NASA Earth Science Division's request to prioritize research areas, observations, and notional missions to make those objectives. In this presentation, we will discuss our approach to connect remote sensing science to decision support applications by establishing a framework to integrate direct measurements, earth system models, inventories, and other information to accurately estimate fresh water resources in global, regional, and local scales. We will discuss our demonstration projects and lessons learned from the experience. Deploying a monitoring system that offers sustained, accurate, transparent and relevant information represents a challenge and opportunity to a broad community spanning earth science, water resource accounting and public policy. An introduction to some of the scientific and technical infrastructure issues associated with monitoring systems is offered here to encourage future treatment of these topics by other contributors as a concluding remark.

climate↗

New insights into ice multiplication using remote-sensing observations of slightly supercooled mixed-phase clouds in the Arctic

Significance During secondary ice events, ice particle number concentrations in mixed-phase clouds can increase by orders of magnitude with profound implications for the cloud evolution. However, characterization of secondary ice events in the natural environment has been a challenge for the community for decades. We show the long-term frequency of secondary ice events in Arctic supercooled clouds for temperatures warmer than − 10 ○ C, made possible by applying a remote-sensing technique to 6 y of data. Secondary ice events are found to occur preferentially in the presence of drizzle droplets, compared with the better-known rime-splintering process, causing up to a 1,000-fold enhancement in ice number concentration. These results provide critical insights for model parameterizations and future laboratory experiments.

54 ENVIRONMENTAL SCIENCES↗

Dissemination of Global Flood Severity and Surface Water Mapping using Remote Sensing Data to Global Stakeholders

Flooding is a natural event that occurs frequently with high severity worldwide, responsible for significant societal and economic impacts. Disaster managers face significant challenges managing essential information for preparedness, response, and recovery efforts. The development of an open access, global flood alerting system for effective identification of flood impacted areas, classification of potential impacts, and the formulation of effective emergency response measures requires the incorporation of a wide variety of flood models and remote sensing data sources from multiple platforms. NASA is currently funding projects focused on flood forecasting, post-event flood mapping, flood depth estimation and pre-event flood severity estimation using Earth observation (EO) datasets and derived flood products. A new initiative in the Disasters Program is underway to disseminate flood products from different hydrologic models and sensors to global stakeholders via Pacific Disaster Center’s DisasterAWARE®, NASA’s Disasters Mapping Portal and potentially other mechanisms. This initiative focuses on improving response capacity and use of EO products in near real-time by a broader community for resource planning in case of extreme events. As part of this initiative, we have deployed Model of Models (MoM) – an open-source ensemble approach, that integrates outputs from hydrologic models and EO data from optical imagery to assess flood severity daily at sub-watershed level globally. The MoM output is integrated with the incident event system of DisasterAWARE to generate flood severity risk and flood impact boundaries, which are disseminated via the DisasterAWARE platform to different stakeholders globally for decision-making and response efforts. The next step will focus on using MoM outputs to estimate flood depth and extent mapping using high-resolution Synthetic Aperture Radar imagery, impact assessment using optical imagery and population datasets, and damage estimation using critical infrastructure datasets, which would be disseminated via DisasterAWARE to decision-makers, emergency managers and first responders around the world.

flood↗

Spaceborne Microwave Remote Sensing of Seasonal Freeze-Thaw Processes in the Terrestrial High Latitudes: Relationships with Land-Atmosphere CO2 exchange

Landscape transitions between seasonally frozen and thawed conditions occur each year over roughly 50 million square kilometers of Earth's Northern Hemisphere. These relatively abrupt transitions represent the closest analog to a biospheric and hydrologic on/off switch existing in nature, affecting surface meteorological conditions, ecological trace gas dynamics, energy exchange and hydrologic activity profoundly. We utilize time series satellite-borne microwave remote sensing measurements from the Special Sensor Microwave Imager (SSM/I) to examine spatial and temporal variability in seasonal freeze/thaw cycles for the pan-Arctic basin and Alaska. Regional measurements of spring thaw timing are derived using daily brightness temperature measurements from the 19 GHz, horizontally polarized channel, separately for overpasses with 6 AM and 6 PM equatorial crossing times. Spatial and temporal patterns in regional freeze/thaw dynamics show distinct differences between North America and Eurasia, and boreal forest and Arctic tundra biomes. Annual anomalies in the timing of thawing in spring also correspond closely to seasonal atmospheric CO2 concentration anomalies derived from NOAA CMDL arctic and subarctic monitoring stations. Classification differences between AM and PM overpass data average approximately 5 days for the region, though both appear to be effective surrogates for monitoring annual growing seasons at high latitudes.

