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At least 361 records · Page 20

An integrated approach to the remote sensing of floating ice

Review article on remote sensing applications to glaciology. Ice parameters sensed include: ice cover vs open water, ice thickness, distribution and morphology of ice formations, vertical resolution of ice thickness, ice salinity (percolation and drainage of brine; flushing of ice body with fresh water), first-year ice and multiyear ice, ice growth rate and surface heat flux, divergence of ice packs, snow cover masking ice, behavior of ice shelves, icebergs, lake ice and river ice; time changes. Sensing techniques discussed include: satellite photographic surveys, thermal IR, passive and active microwave studies, microwave radiometry, microwave scatterometry, side-looking radar, and synthetic aperture radar. Remote sensing of large aquatic mammals and operational ice forecasting are also discussed.

Campbell, W. J.↗

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Fusion↗

The International Space Station: A Unique Platform For Terrestrial Remote Sensing

The International Space Station (ISS) became operational in November of 2000, and until recently remote sensing activities and operations have focused on handheld astronaut photography of the Earth. This effort builds from earlier NASA and Russian space programs (e.g. Evans et al. 2000; Glazovskiy and Dessinov 2000). To date, astronauts have taken more than 600,000 images of the Earth s land surface, oceans, and atmospheric phenomena from orbit using film and digital cameras as part two payloads: NASA s Crew Earth Observations experiment (http://eol.jsc.nasa.gov/) and Russia s Uragan experiment (Stefanov et al. 2012). Many of these images have unique attributes - varying look angles, ground resolutions, and illumination - that are not available from other remote sensing platforms. Despite this large volume of imagery and clear capability for Earth remote sensing, the ISS historically has not been perceived as an Earth observations platform by many remote sensing scientists. With the recent installation of new facilities and sophisticated sensor systems, and additional systems manifested and in development, that perception is changing to take advantage of the unique capabilities and viewing opportunities offered by the ISS.

Stefanov, William L.↗

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗

Remote Sensing of Arctic Atmospheric Aerosols

In this chapter remote sensing techniques as applied to studies of Arctic aerosol are surveyed. They include the analysis of ground and shipborne observations of atmospheric aerosol using sunphotometers and also airborne/satellite observations using optical instrumentation (lidars, imagers, radiometers).

Aerosol↗

Opinion: Aerosol Remote Sensing Over the Next Twenty Years

More than two decades ago, aerosol remote sensing underwent a revolution with the launch of the Terra and Aqua satellites. Advancement continued via additional launches carrying new passive and active sensors. Capable of retrieving parameters characterizing aerosol loading, rudimentary particle properties and in some cases aerosol layer height, the satellite view of Earth’s aerosol system came into focus.The modeling communities have made similar advances. Now the efforts have continued long enough that we can see developing trends in both remote sensing and modeling communities, allowing us to speculate about the future and how the community will approach aerosol remote sensing twenty years from now. We anticipate technology that will replace today’s standard multi-wavelength radiometers with hyperspectral and/or polarimetry all viewing in multiple angles.These will be supported by advanced active sensors with the ability to measure profiles of aerosol extinction in addition to backscatter. The result will be greater insight into aerosol particle properties. Algorithms will move from being primarily physically-based to include an increasing degree of Machine Learning methods, but physically-based techniques will not go extinct. However, the practice of applying algorithms to a single sensor will be in decline. Retrieval algorithms will encompass multiple sensors and all available ground measurements into a unifying framework, and these inverted products will be ingested directly into assimilation systems, becoming “cyborgs”: half observations, half model. In twenty years we will see a true democratization in space with nations large and small, private organizations and commercial entities of all sizes launching space sensors. With this increasing amount of data and aerosol products available, there will be a lot of bad data. User communities will organize to set standards and the large national space agencies will lead the effort to maintain quality by deploying and maintaining validation ground networks and focused field experiments. Through it all, interest will remain high in the global aerosol system and how that system affects climate, clouds, precipitation and dynamics, air quality, the environment and public health, transport of pathogens and fertilization of ecosystems, and how these processes are adapting to a changing climate.

aerosol remote sensing↗

What does remote sensing do for ecology?

The application of remote sensing to ecological investigations is briefly discussed. Emphasis is given to the recruitment problem in marine population dynamics, the regional analysis of terrestrial ecosystems, and the monitoring of ecological changes. Impediments to the use of remote sensing data in ecology are addressed.

Roughgarden, J.↗

Sea Surface Salinity: The Next Remote Sensing Challenge

A brief history of salinity remote sensing is presented. The role of sea surface salinity (SSS) in the far north Atlantic and the influence of salinity variations on upper ocean dynamics in the tropics are described. An assessment of the present state of the technology of the SSS satellite remote sensing is given.

