Earth Observation Satellite Missions Research Articles

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods.

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Spatio-Temporal Interpolation of Cloudy SST Fields Using Conditional Analog Data Assimilation

The ever increasing geophysical data streams pouring from earth observation satellite missions and numerical simulations along with the development of dedicated big data infrastructure advocate for truly exploiting the potential of these datasets, through novel data-driven strategies, to deliver enhanced satellite-derived gapfilled geophysical products from partial satellite observations. We here demonstrate the relevance of the analog data assimilation (AnDA) for an application to the reconstruction of cloud-free level-4 gridded Sea Surface Temperature (SST). We propose novel AnDA models which exploit auxiliary variables such as sea surface currents and significantly reduce the computational complexity of AnDA. Numerical experiments benchmark the proposed models with respect to state-of-the-art interpolation techniques such as optimal interpolation and EOF-based schemes. We report relative improvement up to 40%/50% in terms of RMSE and also show a good parallelization performance, which supports the feasibility of an upscaling on a global scale.

Onboard mission planning for agile satellite using modified mixed-integer linear programming

This paper investigates a new Agile Earth Observation Satellite (AEOS) mission planning algorithm. This new developed algorithm is based on Modified Mixed-Integer Linear Programming (MILP) approach, which takes the minimum slew angle and highest priority criterion. The key point of the paper lies in that the planning process is treated as a Dynamical Combinatorial Optimization (DCO) problem due to the time-varying constraint and the requirement of the problem. The design of the new algorithm is also to meet the real-time requirement of onboard mission planning. The mathematical formulation of the problem is modified to satisfy the demand of the LP solver, and a newly developed dynamic database is used to simulate the constantly changing satellite-target relative position with limited observation windows. The new mission planning model is solved by the LP method to test its reliability. Another solution with Generic Algorithm (GA) is also given to check the result. The calculation time of these two methods is compared to show that the LP approach has a better compatibility with the onboard mission planning requirement.

Treefall Gap Mapping Using Sentinel-2 Images

Proper knowledge about resources in forest management is fundamental. One of the most important parameters of forests is their size or spatial extension. By determining the area of treefall gaps inside the compartments, a more accurate yield can be calculated and the scheduling of forestry operations could be planned better. Several field- and remote sensing-based approaches are in use for mapping but they provide only static measurements at high cost. The Earth Observation satellite mission Sentinel-2 was put in orbit as part of the Copernicus programme. With the 10-m resolution bands, it is possible to observe small-scale forestry operations like treefall gaps. The spatial extension of these gaps is often less than 200 m2, thus their detection can only be done on sub-pixel level. Due to the higher temporal resolution of Sentinel-2, multiple observations are available in a year; therefore, a time series evaluation is possible. The modelling of illumination can increase the accuracy of classification in mountainous areas. The method was tested on three deciduous forest sites in the Börzsöny Mountains in Hungary. The area evaluation produced less than 10% overestimation with the best possible solutions on the sites. The presented work shows a low-cost method for mapping treefall gaps which delivers annual information about the gap area in a deciduous forest.

Extracting Soil Water Holding Capacity Parameters of a Distributed Agro-Hydrological Model from High Resolution Optical Satellite Observations Series

