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At least 415 records · Page 23

Satellite Remote Sensing: Aerosol Measurements

Aerosols are solid or liquid particles suspended in the air, and those observed by satellite remote sensing are typically between about 0.05 and 10 microns in size. (Note that in traditional aerosol science, the term "aerosol" refers to both the particles and the medium in which they reside, whereas for remote sensing, the term commonly refers to the particles only. In this article, we adopt the remote-sensing definition.) They originate from a great diversity of sources, such as wildfires, volcanoes, soils and desert sands, breaking waves, natural biological activity, agricultural burning, cement production, and fossil fuel combustion. They typically remain in the atmosphere from several days to a week or more, and some travel great distances before returning to Earth's surface via gravitational settling or washout by precipitation. Many aerosol sources exhibit strong seasonal variability, and most experience inter-annual fluctuations. As such, the frequent, global coverage that space-based aerosol remote-sensing instruments can provide is making increasingly important contributions to regional and larger-scale aerosol studies.

Kahn, Ralph A.↗

International Symposium on Remote Sensing of Environment, 12th, Manila, Philippines, April 20-26, 1978, Proceedings. Volumes 1, 2 & 3

The papers outline the remote sensing activities being carried out in a number of countries throughout the world, and present details on a variety of individual projects. Topics studied include a worldwide approach to remote sensing and mineral exploration, a land use information system based on statistical inference, acoustic radar and remote sensing in the boundary layer, procedure for land-use analysis in developing countries, an airborne geochemical system, remote sensing of snowpack with microwave radiometers for hydrologic applications, wheat production forecasts based on Landsat data, airborne lidar aerosol measurements over the U.S. and Europe, Landsat inventory of agricultural and forest resources in Bangladesh, application of satellite imagery to flood plain mapping in Thailand, and vegetation mapping of Nigeria from radar.

Source record↗

Overview of remote sensing field research - Requirements and status

The history of the development of remote sensing is briefly discussed, taking into account the study of the optical spectral properties of plants in the early 1950s, the concept of 'spectral signature', the multispectral scanner, and the Thematic Mapper scanner. The present state of development of remote sensing is examined. It is found that the requirements for field measurements for remote sensing field research are the same as the requirements envisioned in the 1960s. However, improved models for predicting scene reflectance and considerable field experience have clarified the aims and procedures. Information related to the status of optical measurements for crops and soils research is presented.

Robinson, B. F.↗

Remote Sensing and the Earth

A text book on remote sensing, as part of the earth resources Skylab programs, is presented. The fundamentals of remote sensing and its application to agriculture, land use, geology, water and marine resources, and environmental monitoring are summarized.

Brosius, C. A.↗

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

NASA Remote Sensing Applications for Archaeology and Cultural Resources Management

NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through the use of remote sensing. In 2007, NASA awarded six competitively chosen projects in Space Archaeology through an open solicitation whose purpose, among several, was to addresses the potential benefits to modern society that can be derived through a better understanding of how past cultures succeeded or failed to adapt to local, regional, and global change. A further objective of NASA's space archaeology is the protection and preservation of cultural heritage sites while planning for the sustainable development of cultural resources. NASA s archaeological approach through remote sensing builds on traditional methods of aerial archaeology (i.e. crop marks) and utilizes advanced technologies for collecting and analyzing archaeological data from digital imagery. NASA s archaeological research and application projects using remote sensing have been conducted throughout the world. In North America, NASA has imaged prehistoric mound sites in Mississippi; prehistoric shell middens in Louisiana, Puebloan sites in New Mexico and more recently the sites associated with the Lewis and Clark Corps of Discovery Expedition (1804-1806). In Central America, NASA archaeologists have researched Mayan sites throughout the region, including the Yucatan and Costa Rica, as well as Olmec localities in Veracruz. Other data has been collected over Angkor, Cambodia, Giza in Egypt, the lost city of Ubar on the Arabian Peninsula.