Lagerloef, Gary S. E.↗

Basic principles, methodology, and applications of remote sensing in agriculture

The basic principles of remote sensing applied to agriculture and the methods used in data analysis are described. Emphasis is placed on the importance of developing a methodology that may help crop forecast, basic concepts of spectral signatures of vegetation, the methodology of the LANDSAT data utilization in agriculture, and the remote sensing program application of INPE (Institute for Space Research) in agriculture.

Moreira, M. A.↗

Remotely Sensing the Photochemical Reflectance Index (PRI)

In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside the leaves in a stand of plants. Developed by Gamon et al., (1990 and 1992), PRI evolved from laboratory measurements of the reflectance of individual leaves (Bilger et al.,1989). Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We conducted laboratory experiments comparing values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. We illuminated single detached leaves using a current controlled light source (Oriel model 66881) and measured the leaf weight using an analytical balance (Mettler model AE 260) and the light reflected and transmitted by the leaf during dry down using two Analytical Spectral Devices spectroradiometers. Polarizers on the incident and reflected light beams allowed us to divide the leaf reflectance into two parts: a polarized surface reflectance and a non-polarized 'leaf interior' reflectance. Our results underscore the importance when calculating PRI of removing the leaf surface reflection, which contains no information about physiological processes ongoing in the leaf interior. The results show that the leaf physiology information is in the leaf interior reflectance, not the leaf transmittance. Applied to a plant stand, these results suggest use of polarization measurements in sun-view directions that minimize the number of sunlit transmitting leaves in the sensor field of view.

Leaves↗

Sensitivity of Multiangle Remote Sensing Observations to Aerosol Sphericity

Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), can distinguish spherical from nonspherical particles over calm ocean for mineral-dust-like particles with the range of sizes and column amounts expected under natural conditions. The ability to make such distinctions is critical if remote sensing of atmospheric aerosol properties is to provide significant new contributions to our understanding of the global-scale, clear-sky solar radiation balance. According to theoretical simulations the measurements can retrieve column optical depth for nonspherical particles to an accuracy of at least 0.05 or 10%, whichever is larger. In addition, three to four distinct size groups between 0.1 and 2.0 microns effective radius can be identified at most latitudes.

Kahn, Ralph↗

A biological and physical oceanographic remote sensing study aboard the Calypso

The paper discusses an oceanographic remote sensing program conducted aboard the R/V Calypso in the Gulf of Mexico and the Caribbean Sea to provide information for correlating ocean measurements with remotely sensed observations. Remote sensors on satellites and aircraft are used as operations and experiment planning tools as well as for scientific data acquisition. Emphasis is on providing surface-truth measurements for OCS flights and on investigating the area of the Gulf affected by the outflow of the Mississippi River. The discussion covers the shipboard instrumentation, ocean color scanner data acquisition and results, NOAA/VHRR data analysis approach, and Landsat and APT/ATS as planning tools. The research effort has demonstrated the feasibility of using satellite data as a supportive method to aid an oceanographic research vessel on a near real-time basis.

Harlan, J. C.↗

Towards a Strategy of Remote Sensing of Aerosol Direct and Indirect Radiative Forcing

The role of aerosol forcing remains one of the largest uncertainties in estimating man's impact on the global climate system. One school of thought suggests that remote sensing by satellite sensors will provide the data necessary to narrow these uncertainties. Much effort has gone into the development of new satellite sensors specifically designed to retrieve aerosol loading and some information about the sizes of the aerosols. These next generation remote sensing instruments (EOS-MODIS, EOS-MISR, POLDER, ATSR) will provide unprecedented accuracy in the retrieval of aerosol loading. Although the new generation of sensors has excellent accuracy compared to the heritage instruments of the past, they still have measurement limitations. In clean, pristine regions the absolute magnitude of the uncertainty in the aerosol retrieval becomes comparable in magnitude to the signal itself. If much of the aerosol forcing is occurring at very low magnitudes of aerosol concentrations, satellite remote sensing will miss it. This study attempts to quantify remote sensing limitations due to the accuracy limits of the retrieval algorithms. We use a combination of numerical aerosol transport models, ground-based AERONET data and ISCCP cloud climatology to determine how much of the forcing occurs in regions too clean to determine from satellite retrievals. This study is not an intercomparison of global transport models. It is not an estimation of global aerosol forcing. This study is an exercise to determine whether satellite remote sensing can live up to our high expectations. The results show that while remote sensing will be able to measure a majority of the direct forcing, it will miss roughly half of the indirect forcing.