Sentinel-2 (S2) earth observation satellite mission, launched in 2015, is foreseen to promote within-field decisions in Precision Agriculture (PA) for both: (1) optimizing crop production; and (2) regulating environmental impacts. In this second scope, a set of Leaf Area Index (LAI) derived from S2 type time-series (2006–2010, using Formosat-2 satellite) is used to spatially constrain the within-field crop growth and the related nitrogen contamination of surface water simulated at a small experimental catchment scale with the distributed agro-hydrological model Topography Nitrogen Transfer and Transformation (TNT2). The Soil Water Holding Capacity (SWHC), represented by two parameters, soil depth and retention porosity, is used to fit the yearly maximum of LAI (LAX) at each pixel of the satellite image. Possible combinations of soil parameters, defining 154 realistic SWHC found on the study site are used to force spatially homogeneous SWHC. LAX simulated at the pixel level for the 154 SWHC, for each of the five years of the study period, are recorded and hereafter referred to as synthetic LAX. Optimal SWHCyear_I,pixel_j, corresponding to minimal difference between observed and synthetic LAXyear_I,pixel_j, is selected for each pixel, independent of the value at neighboring pixels. Each re-estimated soil maps are used to re-simulate LAXyear_I. Results show that simulated and synthetic LAXyear_I,allpixels obtained from SWHCyear_I,allpixels are close and accurately fit the observed LAXyear_I,allpixels (RMSE = 0.05 m2/m2 to 0.2 and R2 = 0.99 to 0.94), except for the year 2008 (RMSE = 0.8 m2/m2 and R2 = 0.8). These results show that optimal SWHC can be derived from remote sensing series for one year. Unique SWHC solutions for each pixel that limit the LAX error for the five years to less than 0.2 m2/m2 are found for only 10% of the pixels. Selection of unique soil parameters using multi-year LAX and neighborhood solution is expected to deliver more robust soil parameters solutions and need to be assessed further. The use of optical remote sensing series is then a promising calibration step to represent crop growth within crop field at catchment level. Nevertheless, this study discusses the model and data improvements that are needed to get realistic spatial representation of agro-hydrological processes simulated within catchments.

An optimized end-to-end process for the analysis of agile earth observation satellite missions

Agile earth observation satellite missions are becoming more and more important due to their capability to perform fast reorientation maneuvers with 3 degrees of freedom to capture different target areas along the orbital path, thus increasing the observed area and complexity of scans. The design of an agile earth observation satellite mission is a non-trivial task due to the fact that a trade-off between observed area and complexity of the scans on the one hand and degree of agility available and thus performance of the attitude control devices on the other hand has to be done. Additionally, the designed mission has to be evaluated in a realistic environment also taking into account the specific characteristics of the chosen actuators. In the present work, several methods are combined to provide an integrated analysis of agile earth observation satellite missions starting from the definition of a desired ground scan scenario, going via the creation of a guidance profile to a realistic simulation and ending at the verification of the feasibility by detailed closed-loop simulation. Regarding its technical implementation at Astrium GmbH, well-proven tools for the different tasks of the analysis are incorporated and well defined interfaces for those tools are specified, allowing a high degree of automatism and thus saving time and minimizing errors. This results in a complete end-to-end process for the design, analysis and verification of agile earth observation satellite missions. This process is demonstrated by means of an example analysis using control moment gyros for a high agility mission.

A Distributed Scene Simulation System for Earth Observation Satellite Mission Design and Analysis

The primary mission objective is gathering information of the Earth by on-board instruments using remote-sensing techniques, and sending the useful information back to the ground. Its mission design and analysis involves identification of critical requirements, determination of mission orbit, analysis of relationship between satellite, the Earth and the Sun. This paper proposed a new scene simulation system based on distributed architecture, which consisted of mission design subsystem, numerical simulation subsystem, scenario display subsystem and model management subsystem. The system can show the updated mission status and performance rapidly and efficiently after user modified the initial mission parameters. Practice has proven that it can help users to make a decision and judgment for the mission design, and improve their work efficiency.

A Distributed Scene Simulation System for Earth Observation Satellite Mission Design and Analysis

A Distributed Scene Simulation System for Earth Observation Satellite Mission Design and Analysis

Do Satellite Data Portals Today Reach Out to Diverse End Users Around the World?

T he space-based vantage of Earth-observing satellites to solve some of the world’s otherwise fundamentally intractable problems is well known. For example, from understanding the global distribution of precipitation, energy, and water cycling to predicting transboundary water fluxes, satellites have been promoted as the only means available for our sparsely instrumented Earth. While most Earthobserving satellite missions have a science-oriented goal, the applied-science value for decision making at tactical or strategic time scales is equally convincing. However, Internet data portals for satellite missions available today do not seem to be making an impact on diverse end users as large as that already made on the scientific community. In a recent end-user training workshop titled “Environmental Applications of Remote Sensing for Water Resources” [held in December 2012 in Bangladesh to introduce existing and emerging satellite missions such as the Global Precipitation Measurement (GPM) and Surface Water and Ocean Topography (SWOT) missions], end users were found unaware of the many highly evolved satellite data portals already in existence because these Internet portals were not as highly visible in the Google search engine as the archaic ones.

