A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Certain events provide a unique opportunity to test the monitoring capability of AVHRR imagery. On 26 August 1992, Hurricane Andrew passed through Louisiana, impacting a large area of forested wetlands. One response to the widespread defoliation resulting from the hurricane impact was an abnormal bloom of new leaves and new growth in the underlying vegetation between September and October. To capture this atypical phenology, a time sequence of AVHRR images was transformed into a normalized difference vegetation index, NDVI, as an indicator of vegetation changes in the forest impacted by the passage of a hurricane. Using geographic information system functions, three sites in the impacted forest were vectorized as polygons, and the inclusive pixels were extracted for subsequent graphical and univariate statistical analysis. Temporal curves of mean NDVIs for the three sites for before, during, and after the hurricane passage, and aggregate curves of the impacted forest to an undisturbed forest, were compared. These comparisons corraborated the atypical phenology of the impacted forested wetland and directly related the cause to the hurricane passage. <s> BIB001 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> A temporal suite of NOAA Advanced Very High Resolution Radiometer (AVHRR) images, transformed into a vegetation biomass indicator, was combined with a single-date classification of Landsat Thematic Mapper (TM) to map the association between forest type and hurricane effects. Hurricane effects to the forested wetland included an abrupt decrease and subsequent increase in biomass. The decrease was associated with hurricane impact and the increase with an abnormal bloom in vegetation in the impacted areas. Impact severity was estimated by differencing the biomass maps before and immediately (3 days) after the hurricane. Recovery magnitude was estimated by differencing the biomass maps from immediately (3 days) after and shortly (1.5 months) after the hurricane. Regions of dominantly hardwoods suffering high to moderate impacts and of dominantly cypress-tupelos suffering low impacts identified in this study corroborated findings of earlier studies. Conversely, areas not reported in previous studies as affected were identified, and these areas showed a reverse relationship, i.e., highly impacted cypresstupelo and low or moderately impacted hardwoods. Additionally, generated proportions of hardwood, cypress-tupelo, and open (mixed) forests per each 1-km pixel (impact and recovery maps) suggest that regions containing higher percentages of cypress-tupelos were more likely to have sustained higher impacts. Visual examination of the impact map revealed a spatial covariation between increased impact magnitudes and river corridors dominated by open forest. This spatial association was corroborated by examining changes in the percentage of open forest per 1-km impact pixel; the percentage of open forest peaked at moderate to high impacts. The distribution of recovery supported the impact spatial distribution; however, the magnitudes of the two indicators of hurricane effects were not always spatially dependent. Converse to univariate statistics describing a11 forested area within the basin, higher recoveries tended to be <s> BIB002 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Wetlands are one of the most important ecosystems in the world and at the same time they are presumed to be a source of methane gas, which is one of the most important greenhouse gases. The West Siberian wetlands is the largest in the world and remote sensing techniques can play an important role for monitoring the wetland. High spatial resolution satellite data are effective for monitoring land cover type changes, but can’t cover a wide area because of a narrow swath width. On the other hand, global scale data are indispensable in covering a large area, but are too coarse to get the detailed information due to the low spatial resolution. It is necessary to devise a method for the fusion of the data with different spatial resolutions for monitoring the scale-differed phenomena. In this paper, firstly, a SPOT HRV image near Plotnikovo mire was used to map four wetland ecosystems (birch forest, conifer forest, forested bog and open bog) supplemented by field observation. Then, spectral mixture analysis was performed between NOAA AVHRR and SPOT HRV data acquired on the same day. Secondly, field observations were scaled up with these different spatial resolution satellite data. Each of the wetland ecosystem coverage fraction at the sub-pixel level was provided by spectral mixture analysis. Field observation shows that the mean rate of CH4 emission from forested bog and open bog averaged 21.1 and 233.1 (mg CH4/m 2 /day), respectively. The methane emission from the area was estimated by multiplying these average methane emission rates and the fraction coverage in each AVHRR pixel. Finally, the total methane emission over AVHRR coverage was estimated to be 9.46 (10 9 gC H4/day) and the mean methane emission over AVHRR coverage was calculated as 59.3 (mg CH4/m 2 /day). We could conclude that this mean value is within the probabilistic variability as <s> BIB003 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Peatlands play a major role in the global carbon cycle but are largely overlooked in current large-scale vegetation mapping efforts. In this study, we investigated the potential of the Moderate Resolution Imaging Spectroradiometer (MODIS) to capture the extent and distributionofpeatlandsintheSt.PetersburgregionofRussiabyanalyzingtherelationshipsbetweenpeatlandcoverfractionsderived from reference maps and ∼1-km resolution MODIS Nadir BRDF-Adjusted Reflectance (NBAR) data from year 2002. First, we characterized and mapped 50 peatlands from forest inventory and peat deposit inventory data. The peatlands