Benthic cover map of Heron Reef derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis

Providing accurate maps of coral reefs where the spatial scale and labels of the mapped features correspond to map units appropriate for examining biological and geomorphic structures and processes is a major challenge for remote sensing. The objective of this work is to assess the accuracy and relevance of the process used to derive geomorphic zone and benthic community zone maps for three western Pacific coral reefs produced from multi-scale, object-based image analysis (OBIA) of high-spatial-resolution multi-spectral images, guided by field survey data. Three Quickbird-2 multi-spectral data sets from reefs in Australia, Palau and Fiji and georeferenced field photographs were used in a multi-scale segmentation and object-based image classification to map geomorphic zones and benthic community zones. A per-pixel approach was also tested for mapping benthic community zones. Validation of the maps and comparison to past approaches indicated the multi-scale OBIA process enabled field data, operator field experience and a conceptual hierarchical model of the coral reef environment to be linked to provide output maps at geomorphic zone and benthic community scales on coral reefs. The OBIA mapping accuracies were comparable with previously published work using other methods; however, the classes mapped were matched to a predetermined set of features on the reef.

Forest disturbance map for the Carpathian ecoregion, 1984-2012

Detailed knowledge of forest cover dynamics is crucial for many applications from resource management to ecosystem service assessments. Landsat data provides the necessary spatial, temporal and spectral detail to map and analyze forest cover and forest change processes. With the opening of the Landsat archive, new opportunities arise to monitor forest dynamics on regional to continental scales. In this study we analyzed changes in forest types, forest disturbances, and forest recovery for the Carpathian ecoregion in Eastern Europe. We generated a series of image composites at five year intervals between 1985 and 2010 and utilized a hybrid analysis strategy consisting of radiometric change classification, post-classification comparison and continuous index- and segment-based post-disturbance recovery assessment. For validation of the disturbance map we used a point-based accuracy assessment, and assessed the accuracy of our forest type maps using forest inventory data and statistically sampled ground truth data for 2010. Our Carpathian-wide disturbance map achieved an overall accuracy of 86% and the forest type maps up to 73% accuracy. While our results suggested a small net forest increase in the Carpathians, almost 20% of the forests experienced stand-replacing disturbances over the past 25 years. Forest recovery seemed to only partly counterbalance the widespread natural disturbances and clear-cutting activities. Disturbances were most widespread during the late 1980s and early 1990s, but some areas also exhibited extensive forest disturbances after 2000, especially in the Polish, Czech and Romanian Carpathians. Considerable shifts in forest composition occurred in the Carpathians, with disturbances increasingly affecting coniferous forests, and a relative decrease in coniferous and mixed forests. Both aspects are likely connected to an increased vulnerability of spruce plantations to pests and pathogens in the Carpathians. Overall, our results exemplify the highly dynamic nature of forest cover during times of socio-economic and institutional change, and highlight the value of the Landsat archive for monitoring these dynamics.

(Table 1) Ice flux, polynya area and sea-ice drift speed in the Kara Sea during winter (Jan-Apr) 1997-2001

The Shelf Seas of the Arctic are known for their large sea-ice production. This paper presents a comprehensive view of the Kara Sea sea-ice cover from high-resolution numerical modeling and space-borne microwave radiometry. As given by the latter the average polynya area in the Kara Sea takes a value of 21.2 × 10**3 km**2 ± 9.1 × 10**3 km**2 for winters (Jan.-Apr.) 1996/97 to 2000/01, being as high as 32.0 × 10**3 km**2 in 1999/2000 and below 12 × 10**3 km**2 in 1998/99. Day-to-day variations of the Kara Sea polynya area can be as high as 50 × 10**3 km**2. For the seasons 1996/97 to 2000/01 the modeled cumulative winter ice-volume flux out of the Kara Sea varied between 100 km**3/a and 350 km**3/a. Modeled high (low) ice export coincides with a high (low) average and cumulative polynya area, and with a low (high) sea-ice compactness in the Kara Sea from remote sensing data, and with a high (low) sea-ice drift speed across its northern boundary derived from independent model data for the winters 1996/97 to 2000/01.