net primary products↗

Final DOE-ASR Report for the Project “Advancing our Understanding and the Remote Sensing of Ice Clouds”

This project has evolved during its execution, and what follows are the key project findings. This project has arguably provided the first global view of how cirrus cloud (defined as having cloud base temperature T < 235 K) nucleation physics (evaluated through satellite retrievals of ice particle number concentration Ni, effective diameter De and ice water content IWC) evolves with the seasons for a given temperature, latitude zone and surface type (e.g. ocean vs. land), based on a new satellite remote sensing method developed for this project. The retrieval method is unique in that it is very sensitive to the small ice crystals that govern the number concentration Ni, allowing Ni to be retrieved. The method currently samples single-layer cirrus clouds having visible optical depth ranging from about 0.3 to 3.0, using co-located observations from the Infrared Imaging Radiometer (IIR) and from the CALIOP (Cloud and Aerosol Lidar with Orthogonal Polarization) lidar aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) polar orbiting satellite, employing IIR channels at 10.6 μm and 12.05 μm. Retrievals of Ni are primarily used to estimate the cirrus cloud formation mechanism; that is, either homo- or heterogeneous ice nucleation (henceforth hom and het). This is possible since, in general, hom produces more than an order of magnitude more ice crystals than does het. Thus the retrievals provide insight on how these mechanisms change with the seasons for a given latitude zone or region, based on the years 2008 and 2013. Using a conservative criterion for hom cirrus, on average, the sampled cirrus clouds formed through hom occur about 43% of the time in the Arctic and 50% of the time in the Antarctic, and during winter at mid-latitudes in the Northern Hemisphere, hom cirrus occur 37% of the time. Elsewhere (and during other seasons in the Northern Hemisphere mid-latitudes), this hom cirrus fraction is lower, and it is lowest in the tropics. Thus, the microphysical properties of cirrus clouds in the Polar Regions are much different than they are in the tropics; something unknown prior to this study. Moreover, the frequency of cirrus cloud occurrence in the Polar Regions varies strongly with season, peaking during winter in the Arctic and during spring in the Antarctic. Considering these seasonal changes in microphysics and inferred cloud coverage, this leads us to speculate that the buildup of Arctic cirrus during winter may significantly contribute to tropospheric heating in that region, possibly affecting winter jet-stream dynamics and mid-latitude weather patterns through the thermal-wind balance relationship. This cirrus cloud research provides essential guidance for realistically representing cirrus clouds in climate models; guidance previously unavailable. For example, mid-latitude hom cirrus were widespread during winter over or nearby mountainous terrain, evidently due to mountain-induced waves that produce strong updrafts at cirrus cloud levels. The treatment of turbulent mountain stress and gravity waves will likely need to be improved in climate models in order to adequately represent cirrus clouds outside the tropics. Another goal of this project was to develop a ground-based 94-GHz radar retrieval for winter snowstorms, based on (1) an improved analytical framework describing the interaction of radiation from radar with snowfall and (2) the development of a steady-state snow growth model that predicts the height-evolution of the ice particle size distribution through ice particle growth by vapor diffusion, aggregation and riming (i.e. the growth of snow through collisions with supercooled cloud droplets). Although activities (1) and (2) were completed, there was insufficient time to test and finalize the radar retrieval scheme. However, activity (2) provided a new method for relating ice particle mass “m” and projected area “A” to the ice particle maximum dimension “D”. The ice cloud microphysical processes (which determine ice cloud radiative properties) in climate models are parameterized in terms of these m-D and A-D relationships. By improving these relationships, the ice cloud radiative properties in Community Atmosphere Model version 5, or CAM5 (an atmosphere global climate model, or GCM) were improved. Student funding from the University of Nevada, Reno, was combined with funds from this project to conduct some basic research on the mechanism of the North American monsoon, or NAM. Federal research on the NAM has dwindled since 2006, but atmospheric soundings taken during research vessel cruises in the Gulf of California (GC) during the North American Monsoon Experiment (NAME) were used to reveal a likely mechanism that explains the relationship between an intrusion of tropical warm water into the GC during late spring-early summer and the onset of relatively heavy NAM rainfall in northwest Mexico and the southwestern United States. These soundings, combined with reanalysis data, satellite sea surface temperatures and satellite measurements of outgoing longwave radiation were used to develop and provide evidence for a planetary-scale NAM mechanism. As far as we know, no other physical explanation has been offered for the spring-summer evolution of the NAM system.

54 ENVIRONMENTAL SCIENCES↗

Active Optical Remote Sensing Sensors and Instrumentation for NASA’s Future Earth and Space Science Measurements/Missions

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 Future↗

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