Habitat map of Danajon Bank, Philippines, derived from a high-spatial-resolution multi-spectral satellite image and georeferenced point intercept transect and spot-check survey field data, using an object-based image classification method

A mosaic of two WorldView-2 high resolution multispectral images (Acquisition dates: October 2010 and April 2012), in conjunction with field survey data, was used to create a habitat map of the Danajon Bank, Philippines (10°15'0'' N, 124°08'0'' E) using an object-based approach. To create the habitat map, we conducted benthic cover (seafloor) field surveys using two methods. Firstly, we undertook georeferenced point intercept transects (English et al., 1997). For ten sites we recorded habitat cover types at 1 m intervals on 10 m long transects (n= 2,070 points). Second, we conducted geo-referenced spot check surveys, by placing a viewing bucket in the water to estimate the percent cover benthic cover types (n = 2,357 points). Survey locations were chosen to cover a diverse and representative subset of habitats found in the Danajon Bank. The combination of methods was a compromise between the higher accuracy of point intercept transects and the larger sample area achievable through spot check surveys (Roelfsema and Phinn, 2008, doi:10.1117/12.804806). Object-based image analysis, using the field data as calibration data, was used to classify the image mosaic at each of the reef, geomorphic and benthic community levels. The benthic community level segregated the image into a total of 17 pure and mixed benthic classes.

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.

Time-series of seagrass and land cover maps from 1972 to 2010, in South East Queensland, Australia, with links to GeoTIFFs

Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.

Bathymetric map of Heron Reef, Australia, derived from airborne hyperspectral data at 1 m resolution

A simple method for efficient inversion of arbitrary radiative transfer models for image analysis is presented. The method operates by representing the shape of the function that maps model parameters to spectral reflectance by an adaptive look-up tree (ALUT) that evenly distributes the discretization error of tabulated reflectances in spectral space. A post-processing step organizes the data into a binary space partitioning tree that facilitates an efficient inversion search algorithm. In an example shallow water remote sensing application, the method performs faster than an implementation of previously published methodology and has the same accuracy in bathymetric retrievals. The method has no user configuration parameters requiring expert knowledge and minimizes the number of forward model runs required, making it highly suitable for routine operational implementation of image analysis methods. For the research community, straightforward and robust inversion allows research to focus on improving the radiative transfer models themselves without the added complication of devising an inversion strategy.

Probability sampling protocol of classification maps from spaceborne/airborne image

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: (i) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. (ii) The inclusion probabilities must be: (a) knowable for nonsampled units and (b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors' knowledge, the first) probability sampling protocol for quality assessment and comparison of thematic maps generated from spaceborne/airborne Very High Resolution (VHR) images, where: (I) an original Categorical Variable Pair Similarity Index (CVPSI, proposed in two different formulations) is estimated as a fuzzy degree of match between a reference and a test semantic vocabulary, which may not coincide, and (II) both symbolic pixel-based thematic quality indicators (TQIs) and sub-symbolic object-based spatial quality indicators (SQIs) are estimated with a degree of uncertainty in measurement in compliance with the well-known Quality Assurance Framework for Earth Observation (QA4EO) guidelines. Like a decision-tree, any protocol (guidelines for best practice) comprises a set of rules, equivalent to structural knowledge, and an order of presentation of the rule set, known as procedural knowledge. The combination of these two levels of knowledge makes an original protocol worth more than the sum of its parts. The several degrees of novelty of the proposed probability sampling protocol are highlighted in this paper, at the levels of understanding of both structural and procedural knowledge, in comparison with related multi-disciplinary works selected from the existing literature. In the experimental session the proposed protocol is tested for accuracy validation of preliminary classification maps automatically generated by the Satellite Image Automatic MapperT (SIAMT) software product from two WorldView-2 images and one QuickBird-2 image provided by DigitalGlobe for testing purposes. In these experiments, collected TQIs and SQIs are statistically valid, statistically significant, consistent across maps and in agreement with theoretical expectations, visual (qualitative) evidence and quantitative quality indexes of operativeness (OQIs) claimed for SIAMT by related papers. As a subsidiary conclusion, the statistically consistent and statistically significant accuracy validation of the SIAMT pre-classification maps proposed in this contribution, together with OQIs claimed for SIAMT by related works, make the operational (automatic, accurate, near real-time, robust, scalable) SIAMT software product eligible for opening up new inter-disciplinary research and market opportunities in accordance with the visionary goal of the Global Earth Observation System of Systems (GEOSS) initiative and the QA4EO international guidelines.

Mass estimates and morphometric meassurements of Discoaster species and Sphenolithus from Ceara Rise ODP Site 927

Mass estimates for Late Miocene and Pliocene (8.6-3.25 Ma) Discoaster species and Sphenolithus are determined using samples of the equatorial Atlantic (Ceara Rise: ODP Site 927). Based on morphometric measurements, 3D computer models were created for 11 Discoaster species and their volumes calculated. From these, shape factors (ks) were derived to allow calculation of mass for different-sized discoasters and Sphenolithus abies. The mass estimates were then used to calculate the contribution of nannofossils to the total nannofossil carbonate. The discoaster contribution ranges from 10% to 40%, with a decreasing trend through the investigated interval. However, our estimates of total nannofossil carbonate from size-corrected abundance data are consistently 30-50% lower than estimates from grain-size measurement; this suggests that data based on mass estimates need to be interpreted with caution.