Circumpolar Scaling Layer for downscaling of Scatterometer derived soil moisture with links to geotiff images and NetCDF files (2005-01 to 2011-12)

This dataset provides scaling information applicable to satellite derived coarse resolution surface soil moisture datasets following the approach by Wagner et al. (2008). It is based on ENVISAT ASAR data and can be utilized to apply the Metop ASCAT dataset (25 km) for local studies as well as to assess the representativeness of in-situ measurement sites and thus their potential for upscaling. The approach based on temporal stability (Wagner et al. 2008) consists of the assessment of the validity of the coarse resolution datasets at medium resolution (1 km, product is the so called 'scaling layer').

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Occurrence (presence-only) of living Lophelia pertusa reefs in the Irish continental margin

The present data set was used as a training set for a Habitat Suitability Model. It contains occurrence (presence-only) of living Lophelia pertusa reefs in the Irish continental margin, which were assembled from databases, cruise reports and publications. A total of 4423 records were inspected and quality assessed to ensure that they (1) represented confirmed living L. pertusa reefs (so excluding 2900 records of dead and isolated coral colony records); (2) were derived from sampling equipment that allows for accurate (<200 m) geo-referencing (so excluding 620 records derived mainly from trawling and dredging activities); and (3) were not duplicated. A total of 245 occurrences were retained for the analysis. Coral observations are highly clustered in regions targeted by research expeditions, which might lead to falsely inflated model evaluation measures (Veloz, 2009). Therefore, we coarsened the distribution data by deleting all but one record within grid cells of 0.02° resolution (Davies & Guinotte 2011). The remaining 53 points were subject to a spatial cross-validation process: a random presence point was chosen, grouped with its 12 closest neighbour presence points based on Euclidean distance and withheld from model training. This process was repeated for all records, resulting in 53 replicates of spatially non-overlapping sets of test (n=13) and training (n=40) data. The final 53 occurrence records were used for model training.

Benthic and substrate cover data derived from a time series of photo-transect surveys for the Eastern Banks, Moreton Bay Australia, 2004-2015

This paper describes seagrass species and percentage cover point-based field data sets derived from georeferenced photo transects. Annually or biannually over a ten year period (2004-2015) data sets were collected using 30-50 transects, 500-800 m in length distributed across a 142 km**2 shallow, clear water seagrass habitat, the Eastern Banks, Moreton Bay, Australia. Each of the eight data sets include seagrass property information derived from approximately 3000 georeferenced, downward looking photographs captured at 2-4 m intervals along the transects. Photographs were manually interpreted to estimate seagrass species composition and percentage cover (Coral Point Count excel; CPCe). Understanding seagrass biology, ecology and dynamics for scientific and management purposes requires point-based data on species composition and cover. This data set, and the methods used to derive it are a globally unique example for seagrass ecological applications. It provides the basis for multiple further studies at this site, regional to global comparative studies, and, for the design of similar monitoring programs elsewhere.

High-resolution digital elevation model (DEM) of a thermokarst depression in Siberian ice-rich permafrost deposits

This data set provides a high-resolution digital elevation model (DEM) of a thermokarst depression (~7 km²) on ice-complex deposits in the Arctic Lena Delta, Siberia. The DEM based on a geodetic field survey and was used for quantitative land surface analyses and detailed description of the thermokarst depression morphology. Detailed morphometrical analyses, volume calculations, and solar radiation modeling were performed and statistically analyzed by Ulrich et al. (2010) to investigate the asymmetrical thermokarst depression development and directed lake migration previously proposed by Morgenstern et al. (2008). Furthermore, the high-resolution DEM in combination with satellite data allowed detailed analyses of spatial and temporal landscape changes due to thermokarst development (Günther, 2009).

Airborne hyperspectral image data of Heron Reef, Australia

This airborne hyperspectral (19 bands) image data of Heron Reef, Great Barrier Reef, Australia is derived from Compact Airborne Spectrographic Imager (CASI) data acquired on 1st and 3rd of July 2002, latitude -23.45, longitude 151.92. Processing and correction to at-surface data was completed by Karen Joyce (Joyce, 2004). Raw imagery consisted several images corresponding to the number of flight paths taken to cover the entire Heron Reef. Spatial resolution is one meter. Radiometric corrections converted the at-sensor digital number values to at surface spectral radiance values using sensor specific calibration coefficients and CSIRO's c-WomBat-c atmospheric correction software. Geometric corrections were done using field collected coordinates of features identified in the image. Projection used was Universal Transverse Mercator Zone 56 South and Datum used was WGS 84. Image data is in TIFF format.