represent three major nutritional types (oligotrophic, mesotrophic, eutrophic) and different sizes (0.6–7800 ha). In addition, parts of 6 peatlands were mined for peat and these were mapped separately. The reference maps provided information on peatland cover for 1105 MODIS pixels. We performed regression analysis on 50% of the pixels and reserved the remainder for model validation. Canonical correlation analysis on the MODIS reflectance bands and the peatland cover fractions produced a multi-spectral peatland cover index (PCI), which served as the predictor in a reduced major axis (RMA) regression model. The results suggest a high potential for mapping peatlands with MODIS. The RMA regression models explained much of the variance in the PCI (r 2 =0.74 for mined and r 2 =0.81 for unmined peatlands). Model validation showed high correlation between observed versus predicted peatland cover (mined: r=0.87; unmined: r=0.92). We used the models to derive peatland cover estimates for the St. Petersburg region and compared the results to current MODIS land cover maps. © 2006 Elsevier B.V. All rights reserved. <s> BIB004 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Summary The proposed approach aims to estimate the flood extent and soil wetness using AMSR-E passive microwave data. The approach is applied over the Peace Athabasca Delta at the Mackenzie River Basin, which is situated in northwestern Canada. The methodology is based on the Polarization Ratio index (PR), which is computed using AMSR-E 37 GHz, vertically and horizontally polarized brightness temperature values. The Water Surface Fraction (WSF), which represents the fraction of flooded soil, was derived on a pixel-per-pixel basis. The fractional vegetation cover was added to the WSF calculation in order to take into account the temporal variation of the vegetation shading effect. The WSF derived from AMSR-E data, WSF(AMSR-E), was compared to that derived from the Moderate-resolution Imaging Spectroradiometer Terra instrument (MODIS-Terra) images (250 m), WSF(MODIS). A rating curve relationship was developed between the observed discharge and WSF(MODIS). It was noted that the WSF obtained from AMSR-E images systematically exceed those from MODIS, as they are formed from a combination of different contributions, including open water surface, flooded area and wetlands, which are abundant in the northern climates. Therefore, a wetness index was defined based on the difference between passive microwave and visible image responses. This index was able to qualitatively describe the temporal evolution of the wetness over a part of the Mackenzie River Basin. The availability of discharge observations and passive microwave data leads to the definition of a consistent wetness index and soil moisture monitoring over the region of the Mackenzie River Basin. The extrapolation of the developed algorithm to the entire Mackenzie River Basin should consider the dependency of the rating curve relationship on the site features. A satisfactory agreement was noted between the wetness index, the precipitation, and the temperature values. The wetness index agrees well with the measured soil moisture. <s> BIB005 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Information regarding the spatial extent and timing of flooding in the world's major wetlands is important to a wide range of research questions including global methane models, water management, and biodiversity assessments. The Florida Everglades is one of the largest wetlands in the US, and is subject to substantial development and pressures that require intensive hydrological modeling and monitoring. The Moderate Resolution Imaging Spectrometer (MODIS) is a global sensor with high frequency repeat coverage and significant potential for mapping wetland extent and dynamics at moderate spatial resolutions. In this study, empirical models to predict surface inundation in the Everglades were estimated using MODIS data calibrated to water stage data from the South Florida Water Management District for the calendar year 2004. The results show that hydropatterns in the Florida Everglades are strongly correlated to a Tasseled Cap wetness index derived from MODIS Nadir Bidirectional Reflectance Function Adjusted Reflectance data. Several indices were tested, including the Normalized Difference Wetness Index and the diurnal land surface temperature difference, but the Tasseled Cap wetness index showed the strongest correlation to water stage data across a range of surface vegetation types. Other variables included in the analysis were elevation and percent tree cover present within a pixel. Using logistic regression and ensemble regression trees, maps of water depth and flooding likelihood were produced for each 16-day MODIS data period in 2004. The results suggest that MODIS is useful for dynamic monitoring of flooding, particularly in wetlands with sparse tree cover. <s> BIB006 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> The use of NOAA-AVHRR NDVI time series from July 1981 to December 2000 was evaluated for the assessment of the functioning of a wetland macrosystem, the Parana River Delta. The spatial resolution of the dataset was 8 by 8 km. Spatial and temporal variations in NDVI pattern were analyzed and evidences for El Nino/South Oscillation events identified. We studied five wetland units (WUs) classified on the basis of landscape pattern and dominant hydrologic regime. Spearman rank correlations were performed among the NDVI time series of the different WUs. NDVI time series were correlated with water level in the Parana River and with records of local rainfall. In order to obtain a synthetic model of NDVI patterns, the autocorrelation functions (ACF) were estimated for each of the WUs. Results indicated that monthly mean NDVI values for all WUs showed a similar annual seasonal pattern, suggesting a control from the plant annual