Very-high resolution side-scan sonar mapping of biogenic reefs of the tube-worm Lanice conchilega

Reefs of the tube-building polychaete Lanice conchilega are known to represent hotspots of biodiversity within inter- and subtidal soft sediments of the North Sea. However, because of their patchy distribution, point sampling does not appropriately map their subtidal spatial distribution. This study evaluated the feasibility to detect L. conchilega reefs by very-high resolution side-scan sonar imagery. A subtidal very-high resolution (410 kHz) side-scan survey, combined with grab sampling, revealed high densities of L. conchilega (up to 1979 ind. m^? 2) to coincide with a higher reflectivity, patchy and grainy acoustic facies. From the side-scan sonar imagery, individual reefs were estimated to reach a maximum size of 15 m². To ground truth the acoustic facies, the distribution of intertidal L. conchilega reefs was mapped at low tide and side-scan sonar imagery was recorded during the following high tide. Intertidal L. conchilega reefs had a patch size of 0.8 m² up to 11.6 m², elevated 7.5 to 11.5 cm above the surrounding seafloor and covered approximately 10% of the selected area. The very-high (445 kHz) resolution side-scan sonar imagery revealed a similar acoustic facies as in the subtidal. Lower-resolution (132 kHz) side-scan sonar imagery was less efficient to detect physically less developed L. conchilega reefs. We conclude that (1) there are no major technical restrictions to map L. conchilega reefs using side-scan sonar, (2) the developmental stage of L. conchilega reefs impacts the detectability of the reefs, and (3) very-high resolution side-scan sonar imagery is considered a necessity when mapping small-scale structures, such as L. conchilega reefs.     

Change detection of coral reef habitat using Landsat-5 TM,Landsat 7 ETM+ and Landsat 8 OLI data in the Red Sea (Hurghada,Egypt)

Owing to continuing touristic developments in Hurghada, Egypt, several coral reef habitats have suffered major deterioration between 1987 and 2013, either by being bleached or totally lost. Such alterations in coral reef habitats have been well observed in their varying distributions using change detection analysis applied to a Landsat 5 image representing 1987, a Landsat 7 image representing 2000, and a Landsat 8 image representing 2013. Different processing techniques were carried out over the three images, including but not limited to rectification, masking, water column correction, classification, and change detection statistics. The supervised classifications performed over the three scenes show five significant marine-related classes, namely coral, sand subtidal, sand intertidal, macro-algae, and seagrass, in different degrees of abundance. The change detection statistics obtained from the classified scenes of 1987 and 2000 reveal a significant increase in the macro-algae and seagrass classes (93 and 47%, respectively). However, major decreases of 41, 40, and 37% are observed in the sand intertidal, coral, and sand subtidal classes, respectively. On the other hand, the change detection statistics obtained from the classified scenes of 2000 and 2013 revealed increases in sand subtidal and macro-algae classes by 14 and 19%, respectively, while major decreases of 49%, 46% and 74% are observed in the sand intertidal, coral, and seagrass classes, respectively.     

The semi-automated classification of acoustic imagery for characterizing coral reef ecosystems

Coral reef habitat maps describe the spatial distribution and abundance of tropical marine resources, making them essential for ecosystem-based approaches to planning and management. Typically, these habitat maps have been created from optical and acoustic remotely sensed imagery using manual, pixel- and object-based classification methods. However, past studies have shown that none of these classification methods alone are optimal for characterizing coral reef habitats for multiple management applications because the maps they produce (1) are not synoptic, (2) are time consuming to develop, (3) have low thematic resolutions (i.e. number of classes), or (4) have low overall thematic accuracies. To address these deficiencies, a novel, semi-automated object- and pixel-based technique was applied to multibeam echo sounder imagery to determine its utility for characterizing coral reef ecosystems. This study is not a direct comparison of these different methods but rather, a first attempt at applying a new classification technique to acoustic imagery. This technique used a combination of principal components analysis, edge-based segmentation, and Quick, Unbiased, and Efficient Statistical Trees (QUEST) to successfully partition the acoustic imagery into 35 distinct combinations of (1) major and (2) detailed geomorphological structure, (3) major and (4) detailed biological cover, and (5) live coral cover types. Thematic accuracies for these classes (corrected for proportional bias) were as follows: (1) 95.7%, (2) 88.7%, (3) 95.0%, (4) 74.0%, and (5) 88.3%, respectively. Approximately half of the habitat polygons were manually edited (hence the name ‘semi-automated’) due to a combination of mis-classifications by QUEST and noise in the acoustic data. While this method did not generate a map that was entirely reproducible, it does show promise for increasing the amount of automation with which thematically accurate benthic habitat maps can be generated from acoustic imagery.     

