About: Earth observation is a(n) research topic. Over the lifetime, 3828 publication(s) have been published within this topic receiving 44085 citation(s). The topic is also known as: EO.
Abstract: The MODIS instrument provides major advances in moderate resolution earth observation. Improved spatial resolution for land observation at 250 and 500 m and improved spectral band placement provide new remote sensing opportunities. NASA has invested in the development of improved algorithms for MODIS, which will provide new data sets for global change research. Surface reflectance is one of the key products from MODIS and is used in developing several higher-order land products. The surface reflectance algorithm builds on the heritage of the Advanced Very High Resolution Radiometer (AVHRR) and SeaWiFS algorithms, taking advantage of the new sensing capabilities of MODIS. Atmospheric correction by the removal of water vapor and aerosol effects provides improvements over previous coarse resolution products and the basis for a new time-series, which will extend through to the NPOESS generation imagers. This paper summarizes the first evaluation of the MODIS surface reflectance product accuracy, in comparison with other data products and in the context of the MODIS instrument performance since launch. The MODIS surface reflectance product will provide an important time-series data set for quantifying global environmental change.
Alexander F. H. Goetz1•Institutions (1)
TL;DR: The further exploitation of hyperspectral imaging on a global basis awaits the launch of a high performance imaging spectrometer and more researchers with sufficient resources to take advantage of the vast information content inherent in the data.
Abstract: Imaging spectrometry, or hyperspectral imaging as it is now called, has had a long history of development and measured acceptance by the scientific community. The impetus for the development of imaging spectrometry came in the 1970's from field spectral measurements in support of Landsat-1 data analysis. Progress required developments in electronics, computing and software throughout the 1980's and into the 1990's before a larger segment of the Earth observation community would embrace the technique. The hardware development took place at NASA/JPL beginning with the Airborne Imaging Spectrometer (AIS) in 1983. The airborne visible/infrared imaging spectrometer (AVIRIS) followed in 1987 and has proved to this day to be the prime provider of high-quality hyperspectral data for the scientific community. Other critical elements for the exploitation of this data source have been software, primarily ENVI, and field spectrometers such as those produced by Analytical Spectral Devices Inc. In addition, atmospheric correction algorithms have made it possible to reduce sensor radiance to spectral reflectance, the quantity required in all remote sensing applications. The applications cover the gambit of disciplines in Earth observations of the land and water. The further exploitation of hyperspectral imaging on a global basis awaits the launch of a high performance imaging spectrometer and more researchers with sufficient resources to take advantage of the vast information content inherent in the data.
TL;DR: Current techniques of multi-source remote sensing data fusion are reviewed and their future trends and challenges are discussed through the concept of hierarchical classification, i.e., pixel/data level, feature level and decision level.
Abstract: With the fast development of remote sensor technologies, e.g. the appearance of Very High Resolution (VHR) optical sensors, SAR, LiDAR, etc., mounted on either airborne or spaceborne platforms, multi-source remote sensing data fusion techniques are emerging due to the demand for new methods and algorithms. The general fusion techniques have been well developed and applied in various fields ranging from satellite earth observation to computer vision, medical image processing, defence security and so on. Despite the fast development, the techniques remain challenging for multi-source data fusion within varying spatial and temporal resolutions. This article reviews current techniques of multi-source remote sensing data fusion and discusses their future trends and challenges through the concept of hierarchical classification, i.e., pixel/data level, feature level and decision level. This article concentrates on discussing optical panchromatic and multi-spectral data fusing methods. So far, the pixel level fus...
TL;DR: This communication identifies the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring, and uses this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large Area land cover applications.
Abstract: Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.
Abstract: Global Monitoring for Environment and Security (GMES) is the European programme to establish a European capacity for Earth Observation. GMES is designed to provide European policy makers and public authorities with accurate and timely information to better manage the environment, understand and mitigate the effects of climate change and ensure civil security. Sentinel-3 is an Earth observation satellite mission specifically designed for GMES to ensure the long-term collection and operational delivery of high-quality measurements to GMES ocean, land, and atmospheric services, while contributing to the GMES, emergency and security services. Key Sentinel-3 measurement requirements, corresponding to identified GMES user needs, have been derived as follows: • Sea surface topography (SSH), significant wave height (Hs) and surface wind speed derived over the global ocean to an equivalent accuracy and precision as that presently achieved by ENVISAT Radar Altimeter-2 (RA-2) but with enhanced surface topography measurements in the coastal zone, sea ice regions and over inland rivers, their tributaries and lakes. • Sea surface temperature (SST) determined for oceanic and coastal waters globally to an equivalent accuracy and precision as that presently achieved by the ENVISAT Advanced Along Track Scanning Radiometer (AATSR) over the ocean (i.e. • Visible, and Short-Wave Infrared radiances for oceanic, inland and coastal waters at a spatial resolution of 0.3 km (simultaneously and co-registered with SST measurements), determined to an equivalent level of accuracy and precision as ENVISAT Medium Resolution Imaging Spectrometer with complete ocean coverage in 2–3 days. • Visible and infrared radiances over global land-surfaces in 1–2 days, sea-ice and ice-sheets equivalent to those currently provided from ENVISAT MERIS, AATSR and Systeme Probatoire d'Observation de la Terre (SPOT) Vegetation. The Sentinel-3 mission addresses these requirements by implementing and operating: • A dual frequency, Synthetic Aperture Radar Altimeter (SRAL) instrument supported by a dual frequency passive microwave radiometer (MWR) for wet-tropospheric correction, a Precise Orbit Determination package including a GPS receiver, a DORIS instrument and a laser retro-reflector. • A highly sensitive Ocean and Land Colour Imager (OLCI) delivering multi-channel wide-swath optical measurements for ocean and land surfaces. • A dual-view Sea and Land Surface Temperature Radiometer (SLSTR) delivering accurate surface ocean, land, and ice temperature. • A collaborative ground segment providing management of the mission, management, development, production and access to core data products in an operational near real time delivery context. The mission foresees a series of satellites, each having 7-year lifetime, over a 20-year period starting with the launch of Sentinel-3A in late 2013 and of Sentinel-3B in late 2014. During full operations two identical satellites will be maintained in the same orbit with a phase delay of 180°. This paper provides an overview of the GMES Sentinel-3 mission including the mission background and user requirements, a technical description of the space segment, a brief overview of the ground segment concept, and a summary description of Sentinel-3 data products and their anticipated performance.