Determination of the cloud fraction in the SCIAMACHY ground scene using MERIS spectral measurements

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY) is a passive remote sensing spectrometer observing backscattered radiation from the atmosphere and the Earth's surface, in the wavelength range between 240 and 2380 nm. The instrument is onboard ENVironmental SATellite (ENVISAT) which was launched on 1 March 2002. The Medium Resolution Imaging Spectrometer (MERIS) is also one of the 10 instruments onboard the ENVISAT satellite. MERIS is a 68.5° field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). It obtains a global coverage of the Earth in three days. Its main objective is to measure sea colour and quantify ocean chlorophyll content and sediment, thus providing information on the ocean carbon cycle and thermal regime. It is also used to derive the cloud top height, aerosol and cloud optical thickness, and water vapour column. The ground spatial resolution of the instrument is 260 m × 290 m. This paper is aimed at determining the cloud fraction in SCIAMACHY pixels (typically, 30 km × 60 km ground scenes) using MERIS observations and number of thresholds for MERIS top-of-atmosphere reflectances and their ratios. Thresholds utilize the fact that clouds are bright white objects having similar reflectances in the blue and red. The MERIS cloud fraction has been derived for a number of SCIAMACHY states with area of 916 km × 400 km. The results are compared with correspondent cloud fractions obtained using SCIAMACHY polarization measurement devices (PMDs). Large differences are found between cloud fractions derived using SCIAMACHY and MERIS measurements. It is recommended to use highly spatially resolved MERIS observations instead of SCIAMACHY PMD measurements to retrieve cloud fractions in SCIAMACHY pixels. The improvements advised will enhance SCIAMACHY trace gas and cloud retrievals in the presence of broken cloud fields.     

MERIS potential for coastal zone applications

The Medium Resolution Imaging Spectrometer (MERIS) will be flown on the Envisat mission in 1999 and will provide the user community with a unique instrument for monitoring important water quality parameters in coastal waters. The instrument will be of special interest for coastal zone research projects such as the International Geosphere Biosphere Program (IGBP), Land Ocean Interactions in the Coastal Zone (LOICZ) and for environmental impact monitoring, assessment and management programmes. MERIS characteristics include nine spectral channels (out of 15) covering the visible spectral range (410-705nm) which are optimized to the radiance level of water surfaces. Within this range there are bands dedicated to mapping concentrations of suspended particulate matter, phytoplankton, gelbstoff (or coloured dissolved organic matter) and bands for determining sunlight-stimulated fluorescence of phytoplankton chlorophyll. Its spatial resolution of 300m and revisit period of 3 days are well suited to the observation of most of the phenomena which are of interest for coastal water quality research and management. New algorithms will have to be developed for computing the different water constituents from the observations and for atmospheric correction of turbid waters. Examples of applications, for which the design of MERIS is optimized, are presented.     

Cover. Wind energy mapping of coastal zones by synthetic aperture radar (SAR) for siting potential windmill locations

MERIS (Medium Resolution Imaging Spectrometer) is a fine spectral and medium spatial resolution satellite sensor and is part of the core instrument payload of Envisat, the European Space Agency's (ESA) environmental research satellite, launched in March 2002. Designed primarily for ocean (‘MER’) and coastal zone remote sensing, this imaging spectrometer (‘IS’) now has a much broader environmental remit covering also land and atmospheric applications. This paper reviews (i) MERIS's development history, focusing on its changing mission objectives; (ii) MERIS's technical specification, including its radiometric, spectral and geometric characteristics, programmability and onboard calibration; (iii) decisions that led to modifications of MERIS's spectral, geometric and radiometric performance for land applications; (iv) MERIS's data products; and (v) some of the ways in which MERIS data might be used to provide information on terrestrial vegetation.     

