A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> Abstract Nine SPOT XS scenes recorded during the dry season (January, February) and after cyclonic storms were analyzed to evaluate both the extent and consequences of floods in Bangladesh, in the deltaic complex of the Ganges. Digital and visual analysis showed the following results: 1) Near the capital, Dahka, within a SPOT scene (3600 km 2 ), the extent of water varies from 324 km 2 during the dry season to 1303 km 2 after a destructive flood. This means that flood-prone areas in this overpopulated deltaic region are at least four times larger than the hydrographic network observed during the dry season. 2) The Sunderbans are the world's largest mangroves (about 6000 km 2 in a single block); two-thirds of this forest (4050 km 2 ) are in Bangladesh, and the rest is in India. These ecosystems seem to resist cyclones. No sign of any kind of mangrove alteration is seen on SPOT images recorded a few weeks after disastrous cyclonic storms (20 August 1987 and 6 September 1988). This is an important fact since the protective role of these coastal swamp forests is tremendously important. 3) The islands located in the very exposed area at the mouth of the Meghna are densely populated (more than 1000 inhabitants/km 2 ). Hathya island has been carefully surveyed. According to the investigations carried out on SPOT images (25 February 1987 and 26 October 1988), the island seems to be at present satisfactorily protected against cyclones and tidal surges, behind newly planted mangroves (Sonneratia apetala Buch.-Ham.) and sheltered by a complex network of embankments which are visible on the images. It was concluded that the spectral separability of classes (water, natural plant communities, land use units) and the geometric accuracy of SPOT are suitable for coastal monitoring in this part of the Bangladesh. <s> BIB001 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <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> BIB002 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <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> BIB003 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> Aquatic vegetation in the relatively pristine coastal wetlands of eastern Georgian Bay provides critical habitat for a diverse fish community. Declining water levels in Lake Huron over the past decade, however, have altered the wetland plant assemblages in favour of terrestrial (emergent and meadow) taxa and have thus reduced or eliminated this important ecosystem service. In this study, we compared IKONOS satellite images for two regions of eastern Georgian Bay (acquired in 2002 and 2008) to determine significant changes in cover of four distinct wetland vegetation groups [meadow (M), emergent (E), high-density floating (HD) and low-density floating (LD)] over the 6 years. While LD decreased significantly (mean 2995.4 m 2 ), M and HD increased significantly (mean +2020.9 m 2 and +2312.6 m 2 , respectively) between 2002 and 2008. Small patches of LD had been replaced by larger patches of HD. These results show that sustained low water levels have led to an increasingly homogeneous habitat and an overall net loss of fish habitat. A comparison of the fish communities sampled between 2003 and 2005 with those sampled in 2009 revealed that there was a significant decline in species richness. The remaining fish communities were also more homogeneous. We suggest that the observed changes in the wetland plant community due to prolonged low water levels may have resulted in significant changes in the fish communities of coastal wetlands in eastern Georgian Bay. <s> BIB004 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <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> BIB005 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> The Straits of Malacca has rich biodiversity, but it experienced a dramatic decline due to the anthropogenic activities for economical development and natural disasters. The objective of this study was to generate the coastal and marine habitat map for the Straits of Malacca using the SPOT and Landsat data acquired at low tide in 2010 ~ 2012. Images were first processed with atmospheric and geometric correction. The hierarchical unsupervised classification and contextual editing were then used to produce the final habitat map. The WorldView2 and GeoEye data were also used for evaluating purposes in some studied area. Our classification scheme included sandy beach, mangrove forest, mud /sand flat, seagrass /algae, coral reefs, water and others. The produced habitat map provides the most up to date habitat information in the Straits of Malacca and will aid for the regional coastal ecosystems assessment as well as for future comparative study. <s> BIB006 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> Land reclamation directly changes the local coastal morphology, causing potential ecological consequences. To quantify how land reclamation influences the shoreline change, we employed shape entropy, in addition to traditional parameters, including shoreline length, land area change rate, and fractal dimension, extracted from SPOT satellite images from a number of representative years throughout two decades (1987–2012) to describe shoreline changes in Yangtze River Estuary, China. The vegetation growth boundary, representing the nearshore vegetation distribution as an ecological indicator, was also extracted and compared with the shoreline result. This comparison indicated that both