Early Maastrichtian stable isotopes: changing deep water sources in the North Atlantic?

We propose that the observed short-term stable isotope fluctuations reflect changes in high- and low-latitude intermediate to deep water sources, based on a high-resolution stable isotope record of planktic and benthic foraminifera from the Early Maastrichtian (~71.3 to ~ 69.6 Ma) of Blake Nose (DSDP Site 390A, North Atlantic). Sources of these waters may have been the low-latitude eastern Tethys and high-latitude North Atlantic. Changes in intermediate to deep water sources were probably steered by eccentricity-controlled insolation fluctuations. Lower insolation favored the formation of high-latitude deep waters due to positive feedback mechanisms resulting in high-latitude cooling. This led to a displacement of low-latitude deep waters at Blake Nose. Higher insolation reduced intermediate to deep-water formation in high latitudes, yielding a more northern flow of low-latitude deep waters.

Microsedimentological characterization as indicators of sedimentary processes and climate changes during Lateglacial at Laguna Potrok Aike, Santa Cruz, Argentina

Palaeoclimatic and paleoenvironmental high latitude records in the Southern Hemisphere are scarce compared to the northern counterpart. However, understanding global evolution of environmental systems during sudden climate changes is inseparable from an equivalent knowledge of both Hemispheres. In this context, a high-resolution study of lacustrine sediments from Laguna Potrok Aike, Santa Cruz province, Patagonia, Argentina, was conducted for the Lateglacial period using concurrent X-Ray Fluorescence (XRF) and Scanning electron microscope analyses. Peaks of Ca/Si and Mn, and occurrences of the green alga Phacotus lenticularis have been interpreted as variations in ventilation of the water column from 13.6 to 11.1 ka cal. BP. During this interval, mild climate conditions during the Younger Dryas are characterized by relatively weak westerlies favouring the formation of a stratified water body as indicated by preserved manganese and Ca/Si peaks and high Total Organic Carbon (TOC) values. In this environment, water in the epilimnion can reach sufficiently high temperature to allow P. lenticularis to grow. Colder conditions are marked by peaks in Ca without P. lenticularis and occur during the Antarctic Cold Reversal (ACR). In this Lateglacial interval, micropumices were also detected in large amount. Image analysis of thin sections allowed the counting and size measurement of detrital particles and micropumices separately. Micropumices significantly influence the iron and titanium content, hence preventing to use them as proxies of detrital input in this interval.

Ocean acidification not likely to affect the survival and fitness of two yemperate benthic foraminiferal species: results from culture experiments

Specimens of Bolivina argentea and Bulimina marginata, two widely distributed temperate benthic foraminiferal species, were cultured at constant temperature and controlled pCO2 (ambient, 1000 ppmv, and 2000 ppmv) for six weeks to assess the effect of elevated atmospheric CO2 concentrations on survival and fitness using Adenosine Triphosphate (ATP) analyses and on shell microfabric using high-resolution SEM and image analysis. To characterize the carbonate chemistry of the incubation seawater, total alkalinity and dissolved inorganic carbon were measured approximately every two weeks. Survival and fitness were not directly affected by elevated pCO2 and the concomitant decrease in seawater pH and calcite saturation states (Omega c), even when seawater was undersaturated with respect to calcite. These results differ from some previous observations that ocean acidification can cause a variety of effects on benthic foraminifera, including test dissolution, decreased growth, and mottling (loss of symbiont color in symbiont-bearing species), suggesting that the benthic foraminiferal response to ocean acidification may be species specific. If so, this implies that ocean acidification may lead to ecological winners and losers even within the same taxonomic group.

Time series of ZOOSCAN images and results of zooplankton samples at Villefranche from 1966 to 2003

ZooScan with ZooProcess and Plankton Identifier (PkID) software is an integrated analysis system for acquisition and classification of digital zooplankton images from preserved zooplankton samples. Zooplankton samples are digitized by the ZooScan and processed by ZooProcess and PkID in order to detect, enumerate, measure and classify the digitized objects. Here we present a semi-automatic approach that entails automated classification of images followed by manual validation, which allows rapid and accurate classification of zooplankton and abiotic objects. We demonstrate this approach with a biweekly zooplankton time series from the Bay of Villefranche-sur-mer, France. The classification approach proposed here provides a practical compromise between a fully automatic method with varying degrees of bias and a manual but accurate classification of zooplankton. We also evaluate the appropriate number of images to include in digital learning sets and compare the accuracy of six classification algorithms. We evaluate the accuracy of the ZooScan for automated measurements of body size and present relationships between machine measures of size and C and N content of selected zooplankton taxa. We demonstrate that the ZooScan system can produce useful measures of zooplankton abundance, biomass and size spectra, for a variety of ecological studies.