Mapping coral reefs at reef to reef-system scales, 10s–1000s km2, using object-based image analysis

Coral reef maps at various spatial scales and extents are needed for mapping, monitoring, modelling, and management of these environments. High spatial resolution satellite imagery, pixel <10 m, integrated with field survey data and processed with various mapping approaches, can provide these maps. These approaches have been accurately applied to single reefs (10–100 km²), covering one high spatial resolution scene from which a single thematic layer (e.g. benthic community) is mapped. This article demonstrates how a hierarchical mapping approach can be applied to coral reefs from individual reef to reef-system scales (10–1000 km²) using object-based image classification of high spatial resolution images guided by ecological and geomorphological principles. The approach is demonstrated for three individual reefs (10–35 km²) in Australia, Fiji, and Palau; and for three complex reef systems (300–600 km²) one in the Solomon Islands and two in Fiji. Archived high spatial resolution images were pre-processed and mosaics were created for the reef systems. Georeferenced benthic photo transect surveys were used to acquire cover information. Field and image data were integrated using an object-based image analysis approach that resulted in a hierarchically structured classification. Objects were assigned class labels based on the dominant benthic cover type, or location-relevant ecological and geomorphological principles, or a combination thereof. This generated a hierarchical sequence of reef maps with an increasing complexity in benthic thematic information that included: ‘reef’, ‘reef type’, ‘geomorphic zone’, and ‘benthic community’. The overall accuracy of the ‘geomorphic zone’ classification for each of the six study sites was 76–82% using 6–10 mapping categories. For ‘benthic community’ classification, the overall accuracy was 52–75% with individual reefs having 14–17 categories and reef systems 20–30 categories. We show that an object-based classification of high spatial resolution imagery, guided by field data and ecological and geomorphological principles, can produce consistent, accurate benthic maps at four hierarchical spatial scales for coral reefs of various sizes and complexities.     

Mapping the distribution of coral reefs and associated sublittoral habitats in Pacific Panama: a comparison of optical satellite sensors and classification methodologies

This research compared the ability of Landsat ETM+, Quickbird and three image classification methods for discriminating amongst coral reefs and associated habitats in Pacific Panama. Landsat ETM+ and Quickbird were able to discriminate coarse and intermediate habitat classes, but this was sensitive to classification method. Quickbird was significantly more accurate than Landsat (14% to 17%). Contextual editing was found to improve the user's accuracy of important habitats. The integration of object‐oriented classification with non‐spectral information in eCognition produced the most accurate results. This method allowed sufficiently accurate maps to be produced from Landsat, which was not possible using the maximum likelihood classifier. Object‐oriented classification was up to 24% more accurate than the maximum likelihood classifier for Landsat and up to 17% more accurate for Quickbird. The research indicates that classification methodology should be an important consideration in coral reef remote sensing. An object‐oriented approach to image classification shows potential for improving coral reef resource inventory.     