The Global Monitoring for Environment and Security (GMES) Sentinel-3 mission

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. <0.3K), at a spatial resolution of 1km.•Visible, and Short-Wave Infrared radiances for oceanic, inland and coastal waters at a spatial resolution of 0.3km (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 2–3days.•Visible and infrared radiances over global land-surfaces in 1–2days, sea-ice and ice-sheets equivalent to those currently provided from ENVISAT MERIS, AATSR and Système 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.

Forest biomass mapping from lidar and radar synergies

The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R 2 of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and was used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R 2 of 0.63–0.71, RMSE of 32.0–28.2 Mg/ha up to biomass levels of 200–250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar–SAR synergy was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the potential of the combined use of lidar samples and radar imagery for forest biomass mapping. Various issues regarding lidar/radar data synergies for biomass mapping are discussed in the paper.

FORMOSAT-2 Mission: Current Status and Contributions to Earth Observations

This paper presents an overview of the current status and data applications of FORMOSAT-2, Taiwanese's first earth observation satellite mission. Highlights of its contributions to monitoring of global natural disasters and earth environmental changes will be illustrated. The FORMOSAT-2 satellite successfully complements existing high spatial resolution imaging satellites such as SPOT-5, IKONOS, and QuickBird, among others, with its unique capability of daily revisits worldwide. The FORMOSAT-2 follow-up program to ensure data continuity to the user community is briefly introduced.

Miniature high-resolution Fabry–Perot guided-wave spectrometer for planetary atmospheric remote sensing

Infrared (IR) remote sensing of planetary atmospheres typically requires spectral resolution below 0.1 nm to resolve the fine structure of the optical absorption characteristics of relevant gas-phase species and minimize interferences. This is currently accomplished using large bulk-optic Fourier transform infrared (FT IR) or dispersive spectrometers with complex optomechanics to provide the required spectral discrimination through the selection of a large optical path length. However, the resultant large mass and power requirements carry a high cost penalty and risk for spaceborne missions, requiring costly, large space platforms. This paper describes the breadboarding of an innovative spectrometer concept, the Fabry–Perot (FP) guided-wave integrated optical spectrometer (IOSPEC), which synergistically combines two mature technologies to provide a miniature spectrometer capable of broadband operation at high spectral resolution to below 0.03 nm full width half maximum (FWHM) with a net mass under 3 kg. A special, tailored tunable FP filter is employed to provide the high spectral discrimination, allowing a large spectrometer input aperture. This is matched with a high-performance guided-wave IR spectrometer based on MPB Communications Inc. patented IOSPEC technologies to simultaneously provide the measurement of 256–512 high-resolution spectral channels over a relatively broad spectral range. By tuning the FP filter, a continuum of spectral measurement points can be obtained with a signal-to-noise ratio (SNR) advantage of at least SQRT(256) over scanned spectrometer systems. The guided-wave optics integration provides robust, long-term optical alignment and minimizes the system mechanical complexity. The FP–IOSPEC spectrometer volume and mass minimization enable multiple spectrometers to be accommodated on a low-cost microsat, optimized for selected measurement tasks and views, thereby enabling significantly improved data acquisition for remote sensing and science while minimizing the mission cost. The application of this innovative technology to the requirements of the potential Miniature Earth Observation Satellite (MEOS) mission to study critical aspects of the carbon and hydrologic cycles associated with climate change is discussed.

Editorial &amp;quot;Remote sensing in hydrological sciences&amp;quot;

City University of New York, USA1 IntroductionSpace age, and with it the era of earth observation, is gener-ally considered to have begun more than 50 years ago withthe launch of Sputnik-1 on 4 October 1957 (Kramer, 2002).Sputnik’s beeping radio signals did not only serve to demon-strate the technological capabilities of the Soviet Union, theywere also used to gather information about the electron den-sity of the ionosphere. In legacy of Sputnik, most of the Earthobservation satellite missions that were to follow served mul-tiple purposes. Unfortunately, up to this day, political andtechnological motives may be more important drivers for thedesign of remote sensing missions than the requirements andneeds of the geoscientific community. It is probably for thisreason that remote sensing continues to be underutilized inmany Earth science applications. Hydrology is not an excep-tion.This mismatch of technological capabilities and use of re-motely sensed data has increasingly been recognised in the1990s. Consequently, an increasing number of space-relatedprogrammes with the goal to bridge the gap between remotesensing data providers and users have been initiated. One ex-ample is GMES

