A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> IKONOS 1-m panchromatic and 4-m multispectral images were used to map mangroves in a study site located at Punta Galeta on the Caribbean coast of Panama. We hypothesized that spectral separability among mangrove species would be enhanced by taking the object as the basic spatial unit as opposed to the pixel. Three different classification methods were investigated: maximum likelihood classification (MLC) at the pixel level, nearest neighbour (NN) classification at the object level, and a hybrid classification that integrates the pixel and object-based methods (MLCNN). Specifically for object segmentation, which is the key step in object-based classification, we developed a new method to choose the optimal scale parameter with the aid of Bhattacharya Distance (BD), a well-known index of class separability in traditional pixel-based classification. A comparison of BD values at the pixel level and a series of larger scales not only supported our initial hypothesis, but also helped us to determine an optimal ... <s> BIB001 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> This study is an attempt to produce an assessment of the impact of shrimp aquaculture in the Mekong Delta (Viet Nam) on mangrove ecosystems. For this exercise we selected two sub-areas (Ca Mau and Tra Vinh provinces) encompassing a variety of land uses and ecological conditions. Twenty stations in Tra Vinh and 15 stations in Ca Mau have been surveyed several times from September 2000 to March 2002. Field investigations included mangrove soils studies, measurements of pH and salinity of the water, analysis of mangrove flora, and density and structure of the vegetation. Four Syst@me Probatoire de l'Observation de la Terre (SPOT) scenes were used for the discrimination of mangrove types and for the delineation of landscape units. For the first time, five ecologically distinct landscape classes were identified and delineated. Their possible links with the farming and yields of high valued species of shrimps, especially the giant tiger shrimp (Penaeus monodon) destined for export markets, need further studies.... <s> BIB002 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Abstract Leaf Area Index (LAI) values from 124 mangrove plots were acquired within a degraded mangrove forest of the Agua Brava Lagoon System of Nayarit (Mexico) using a hand held LAI-2000 Plant Canopy Analyzer. For each plot, two values of LAI were calculated to represent approximate half radii (180°) ground coverage of 8 m and 15 m. The location of each plot was recorded at sub-meter accuracy using an Ashtech SCA-12 GPS. Using a geometrically corrected IKONOS satellite image, the mean values for both the Normalized Difference Vegetation Index (NDVI) and the simple ratio (SR) vegetation indices were also calculated for each plot. Regression analyses of the in situ LAI with both vegetation indices revealed significant positive relationships (LAI versus NDVI at 8 m ( R 2 = 0.71); LAI versus NDVI at 15 m ( R 2 = 0.70); LAI versus SR at 8 m ( R 2 = 0.73); LAI versus SR at 15 m ( R 2 = 0.72)) at the 8 m and 15 m plot sizes. Standard errors, derived from the testing of the regression models with a random sample, revealed little difference between the models. Moreover, F -tests of the residual variances also indicated no significant difference between the SR and NDVI models at both plot sizes. Consequently, the results indicate that each model could be used to successfully predict LAI. It is thus suggested that high spatial resolution IKONOS data can be employed as a valuable tool for monitoring LAI in less than ideal mangrove forests (i.e. disturbed stands). <s> BIB003 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Mangrove stands of differing species composition are hard to distinguish in conventional, coarse resolution satellite images. The new generation of meter-level satellite imagery provides a unique opportunity to achieve this goal. In this study, an IKONOS Geo bundle image and a QuickBird Standard bundle image were acquired for a study area located at Punta Galeta on the Caribbean coast of Panama. The two images cover the same area and were acquired under equivalent conditions. Three comparison tests were designed and implemented, each with separate objectives. First, a comparison was conducted band by band by examining their spectral statistics and species by species by inspecting their textural roughness. The IKONOS image had a higher variance and entropy value in all the compared bands, whereas the QuickBird image displayed a finer textural roughness in the forest canopy. Second, maximum likelihood classification (MLC) was executed with two different band selections. When examining only multispectral bands, the