Remer, L. A.↗

Analysis of Vegetation Within A Semi-Arid Urban Environment Using High Spatial Resolution Airborne Thermal Infrared Remote Sensing Data

High spatial resolution (5 m) remote sensing data obtained using the airborne Thermal Infrared Multispectral Scanner (TIMS) sensor for daytime and nighttime have been used to measure thermal energy responses for 2 broad classes and 10 subclasses of vegetation typical of the Salt Lake City, Utah urban landscape. Polygons representing discrete areas corresponding to the 10 subclasses of vegetation types have been delineated from the remote sensing data and are used for analysis of upwelling thermal energy for day, night, and the change in response between day and night or flux, as measured by the TIMS. These data have been used to produce three-dimensional graphs of energy responses in W/ sq m for day, night, and flux, for each urban vegetation land cover as measured by each of the six channels of the TIMS sensor. Analysis of these graphs provides a unique perspective for both viewing and understanding thermal responses, as recorded by the TIMS, for selected vegetation types common to Salt Lake City. A descriptive interpretation is given for each of the day, night, and flux graphs along with an analysis of what the patterns mean in reference to the thermal properties of the vegetation types surveyed in this study. From analyses of these graphs, it is apparent that thermal responses for vegetation can be highly varied as a function of the biophysical properties of the vegetation itself, as well as other factors. Moreover, it is also seen where vegetation, particularly trees, has a significant influence on damping or mitigating the amount of thermal radiation upwelling into the atmosphere across the Salt Lake City urban landscape. Published by Elsevier Science Ltd.

Quattrochi, Dale A.↗

IGARSS '91; Proceedings of the 11th Annual International Geoscience and Remote Sensing Symposium, Helsinki University of Technology, Espoo, Finland, June 3-6, 1991. Vols. 1, 2, 3, & 4

The papers presented at the symposium focus on global monitoring of the earth with emphasis on the solution of environmental problems and utilization of natural resources. Topics discussed include radar forestry modeling, hydrological remote sensing, polarimetric SAR observations of sea ice, optical and IR oceanography, and satellite remote sensing of precipitation and related phenomena. Other subject areas covered are microwave sensing of trace gases; atmospheric pressure, temperature, and humidity; spaceborne sensor technology; geodynamic and geophysical remote sensing; space radar missions; remote sensing of vegetation and crops; and remote sensing of weather systems.

Source record↗

Remote sensing of seasonal variation of LAI and fAPAR in a deciduous broadleaf forest

Climate change is affecting the phenology of terrestrial ecosystems. In deciduous forests, phenology in leaf area index (LAI) is the primary driver of seasonal variation in the fraction of absorbed photosynthetically active radiation (fAPAR), which drives photosynthesis. Remote sensing has been widely used to estimate LAI and fAPAR. However, while many studies have examined both empirical and model-based relationships among LAI, fAPAR, and spectral vegetation indices (SVI) from remote sensing, few studies have systematically and empirically examined how relationships among these variables change over the growing season. In this study, we examine how and why seasonal-scale covariation differs among time series of remotely sensed SVIs and both LAI and fAPAR based on current understanding and theory. To do this we use newly available remote sensing data sets in combination with time series of in-situ measurements and a canopy radiative transfer model to analyze how seasonal variation in canopy and environmental conditions affect relationships among remotely sensed SVIs, LAI, and fAPAR at a temperate deciduous forest site in central Massachusetts. Our results show that accounting for seasonal variation in canopy shadowing, which is driven by variation in solar zenith angle, improved remote sensing-based estimates of LAI, fAPAR, and daily total APAR. Specifically, we show that the phenology of SVIs is strongly influenced by seasonal variation in near infrared (NIR) reflectance arising from systematic variation in the canopy shadow fraction that is independent of changes in LAI or fAPAR. Therefore, results of this work provide a refined basis for understanding how remote sensing can be used to monitor and model the phenology of LAI, fAPAR, APAR, and gross primary productivity in temperate deciduous forests.

54 ENVIRONMENTAL SCIENCES↗

Development of mathematical techniques for the assimilation of remote sensing data into atmospheric models

The problem of the assimilation of remote sensing data into mathematical models of atmospheric pollutant species was investigated. The problem is posed in terms of the matching of spatially integrated species burden measurements to the predicted three dimensional concentration fields from atmospheric diffusion models. General conditions are derived for the "reconstructability' of atmospheric concentration distributions from data typical of remote sensing applications, and a computational algorithm (filter) for the processing of remote sensing data is developed.

Seinfeld, J. H.↗

The use of remotely sensed data for operational fisheries oceanography

Satellite remote sensing data are used under two contexts in fisheries: as a tool for fisheries research and as a means to provide operational support to fishing activities. Fishing operations need synoptic data provided timely; fisheries research needs that type of data and, also, good short-term climatologies. A description is given of several experiences conducted around the world which have employed or are using satellite data for operational fisheries problems. An overview is included of the Portuguese program for fisheries support using remotely sensed data provided by satellites and in situ observations conducted by fishermen. Environmental products useful for fisheries necessarily combine satellite and in situ data. The role of fishermen as a source of good, near-real-time in situ environmental data is stressed; so far, this role seems to have been largely overlooked.

Fiuza, Armando F. G.↗