Merged satellite ocean color data products using a bio-optical model: Characteristics, benefits and issues

The characteristics and benefits of ocean color merged data sets created using a semi-analytical model and the normalized water-leaving radiance observations from the SeaWiFS, MODIS-AQUA and MERIS ocean color missions are presented. Merged data products are coalesced from multiple mission observations into a single data product with better spatial and temporal coverage than the individual missions. Using the data from SeaWiFS, MODIS-AQUA and MERIS for the 2002-2009 time period, the average daily coverage of a merged product is ∼ 25% of the world ocean which is nearly twice that of any single mission's observations. The frequency at which a particular area is sampled from space is also greatly improved in merged data as some areas can be sampled as frequently as 64% of the time (in days). The merged data presented here are validated through matchup analyses and by comparing them to the data sets obtained from individual missions. Further, a complete error budget for the final merged data products was developed which accounts for uncertainty associated with input water-leaving radiances and provides uncertainty levels for the output products (i.e. the chlorophyll concentration, the combined dissolved and detrital absorption coefficient and the particulate backscattering coefficient). These merged products and their uncertainties at each pixel were developed within the NASA REASON/MEaSUREs and ESA GlobColour projects and are available to the scientific community. Our approach has many benefits for the creation of unified Climate Data Records from satellite ocean color observations.     

Inter-comparison of OC-CCI chlorophyll-a estimates with precursor data sets

Ocean colour is the only essential climate variable that targets a biological variable (chlorophyll-a concentration (chl-a)) and is also amenable to remote sensing at the global scale. However, the finite lifetime of individual ocean-colour sensors, and the differences in their characteristics increase the difficulty of creating a long-term, consistent, ocean-colour time series that meets the requirements of climate studies. The Ocean Colour Climate Change Initiative (OC-CCI), a European Space Agency programme, has recently produced a time series of satellite-based ocean-colour products at the global scale, merging data from three sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer on the Aqua Earth Observing System (MODIS-Aqua), and Medium Resolution Imaging Spectrometer (MERIS), while attempting to reduce inter-sensor biases.In this work we present a comparison between the OC-CCI chlorophyll-a product and precursor satellite-derived data sets, from both single missions (SeaWiFS, MODIS-Aqua, and MERIS) and multi-mission products (global ocean colour (GlobColour) and Making Earth Science Data Records for Use in Research Environments (MEaSUREs)). To this end, OC-CCI global monthly composites are compared to the similar products offered by single-mission and multi-mission records. Our results indicate that the OC-CCI product provides a higher number of observations. Comparing the observations that match with precursors, the OC-CCI product was generally most similar to the single-mission products. Relationships between OC-CCI and other precursors did not change significantly during a common and continuous period, and, on average the root-mean-square differences between log-transformed chlorophyll-a concentration are below or equal to 0.11. Further, when considering variability that could arise when merging data from different sources, it is shown that the OC-CCI product is a longer term constant than those from other multi-mission initiatives studied here.     

Downscaling time series of MERIS full resolution data to monitor vegetation seasonal dynamics

Monitoring vegetation dynamics is fundamental for improving Earth system models and for increasing our understanding of the terrestrial carbon cycle and the interactions between biosphere and climate. Medium spatial resolution sensors, like MERIS, exhibit a significant potential to study these dynamics over large areas because of their spatial, spectral and temporal resolution. However, the spatial resolution provided by MERIS (300 m in full resolution mode) is not appropriate to monitor heterogeneous landscapes, where typical length scales of these dynamics rarely reach 300 m. We, therefore, motivate the use of data fusion techniques to downscale medium spatial resolution data (MERIS full resolution, FR) to a Landsat-like spatial resolution (25 m). An unmixing-based data fusion approach was applied to a time series of MERIS FR images acquired over The Netherlands. The selected data fusion approach is based on the linear mixing model and uses a high spatial resolution land use database to produce images having the spectral and temporal resolution as provided by MERIS, but a Landsat-like spatial resolution. A quantitative assessment of the quality of the fused images was done in order to test the validity of the proposed method and to evaluate the radiometric characteristics of the MERIS fused images. The resulting series of fused images was subsequently used to compute two vegetation indices specifically designed for MERIS: the MERIS terrestrial chlorophyll index (MTCI) and the MERIS global vegetation index (MGVI). These indices represent continuous fields of canopy chlorophyll (MTCI) and of the fraction of photosynthetically active radiation absorbed by the canopy (MGVI). Results indicate that the selected data fusion approach can be successfully used to downscale MERIS data and, therefore, to monitor vegetation dynamics at Landsat-like spatial, and MERIS-like spectral and temporal resolution.     