IKONOS image had better spectral discrimination than QuickBird while the inclusion of panchromatic bands had no effect on the classification accuracy of either the IKONOS or QuickBird image. Third, first- and second-order texture features were extracted from the panchromatic images at different window sizes and with different grey level (GL) quantization levels and were compared through MLC classification. Results indicate that the consideration of image texture enhances classifications based on the IKONOS panchromatic band more than it does classifications based on comparable QuickBird imagery. An object-based classification was also utilized to compare underlying texture in both panchromatic and multispectral bands. On the whole, both IKONOS and QuickBird images produced promising results in classifying mangrove species. <s> BIB004 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> This paper presents an automated method for mangrove stand recognition (delineation and labeling) and species mapping based on fuzzy per‐pixel classification techniques of a QuickBird satellite image. The four dominant mangrove species in Gazi Bay (Kenya) are mapped with an overall accuracy of 72 percent, where the two socio‐economically most important species are mapped with user accuracies above 85 percent. Mangrove stand maps were compared to visual delineations done by an expert interpreter and the quality was based on the quantity of overlap one has with the other. An overall correspondence up to 86 percent was achieved. <s> BIB005 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Abstract Object-based methods for image analysis have the advantage of incorporating spatial context and mutual relationships between objects. Few studies have explored the application of object-based approaches to mangrove mapping. This research applied an object-based method to SPOT XS data to map the land cover in the mangrove ecosystem of Low Casamance, Senegal. In parallel, the object-based method was tested to analyse the changes in the mangrove area between 1986 and 2006. The object-based method for mangrove mapping applied a multi-resolution segmentation and implemented class-specific rules that incorporate spectral properties and relationships between image objects at different hierarchical levels. The object-based approach for change analysis conducted the segmentation on the multi-date composite of the 1986 and 2006 images and applied a nearest neighbour classifier. The object-based method clearly discriminated the different land cover classes within the mangrove ecosystem. The overall accuracy of the land cover classification was 86%, the overall kappa value was 0.83 and the user’s accuracy of the ‘mangroves’ class was higher than 97%. The estimated area of mangroves was 76,550 hectares in 2006. This result is an important update reference for mangrove studies in Senegal and the proposed method may represent a valid instrument for similar exercises in other regions. The image-to-image, object-based approach to change analysis clearly captured the fragmented and scattered pattern of change that prevails in the study area. The user’s accuracy of the increase and decrease classes of transition produced results better than 85%. The overall accuracy, however, is lower due to the method’s difficulties in detecting the small areas of change. To have conclusive evidence for the suitability of this method for change analysis of mangrove forest, this object-based approach should be tested in mangrove ecosystems where changes have different spatial patterns and modifications are more evident. Between 1986 and 2006, a small increase in the mangrove area was observed in Low Casamance. This was probably due to improved rainfall conditions after the droughts of the 1970s and 1980s. The pattern of change detected with the object-based approach corresponds to natural transitions and suggests that anthropogenic influence was limited. <s> BIB006 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> This letter aims to exploit morphological textures in discriminating three mangrove species and surrounding environment with multispectral IKONOS imagery in a study area on the Caribbean coast of Panama. Morphological texture features are utilized to distinguish red (Rhizophora mangle), white (Laguncularia racemosa), and black (Avicennia germinans) mangroves and rainforest regions. Meanwhile, two fusion methods are presented, i.e., vector stacking and support vector machine (SVM) output fusion, for integrating the hybrid spectral-textural features. For comparison purposes, the object-based analysis and the gray-level co-occurrence matrix (GLCM) textures are adopted. Results revealed that the morphological feature opening by reconstruction (OBR) followed by closing