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The European contribution to the Forest DRAGON 2 focused on the evaluation of multi-temporal, multi-sensor and multi-scale Earth Observation images and data products within the vegetation ecosystem of Northeast China. The forest growing stock volume (GSV) map produced with ERS-1/2 coherence images for 1995-1998 and two GSV maps produced from Envisat ASAR ScanSAR data for 2005 and 2010 were inter-compared with respect to several datasets (in situ, EO images and EO data products) to assess the plausibility of the GSV estimates, the contribution to land cover mapping and the dynamics over time. For this purpose, a multi-source database was set up including in situ data and EO data products. Land use / land cover (LULC) datasets identified mis-classification of GSV in the ERS dataset primarily for cropland. An a posteriori correction of the GSV resulted in an increase of overall accuracy up to 7%. LULC products can also support the fine tuning of the algorithm to estimate GSV from ASAR data particularly in transition regions between forest and shrubland. The ASAR-based GSV estimates were consistent and highlighted areas of change. From the two ASAR maps, slight loss of volume from 2005 to 2010 was estimated.

A representative and consistent wetland map for the circumpolar region is required for a range of applications including modelling of permafrost properties as well as upscaling of carbon pools and fluxes. Synthetic Aperture Radar (SAR) data has been shown to be suitable for wetland mapping, especially C-band ASAR GM data (1-km resolution). A circumpolar wetness classification map has been introduced previously [1]. With heterogeneity being a major challenge in the Arctic, higher spatial resolution products than GM are essential. In this study we therefore investigate the potential of this approach at site scale using ENVISAT ASAR WS data (∼120 m resolution). These higher resolution ASAR WS maps have been produced for study sites representing different settings throughout the Arctic and compared to high resolution land cover maps and field survey data. It can be shown that a medium resolution C-band SAR based wetness level map can be derived for tundra regions where no scattering due to tree trunks hampers the applied methodology.

This work aims to analyse red and far red sun-induced chlorophyll fluorescence (F) and biophysical variable patterns in a plain mixed forest (Forêt de Hardt, France) using ground measurements and airborne data. The airborne data were acquired using the novel airborne imaging spectrometer HyPlant developed by the Forschungszentrum Jülich in collaboration with SPECIM Spectral Imaging Ltd (Finland), covering the visible, near infrared and shortwave infrared spectral regions. The HyPlant sensor is the only currently available airborne imaging spectrometer with a subnanometer spectral resolution in the region from 670 to 780 nm, offering the opportunity to quantify F at the two fluorescence emission peaks (red and far-red). The hyperspectral images were used to obtain three different products: (i) a forest species composition map based on a classification approach (ii) red and far red F maps obtained applying the singular vector decomposition (SVD) method and (iii) maps of leaf chlorophyll content (Chl) and Leaf Area Index (LAI) produced by means of radiative transfer models. Ground data were collected in a field campaign that was conducted concurrently with the airborne data acquisition with the aim to evaluate the accuracy of all the products. The ground measurements were acquired in 22 elementary sampling units of 20 x 20 m spread over an extensive area and consisted on species composition and crown condition assessment, leaf sampling for pigment extraction, digital hemispherical photography acquisition for LAI estimation, and top of canopy F measurements for each of the main forest species (i.e., hornbeam (Carpinus betulus L.), oak (Quercus robur L.), linden (Tilia L.) and pine (Pinus L.)) with high-resolution spectroradiometers manually operated from a mobile hydraulic platform. The spatial variability of the biophysical variables (Chl and LAI) and F retrieved from the airborne data were compared and analysed in relation with species-specific patterns and forest s

The aim of this study is the analysis of trend in the trophic level evolution in clear deep lakes which, being characterised by good quality state, are important socio-economic resources for their regions. The selected lakes are situated in Europe (Garda, Maggiore, Constance and Vättern), North America (Michigan) and Africa (Malawi and Tanganyika) and cover a range of eco-regions (continental, perialpine, boreal, rift valley) distributed globally. To evaluate trophic level tendency we mainly focused on chlorophyll-A concentrations (chl-a) which is a direct proxy of trophic status. The chl-A concentrations were obtained from 5216 cloud-free MERIS imagery from 2002 to 2012. The 'GLaSS RoIStats tool' available within the GLaSS project was used to extract chl-A in a number of region of interests (ROI) located in pelagic waters as well as some few other stations depending on lakes morphology. For producing the time-series trend, these extracted data were analysed with the Seasonal Kendall test. The results overall show almost stable conditions with a slight increase in concentration for lakes Maggiore, Constance, and the Green Bay of Lake Michigan; a slight decrease for lakes Garda and Tanganyika and absolutely stable conditions for lakes Vättern and Malawi. The results presented in this work show the great capability of MERIS to perform trend tests analysis on trophic status with focus on chl-A concentration. Being chl-A also a key parameter in water quality monitoring plans, this study also supports the managing practices implemented worldwide for using the water of the lakes.