MERIS potential for ocean colour studies in the open ocean

The interest of space observations of ocean colour for determining variations in phytoplankton distribution and for deriving primary production (via models) has been largely demonstrated by the Coastal Zone Color Scanner (CZCS) which operated from 1978 to 1986. The capabilities of this pioneer sensor, however, were limited both in spectral resolution and radiometric accuracy. The next generation of ocean colour sensors will benefit from major improvements. The Medium Resolution Imaging Spectrometer (MERIS), planned by the European Space Agency (ESA) for the Envisat platform, has been designed to measure radiances in 15 visible and infrared channels. Three infrared channels will allow aerosol characterization, and therefore accurate atmospheric corrections, to be performed for each pixel. For the retrieval of marine parameters, nine channels between 410 and 705nm will be available (as opposed to only four with the CZCS). In coastal waters this should, in principle, allow a separate quantification of different substances (phytoplankton, mineral particles, yellow substance) to be performed. In open ocean waters optically dominated by phytoplankton and their associate detrital matter, the basic information (i.e. the concentration of phytoplanktonic pigments) will be retrieved with improved accuracy due to the increased radiometric performances of MERIS. The adoption of multi-wavelength algorithms could also lead to additional information concerning auxiliary pigments and taxonomic groups. Finally, MERIS will be one of the first sensors to allow measurements of Sun-induced chlorophyll a in vivo fluorescence, which could provide a complementary approach for the assessment of phytoplankton abundance. The development of these next-generation algorithms, however, requires a number of fundamental studies.     

The potential for estimating chlorophyll content from a vegetation canopy using the Medium Resolution Imaging Spectrometer (MERIS)

In 2000, the European Space Agency aims to launch the Envisat-1 satellite platform which will carry the Medium Resolution Imaging Spectrometer (MERIS), an advanced optical sensor designed to acquire Earth observation data at regional to global scales. Of particular relevance to terrestrial ecosystems functioning, the MERIS offers the potential to estimate the spectral location of the maximum slope, termed the red edge position (REP), which marks the boundary between chlorophyll absorption in the red wavelengths and the high infrared reflectance due to leaf internal scattering. However, although a first derivative transformation of the reflectance spectra will highlight the maximum slope position, the accurate location of the REP is limited by the spectral sampling resolution of the sensor. A theoretical analysis, using a combined leaf-canopy radiative transfer model, demonstrates that the MERIS, having five coarsely spaced wavebands in the region of the REP, can be utilized for monitoring spectral shifts of the REP, resulting from variation in leaf chlorophyll content or leaf area index.     

Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D

Understanding global climate change and developing strategies for sustainable use of our environmental resources are major scientific and political challenges. In response to an announcement of the German Aerospace Center (DLR) for a national Earth observation (EO) mission, the Friedrich-Schiller University Jena and the JenaOptronik GmbH proposed the EO mission Carbon-3D. The data products of this mission will for the first time accurately estimate aboveground biomass globally, one of the most important parameters of the carbon cycle. Simultaneous acquisition of multiangle optical with Light Detection and Ranging (LIDAR) observations is unprecedented. The optical imager extrapolates the laser-retrieved height profiles to biophysical vegetation maps. This innovative mission will reduce uncertainties about net effects of deforestation and forest regrowth on atmospheric CO₂ concentrations and will also provide key biophysical information for biosphere models.     

Snow cover monitoring in Alpine regions using ENVISAT optical data

The ENVISAT mission with a suite of high performance sensors offers some opportunities for mapping snow cover at regional and catchment scales. The spatial resolution of the Medium Resolution Imaging Spectrometer Instrument (MERIS) data and the spectral characteristics of the Advanced Along Track Scanning Radiometer (AATSR) data are suitable for these purposes. A new approach has been developed for the generation of snow cover products in Alpine regions, based on the combined use of ENVISAT optical data and topographic information. The Alpine region is selected as a test area to demonstrate the potential and the limitations of the novel approach. In particular, attention is focused on three regions of northern Italy (Valle d'Aosta, Piemonte, Lombardia). The first results obtained by the application of this new method to Earth Observation data will be presented and analysed.     