An evaluation of Landsat Thematic Mapper (TM) digital data for discriminating coral reef zonation: Heron Reef (GBR)

Coral reefs exhibit patterns of zonation. In this study we have evaluated the usefulness of Landsat-TM digital data as a tool for discrimination and mapping of reef zones. Classification, on bands 1, 2 and 3, and grouping of classes into reef zones was carried out with the aid of canonical variate analysis and minimum spanning trees. Thirteen reef zones can be identified and mapped, at a spatial scale relevant to their dimensions, with confidence. These zones can be further subdivided and mapped as spatially coherent subzones, in order to provide detailed information regarding the density of coral cover on the reef flat. In addition, the canonical variate analysis provides the basis for the aggregation of classes into sub-zones on interpreted primary productivity gradients, which is of relevance to coral reef management, monitoring and research.     

Accuracy of IKONOS for mapping benthic coral-reef habitats: a case study from the Puerto Morelos Reef National Park,Mexico

Reefs are being threatened by global warming, natural disasters, and the increased pressure of the global population. These habitats are in urgent need of mapping at high resolution so that these threats can be quantified. Remote sensing can potentially provide such quantitative data. In this article, we attempt to map benthic coral-reef habitats at the Puerto Morelos Reef National Park in Yucatan Peninsula (México) and to assess the accuracy of the technique in providing a baseline data for future monitoring of changes and evolution of the reef system. An IKONOS image was used in combination with checkpoint ground sampling and classified using a supervised maximum likelihood classifier (ENVI 4.5). We show that it is possible to map the reef with acceptable accuracy for the lagoon and discriminate the main habitat types, including vegetation, corals, and bare substrate. But, in areas close to the shore and in the front-reef zone, there were significant misclassifications as well as a failure to delineate spatial structures evident on the ground and in aerial imagery. These difficulties and failures occurred either in the areas deeper than 5–8 m where depth limits light transmission (particularly in the red channel) or when the spectral response of habitats were too close to be discriminated. This highlights the need to combine these data with other methods, such as acoustic mapping, in order to provide more accurate representations of the benthic habitats of entire reef systems.     

Change detection using remote sensing in a reef environment of the UAE during the extreme event of El Niño 2015–2016

ABSTRACT

Coral reefs of the United Arab Emirates (UAE) are living in the world’s hottest sea. Recently, corals harbouring Symbiodinium thermophilum, a thermotolerant microalgae, were found to be prevalent among UAE reefs and were reported to endure extreme sea-surface temperatures. Late 2015–early 2016 was marked with the strongest El Niño on record worldwide, which caused massive coral bleaching (loss of symbiotic microalgae from reef-building corals). In September 2015, the waters flanking UAE coasts were identified to be among the areas facing a thermal stress reaching its highest level liable to cause massive coral bleaching. However, the effect of this thermal stress on UAE corals remained largely unknown. Here, multi-temporal DubaiSat-2 satellite images were used to show that changes in the reef environment of Dalma Island, UAE, between 2014 and 2016, occurred in macroalgae-dominant habitats, whereas live corals remained unaltered. Furthermore, extending the study to a larger area helped in discovering a continuum of live and pristine corals, which was not reported or studied before. While sea-surface temperature anomalies of 1°C were reported to significantly damage coral reefs around the world, the live coral habitat was observed to exhibit no-change despite four consecutive months of +2°C to 3°C anomalies reported during the study period. These findings point to the tolerance of UAE live corals faced with extreme climate conditions.     

Time-lapse side-scan sonar imaging of bleached coral reefs: A case study from the Seychelles