Preliminary results of a new algorithm for the atmospheric correction of OLI imagery acquired over coastal and inland water are presented. The algorithm was based on the Second Simulation of the Satellite Signal in the Solar Spectrum (6SV) radiative transfer model and the atmopheric contribution was simulated by using the microphysical properties of the aerosol, their size distribution and refractive index, available from the AERONET stations located in the study area. The SeaDAS software was also applied to the OLI data to compare the results obtained by OLI@CRI algorithm with the standard procedure for atmospheric correction of remotely data. Furthermore, the adjacency effect was removed by the wellknown empirical formula as well as a new empirical formula to assess any possible improvement of the atmospheric correction products using the diffuse fraction of the total atmospheric transmission as weight for averaged reflectance removal. To validate the results and assess its accuracy, the above-water data acquired at AERONETOC sites were used. A coastal area and a lake are considered, where AERONET and AERONET-OC data are available. These sites cover a significant range of both atmospheric (from boreal to tropics) and water quality conditions.

Decreasing availability of in-situ river monitoring datacan be met with increasing availability and quality ofsatellite altimetry data over rivers. CryoSat-2 is analtimeter mission launched in 2010 by the EuropeanSpace Agency (ESA). With its unique drifting orbit,common procedures of working with satellite altimetrydata over rivers cannot be easily applied. This workpresents a way of informing a hydrologic-hydrodynamicmodel of the Brahmaputra River with CryoSat-2altimetry. For one, CryoSat-2 data with its high spatialresolution was used to calibrate water levels in the 1Dhydrodynamic model. For the other, a data assimilationframework was developed and applied, showingpromising results for assimilation experiments with realand synthetic CryoSat-2 data.

Almost all natural surfaces exhibit an individual anisotropic reflectance behaviour due to the contrast between the optical properties of surface elements and background and the geometric surface properties of the observed scene. The resulting bidirectional effects are present in all reflectance data and thus occur as well in various vegetation indices (VI’s) retrieved from multiangular data. No matter whether these effects are considered as noise or as a source of additional information, accurate knowledge about their magnitude is important. This preliminary study is based on data of the spaceborne ESA-mission CHRIS (Compact High Resolution Imaging Spectrometer) onboard PROBA-1 and on ground-based spectrodirectional measurements performed with the dual view field goniometer system FIGOS. The objectives of this study are focused on directional effects in CHRIS and FIGOS reflectance data of a Triticale field as well as on the variability of retrieved vegetation indices for selected view angles in both multiangular datasets.

A program has been written to create image mosaics from ASA_WSS_1P ASAR-WSS level-1 products, providing an overview of the imaged area. The ability to generate WSS mosaics facilitates the study of several WSS product features. This study focuses on their radiometric and geometric characteristics. The incidence angle variation of 16 to 43 degrees across beams SS1 through SS5 creates large differences in the nominal near- and far-range backscatter intensities. Radiometric calibration is applied to the mosaics, taking the range-spreading loss as well as the incidence angle effect into account, normalising for systematic radiometric trends. The five WSS beams acquire data with a substantial overlap (typically several hundred range samples). These overlap regions are of interest because the same ground targets are imaged by two different beams. We calculate the mean radiometric differences between the two beams for each overlap region, and draw conclusions based on the statistics. WSS geolocation accuracy is assessed for the image mosaics as well, using two methods. First, predicted positions of transponders in the Netherlands and Canada are compared to measured positions. Second, terrain geocoding of selected WSS scenes is performed, using DORIS precise state vectors and a digital terrain model (DTM). The geolocation accuracy is estimated using survey points or ground control points (GCPs) derived from topographic maps. The radiometric and geometric investigations confirm a high quality of the level-1 WSS products.