Validation of MERIS LAI and FAPAR products for winter wheat-sown test fields in North-East Bulgaria

Progress in deriving land surface biophysical parameters in a spatially explicit manner using remotely sensed data has greatly enhanced our ability to model ecosystem processes and monitor crop development. A multitude of satellite sensors and algorithms have been used to generate ready-to-use maps of various biophysical parameters. Validation of these products for different vegetation types is needed to assess their reliability and consistency. While most of the current satellite biophysical products have spatial resolution of one kilometre, a recent effort utilizing data from the Medium Resolution Imaging Spectrometer (MERIS) provided leaf area index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and other canopy parameters in a resolution as fine as 300 m over the European continent. This resolution would be more appropriate for application at the regional scale, particularly for crop monitoring. This higher-resolution MERIS product has been evaluated in a limited number of studies to date. This article aims to validate LAI and FAPAR from the MERIS 10-day composite BioPar BP-10 product over winter wheat fields in northeast Bulgaria. The ground measurements of LAI and FAPAR were up-scaled and 30 m resolution reference raster layers were created using empirical relationships with Landsat TM (RMSE = 0.06 and RMSE = 0.22 for FAPAR and LAI, respectively). MERIS FAPAR and LAI were found to have significant correlation with FAPAR and LAI from the reference raster layers (R² = 0.84 and R² = 0.78, respectively). When MERIS Green LAI was calculated (incorporating the fraction of vegetation and brown vegetation cover from the BioPar BP-10 product), better correspondence with LAI values from the reference raster layer was achieved, with RMSE and bias reduced by 30–35%. The results from this study confirm the findings of previous validations showing that MERIS Green LAI tends to overestimate LAI values lower than 1. As a conclusion of the study, the BioPar BP-10 product was found to provide reliable estimates of FAPAR and acceptably accurate estimates of LAI for winter wheat crops in North-East Bulgaria.     

基于AMSR-E的全球陆表被动微波发射率数据集

地表微波发射率表征了地物向外发射微波辐射的能力,星载被动微波发射率估算可在宏观、大尺度上对陆表微波辐射进行整体表达,是被动微波地表参数定量反演中重要基础数据,也是在大尺度上获取陆表微波辐射特征的一种途径。本数据集利用搭载在Aqua卫星上的高级微波扫描辐射计(AMSR-E)和中分辨率成像光谱仪(MODIS)的同步观测特点,采用MODIS的地表温度和大气水汽产品数据作为输入,基于考虑大气影响的发射率估算模型,生产了全球晴空条件下AMSR-E传感器运行期间(2002年6月~2011年10月)的陆表多通道双极化微波瞬时发射率。通过产品低频无线电信号影响、数据间比对、分布统计、不同地表覆盖条件的发射率特征、频率依赖和相关性研究等开展验证性分析,结果表明:瞬时发射率的动态大、细节表达丰富,月内日变化标准差在0.02以内,其时空变化、频率依赖和相关性等符合微波理论分析和自然物理过程理解。此套数据集还包括AMSR-E全生命周期的全球陆表逐日、侯、旬、半月及月产品,可用于开展星载被动微波遥感模拟、陆面模型以及陆表温度、积雪、大气降水/水汽/可降水量等反演研究。     

A near‐real time automatic MODIS data processing system

The Moderate Resolution Imaging Spectroradiometer (MODIS) on‐board the Aqua and Terra platforms was designed to improve understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. The UK Dundee Satellite Receiving Station has two X‐band receiving systems capable of capturing direct broadcast data from these spacecraft with a range covering the European shelf‐areas, north‐east Atlantic ocean and the western Mediterranean Sea. Raw data are transferred to the Plymouth Marine Laboratory (PML) and processed in near‐real time into ocean colour and sea‐surface temperature products for the academic community. Data can be used operationally and are made available through the web within 1.5 hours of the satellite overpass time. To our knowledge this is the only such developed system in Europe producing near‐real time MODIS ocean colour products.     

