Luc Bertels

Mapping of coral reefs using hyperspectral CASI data; a case study: Fordata, Tanimbar, Indonesia

Airborne remote sensing with a CASI‐550 sensor has been used to map the benthic coverage and the bottom topography of the Pulau Nukaha coral reef located in the Tanimbar Archipelago (Southeast Moluccas, Eastern Indonesia). The image classification method adopted was performed in three steps. Firstly, five geomorphological reef components were identified using a supervised spectral angle mapping algorithm in combination with data collected during the field survey, i.e. benthic cover type, percentage cover and depth. Secondly, benthic cover mapping was performed for each of the five geomorphological components separately using an unsupervised hierarchical clustering algorithm followed by class aggregation using both spectral and spatial information. Finally, 16 benthic cover classes could be labelled using the benthic cover data collected during the field survey. The overall classification accuracy, calculated on the biological diverse fore reef, was 73% with a kappa coefficient of 0.63. A reliable bathymetric model (up to a depth of 15 m) of the Pulau Nukaha reef was also obtained using a semi‐analytical radiative transfer model. When compared with independent in‐situ depth measurements, the result proved relatively accurate (mean residual error: −0.9 m) and was consistent with the seabed topography (Pearson correlation coefficient: 86%).

Atmospheric correction of APEX hyperspectral data

Abstract Atmospheric correction plays a crucial role among the processing steps applied to remotely sensed hyperspectral data. Atmospheric correction comprises a group of procedures needed to remove atmospheric effects from observed spectra, i.e. the transformation from at-sensor radiances to at-surface radiances or reflectances. In this paper we present the different steps in the atmospheric correction process for APEX hyperspectral data as applied by the Central Data Processing Center (CDPC) at the Flemish Institute for Technological Research (VITO, Mol, Belgium). The MODerate resolution atmospheric TRANsmission program (MODTRAN) is used to determine the source of radiation and for applying the actual atmospheric correction. As part of the overall correction process, supporting algorithms are provided in order to derive MODTRAN configuration parameters and to account for specific effects, e.g. correction for adjacency effects, haze and shadow correction, and topographic BRDF correction. The methods and theory underlying these corrections and an example of an application are presented.

Integration of Optical and Acoustic Remote Sensing Data over the Backshore–Foreshore–Nearshore Continuum: A Case Study in Ostend (Belgium)

ABSTRACT Bertels, L.; Houthuys, R.; Deronde, B.; Janssens, R.; Verfaillie, E., and Van Lancker, V., 2012. Integration of optical and acoustic remote sensing data over the backshore-foreshore-nearshore continuum: a case study in Ostend (Belgium). This research addresses the possibilities of the combined use of airborne hyperspectral imaging spectroscopy, airborne laser scanning, and seaborne sonar to study the sediment dynamics in the back-, fore-, and nearshore continuum. In May 2009, airborne light detection and ranging (LiDAR) and hyperspectral data were acquired at low tide of the beach in Ostend, Belgium. In June 2009, seaborne side-scan sonar and single- and multibeam depth and backscatter data were acquired in the nearshore part of the Ostend coastal area at high tide. Both LiDAR and single- and multibeam data were used to create a topographic reference of the back- to nearshore continuum, with an average vertical accuracy of 10 cm. This reference framework was used, in combination with historical data, to study the morphological evolution over the last few years. Hyperspectral data, optionally combined with LiDAR-derived intensity, slope, and elevation data, were used for sedimentological mapping of the back- and foreshore area. Both multibeam backscatter and side-scan sonar data were used to produce a sedimentary surface facies map of the nearshore area. Because no automatic classification of subtle seabed gradients is yet available, the data were manually screened to produce 12 sedimentary classes. Subsequently, the airborne- and seaborne-derived maps were combined to construct an integrated sedimentological and morphological map of the entire area. This was used to interpret and formulate statements about the sediment dynamics of the area.

Geometric Errors of Remote Sensing Images Over Forest and Their Propagation to Bidirectional Studies

This study focused on the need of accurate digital surface models rather than existing digital terrain models for the geometric correction of high spatial resolution images over forests. Based on both theoretical and experimental results, it was shown here that even for close to nadir observations (view angles less than 7°), the geometric error increased from within to beyond the pixel level when not taking into account the canopy height. This is particularly relevant for forest studies on bidirectional effects, data fusion and change detection techniques. The propagation of geometric errors for studies on bidirectional effects was quantified as a case study here, showing that geometric errors can easily mask such effects.

Large-scale mapping of the riverbanks, mud flats and salt marshes of the Scheldt basin, using airborne imaging spectroscopy and LiDAR

For maintaining the tidal waterways in the Scheldt basin, including the rivers Rupel and Durme and a large part of the Nete catchment, and for ecological monitoring of the mud flats, salt marshes and riverbank vegetation, the Flemish government needs detailed maps of these rivers and their bank structures. These maps indicate not only vegetation types, plant associations and sediment types but also hard structures, such as quays, locks, sluices and roads. Different remote sensing techniques were used to collect the data necessary to produce the required detailed maps. During the months of July and August 2007 an airborne flight campaign took place to collect hyperspectral and LiDAR data of the Scheldt basin and the Nete catchments. These rivers have a total length of about 240 km. The Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor acquired hyperspectral data in 32 spectral bands covering the visible/near-infrared (VIS/NIR) part of the electromagnetic spectrum with a ground resolution of 1 m. A multiple binary classification algorithm based on Fishers linear discriminant analysis (LDA) was used to map the salt marshes and riverbank vegetation. Ground truth information, that is vegetation and sediment types, together with their geographical locations collected around the time of the flight campaign, was used to train the classifier in the later classification step. Laser scanning was performed using the Riegl LMS-Q560. The LiDAR dataset obtained had a resolution of at least 1 point per m2 and was used to produce a digital elevation model (DEM) that contains all elements of the terrain. From this DEM a digital terrain model (DTM) was derived by applying appropriate filtering techniques. The elevation models were used primarily to derive information on the height, slope and aspect of the banks and dikes, but they also served as expert knowledge in the classification of the mud flats and bank vegetation. Overall, this work illustrates how airborne hyperspectral and LiDAR data can be used to derive highly detailed maps of the sediments, vegetation and hard structures along tidal rivers in large river basins. It also shows how large datasets can be handled in an expert system, in combination with different classification techniques, to produce the required result and accuracy.