The GonioExp06 field campaign from 19th to 24th of June 2006 is part of a strategic initiative to improve bio-geo-chemo-physical parameter estimation from optical remote sensing data. The focus of the research is on the investigation of the directional fraction of hyperspectral data, emphasising the value adding effect of directional information as supplement to the well known spectral one. Three field goniometric systems (FIGOS, MGS and AIS A gon) of different design, an extensive accompanying measurement campaign and simultaneous multidirectional data takes by Proba/CHRIS (space) and ROSIS (airborne) are combined to create the data base necessar y to investigate the radiative transfer between the surface and the sensors and to contribute improving physical modelling and inversion techniques. The application focus is the “precision” domain in land use (agriculture, forestry, nature conservation).

Leaf area index (LAI) is a key variable for the understanding and modeling of several ecophysiological processes within a vegetation canopy. The LAI could thus provide vital information for the management of the environment and agricultural practices when estimated continuously over time and space thanks to remote sensing sensors such as CHRIS/PROBA. The spaceborne ESA-mission CHRIS/PROBA provides multi-temporal observations of the land surface in the spectral and directional information dimensions. This system represents a rich source of information for Earth observation purposes specifically adapted for monitoring the high dynamic of agricultural crops. For this purpose a radiative transfer model (RTM) is coupled to a canopy structure dynamic model (CSDM). The coupled models are used to exploit the complementary content of the spectral and temporal information dimensions for LAI estimation over a maize canopy. The resulting estimation of the temporal and spatial variation of LAI is improved by integrating multi-temporal CHRIS/PROBA data and ground meteorological observations. Further, the presented method provides the continuous LAI time course over the season, which is required by crop growth and land surface process models.

A multitemporal assessment of chlorophyll-a distribution using MERIS/ENVISAT FR data from 2003 through 2005 shows increased chlorophyll concentrations correlated to high algae bloom during the dry season from July to September. Intra- and interannual distribution patterns were investigated using spectral band ratio approaches. Maximum chlorophyll-a concentrations in Lake Kivu were found along the lake’s shore line, the southern basin, Bukavu Bay and Kabuno Bay. Regional and temporal variations are lowest in the lake’s central northern basin. Increased knowledge on the lake’s regional and temporal chlorophyll-a distribution may help for an improved description of the main features of nutrient cycling.

Sun and sensor geometry cause directional effects in remotely sensed reflectance data which can influence the estimation of biophysical and biochemical variables. Previous studies have indicated that bidirectional measurements contain added information with which the accuracy of derived plant structural parameters can be increased. Because accurate biochemistry mapping is linked to vegetation structure, estimates of nitrogen concentration (CN) and water content (CW) might be indirectly improved with multiangular information. We analyzed data of the spaceborne ESA-mission CHRIS on-board PROBA-1, which provides hyperspectral and directional data. The images were acquired in July 2006 over a forest study site in Switzerland. From each of the five CHRIS images (five different viewing zenith angles) we extracted 60 crown spectra, which correspond to field-sampled trees. Then we developed four-term models by regressing lab-measured CN and CW on two datasets either consisting of original reflectance values (SPEC) or continuum-removed data (BNC). The wavebands used in the regression models were determined with a subset selection algorithm. For the data of all view angle combinations particular models were generated, in total 31 equations were evaluated per spectral dataset by comparing the coefficients of determination (R2) and cross-validated root mean square errors. The results showed that directional information contained in multiangular data improved regression models for CN and CW estimation and lowered RMS errors. Considerable contribution can be achieved with data of a second and third viewing zenith angle. Monodirectional models developed on data of backward scattering angles performed in general better than models based on forward scattering data. Multidirectional models based on combinations of off-nadir data performed best for CN but not for CW. These findings support the potential of multiangular Earth observations for ecological monitoring and modeling studies.

The physically based Modular Inversion & Processing System (MIP) is used in a processing chain for inland water constituent retrieval from MERIS level 1B full resolution data. Reformatting, data import, water/land masking, atmospheric correction and water constituent retrieval are fully automized, in order to allow the efficient analysis of large data quantities in a time series of water quality in Swiss Lakes. To account for the temporal variation of atmosphere and water properties, a set of input parameters is optimized specifically for Lake Constance. The algorithm’s sensitivity to its input parameters is studied, allowing the derivation of a first guess parameterization. Results of successfully processed data are presented and reasons for processing errors are discussed.