High resolution spatio‐temporal water vapour mapping using GPS and MERIS observations

Improved knowledge of atmospheric water vapour and its temporal and spatial variability is of great scientific interest for climate research and weather prediction. Moreover, the availability of fine resolution water vapour maps is expected to reduce significant errors in applications using the Global Positioning System, GPS, or radar interferometry. Several methods exist to estimate water vapour using satellite systems. Combining radiances as measured in two spectral bands of the Medium Resolution Imaging Spectrometer (MERIS) results in an Integrated Water Vapor (IWV) product with high spatial resolution, up to 300 m, but a limited temporal resolution of about three days, in case of cloud free conditions. On the other hand, IWV estimates can be derived from the zenith total delays as observed by continuous GPS networks. The GPS IWV estimates have a higher temporal resolution of typically 1 hour, but, even in Western Europe, inter‐station distances are at least tenths of kilometres. Here we describe how to obtain IWV products with high spatio‐temporal resolution by combining GPS and MERIS IWV estimates. For this purpose an analysis is made of MERIS and GPS based IWV data, retrieved at the same day over Western Europe. A variance–covariance analysis is performed and is subsequently applied to produce time series of combined high‐resolution water vapour maps using Kriging. The research presented here is a first step towards near real‐time fine resolution water vapour products.     

Satellite-based water quality monitoring in Lake Vänern,Sweden

Lake Vänern, Sweden, is one of Europe’s largest lakes and has a historical, cultural, ecological as well as economic importance. Lake water quality monitoring is required by national and international legislations and directives, but present programmes are insufficient to meet the requirements. To complement in situ based monitoring, the possibility to obtain reliable information about spatial and temporal water quality trends in Lake Vänern from the ENVISAT mission’s MERIS instrument was evaluated. The complete archive (2002–2012) of MERIS (Medium Resolution Imaging Spectrometer) full resolution data was processed using the water processor developed by Free University Berlin (FUB) to derive aerosol optical thickness (AOT), remote-sensing reflectance (R_rs) and water quality parameters: chlorophyll-a (chl-a) concentration, coloured dissolved organic matter absorption at 443 nm (CDOM), and total suspended matter (TSM) concentration. The objective was to investigate if, either, FUB reflectance products in combination with potential lake-specific band ratio algorithms for water quality estimation, or directly, FUB water quality products, could complement the existing monitoring programme.

Application of lake-specific band ratio algorithms requires high-quality reflectance products based on correctly estimated AOT. The FUB reflectance and AOT products were evaluated using Aerosol Robotic Network – Ocean Color (AERONET-OC) match-up data measured at station Pålgrunden in Lake Vänern. The mean absolute percentage differences (MAPDs) of the final reflectance retrievals at 413, 443, 490, 555, and 665 nm were 510%, 48%, 33%, 34%, and 33%, respectively, corresponding to a large positive bias in 413 nm, positive bias in 443–555 nm, and a negative bias in 665 nm. AOT was strongly overestimated in all bands.

The FUB water quality products were evaluated using match-up in situ data of chl-a, filtered absorbance (Abs_F(420)) and turbidity as Abs_F(420) is related to CDOM and turbidity is strongly related to TSM. The in situ data was collected within the Swedish national and regional monitoring programmes. In order to widen the range of water constituents and add more data to the analysis, data from four large Swedish lakes (Vänern, Vättern, Mälaren, and Hjälmaren) was included in the analysis. High correlation (r ≥ 0.85) between in situ data and MERIS FUB derived water quality estimates were obtained, but the absolute levels were over- (chl-a) or under- (CDOM) estimated. TSM was retrieved without bias.

Calibration algorithms were established for chl-a and CDOM based on the match-up data from all four lakes. After calibration of the MERIS FUB data, realistic time series could be derived that were well in line with in situ measurements. The MAPDs of the final retrievals of chl-a, Abs_F(420) and Turbidity in Lake Vänern were 37%, 15%, and 35%, respectively, corresponding to mean absolute differences (MADs) of 0.9 µg l^?1, 0.17 m^?1, and 0.32 mg l^?1 in absolute values.