by reconstruction (CBR) and its dual operator CBR followed by OBR gave very promising accuracies for both mangrove discrimination (89.1% and 91.1%, respectively) and forest mapping (91.4% and 93.7%, respectively), compared with the object-based analysis (80.5% for mangrove discrimination and 82.9% for forest mapping) and the GLCM method (81.9% and 87.2%, respectively). With respect to the spectral-textural information fusion algorithms, experiments showed that the SVM output fusion could obtain an additional 2.0% accuracy improvement than the vector-stacking approach. <s> BIB007 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Mangroves provide valuable ecosystem goods and services such as carbon sequestration, habitat for terrestrial and marine fauna, and coastal hazard mitigation. The use of satellite remote sensing to map mangroves has become widespread as it can provide accurate, efficient, and repeatable assessments. Traditional remote sensing approaches have failed to accurately map fringe mangroves and true mangrove species due to relatively coarse spatial resolution and/or spectral confusion with landward vegetation. This study demonstrates the use of the new Worldview-2 sensor, Object-based image analysis (OBIA), and support vector machine (SVM) classification to overcome both of these limitations. An exploratory spectral separability showed that individual mangrove species could not be spectrally separated, but a distinction between true and associate mangrove species could be made. An OBIA classification was used that combined a decision-tree classification with the machine-learning SVM classification. Results showed an overall accuracy greater than 94% (kappa = 0.863) for classifying true mangroves species and other dense coastal vegetation at the object level. There remain serious challenges to accurately mapping fringe mangroves using remote sensing data due to spectral similarity of mangrove and associate species, lack of clear zonation between species, and mixed pixel effects, especially when vegetation is sparse or degraded. <s> BIB008 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Whereas anthropogenic impacts on the mangroves are often directly visible, some in- direct impacts like biodiversity change are witnessed only over a period of time and therefore re- quire medium to long-term monitoring. This study focuses on testing the predictions made 10 yr ago concerning the evolution of a mangrove forest in Galle-Unawatuna, Sri Lanka. The very high reso- lution (VHR) ground inventory revealed that the adult mangrove species composition is dominated by Rhizophora apiculata, Excoecaria agallocha, Bruguiera gymnorrhiza and B. sexangula, with a total density of 216 to 267 stems 0.1 ha �1 and a basal area of 1.19 to 1.44 m 2 0.1 ha �1 . However, both young and juvenile vegetation in most sectors were dominated solely by B. gymnorrhiza (128 to 869 stems and 356 to 1482 propagules 0.1 ha �1 ). The recent decadal changes between 1994 and 2004 observed through IKONOS imagery and ground truthing confirmed many of the predictions and showed dynamic shifts in young/adult vegetation of B. gymnorrhiza. Although dominance of R. apiculata and E. agallocha has been seen to alternate over decades (1956 to 2004), the emerging growth of B. gymnorrhiza might cause yet another transition of this mangrove area into a Bruguiera-dominated forest in the near future, resulting in the conclusion that the 'moving mosaic' pattern of mangrove species distribution at Galle-Unawatuna still persists. We maintain that this mangrove forest is probably one of the most dynamic in the world in terms of species turnover. To our knowledge, the present study represents one of the few long-term field-based monitoring re- search projects on mangroves using VHR remote sensing and VHR fieldwork at decadal intervals, and is probably the only study testing forest development predictions made in the past. <s> BIB009 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Mangrove forests are declining across the globe, mainly because of human intervention, and therefore require an evaluation of their past and present status (e.g. areal extent, species-level distribution, etc.) to implement better conservation and management strategies. In this paper, mangrove cover dynamics at Gaoqiao (P. R. China) were assessed through time using 1967, 2000 and 2009 satellite imagery (sensors Corona KH-4B, Landsat ETM+, GeoEye-1 respectively). Firstly, multi-temporal analysis of satellite data was undertaken, and secondly biotic and abiotic differences were analysed between the different mangrove stands, assessed through a supervised classification of a high-resolution satellite image. A major decline in mangrove cover (−36%) was observed between 1967 and 