High-resolution (675 kHz) side-scan sonar surveys were collected six and thirty months after a major coral bleaching event in the Seychelles. The surveyed areas contain four different reef morphologies, the distribution of which depends on water depth and distance from the shoreline. These four reef types also have different coral densities and colony morphologies (branching or mixed massive/branching). Textural analysis, based on first order statistics, unsupervised cluster analysis and Mann-Whitney U-tests, showed a correlation between recorded backscatter response and reef type that is attributed to the link between community composition and rugosity on a millimetre to tens of metre scale. Branching coral colonies are found to be relatively good scatterers of acoustic energy, and result in a broad intermediate to high intensity response. Massive coral colonies and reefs with a hard carbonate pavement are found to be principally reflectors of the acoustic energy, resulting in a narrow low intensity response. Comparison of the two surveys separated in time by two years, showed seabed texture to change most significantly over the reef areas that contained the highest coral abundances and mortality rates. In particular, the disintegration of dense branching colonies that suffered almost 100% mortality during the bleaching event resulted in a characteristic loss of intermediate to high backscatter intensity. The work demonstrates the contribution that side-scan sonar could make in the assessment of loss of rugosity following a bleaching episode, which has important implications to both the recovery of the reef itself and the abundance and distribution of associated reef organisms.     

The effects of ecologically determined spatial complexity on the classification accuracy of simulated coral reef images

Numerous studies have been conducted to compare the classification accuracy of coral reef maps produced from satellite and aerial imagery with different sensor characteristics such as spatial or spectral resolution, or under different environmental conditions. However, in additional to these physical environment and sensor design factors, the ecologically determined spatial complexity of the reef itself presents significant challenges for remote sensing objectives. While previous studies have considered the spatial resolution of the sensors, none have directly drawn the link from sensor spatial resolution to the scale and patterns in the heterogeneity of reef benthos. In this paper, we will study how the accuracy of a commonly used maximum likelihood classification (MLC) algorithm is affected by spatial elements typical of a Caribbean atoll system present in high spectral and spatial resolution imagery.The results indicate that the degree to which ecologically determined spatial factors influence accuracy is dependent on both the amount of coral cover on the reef and the spatial resolution of the images being classified, and may be a contributing factor to the differences in the accuracies obtained for mapping reefs in different geographical locations. Differences in accuracy are also obtained due to the methods of pixel selection for training the maximum likelihood classification algorithm. With respect to estimation of live coral cover, a method which randomly selects training samples from all samples in each class provides better estimates for lower resolution images while a method biased to select the pixels with the highest substrate purity gave better estimations for higher resolution images.     

Combining optical and acoustic data to enhance the detection of Caribbean forereef habitats

Maps of coral reef habitats are fundamental tools for reef management, and high map accuracy is desirable to support appropriate decisions, such as the stratification of marine reserves by habitat class. While satellite sensors have been used to map different reef communities, the accuracy of these maps tends to be low (overall accuracy < 50%) and optical airborne methods with high spectral resolution have, to date, been the most effective (if expensive) means of achieving higher accuracy. A potential means of compensating for the low spectral and radiometric resolution of optical satellite data, which is a major cause of its poor performance, is to combine satellite data with acoustic remote sensing. This study quantified the benefit of the synergy between optical satellite data (IKONOS) and acoustic (RoxAnn) sensors. The addition of acoustic data provided three new data axes for discriminating habitats: seabed roughness (E1), reef depth (z) and the depth correction of satellite spectral data to uniform depth. Seabed hardness (E2) was not an informative channel in our study. The use of z to conduct the water-column correction of the optical bands to uniform depth is a potential improvement over applying the depth-invariant index approach to optical data in the absence of ancillary information on depth. Habitat maps of the forereef of Glovers Atoll (Belize, Central America) were created using k-means unsupervised classification on eleven different treatment images constructed from various combinations of optical and acoustic data layers. The maximum benefit of data synergy was achieved by depth correcting the optical bands. The accuracy of maps based on the depth-invariant optical index was not enhanced when E1, E2 or z were added as separate layers but was enhanced when these three acoustic measures were added in concert. Data synergy can improve the accuracy of habitat maps and the availability of both data sets allows practitioners to take advantage of each techniques' additional strengths such as providing synoptic continuous imagery for education and general management planning (in the case of optical imagery) and maps of reef rugosity (in the case of acoustic data).     

Multi-scale,object-based image analysis for mapping geomorphic and ecological zones on coral reefs

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.     