The partly inaccurate reflectance estimations in combination with both positive and negative bias imply that successful application of band ratio algorithms is unlikely. The high correlation between MERIS FUB water quality products and in situ data, on the other hand, shows a potential to complement present water quality monitoring programmes and improve the understanding and representability of the temporally and spatially sparse in situ observations. The monitoring potential shown in this study is applicable to the Sentinel-3 mission’s OLCI (Ocean Land Colour Instrument), which was launched by the European Space Agency (ESA) in February 2016 as a part of the EC Copernicus programme.     

Uncertainty estimates for the FAPAR operational products derived from MERIS — Impact of top-of-atmosphere radiance uncertainties and validation with field data

This paper discusses the accuracy of the operational Medium Resolution Imaging Spectrometer (MERIS) Level 2 land product which corresponds to the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). The FAPAR value is estimated from daily MERIS spectral measurements acquired at the top-of-atmosphere, using a physically based approach. The products are operationally available at the reduced spatial resolution, i.e. 1.2 km, and can be computed at the full spatial resolution, i.e. at 300 m, from the top-of-atmosphere MERIS data by using the same algorithm. The quality assessment of the MERIS FAPAR products capitalizes on the availability of five years of data acquired globally. The actual validation exercise is performed in two steps including, first, an analysis of the accuracy of the FAPAR algorithm itself with respect to the spectral measurements uncertainties and, second, with a direct comparison of the FAPAR time series against ground-based estimations as well as similar FAPAR products derived from other optical sensor data. The results indicate that the impact of top-of-atmosphere radiance uncertainties on the operational MERIS FAPAR products accuracy is expected to be at about 5-10% and the agreement with the ground-based estimates over different canopy types is achieved within ± 0.1.     

An evaluation of satellite aerosol products against sunphotometer measurements

Because atmospheric aerosols scatter sunlight back to space, reflectance measurements from spaceborne radiometers can be used to estimate the aerosol load and its optical properties. Several aerosol products have been generated in a systematic way, and are available for further studies. In this paper, we evaluate the accuracy of such aerosol products derived from the measurements of POLDER, MODIS, MERIS, SEVIRI and CALIOP, through a statistical comparison with Aerosol Optical Depth (AOD) measurements from the AERONET sunphotometer network. Although this method is commonly used, this study is, to our knowledge, among the most extensive of its type since it compares the performance of the products from 5 different sensors using up to five years of data for each of them at global scale. The choice of these satellite aerosol datasets was based on their availability at the ICARE Data and Service Centre (www.icare.univ-lille1.fr).We distinguish between retrievals over land and ocean and between estimates of total and fine mode AOD. Over the oceans, POLDER and MODIS retrievals are of similar quality, with RMS difference lower than 0.1 and a correlation with AERONET of around 0.9. The POLDER estimates suffer from a small positive bias for clean atmospheres, which weakens its statistics. The other aerosol products are of lesser quality, although the SEVIRI products may be of interest for some applications that require a high temporal resolution. The MERIS product shows a very high bias. Over land, only the MODIS product offers a reliable estimate of the total AOD. On the other hand, the polarization-based retrieval using POLDER data allows a better fine mode estimate than that from MODIS. These results suggest the need for a product combining POLDER and MODIS products over land.The paper also analyses how the statistics change with the spatial and temporal thresholds that are used. Spatio-temporal averaging improves the statistics only slightly, which indicates that random errors are not dominant in the error budget. The paper includes various statistical indicators at global scale, and detailed results at individual ground stations can be obtained on request from the authors.     