Among the several applications that will take advantage of the newly available data from the ALOS PALSAR instrument, considerable interest is in the peculiar features that derive from the penetration and polarimetric capabilities of the system. These capabilities, new for a single spaceborne sensor, need specific software tools for the processing of the different acquisition modes. This paper presents a verification processor, developed under ESA contract, for the generation of polarimetric, interferometric and polarimetric-interferometric geocoded products derived from ALOS PALSAR data. The processor, developed with a modular approach, contains the following main elements: - Phase-preserving fine resolution processor; - Phase-preserving ScanSAR processor; - Interference removal tools; - Polarimetric calibration tools; - Polarimetric analysis tools; - Fine resolution interferometric processor; - ScanSAR interferometric processor; - Polarimetric-interferometric processor; - Geocoding; - Atmospheric modelling tools. The processor architecture is presented; highlights are given on specific modules and algorithms. Early results are shown, in particular of the processing of polarimetric and polarimetric-interferometric data over different test sites.

Accurate geolocation of SAR imagery enables not only precise overlays with other data sources in a common map geometry, but also normalisation for the systematic influence of terrain on image radiometry. We begin by describing our verifications of the geometric behaviour of ENVISAT ASAR products, including all image mode (IM), alternating polarisation (AP), and wide swath (WS) types: IMS, IMP , IMM, IMG, APS, APP , APM, APG, WSM, and WSS. Radar transponders in Canada and Europe are used as easily identifiable targets in radar images to test the accuracy of the nominal timing and state vector annotations accompanying each product. Accuracies achievable using DORIS precise state vectors are also evaluated. In addition to ENVISAT's ASAR, geolocation accuracies achievable using ERS-1/2 and ALOS PALSAR data are demonstrated. Given accurate knowledge of the acquisition geometry of a SAR image from one of the above sensors together with a digital elevation model (DEM) of the area imaged, the process of terrain geocoding is used to transform a diverse set of images into a common reference map geometry. The prerequisite DEM combined with accurate knowledge of the acquisition geometry also enables a radiometric correction, whereby variations in terrain specific to each scene are normalised to a common standard. Thematic interpretation benefits from such pre-processing: we demonstrate improved thematic discriminations using product overlays in a common map geometry where radiometric terrain correction (RTC) has been applied in comparison to typical GTC results.

This paper presents a verification processor, developed under ESA contract, for the generation of polarimetric, interferometric and polarimetric-interferometric geocoded products derived from SAR data obtained from the ALOS PALSAR instrument. The processor, developed with a modular approach, contains the following main elements: - Phase-preserving fine resolution processor; - Phase-preserving ScanSAR processor; - Interference removal tools; - Polarimetric calibration tools; - Polarimetric analysis tools; - Fine resolution interferometric processor; - ScanSAR interferometric processor; - Polarimetric-interferometric processor; - Geocoding; - Atmospheric modelling tools. All of the PALSAR acquisition modes (i.e. stripmap in one, two and full polarisations as well as ScanSAR) are supported both starting from raw and focused data. The processor architecture is presented; highlights are given on modules and algorithms specifically developed for handling the peculiarities of these L-Band SAR data. Examples are shown obtained during the first year of operation of the system, over a number of test sites and of different types of products and acquisition modes.

Monitoring vegetation dynamics is fundamental to improve Earth systems models and to increase our understanding of the terrestrial carbon cycle and the interactions biosphere-climate. Medium spatial resolution sensors, like MERIS, have a great potential to study these dynamics at regional/global scales. However, the spatial resolution provided by MERIS (300m in full resolution mode) might not be appropriate over highly heterogeneous landscapes. This is why the synergistic use of MERIS full resolution (FR) and Landsat TM data is studied in this paper. An unmixing-based data fusion approach was applied to a time series of MERIS FR images acquired over the Netherlands in 2003. The selected data fusion approach uses the linear mixing model and the information derived from Landsat TM imagery acquired in the same year to produce images that have the spectral and temporal resolutions provided by MERIS but with the spatial resolution of Landsat TM. After the fusion, a quantitative assessment of the quality of the fused images was done in order to assess the validity of the proposed methodology and to evaluate the radiometric characteristics of the images. Finally, the time series of fused images was used to compute land cover specific NDVI, MTCI and MGVI profiles.