Detecting end-member structural and biological elements of a coral reef using a single-beam acoustic ground discrimination system

A thematic map of benthic habitat was produced for a coral reef in the Republic of Palau, utilizing hydroacoustic data acquired with a BioSonics DT-X echosounder and a single-beam 418 kHz digital transducer. This article describes and assesses a supervised classification scheme that used a series of three discriminant analyses (DAs) to refine training samples into end-member structural and biological elements utilizing E1′ (leading edge of first echo), E1 (trailing edge of first echo), E2 (complete second echo), fractal dimension (first echo shape) and depth as predictor variables. Hydroacoustic training samples were assigned to one of six predefined groups based on the plurality of benthic elements (sand, sparse submerged aquatic vegetation (SAV)) rubble, pavement, rugose hardbottom, branching coral) that were visually estimated from spatially co-located ground-truthing videos. Records that classified incorrectly or failed to exceed a minimum probability of group membership were removed from the training data set until only ‘pure’ end-member records remained. This refinement of ‘mixed’ training samples circumvented the dilemma typically imposed by the benthic heterogeneity of coral reefs, that is either train the acoustic ground discrimination system (AGDS) on homogeneous benthos and leave the heterogeneous benthos unclassified, or attempt to capture the many ‘mixed’ classes and overwhelm the discriminatory capability of the AGDS. It was made possible by a conjunction of narrow beam width (6.4°) and shallow depth (1.2 to 17.5 m), which produced a sonar footprint small enough to resolve the microscale features used to define benthic groups. Survey data classified from the third-pass training DA were found to: (i) conform to visually apparent contours of satellite imagery, (ii) agree with the structural and biological delineations of a benthic habitat map (BHM) created from visual interpretation of IKONOS imagery and (iii) yield values of benthic cover that agreed closely with independent, contemporaneous video transects. The methodology was proven on a coral reef environment for which high-quality satellite imagery existed, as an example of the potential for single-beam systems to thematically map coral reefs in deep or turbid settings where optical methods are not applicable.     

The use of multi‐temporal Landsat images for the change detection of the coastal zone near Hurghada,Egypt

A Landsat 5 Thematic Mapper (TM) image of 1987 and a Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image of 2000 were used to examine changes in land use/land cover (LULC) around Hurghada, Egypt, and changes in the composition of coral reefs offshore. Prior to coral reef bottom‐type classification, the radiance values were transformed to depth‐invariant bottom indices to reduce the effect of the water column. Subsequently, a multi‐component change detection procedure was applied to these indices to define changes. Preliminary results showed significant changes in LULC during the period 1987–2000 as well as changes in coral reef composition. Direct impacts along the coastline were clearly shown, but it was more difficult to link offshore changes in coral reef composition to indirect impacts of the changing LULC. Further research is needed to explore the effects of the different image‐processing steps, and to discover possible links between indirect impacts of LULC changes and changes in the coral reef composition.     

Predictive mapping of reef fish species richness, diversity and biomass in Zanzibar using IKONOS imagery and machine-learning techniques

During the last three decades, the large spatial coverage of remote sensing data has been used in coral reef research to map dominant substrate types, geomorphologic zones, and bathymetry. During the same period, field studies have documented statistical relationships between variables quantifying aspects of the reef habitat and its fish community. Although the results of these studies are ambiguous, some habitat variables have frequently been found to correlate with one or more aspects of the fish community. Several of these habitat variables, including depth, the structural complexity of the substrate, and live coral cover, are possible to estimate with remote sensing data. In this study, we combine a set of statistical and machine-learning models with habitat variables derived from IKONOS data to produce spatially explicit predictions of the species richness, biomass, and diversity of the fish community around two reefs in Zanzibar. In the process, we assess the ability of IKONOS imagery to estimate live coral cover, structural complexity and habitat diversity, and we explore the importance of habitat variables, at a range of spatial scales, in the predictive models using a permutation-based technique. Our findings indicate that structural complexity at a fine spatial scale (∼ 5 to 10 m) is the most important habitat variable in predictive models of fish species richness and diversity, whereas other variables such as depth, habitat diversity, and structural complexity at coarser spatial scales contribute to predictions of biomass. In addition, our results demonstrate that complex model types such as tree-based ensemble techniques provide superior predictive performance compared to the more frequently used linear models, achieving a reduction of the cross-validated root-mean-squared prediction error of 3-11%. Although aerial photographs and airborne lidar instruments have recently been used to produce spatially explicit predictions of reef fish community variables, our study illustrates the possibility of doing so with satellite data. The ability to use satellite data may bring the cost of creating such maps within the reach of both spatial ecology researchers and the wide range of organizations involved in marine spatial planning.     