Potential observations with EURECA/VEXUVIO imagingspectrometer

Despite its geological importance, the Earth's volcanic activity has only recently been studied as a global system, with the advent of sophisticated airborne and spaceborne remote sensing systems that safely and economically provide global access at will. Particularly relevant to this approach are global studies of the effects on weather and climate caused by volcanic solid/gaseous products and thermal flux into the environment. To study such time-varying phenomena, observations of volcanic emissions spectral response, acquired simultaneously at a variety of wavelengths from ultra-violet to infra-red, could yield relevant information on the compositions and concentrations of environmentally important components, such as volcanically generated sulphur compounds (e.g., SO₂ H₂SO₄), and on volcanoes thermal behaviour. For this purpose, a multi-band imaging spectrometer, dedicated to volcanological observations (VEXUVIO, Visible EXplorer Ultra Violet Infra-red Observer) has been designed to be flown on-board EURECA (EUropean REtrievable CArrier) spacecraft, to be launched by the European Space Agency on the NASA Space Shuttle in 1996. In order to analyse potential observation scenarios with this sensor, volcanoes active during 1991 were studied using a computer code to simulate VEXUVIO capabilities on-board EURECA. Some parameters, representative of the sensor viewing geometry and of the volcanoes observation conditions, are exploited, and several plots are reported, shown their values during the six-months nominal EURECA mission. Despite the limited science objectives of EURECA program and a tightly constrained operational environment, our simulation demonstrates that a reasonable program of volcanologically interesting time-series observations can be carried out during the planned sixmonths lifetime of the EURECA mission.     

Automated cloud detection and classification of data collected by the Visible Infrared Imager Radiometer Suite (VIIRS)

The Visible Infrared Imager Radiometer Suite (VIIRS) is a high‐resolution Earth imager of the United States National Polar‐orbiting Operational Environmental Satellite System (NPOESS). VIIRS has its heritage in three sensors currently collecting imagery of the Earth—the Advanced Very High Resolution Radiometer, the Moderate Resolution Imaging Spectroradiometer, and the Operational Linescan Sensor. The first launch of the VIIRS sensor is on NASA's NPOESS Preparatory Project (NPP). Data collected by VIIRS will provide products to a variety of users, supporting applications from real‐time to long‐term climate change timescales. VIIRS has been uniquely designed to satisfy this full range of requirements. Cloud masks derived from the automated analyses of VIIRS data are critical data products for the NPOESS program. In this paper, the VIIRS cloud mask (VCM) performance requirements are highlighted, along with the algorithm developed to satisfy these requirements. The expected performance of the VCM algorithm is established using global synthetic cloud simulations and manual cloud analyses of VIIRS proxy imagery. These results show the VCM analyses will satisfy the performance expectations of products created from it, including land and ocean surface products, cloud microphysical products, and automated cloud forecast products. Finally, minor deficiencies that remain in the VCM algorithm logic are identified along with a mitigation plan to resolve each prior to NPP launch or shortly thereafter.     

The PROBA-V mission: the space segment

PROBA-V (Project for On-Board Autonomy – Vegetation) is an ESA (European Space Agency) mission developed within the framework of the Agency’s General Support Technology Programme (GSTP) devoted to the observation of the Earth’s vegetation, providing data continuity with the SPOT (Satellite pour l’Observation de la Terre) 4 and 5 VEGETATION payloads as a gap-filler to the ESA Sentinel-3 mission. The PROBA-V space segment is based on a three-axis stabilized PROBA small-satellite platform of about 140 kg equipped with a state-of-the-art compact 4-band multi-spectral imager with a large field of view. The instrument’s optomechanics is based on three very compact TMA (three mirror anastigmat) telescopes placed on an optical bench. At an altitude of 820 km, the instrument is able to provide daily coverage of the Earth in three VNIR (visible and near-infrared) bands and one SWIR (short-wave infrared) spectral band, with a spatial resolution of up to 100 m × 100 m at nadir for the VNIR. The instrument raw data will be downlinked with an X-band transmitter to the ground reception station in Kiruna, Sweden. The mission control centre is located in Redu, Belgium. The image processing centre, the so-called ‘user segment’, automatically accesses the raw data and is responsible for the processing and the dissemination of the data products towards the user community. The PROBA-V spacecraft was launched on board the new European launcher Vega on 7 May 2013. It is designed for a nominal mission lifetime of 2.5 years with a possible extension to 5 years.