A Review of Wetland Remote Sensing <s> Introduction <s> Boreal and subarctic peatlands comprise a carbon pool of 455 Pg that has accumulated during the postglacial period at an average net rate of 0.096 Pg/yr (1 Pg = 1015g). Using Clymo's (1984) model, the current rate is estimated at 0.076 Pg/yr. Longterm drainage of these peatlands is estimated to be causing the oxidation to CO2 of a little more than 0.0085 Pg/yr, with conbustion of fuel peat adding °0.026 Pg/yr. Emissions of CH4 are estimated to release ° 0.046 Pg of carbon annually. Uncertainties beset estimates of both stocks and fluxes, particularly with regard to Soviet peatlands. The influence of water table alterations upon fluxes of both CO2 and CH4 is in great need of investigation over a wide range of peatland environments, especially in regions where permafrost melting, thermokarst erosion, and the development of thaw lakes are likely results of climatic warming. The role of fire in the carbon cycle of peatlands also deserves increased attention. Finally, satellite—monitoring of the abundance of open water in the peatlands of the West Siberian Plain and the Hudson/James Bay Lowland is suggested as a likely method of detecting early effects of climatic warming upon boreal and subarctic peatlands. <s> BIB001 </s> A Review of Wetland Remote Sensing <s> Introduction <s> Different approaches to the classification of remotely sensed data of mangroves are reviewed, and five different methodologies identified. Landsat TM, SPOT XS and CASI data of mangroves from the Turks and Caicos Islands, were classified using each method. All classifications of SPOT XS data failed to discriminate satisfactorily between mangrove and non-mangrove vegetation. Classification accuracy of CASI data was higher than Landsat TM for all methods, and more mangrove classes could be discriminated. Merging Landsat TM and SPOT XP data improved visual interpretation of images, but did not enhance discrimination of different mangrove categories. The most accurate combination of sensor and image processing method for mapping the mangroves of the eastern Caribbean islands is identified. <s> BIB002 </s> A Review of Wetland Remote Sensing <s> Introduction <s> Abstract Remote sensing is an important tool for mapping and monitoring vegetation. Advances in sensor technology continually improve the information content of imagery for airborne, as well as space-borne, systems. This paper investigates whether vegetation associations can be differentiated using hyperspectral reflectance in the visible to shortwave infrared spectral range, and how well species can be separated based on their spectra. For this purpose, the field reflectance spectra of 27 saltmarsh vegetation types of the Dutch Waddenzee wetland were analysed in three steps. Prior to analysis, the spectra were smoothed with an innovative wavelet approach. In the first stage of the analysis, the reflectance spectra of the vegetation types were tested for differences between type classes. It was found that the reflectance spectra of saltmarsh vegetation types are statistically significantly different for various spectral regions. Secondly, it was tested whether this statistical difference could be enhanced by using continuum removal as a normalisation technique. For vegetation spectra, continuum removal improves the statistical difference between vegetation types in the visible spectrum, but weakens the statistical difference of the spectra in the near-infrared and shortwave infrared part of the spectrum. Thirdly, after statistical differences were found, it was determined how distant in spectral space the vegetation type classes were from each other, using the Bhattacharyya (BH) and the Jeffries–Matusita (JM) distance measures. We selected six wavelengths for this, based on the statistical analysis of the first step. The potential of correct classification of the saltmarsh vegetation types using hyperspectral remote sensing is predicted by these distance measures. It is concluded that the reflectance of vegetation types is statistically different. With high quality radiometric calibration of hyperspectral imagery, it is anticipated that vegetation species may be identified from imagery using spectral libraries that were measured in the field during the time of image acquisition. <s> BIB003 </s> A Review of Wetland Remote Sensing <s> Introduction <s> This paper considers the implications of a range of global-mean sea-level rise and socio-economic scenarios on: (1) changes in flooding by storm surges; and (2) potential losses of coastal wetlands through the 21st century. These scenarios are derived from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). Four different storylines are analysed: the A1FI, A2, B 1 and B2 'worlds'. The climate scenarios are derived from the HadCM3 climate model driven by the SRES emission scenarios. The SRES scenarios for global-mean sea-level rise range from 22 cm (B I world) to 34 cm (A1FI world) by the 2080s, relative to 1990. All other climate factors, including storm characteristics, are assumed to remain constant in the long term. Population and GDP scenarios are downscaled from the SRES regional analyses supplemented with other relevant scenarios for each impact analysis. The flood model predicts that about 10 million people/year experienced coastal flooding due to surges in 1990. The incidence of flooding will change without sea-level rise, but these changes are strongly controlled by assumptions on protection. Assuming that defence standards improve with growth in GDP/capita (lagged by 30 years), flood incidence increases in all four cases to the 2020s due to the growing exposed population. Then to the 2080s, the incidence of flooding declined significantly to 5 million people/ year in the B2 world, 2 million people/year in the B1 world and 1 million people/year in the A1FI world due to improving defence standards. In contrast, flood incidence continues to increase in the A2 world to the 2050s, and in the 2080s it is still 18–30 million people/year. This reflects the greater exposure and more limited adaptive capacity of the A2 world, compared to the other SRES storylines. Sea-level rise increases the flood impacts in all cases although significant impacts are not apparent until the 2080s when the additional people flooded are 7–10 million, 29–50 million, 2–3 million and 16–27 million people/year under the A1FI, A2, B1 and B2 worlds, respectively. Hence, the A2 world also experiences the highest increase in the incidence of flooding. This is true under all the realistic scenario combinations that were considered demonstrating that socio-economic factors can greatly influence vulnerability to sea-level rise. The trends of the results also suggest that flood impacts due to sea-level rise