Due to the specific climate conditions in the dry regions of Africa, an effective integrated water management is of great interest for the national authorities. This paper explains the workflow of the Aquifer Project product ‘Water and Vegetation Monitoring over entire Aquifer’. The large scale water and vegetation monitoring will be accomplished for the transboundary aquifer Iullemeden, which represents one of the major freshwater reservoirs of Africa. By the synergetic use of radar and optical data land cover classification maps for four different times within one season are provided. The changes between these dates as well as the seasonal vegetation and water dynamics were analysed. Furthermore, by inclusion of specific contextual features of irrigated vegetation in the region, an irrigated vegetation map could be derived. The results demonstrate the high potential of Earth Observation data for the decision support for a more efficient water management in Africa.

This paper presents the current status of UK land cover mapping and considers the requirements for future land cover monitoring systems, including accurate change detection. The paper then presents preliminary results from two different change detection methodologies. Plans for future work are also described.

A range of monitoring techniques including digital cameras, radiometers and satellites have the potential to provide new sources of data on vegetation dynamics, including consistent data on the spatial and temporal variability of phenological events and vegetation productivity. This paper compares four data sets collected in 2012 that capture the above-canopy and below-canopy phenology of a deciduous woodland. The longest time-series is provided by weekly below-canopy photos recorded weekly from 1998 onwards. The weekly photos are used to assess the inter-annual variability from 2004 onwards and suggest that green-up varies between 8th April and 3rd May.

The timing and duration of ice-onset on lakes and river channels is a relevant climate signal since it is strongly driven by the air temperature. Space-borne imaging radar is a suitable tool for the detection of freeze processes, as the backscattering of radar waves is highly dependent on the dielectric properties of the surface. For this study, a time series of high-resolution TerraSAR-X images recorded during fall and winter 2012 was analysed. The images cover several lakes and river channels located in the central Lena Delta, North Siberia, Russia. On the basis of radar signature analysis and of classification results from visible inspection of the images we discuss the potential of change detection and intensity-thresholds for the separation of thin ice covers and water surfaces.

With the possibility of acquiring satellite radar images at different spatial resolutions and swath widths (i. e. at different scales) there is a need for selecting the optimal image product for the analysis of sea ice conditions. Both resolution and areal coverage influence the discrimination (and definition) of different sea ice zones and structures. A wide coverage is usually linked with a relatively coarse spatial resolution, whereas high-resolution products are restricted to narrow swath widths. Examples are presented which demonstrate pros and cons when balancing both parameters for the analysis of sea ice conditions. It is shown that X- and C-band images reveal similar signature variations (except over thin ice) and are hence well suited for combining images taken at different scales. Cases were observed for which strongly averaged intensity images are beneficial for discriminating different ice zones. For making full use of texture analysis, higher resolution products are preferable.

The only remote sensing technique capable of obtaining sea ice thickness on basin-scale are satellite altimeter missions, such as the 2010 launched CryoSat-2. It is equipped with a Ku-Band radar altimeter which measures the height of the ice surface above the water level. This method requires highly accurate range measurements. During the CryoSat Validation Experiment (CryoVEx) 2011 in the Lincoln Sea Cryosat-2 underpasses were accomplished with two aircraft which carried an airborne laser scanner, a radar altimeter and an electromagnetic induction device for direct sea ice thickness retrieval. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard distribution of laser scanner and radar altimeter measurements with the CryoSat-2 product within the multi-year sea ice region of the Lincoln Sea in spring, with respect to the penetration of the Ku-Band signal into the snow and the effect of surface roughness on the radar range retrieval.

Cryosat2 Level 1B SAR data can be processed using different empirical retrackers to determine the sea surface height and its variations in the Arctic Ocean. Two improved retrackers based on the combination of OCOG (Offset Centre of Gravity), Threshold methods and Leading Edge Retrieval is used to estimate the sea surface height in the Arctic Region. This sea surface height determination is to be compared with the Level2 sea surface height components available in the Cryosat2 data. Further a comparison is done with the marine gravity field for retracker performance evaluation.

Met samenvatting in het Engels onder de titel Acclimatization to heat and its effect on performance : a review.; Met literatuuropgave., De relatief lagere kerntemperatuur bij inspanning, verworven door acclimatisatie, heeft een positief effect op de aërobe prestatie. Voor kortdurende inspanning is het effect van acclimatisatie op de prestatie te verwaarlozen. Het voornaamste inzetgebied van de Nederlandse krijgsmacht heeft zich verplaatst naar warme gebieden, o.a. Irak en Afghanistan, in het laatste decennium waar de warmte problemen kan opleveren voor militairen die langdurige inspanningen moeten leveren.