Damage to seagrass and seaweed beds in Matsushima Bay,Japan, caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011

Damage to seagrass and seaweed beds caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011 was investigated in Matsushima Bay, Miyagi Prefecture, Japan, by comparing satellite images taken before the tsunami in November 2009 and after the tsunami in May 2011. The results showed that the tsunami destroyed 220 ha of seagrass and seaweed beds, from 320 ha in 2009 to 100 ha just after the tsunami. Zostera marina beds on the sandy and muddy bottom were rather severely damaged compared with brown seaweed beds of Sargassum horneri on the rocky substrate. Substrates of the beds and directions of the tsunami seem to be responsible for the magnitude of the damage to the beds. Maps of the spatial distributions of the beds before and after the tsunami can provide information for the restoration of seagrass and seaweed beds as natural infrastructures of coastal fisheries resources.     

Characterization of coral bleaching environments and their variation along the Bahia state coast,Brazil

The relation between climate variability and coral bleaching in the Bahia reefs was investigated in an attempt to characterize the bleaching environments. The following 13-year time series were derived from the remote-sensing, analysis and reanalysis data: maximum summertime sea surface temperature (SST), maximum sea surface temperature (MaxSST) accumulated in 5 days (SSTAc5day), diffuse attenuation coefficient for downward irradiance at 490 nm (K ₄₉₀), rainfall and magnitude of surface wind fields, including the zonal (U) and meridional components. Principal component analysis, non-metric multidimensional scaling (MDS) and cluster and similarity analyses indicate the complex nature of the bleaching patterns and the influence of the strong 1997–1998 El Niño. A significant (global R-value?=?0.65; p < 0.01) compounding effect of the reef location and bleaching intensity on the differentiation of bleaching environments was detected. A combination of high SSTAc5day and low K ₄₉₀ may cause coral bleaching in the northernmost reefs. Evidence clearly points to a scenario where the influence of reef location, bleaching year and intensity may produce a compounded effect that determines the bleaching environments in Bahia.     

Airborne lidar sensing of massive stony coral colonies on patch reefs in the northern Florida reef tract

In this study we examined the ability of the NASA Experimental Advanced Airborne Research Lidar (EAARL) to discriminate cluster zones of massive stony coral colonies on northern Florida reef tract (NFRT) patch reefs based on their topographic complexity (rugosity). Spatially dense EAARL laser submarine topographic soundings acquired in August 2002 were used to create a 1-m resolution digital rugosity map for adjacent NFRT study areas characterized by patch reefs (Region A) and diverse substratums (Region B). In both regions, sites with lidar-sensed rugosities above 1.2 were imaged by an along-track underwater videography system that incorporated the acquisition of instantaneous GPS positions. Subsequent manual interpretation of videotape segments was performed to identify substratum types that caused elevated lidar-sensed rugosity. Our study determined that massive coral colony formation, modified by subsequent physical and biological processes that breakdown patch reef framework, was the primary source of topographic complexity sensed by the EAARL in the NFRT. Sites recognized by lidar scanning to be topographically complex preferentially occurred around the margins of patch reefs, constituted a minor fraction of the reef system, and usually reflected the presence of massive coral colonies in cluster zones, or their derivatives created by mortality, bioerosion, and physical breakdown.     