vegetation growth boundary and shoreline evolve in a more complex and yet more orderly pattern partly because of land reclamation. Vegetation growth boundary changes more dramatically than shoreline, due to the combined effects of agricultural development and artificial beach nourishment, as well as the alternation of tidal creeks. These results have important implications for coastal wetland conservation and utilization in regions with intensive land reclamation such as the Yangtze River Estuary. <s> BIB007 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> Remote sensing has been an important mean of resource monitor, especially monitoring wetlands where researchers can hardly get to. This paper applied SPOT-5 image to classify the East Dongting Lake area into five cover types using the decision tree classification method. The five cover types were water, mudflats, bare ground, low-coverage marsh land and high-coverage marsh land. According to results of band analysis, this paper extracted the water by adding fourth band and first band, resulting that the water body boundaries extracted by band calculated using this method are highly consistent with water body in the image after SPOT-5 panchromatic and Multi-spectral bands fusion. Then a multilayer buffer was created based on waterbody through referring to the elevation value distribution histogram. we defined the levels range and divided the elevation into 6 levels. Finally, relationship between various cover types and elevation and relationship between various cover types and water buffers were analyzed, drawing them with water distance relationship. <s> BIB008 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> Abstract Peatlands are known to have accumulated and stored carbon over thousands of years and play a vital role in global greenhouse gas balances. However, there are still inadequate high quality estimates of peatland carbon stock at regional level especially in the James Bay Lowlands in Far North Ontario, Canada. The aim of this study is to estimate regional peatland carbon stock in a delineated watershed region in northern Ontario. SPOT 5 satellite data was used to delineate and classify peatland types using maximum likelihood standard algorithm. The peatland map derived from remote sensing was integrated with peat depth, carbon content and bulk density data in geographic information system (GIS) in order to estimate regional peatland carbon stock. The total regional peatland carbon stock was estimated using the following equation: area of peatland (ha) × depth of peat (m) × mean bulk density of peat (g m − 3 ) × carbon content of dry mass (%) × conversion factor (10,000 m 2 ha − 1 ). Peatlands in the study area covered a geographic area of about 130,429 ha and stored about 128 ± 0.05 Tg of carbon. Peat carbon per unit area varied among peatland types with a mean ± SD of 100 ± 17 kg C m − 2 . This high quality account of carbon stock estimates clearly demonstrates the high carbon stored by northern peatlands which makes them major carbon storehouses. <s> BIB009 </s> A Review of Wetland Remote Sensing <s> Obtain Fine-Accuracy Maps <s> Abstract Accurate wetland maps are a fundamental requirement for land use management and for wetland restoration planning. Several wetland map products are available today; most of them based on remote sensing images, but their different data sources and mapping methods lead to substantially different estimations of wetland location and extent. We used two very high-resolution (2 m) WorldView-2 satellite images and one (30 m) Landsat 8 Operational Land Imager (OLI) image to assess wetland coverage in two coastal areas of Tampa Bay (Florida): Fort De Soto State Park and Weedon Island Preserve. An initial unsupervised classification derived from WorldView-2 was more accurate at identifying wetlands based on ground truth data collected in the field than the classification derived from Landsat 8 OLI (82% vs. 46% accuracy). The WorldView-2 data was then used to define the parameters of a simple and efficient decision tree with four nodes for a more exacting classification. The criteria for the decision tree were derived by extracting radiance spectra at 1500 separate pixels from the WorldView-2 data within field-validated regions. Results for both study areas showed high accuracy in both wetland (82% at Fort De Soto State Park, and 94% at Weedon Island Preserve) and non-wetland vegetation classes (90% and 83%, respectively). Historical, published land-use maps overestimate wetland surface cover by factors of 2–10 in the study areas. The proposed methods improve speed and efficiency of wetland map production, allow semi-annual monitoring through repeat satellite passes, and improve the accuracy and precision with which wetlands are identified. <s> BIB010
High spatial resolution images are of advantage for the identification of wetland boundary and species. Many scholars used high spatial resolution images in wetland studies to improve the research accuracy. Midwood and Chow-Fraser BIB004 used two stages of IKONOS images to compare the changes of four wetland plant communities. Leempoel et al. BIB005 used GeoEye-1 and other sensors to assess the mangrove forest decline in Gaoqiao of China. SPOT, IKONOS, and WorldView-2 data were used to generate coastal and marine habitat map BIB006 , evaluate both the extent and consequences of floods BIB001 , describe shoreline changes BIB007 , classify land cover BIB008  BIB009 BIB010 , and map mangroves BIB002 BIB003 .