Giardino, Marco J.↗

Ambiguity of Quality in Remote Sensing Data

This slide presentation reviews some of the issues in quality of remote sensing data. Data "quality" is used in several different contexts in remote sensing data, with quite different meanings. At the pixel level, quality typically refers to a quality control process exercised by the processing algorithm, not an explicit declaration of accuracy or precision. File level quality is usually a statistical summary of the pixel-level quality but is of doubtful use for scenes covering large areal extents. Quality at the dataset or product level, on the other hand, usually refers to how accurately the dataset is believed to represent the physical quantities it purports to measure. This assessment often bears but an indirect relationship at best to pixel level quality. In addition to ambiguity at different levels of granularity, ambiguity is endemic within levels. Pixel-level quality terms vary widely, as do recommendations for use of these flags. At the dataset/product level, quality for low-resolution gridded products is often extrapolated from validation campaigns using high spatial resolution swath data, a suspect practice at best. Making use of quality at all levels is complicated by the dependence on application needs. We will present examples of the various meanings of quality in remote sensing data and possible ways forward toward a more unified and usable quality framework.

Lynnes, Christopher↗

An overview of NASA's remote sensing program

The present status of NASA's remote sensing program and its future plans are reviewed, and some investigations into the possible uses of remotely sensed data are briefly summarized. Landsat-1 photographs are presented to demonstrate how such data can be employed for monitoring and forecasting of agricultural production, for watershed management and flood control, and for mineral exploration. The performance of Landsat-2 and expectations for Landsat-C are evaluated. High-priority problems which should be the driving forces for designing space observation systems for the 1980's are outlined, including the problem of world food supply and the relationship between land use and climatic changes. The design of the modular Landsat-D spacecraft, which will fly a thematic mapper for agricultural observations, is described.

Thome, P. G.↗

Remote sensing education in NASA's technology transfer program

Remote sensing is a principal focus of NASA's technology transfer program activity with major attention to remote sensing education the Regional Program and the University Applications Program. Relevant activities over the past five years are reviewed and perspective on future directions is presented.

Weinstein, R. H.↗

Atmospheric Radiative Transfer for Satellite Remote Sensing

I will discuss the science of satellite remote sensing which involves the interpretation and inversion of radiometric measurements made from space. The goal of remote sensing is to retrieve some physical aspects of the medium which are sensitive to the radiation at specific wavelengths. This requires the use of fundamentals of atmospheric radiative transfer. I will talk about atmospheric radiation or, more specifically, about the interactions of solar radiation with aerosols and cloud particles. The focus will be more on cloudy atmospheres. I will also show how a standard one-dimensional approach, that is traced back at least 100 years, can fail to interpret the complexity of real clouds. I n these cases, three-dimensional radiative transfer should be used. Examples of satellite retrievals will illustrate the cases.

Marshak, Alexander↗

Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems; Workshop Report

The purpose of the workshop was to invite statisticians, applied mathematicians, computer scientists, data system architects, experts in remote sensing technology, and Climate and Earth System scientists to review, discuss, and plan research on issues related to large-scale, efficient analysis of distributed data using spatial statistical methods. Our motivation in organizing this event was to catalyze interchange among experts on the fast-emerging problem of analysis of distributed data. As part of SAMSI's 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System, a Working Group on Remote Sensing was established to address statistical and mathematical research problems in the analysis of remote sensing data. The Working Group has five subgroups: 1) Spatial Retrieval Methodology (the so-called \Spatial-X" subgroup); 2) Spatial Analysis for Hyperspectral Data (the so-called \Spatial-Y" subgroup); 3) Emulators for Complex Forward Models; 4) Optimization for Remote Sensing Retrievals; and 5) Theory of Data Systems (ToDS). The ToDS subgroup spent the first half of this academic year formulating a framework in which to consider the joint problem of a) optimizing statistical methods for environments where data are distributed and too large to move to a central location, and b) the design of data system infrastructures within which to implement those statistical methods. To x ideas, the Workshop focused on spatial statistical methods. To date there are many new spatial statistical methods designed with massive data sets in mind, in the literature. However, very few have been implemented for remote sensing data, and none have been implemented in operational settings like those used by NASA and NOAA. A major impediment to their use in these cases is that the data are not only massive, but are stored in different physical locations. These data must be brought together in some way in order to estimate spatial covariance functions, but moving data to a central location for analysis is tedious at best and impossible at worst. Some remote data reduction is almost certainly necessary, but how much? What are the consequences for inference? The fundamental issue underlying these questions is how to navigate the trade-space between costs and uncertainty in the estimates or inferences that are ultimately produced.