Quantification of two decades of shallow-water coral reef habitat decline in the Florida Keys National Marine Sanctuary using Landsat data (1984–2002)

The loss of coral reef habitats has been witnessed at a global scale including in the Florida Keys and the Caribbean. In addition to field surveys that can be spatially limited, remote sensing can provide a synoptic view of the changes occurring on coral reef habitats. Here, we utilize an 18-year time series of Landsat 5/TM and 7/ETM+ images to assess changes in eight coral reef sites in the Florida Keys National Marine Sanctuary, namely Carysfort Reef, Grecian Rocks, Molasses Reef, Conch Reef, Sombrero Reef, Looe Key Reef, Western Sambo and Sand Key Reef. Twenty-eight Landsat images (1984–2002) were used, with imagery gathered every 2 years during spring, and every 6 years during fall. The image dataset was georectified, calibrated to remote sensing reflectance and corrected for atmospheric and water-column effects. A Mahalanobis distance classification was trained for four habitat classes (‘coral’, ‘sand’, ‘bare hardbottom’ and ‘covered hardbottom’) using in situ ground-truthing data collected in 2003–2004 and using the spectral statistics from a 2002 image. The red band was considered useful only for benthic habitats in depths less than 6 m. Overall mean coral habitat loss for all sites classified by Landsat was 61% (3.4%/year), from a percentage habitat cover of 19% (1984) down to 7.6% (2002). The classification results for the eight different sites were critically reviewed. A detailed pixel by pixel examination of the spatial patterns across time suggests that the results range from ecologically plausible to unreliable due to spatial inconsistencies and/or improbable ecological successions. In situ monitoring data acquired by the Coral Reef Evaluation and Monitoring Project (CREMP) for the eight reef sites between 1996 and 2002 showed a loss in coral cover of 52% (8.7%/year), whereas the Landsat-derived coral habitat areas decreased by 37% (6.2%/year). A direct trend comparison between the entire CREMP percent coral cover data set (1996–2004) and the entire Landsat-derived coral habitat areas showed no significant difference between the two time series (ANCOVA; F-test, p = 0.303, n = 32), despite the different scales of measurements.     

Multidate MESMA for monitoring vegetation growth forms in southern California shrublands

Identifying habitats that should be protected from further disturbance or conversion and isolating high-risk areas is a focus of community habitat plans in southern California shrublands. Larger wildfires are occurring at shorter intervals in recent decades, contributing to degradation and conversion of shrubland vegetation. Multitemporal remote-sensing approaches can bridge the gap between vegetation mapping and field sampling in habitats where frequent quantification and mapping of vegetation growth forms over large extents is required. The objective of this study is to examine the reliability and stability of a multiple endmember spectral mixture analysis (MESMA) approach with moderate spatial resolution imagery for monitoring changes in growth form fractional cover in shrubland habitats. Estimates from visual interpretation of high spatial resolution image were used as reference data for validating MESMA-derived maps and as basis for providing complementary monitoring protocols that may be accurate and cost-effective across multiple scales. Growth form proportions modelled in burned and unburned management areas compare well with expected fractional cover in mature and regenerating shrublands. In the management areas recovering from fire, herbaceous cover fraction exceeded 0.40 for all three study dates, suggesting that large portions of those management areas may already be invaded. From 2008 to 2011 overall herbaceous cover fraction in shrubland area increased by 2%. Herbaceous cover fraction was modelled with an overall mean absolute error (MAE) of 0.08, a smaller percentage than the percentage of herbaceous cover change recorded in areas recovering from fire (increase in herbaceous cover fraction from 0.09 to 0.13). This MESMA approach would be effective for quantifying changes in fractional cover that exceed 0.10, providing a way to delineate and quantify herbaceous invasions and expansions following disturbance or succession.