Soil moisture observations in CEOP, GEOSS and earth observation satellite missions

Soil moisture observations in CEOP, GEOSS and earth observation satellite missions

When Missions Meet: Using Systems Engineering to Analyse the Potential for Interoperability between Earth Observation Satellite Missions

INSIGHTVolume 11, Issue 5 p. 22-25 INSIGHT Special Feature When Missions Meet: Using Systems Engineering to Analyse the Potential for Interoperability between Earth Observation Satellite Missions Ian Raper, Ian Raper ian.raper@incose.org Search for more papers by this author Ian Raper, Ian Raper ian.raper@incose.org Search for more papers by this author First published: 23 June 2015 https://doi.org/10.1002/inst.200811522Citations: 1AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume11, Issue5December 2008Pages 22-25 RelatedInformation

OBSERVING EARTH VIA SATELLITE

THE U.S. GOVERNMENT needs to fund 17 new Earth-observing satellite missions over the next decade, says a two-year study from the National Research Council. Without increased funding for such missions, the report warns, critical data on climate change, hurricanes, winds, polar ice, and shifting patterns of drought and rainfall will not be available. Prepared by a panel of more than 100 earth scientists, the NRC report sets priorities for the next decade for Earth observation projects at NASA and the National Oceanic & Atmospheric Administration (NOAA). At a time when it's never been more important to observe and understand the Earth in all its aspects and to apply this understanding for the benefit of society, the number of Earth-observing instruments on NASA satellites will fall 40% by 2010 unless something is done to reverse the trend, says report cochair Richard A. Anthes, president of the University Corporation for Atmospheric Research. The general investments in earth ...

地球観測衛星の地表点トラッキングに関する研究

Recently, earth observation satellite missions are becoming more demanding and diversified to note 3-dimensional map production, disaster observation, earth resource exploration, and so on. As a result, the pointing or tracking requirements of mission instruments such as CCD camera or Rader to the ground target are decisive factors in designing the Attitude and Orbit Control System (AOCS). In this paper, the relation between AOCS capability of the satellite main body and the ground tracking accuracy is strictly defined and a new determination method of attitude and attitude rate specifications to meet these requirements is proposed. Assuming an AOCS with a star tracker unit and GPS, the validity of the proposed method is demonstrated by numerical simulations.

SAC-C mission, an example of international cooperation

The SAC-C is an international Earth observing satellite mission developed as a partnership between CONAE and NASA, with additional support in instrumentation and satellite development from the Danish DSRI, the Italian ASI, the French CNES and the Brazilian INPE. The SAC-C satellite was successfully launched by a Delta II rocket on November 21, 2000, from Vandenberg AFB, California, USA. The purpose of this mission is to carry out observations which bear interest both for the USA and Argentina, thus contributing effectively to NASA's Earth Science Program and to CONAE's National Space Program. The inclusion of SAC-C in the “morning constellation”, jointly with NASA satellites Landsat 7, EO 1 and Terra, is another example of an important international cooperation which strengthens the output of any single mission.

Aqua: an Earth-Observing Satellite mission to examine water and other climate variables

Aqua is a major satellite mission of the Earth Observing System (EOS), an international program centered at the U.S. National Aeronautics and Space Administration (NASA). The Aqua satellite carries six distinct Earth-observing instruments to measure numerous aspects of Earth's atmosphere, land, oceans, biosphere, and cryosphere, with a concentration on water in the Earth system. Launched on May 4, 2002, the satellite is in a Sun-synchronous orbit at an altitude of 705 km, with a track that takes it north across the equator at 1:30 p.m. and south across the equator at 1:30 a.m. All of its Earth-observing instruments are operating, and all have the ability to obtain global measurements within two days. The Aqua data will be archived and available to the research community through four Distributed Active Archive Centers (DAACs).