could become much more severe through the 22nd century in all cases, especially in the A1FI world. Note that impacts using a climate model with a higher climate sensitivity would produce larger impacts than HadCM3. Coastal wetlands will be lost due to sea-level rise in all world futures with 5–20% losses by the 2080s in the A1FI world. However, these losses are relatively small compared to the potential for direct and indirect human destruction. Thus, the difference in environmental attitudes between the A1/A2 worlds and the B1/B2 worlds would seem to have more important implications for the future of coastal wetlands, than the magnitude of the sea-level rise scenarios during the 21st Century. These results should be seen as broad analysis of the sensitivity of the coastal system to the HadCM3 SRES global-mean sea-level rise scenarios. While these impact estimates are only for one climate model, for both impact factors they stress the importance of socio-economic conditions and other non-climate factors as a fundamental control on the magnitude of impacts both with and without sea-level rise. The A2 world experiences the largest impacts during the 21st century, while the B1 world has the smallest impacts, with the differences more reflecting socio-economic factors than climate change. This suggests that the role of development pathways in influencing the impacts of climate change needs to be given more attention. <s> BIB004 </s> A Review of Wetland Remote Sensing <s> Introduction <s> The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces. <s> BIB005 </s> A Review of Wetland Remote Sensing <s> Introduction <s> Abstract An effective bibliometric analysis based on the Science Citation Index (SCI) published by the Institute of Scientific Information (ISI) was carried out to identify wetland research between 1991 and 2008. The objective was to conduct a quantitative and qualitative analysis for global trends of wetland-related research. The characteristics related to publications were analyzed. The results showed the significant wetland research issues in the SCI database. From 1991 to 2008, the annual number of journal articles published and the number of articles cited to wetland research increased more than sixfold and ninefold respectively. The USA produced the most single-country articles and international collaborative articles, followed by Canada and UK. The results also showed the significant wetland research issues in SCI database. The most frequently used words were: “water” (or “water quality”), which ranked 3rd, 7th, and 3rd according to the word in article title, author keyword, and keyword plus analysis, respectively. Constructed wetland biodiversity became more active in wetland research. The keywords “constructed wetland” and “constructed wetlands” ranked 58th and 12th in 1991–1996, while they ranked 5th and 4th in 2003–2008; the author keyword “biodiversity” ranked 45th in 1991–1996, while it ranked 23rd in 1997–2002, and 14th in 2003–2008; and keyword plus “diversity” ranked 93rd in 1991–1996, while it ranked 20th in 1997–2002, and 17th in 2003–2008. Moreover, it was proved that article title, author keyword, and keyword plus analysis methods were effective approaches for mapping wetland research. Popular wetland research issues and wetland research changes were also identified by statistical analysis. <s> BIB006 </s> A Review of Wetland Remote Sensing <s> Introduction <s> In Oregon’s Willamette Valley, remaining wetlands are at high risk to loss and degradation from agricultural activity and urbanization. With an increased need for fine temporal-scale monitoring of sensitive wetlands, we used annual Landsat MSS and TM/ETM+ images from 1972 to 2012 to manually interpret loss, gain, and type conversion of wetland area in the floodplain of the Willamette River. By creating Tasseled Cap Brightness, Greenness, and Wetness indices for MSS data that visually match TM/ETM+ Tasseled Cap images, we were able to construct a complete and consistent, annual time series and utilize the entire Landsat archive. With an extended time series we were also able to compare annual trends of net change in wetland area before and after the no-net-loss policy established under Section 404 of the Clean Water Act in 1990 using a Theil-Sen Slope estimate analysis. Vegetated wetlands experienced a 314 ha net loss of wetland area and non-vegetated wetlands experienced a 393 ha net gain, indicating higher functioning wetlands were replaced in area by non-vegetated wetland habitats such as agricultural and quarry ponds. The majority of both gain and loss in the study area was attributed to gains and losses of agricultural land. After 1990 policy implementations, the rate of wetland area lost slowed for some wetland categories and reversed into trends of gain in wetland area for others, perhaps representative of the success of increased regulations. Overall accuracy of land use classification through manual interpretation was at 80 %. This accuracy increased to 91.1 % when land use classes were aggregated to either wetland or upland categories, indicating that our methodology was more accurate at distinguishing between general upland and wetland than finer categorical classes. <s> BIB007
Wetlands can be described as regions with low water levels, often near ground surface, which are covered by active plants during the growing season and water saturation period BIB005 . Wetlands are some of the most important and valuable ecosystems on Earth and are called "kidneys of the Earth". There are two basic types of wetlands: natural and constructed BIB006 . Wetlands can improve water quality, protect shorelines, recharge groundwater, ease flood and drought severity, and provide unique habitats for many plants and animals. Scientists and government staff have paid increasing attention to wetlands to maintain the biodiversity of the aquatic system BIB006 BIB007 . A wetland is a generalized concept including coastal wetlands, peatland, mangrove forests, estuarine wetlands, marshes, and other types of wetland. The coastal wetland functions as an important nutrient cycling capacity source to maintain water quality BIB003 . Peatlands play a key role in carbon cycle because they sequester carbon dioxide (CO 2 ), the major greenhouse gas, from the atmosphere as peat; however, they also emis large quantities of CO 2 and the second most important greenhouse gas, methane (CH 4 ) BIB001 . Mangrove forests are important habitats for many fish and crustacean species and play important roles in coastal protection and water quality BIB002 . Despite the importance of wetlands, roughly 50% of wetlands have been lost since the 1900s BIB004 . Wetland-related studies are therefore of great importance to protect wetlands and mitigate climate change.