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Land surface albedo is one of the most important parameters accountable for the planetary radiative energy budget. It is known that albedo varies in both space and time as a result of various natural processes and human interventions. Especially in forest ecosystems these variations are much more intense due to inherent canopy structural differences and anticipated seasonal changes. In such environments, estimation of spatially distributed surface albedo poses challenges in terms of capturing the spatial variability using a remotely sensed sensor with a finite field of view. This study investigated the stand level surface albedo variability of a patchwork forest in the central part of The Netherlands. The data used for the study included airborne and satellite imageries and tower-based solar radiation measurements acquired through a dedicated field campaign. The imageries were preprocessed and atmospherically corrected to obtain top of the canopy (TOC) reflectance. The TOC reflectance bands in the visible and near-infrared domain were integrated to estimate spatially distributed surface albedo while the tower-based radiation measurements in the solar-reflective region were used to obtain the temporal variation of surface albedo over a needleleaf forest canopy. The diurnal variation of surface albedo is consistent with the previous findings for needleleaf forest canopies. The spatial mean surface albedo values estimated from remote sensing data for needleleaf (pure Douglas fir), broadleaf (pure Beech) and mixed forest classes are 0.09, 0.13 and 0.11, respectively. Both visual characteristics and descriptive statistics indicate that with increased pixel size, the spatial variability of albedo progressively decreases. The semivariogram analysis was more insightful to perceive the nature and causes of albedo spatial variability in different forest classes in relation to sensor spatial resolution. [ABSTRACT FROM AUTHOR]

Remote sensing of water quality in inland waters requires reliable retrieval algorithms, accurate atmospheric correction and consistent method for uncertainty estimation. In this paper, the GSM semi-analytical inversion model is modified for inland waters to derive inherent optical properties (IOPs) and their spectral dependencies from air and space borne data. The modified model was validated using two data sets from the Veluwe and the Vecht Dutch lakes. For the Veluwe lakes, the model was able to derive a linear relationship between measured concentrations and estimated IOPs with R2 values above 0.7 for chlorophyll-ɑ (Chl-ɑ) and up to 0.9 for suspended particulate matters (SPM). In the Vecht lakes, the modified model derived accurate values of IOPs. The R2 values were 0.89 for Chl-ɑ and up to 0.95 for SPM. The RMSE values were 0.93 mg m-3 and 0.56 g m-3 for Chl-ɑ and SPM respectively. Finally, the IOPs of the Veluwe lakes are derived from multi-spectral, ocean color and hyperspectral airborne data. Inversion-uncertainties of the derived IOPs were also estimated using a standard nonlinear regression technique. The study shows that inversion-uncertainties of remote sensing derived IOPs are proportional to water turbidity. [ABSTRACT FROM AUTHOR]

EAGLE2006 - an intensive field campaign for the advances in land surface hydrometeorological processes - was carried out in the Netherlands from 8th to 18th June 2006, involving 16 institutions with in total 67 people from 16 different countries. In addition to the acquisition of multiangle and multi-sensor satellite data, several airborne instruments - an optical imaging sensor, an imaging microwave radiometer, and a flux airplane - were deployed and extensive ground measurements were conducted over one grassland site at Cabauw and two forest sites at Loobos and Speulderbos in the central part of the Netherlands. The generated data set is both unique and urgently needed for the development and validation of models and inversion algorithms for quantitative land surface parameter estimation and land surface hydrometeorological process studies. EAGLE2006 was led by the Department of Water Resources of the International Institute for Geo-Information Science and Earth Observation (ITC) and originated from the combination of a number of initiatives supported by different funding agencies. The objectives of the EAGLE2006 campaign were closely related to the objectives of other European Space Agency (ESA) campaign activities (SPARC2004, SEN2FLEX2005 and especially AGRISAR2006). However, one important objective of the EAGLE2006 campaign is to build up a data base for the investigation and validation of the retrieval of bio-geophysical parameters, obtained at different radar frequencies (X-, C- and L-Band) and at hyperspectral optical and thermal bands acquired simultaneously over contrasting vegetated fields (forest and grassland). As such, all activities were related to algorithm development for future satellite missions such as the Sentinels and for validation of retrievals of land surface parameters with optical and thermal and microwave sensors onboard current and future satellite missions. This contribution describes the campaign objectives and provides an overview of the airborne and field campaign dataset. This dataset is available for scientific investigations and can be accessed on the ESA Principal Investigator Portal http://eopi.esa.int. [ABSTRACT FROM AUTHOR]