Evaluation of PROBA-V Collection 1: Refined Radiometry, Geometry, and Cloud Screening

PROBA-V (PRoject for On-Board Autonomy–Vegetation) was launched in May-2013 as an operational continuation to the vegetation (VGT) instruments on-board the Système Pour l’Observation de la Terre (SPOT)-4 and -5 satellites. The first reprocessing campaign of the PROBA-V archive from Collection 0 (C0) to Collection 1 (C1) aims at harmonizing the time series, thanks to improved radiometric and geometric calibration and cloud detection. The evaluation of PROBA-V C1 focuses on (i) qualitative and quantitative assessment of the new cloud detection scheme; (ii) quantification of the effect of the reprocessing by comparing C1 to C0; and (iii) evaluation of the spatio-temporal stability of the combined SPOT/VGT and PROBA-V archive through comparison to METOP/advanced very high resolution radiometer (AVHRR). The PROBA-V C1 cloud detection algorithm yields an overall accuracy of 89.0%. Clouds are detected with very few omission errors, but there is an overdetection of clouds over bright surfaces. Stepwise updates to the visible and near infrared (VNIR) absolute calibration in C0 and the application of degradation models to the SWIR calibration in C1 result in sudden changes between C0 and C1 Blue, Red, and NIR TOC reflectance in the first year, and more gradual differences for short-wave infrared (SWIR). Other changes result in some bias between C0 and C1, although the root mean squared difference (RMSD) remains well below 1% for top-of-canopy (TOC) reflectance and below 0.02 for the normalized difference vegetation index (NDVI). Comparison to METOP/AVHRR shows that the recent reprocessing campaigns on SPOT/VGT and PROBA-V have resulted in a more stable combined time series.

Proba-V cloud detection Round Robin: Validation results and recommendations

This paper discusses results from 12 months of a Round Robin exercise aimed at the inter-comparison of different cloud detection algorithms for Proba-V. Clouds detection is a critical issue for satellite optical remote sensing, since potential errors in cloud masking directly translates into significant uncertainty in the retrieved downstream geophysical products. Cloud detection is particularly challenging for Proba-V due to the presence of a limited number of spectral bands and the lack of thermal infrared bands. The main objective of the project was the inter-comparison of several cloud detection algorithms for Proba-V over a wide range of surface types and environmental conditions. Proba-V Level 2a products have been distributed to six different algorithm providers representing companies and research institutes in several European countries. The considered cloud detection approaches are based on different strategies: Neural Network, Discriminant Analysis, Multi-spectral and Multi-textural Thresholding, Self-Organizing Feature Maps, Dynamic Thresholding, and physically-based retrieval of Cloud Optical Thickness. The results from all algorithms were analysed and compared against a reference dataset, consisting of a large number (more than fifty thousands) of visually classified pixels. The quality assessment was performed according to a uniform methodology and the results provide clear indication on the potential best-suited approach for next Proba-V cloud detection algorithm.

Imaging Spectroscopy And Integrated CoastalZone Management: A Promising Marriage

This paper provides an overview of the coastal and marine applications which make use of Imaging Spectroscopy (IS), recently under development in Vito. It should be considered as a concise overview rather than an in depth presentation of one application or development. The first two applications focus on sediment mapping; firstly, a classification of sediment habitat types of the Molenplaat, a tidal sand bank in the Westerschelde, is presented. By means of feature selection and a supervised binary classification approach the sediment is classified according to its grain size, moisture content, organic matter content and chlorophyll-a concentration. The second application uses airborne IS to classify the different sand types present along the Belgian coast, in combination with airborne laserscanning to derive accurate erosion maps. The combination of both data products results in a method which proves to be very suited to monitoring the sand transport processes along the Belgian coast. Afterwards two aquatic applications are presented; in the first, coral reef communities in Indonesia are classified. Extensive field work served to collect a spectral library which is used to classify the coral reef communities in as much detail and as accurately as possible. The second aquatic application addresses the difficult challenge of quantifying the amount of suspended sediment and chlorophyll-a in water and rivers; this is performed by inversion of a bio-optical model using a set of Specific Inherent Optical Properties (SIOP’s) measured in-situ. Many marine applications ask for some specific processing steps which are inherent to the aquatic environment. Therefore the last study in this overview focuses on the atmospheric correction above water bodies. Due to the high absorption and transmission of water bodies the reflected radiation level is low compared to land. To extract this small signal from a much greater base of other radiance a very accurate atmospheric correction algorithm is required. Therefore a specific atmospheric correction algorithm, WATCOR, has been developed to account for the marine atmospheric conditions as well as for the air-water interface. www.witpress.com, ISSN 1743-3541 (on-line)