2009 due to rice cultivation and aquaculture practices. Moreover, dike construction has prevented mangroves from expanding landward. Although a small increase of mangrove area was observed between 2000 and 2009 (+24%), the ratio mangrove / aquaculture kept decreasing due to increased aquaculture at the expense of rice cultivation in the vicinity. From the land-use/cover map based on ground-truth data (5 × 5 m plot-based tree measurements) (August–September, 2009) as well as spectral reflectance values (obtained from pansharpened GeoEye-1), both Bruguiera gymnorrhiza and small Aegiceras corniculatum are distinguishable at 73–100% accuracy, whereas tall A. corniculatum was correctly classified at only 53% due to its mixed vegetation stands with B. gymnorrhiza (overall classification accuracy: 85%). In the case of sediments, sand proportion was significantly different between the three mangrove classes. Overall, the advantage of very high resolution satellite images like GeoEye-1 (0.5 m) for mangrove spatial heterogeneity assessment and/or species-level discrimination was well demonstrated, along with the complexity to provide a precise classification for non-dominant species (e.g. Kandelia obovata ) at Gaoqiao. Despite limitations such as geometric distortion and single panchromatic band, the 42 yr old Corona declassified images are invaluable for land-use/cover change detections when compared to recent satellite data sets. <s> BIB010 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Abstract Large areas of mangrove forests were devastated in South Viet Nam during the second Indochina war. After its end in 1975, extensive reforestation with monocultures took place. Can Gio, one of the biggest replanted sites with about 20,000 ha of mangroves mainly Rhizophora apiculata , was declared a biosphere reserve by the UNESCO in 2000. Although this status now enables progressive forest dynamics, there are still drawbacks resulting from the unnatural character of the plantations. For example, the homogeneous size and age structure as well as the regular arrangement of the planted trees make larger forest stands more vulnerable to synchronized collapsing which can be triggered by stronger winds and storms. A transformation into a more natural forest characterized by a heterogeneous age and size structure and a mixed species composition is of urgent need to avoid a synchronized dieback. In this study we test the capability of natural canopy disturbances (e.g. lightning strikes) to facilitate this transformation. Canopy gaps created by lightning strikes were detected and quantified by remote sensing techniques. SPOT satellite images from the years 2003, 2005 and 2007 provided information about the spatial distribution, size, shape, and formation frequency of the gaps. Lightning strike gaps were identified based on their shape and size. They form small openings (mean: 0.025 ha) and their yearly probability of occurrence was determined to be approximately 0.012 per hectare. Selected gaps were surveyed in the field in 2008 to complement the remote sensing data and to provide information upon forest structure and regeneration. Simulation experiments were carried out with the individual-based KiWi mangrove model for quantifying the influence of different lightning regimes on the vertical and horizontal structure of the R. apiculata plantation. In addition, we conducted simulations with a natural and thus randomly generated forest to compare the structure of the two different cultivation types (i.e. plantation and natural forest). The simulation shows that even small disturbances can already partly buffer the risk of cohort senescence of monospecific even-aged plantations. However, after the decline of the plantation, the disturbance regime does not play an important role for further stand development. After the break-up of the initial strongly regular structure of the simulated plantation, a vertical pattern, i.e. height distribution of the trees, similar to the one of the natural forest, emerged quickly. However, the convergence for the horizontal structure i.e. the distance of trees to their nearest neighbor, took twice as long as for the vertical structure. Our results highlight the importance of small disturbances such as lightning strikes to mitigate vulnerability against synchronous windfall in homogenous forest structures. Hence, creating small openings artificially may be an appropriate management measure in areas where the frequency of natural small-scale disturbances is low. <s> BIB011 </s> A Review of Wetland Remote Sensing <s> Mangrove Forest Study <s> Based on Geoeye-1 high spatial resolution images and field canopy hyperspectral reflectance of five mangrove communities located at Beibu Gulf,this paper verified the