Braverman, Amy↗

Role of remote sensing in documenting living resources

Specific cases of known or potentially useful applications of remote sensing in assessing biological resources are discussed. It is concluded that the more usable remote sensing techniques relate to the measurement of population fluctuations in aquatic systems. Sensing of the flora and the fauna of the Bay is considered with emphasis on direct sensing of aquatic plant populations and of water quality. Recommendations for remote sensing projects are given.

Wagner, P. E.↗

Topographic Correction of Optical Remote Sensing Images in Mountainous Areas: A systematic review

Rugged terrain distorts optical remote sensing observations and subsequently impacts land cover classification and biophysical and biochemical parameter retrieval over mountainous areas. Therefore, topographic correction (TC) is a prerequisite for many remote sensing applications. Although various TC methods have been explored over the past four decades to mitigate topographic effects, a systematic and global review of these studies is still lacking. Using a multicomponent bibliometric approach, we extracted bibliometric metadata from 426 publications identified by searching titles, keywords, and abstracts for research on “topographic correction” and “topographic effects” in Scopus and Web of Science (WoS) from 1980 to 2022. Here this systematic review revealed a rapid growth in the number of TC studies since the 1980s, primarily driven by the availability of decametric-resolution remote sensing observations and digital elevation models (DEMs). Most of the research has focused on relatively low-elevation regions, with increasing attention beyond American and European regions, particularly in China. The seasonal distribution of satellite acquisition for TC showed considerable imbalance, mainly concentrated in months with favorable solar illumination conditions (e.g., May to October). Important themes emerged from the keyword analysis, including satellite sensors, DEMs, TC methods, evaluation criteria, and applications.

58 GEOSCIENCES↗

2024 Workshop - Remote Sensing and Fluxes Upscaling for Real-world Impact - Tutorial v1

The software-tutorial was developed within the 2024 Remote Sensing and Fluxes Upscaling for Real-world Impact workshop as part of the hands-on session. The workshop was supported by AmeriFlux, National Ecological Observatory Network (NEON) and CarbonDew. The software provides basic tools to perform the following tasks: - gather remote sensing images using Google Earth Engine API; - gather flux data; - perform basic functions, such as plotting time-series, perform QA of the data, compute vegetation indices; - perform correlation analysis between flux data and remote sensing data; - perform flux predictions based on remote sensing data integrated in different modalities.

Falco, Nicola [Lawrence Berkeley National Laborato↗

Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement

In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Moving Object Detection System (MMODS)”, to detect small, low SNR objects that are beyond what a human can observe in a single video frame. This is demonstrated by using simulated data where our technology-detected objects are as small as one pixel with a targeted SNR, close to 1:1. We also demonstrate a similar improvement using live data collected with a remote camera. The MMODS technology fills a major technology gap in remote sensing surveillance applications for small target detection. Our method does not require prior knowledge about the environment, pre-labeled targets, or training data to effectively detect and track slow- and fast-moving targets, regardless of the size or the distance.

47 OTHER INSTRUMENTATION↗

Tropospheric Passive Remote Sensing

The long term role of airborne/spaceborne passive remote sensing systems for tropospheric air quality research and the identification of technology advances required to improve the performance of passive remote sensing systems were discussed.

Keafer, L. S., Jr.↗

Some Opinions on Remote Sensing and Geologic Studies

The principal role of remote sensing data in geologic studies is as a source of geologic information from which meaningful geologic interpretations can be made. Remote sensing data are important in sedimentary basin analysis and other geologic studies as independent and sometimes unique sources of important lithologic and structural information; however, their greatest benefit to exploration-oriented investigations may come when these data are used with other relevant data in a digital database approach to exploration. Modern computer technology facilitates the rapid integration and synthesis of satellite, topographic, gravity, aeromagnetic, geochemical, and other data collected from a given region. Once such data are geometrically registered, they can be digitally processed, within the constraints of defined geologic models, to rapidly identify, and focus further exploration efforts on, target areas that have the greatest potential for success.

Bailey, G. B.↗

Uncertainties in Remote Sensing of Aerosol 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.

Remer, L.↗