During latter half of the twentieth century the concept that the behavior of the planet Earth can only be understood in terms of coupling between dynamic systems in atmosphere, solid Earth, hydrosphere, cryosphere, biosphere and anthroposphere was launched. The study of these interactions has become known as Earth System Science. The land surface plays a driving role in Earth System Science through its dominant biospheric and anthropogenic populations. It plays a key connecting role between systems, for example, interacting with the atmosphere through exchange of heat, momentum and trace gases. It serves as a central but complex stage in the carbon and water cycles. Missions to study the land surface are very important and will be increasingly high impact. This paper examines the challenges and gaps in observations of the Land Surface from satellite remote sensing. Satellite observations are required to monitor change, to allow the causes of change to be diagnosed and to understand in detail the current state. However, these observations must also be integrated to have greatest impact, flying in formation or as part of an overall system can yield a much greater dividend than individual measurements. Hence there are a large number of application areas of the land surface, which are increasing at a rapid rate. Fortunately, there is a strong link between variables observed as useful and products, which can be used in application services. Therefore science gaps tend to map into application service gaps, although application areas also demand long-term operational services usually.
KEYWORDS: Reflectivity, Polarization, Carbon monoxide, Absorption, Gases, Near infrared, Spectrometers, Spatial resolution, Signal to noise ratio, Short wave infrared radiation
CarbonSat is a candidate mission for ESA's Earth Explorer program, currently undergoing industrial feasibility studies. The primary mission objective is the identification and quantification of regional and local sources and sinks of carbon dioxide (CO2) and methane (CH4). The mission also aims at discriminating natural and anthropogenic fluxes. The space-borne instrument will quantify the spatial distribution of CO2 and CH4 by measuring dry air column-averaged mixing ratios with high precision and accuracy (0.5 ppm for CO2 and 5 ppb for CH4). These products are inferred from spectrally resolved measurements of Earth reflectance in three spectral bands in the Near Infrared (747-773 nm) and Short Wave Infrared (1590-1675 nm and 1925-2095 nm), at high and medium spectral resolution (0.1nm, 0.3 nm, and 0.55 nm). Three spatially co-aligned push-broom imaging spectrometers with a swath width <180 km will acquire observations at a spatial resolution of 2 x 3 km2 , reaching global coverage every 12 days above 40 degrees latitude (30 days at the equator). The targeted product accuracy translates into stringent radiometric, spectral and geometric requirements for the instrument. Because of the high sensitivity of the product retrieval to spurious spectral features of the instrument, special emphasis is placed on constraining relative spectral radiometric errors from polarisation sensitivity, diffuser speckles and stray light. A new requirement formulation targets to simultaneously constrain both the amplitude and the correlation of spectral features with the absorption structures of the targeted gases. The requirement performance analysis of the so-called effective spectral radiometric accuracy (ESRA) establishes a traceable link between instrumental artifacts and the impact on the level-2 products (column-averaged mixing ratios). This paper presents the derivation of system requirements from the demanding mission objectives and report preliminary results of the feasibility studies.
The performance analysis of a satellite mission requires specific tools that can simulate the behavior of the platform; its payload; and the acquisition of scientific data from synthetic scenes. These software tools, called End-to-End Mission Performance Simulators (E2ES), are promoted by the European Space Agency (ESA) with the goal of consolidating the instrument and mission requirements as well as optimizing the implemented data processing algorithms. Nevertheless, most developed E2ES are designed for a specific satellite mission and can hardly be adapted to other satellite missions. In the frame of ESA's FLEX mission activities, an E2ES is being developed based on a generic architecture for passive optical missions. FLEX E2ES implements a state-of-the-art synthetic scene generator that is coupled with dedicated algorithms that model the platform and instrument characteristics. This work will describe the flexibility of the FLEX E2ES to simulate complex synthetic scenes with a variety of land cover classes, topography and cloud cover that are observed separately by each instrument (FLORIS, OLCI and SLSTR). The implemented algorithms allows modelling the sensor behavior, i.e. the spectral/spatial resampling of the input scene; the geometry of acquisition; the sensor noises and non-uniformity effects (e.g. stray-light, spectral smile and radiometric noise); and the full retrieval scheme up to Level-2 products. It is expected that the design methodology implemented in FLEX E2ES can be used as baseline for other imaging spectrometer missions and will be further expanded towards a generic E2ES software tool.
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