capability of Geoeye-1 imagery for mangrove canopy species identification by utilizing spectral information.The research investigated that:(1) in the spectrum range between 350 and 1 100 nm,the mangrove canopy reflectance exhibited optimum separability in six wavebands(435,469,523,677,751 and 761 nm);(2) three mangrove species could be effectively identified through the pixel-based spectrum operation,while the Bruguiera acquired the highest producer accuracy up to 93.03%;(3) species end member of Bruguiera extracted directly from the combined imagery conducted on hyperspectral hypothesis performed higher precision than the field training samples behaved.The spectrum significance of the high spatial resolution image was approved,and reference and basis were also illustrated for the further mangrove species distinguishing from the object-oriented perspective. <s> BIB012
Mangroves are salt-tolerant forest species that live in intertidal zones, which provide important ecosystem characteristics and services BIB005 . However, mangrove forest areas have notably declined in the past 50 years due to anthropic destruction  . Some authors argue that mangrove forest will be lost soon, without appropriate and effective actions BIB005  . Mangrove research has been a research frontier in recent years. Twenty of the 73 research papers that study wetlands using high spatial resolution images focus on mangrove forest. Three main categories were discussed in these BIB001 BIB008  BIB006 BIB007 ; (2) mangrove evolution or degradation BIB010 BIB009 BIB002 BIB011 BIB003 ; and (3) mapping of mangrove species BIB005  BIB007 BIB004 BIB012  : Classification or mapping of mangroves. Conchedda et al. BIB006 used object-based classification and SPOT data to map the land cover in the mangrove ecosystem in Senegal and reported clear changes between 1986 and 2006 with an overall classification accuracy of 86%; a 94% overall classification accuracy was obtained when object-based analysis, support vector machine classification and WorldView-2 images were used BIB008 . Gao  used SPOT images to map mangroves and discussed the reasons for the different classification accuracies. Mangrove evolution or degradation. The decline of the mangrove forest has been verified globally. The decline is due to human activities and its rate is different in different regions. Tong et al. BIB002 used SPOT images to assess how shrimp aquaculture impacts mangrove ecosystem. They classified mangrove ecosystem into five ecologically distinct parts and analyzed the possible links to shrimp aquaculture for some regions of Vietnam. They concluded that, from 1965 to 2002, approximately 30% of mangrove ecosystem has been lost and more than 30% of the present mangroves are replanted monospecific species. During the second Indochina war, many mangrove forests have been destroyed; at present, these regions were reforested with monocultures. Landscape heterogeneity is essential for ecosystem survival and lightning is the main natural disturbance of mangroves. To estimate the capability of lightning to increase the heterogeneity, Vogt et al. BIB011 used SPOT images to detect and quantify the disturbance and heterogeneity of mangrove forests. They proposed the importance of small disturbances in maintaining the biodiversity of mangrove forests. The forest degradation can be reflected by the green leaf, which can be calculated from remote sensing data. Kovacs and Flores BIB003 determined the relationship between leaf area index (LAI) from field surveys and the vegetation index derived from satellite imagery (IKONOS) in disturbed mangrove forests; they established a close relationship, which indicates that IKONOS can be used as a robust tool in monitoring mangrove forest degradation. Mapping of mangrove species. Mangrove forests often comprise different species depending on the distance of water edge, which fulfill different ecological functions and have a different ability to resist risk. It is urgent to identify mangrove forest structure to better understand basic mangrove information and guide conservation and restoration activities. Because of spatial resolution limitations, conventional images have been rarely used for mangrove species identification. To obtain an accurate mangrove species map, many scholars explored the use of high spatial resolution images. Neukermans et al. BIB005 employed Quickbird images to identify four dominant mangrove species and obtained satisfactory results with an overall accuracy of 72%. Wang et al.  used two IKONOS images from different seasons (February and May 2004) to identify mangrove species. Wang et al. BIB004 compared the mangrove species maps from IKONOS and Quickbird images and found that both sensors have the capacity to classify mangrove species.