cycle on the NDVI signal. Besides, two general NDVI patterns were identified. The first pattern is represented by WUs under fluvial hydrologic regime. This is subjected to a significative interannual variability associated mainly to ENSO events. The second pattern corresponds to WUs with a very regular NDVI patterns. It includes wetlands which water input corresponds to tides or to rainfall. The ENSO had no significant influence on this pattern. This study suggests that NOAA-AVHRR NDVI long time series might provide valuable information about functioning of the large scale fluvial wetlands like those associated with South America basins. <s> BIB007 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Lake Baiyangdian, a largest wetland ecosystem in North China Plain, has dried up on seven occasions since the 1960s. In ::: recent years, more than one billion of cubic meters of water from upstream reservoirs and Yellow river have been ::: transported to the lake to rescue the shrinking wetlands. Since the Lake Baiyangdian was actually composed of 143 small ::: lakes and more than 70 villages with large or small area of cropland, dynamic distribution of aquatic plants in wetland ::: such as reed and associated growth condition of these allowed to monitor the changes of wetland landscape and water ::: quality to support the policy applications of water conveyance and wetland environmental treatment and control. ::: Assisted with ground survey analyses and Landsat TM image, the MODIS 250 m time series Normalized Difference ::: Vegetation Index (NDVI), given its combination of medium spatial and high temporal resolution, were applied to detect ::: the unique rapid growth stage of reed in the spring from adjacent crops such as winter wheat, cotton, and spring maize, ::: of which has a similar phenology in development of leaf area index, and dynamic reed areas were mapped in recent ::: decade. Landscape changes of the wetland were analyzed using maps of reed area and hydrological data. <s> BIB008 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Abstract Accurate depiction of the land and water is critical for the production of land surface parameters from remote sensing data products. Certain parameters, including the land surface temperature, active fires and surface reflectance, can be processed differently when the underlying surface is water as compared with land. Substantial errors in the underlying water mask can then pervade into these products and any products created from them. Historically many global databases have been created to depict global surface water. These databases still fall short of the current needs of the terrestrial remote sensing community working at 250 m spatial resolution. The most recent attempt to address the problem uses the Shuttle Radar Topography Mission (SRTM) data set to create the SRTM Water Body Data set (SWBD 2005). The SWBD represents a good first step but still requires additional work to expand the spatial coverage to include the whole globe and to address some erroneous discontinuities in major river networks. To address this issue a new water mask product has been created using the SWBD in combination with MODIS 250 m data to create a complete global map of surface water at 250 m spatial resolution. This effort is automated and intended to produce a dataset for use in processing of raster data (MODIS and future instruments) and for masking out water in final terrestrial raster data products. This new global dataset is produced from remotely sensed data and provided to the public in digital format, free of charge. The data set can be found on the Global Land Cover Facility (GLCF) website at http://landcover.org. This dataset is expected to be a base set of information to describe the surface of Earth as either land or water which is a fundamental distinction upon which other descriptions can be made. <s> BIB009 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> [1] We developed a remote sensing approach based on multi-satellite observations, which provides an unprecedented estimate of monthly distribution and area of land-surface open water over the whole globe. Results for 1993 to 2007 exhibit a large seasonal and inter-annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen-year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals. Citation: Prigent, C., F. Papa, F. Aires, C. Jimenez, W. B. Rossow, and E. Matthews (2012), Changes in land surface water dynamics since the 1990s and relation to population pressure, Geophys. Res. Lett., 39, L08403, doi:10.1029/2012GL051276. <s> BIB010 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> We have presented two conceptual approaches for building flood inundation modelling capability in river system models. The first approach is a simple method suitable for data limited environments. In this approach during any flood event, flow in a river reach within a floodplain is partitioned into two components, in-stream and overbank flow, based on the in-stream capacity. A flood volume-area relationship derived from the flood inundation time series, which is generated by analysing daily MODIS satellite imagery and SRTM DEM, is used to estimate flooded area for the overbank flow. The losses due to evaporation and groundwater seepage from the floodplain are calculated using the estimated flooded area. This approach can be integrated with a more detailed approach for flood inundation dynamics. This second approach is more comprehensive and suitable for areas with high resolution topography data such as LiDAR based data. LiDAR DEM is used to divide a floodplain into multiple storages based on pre-defined thresholds of flood inundation heights. The storage characteristics, including disconnected storage volume and hydraulic connectivity between floodplain storages and a river reach, are derived from the LiDAR DEM using a spatial data processing technique. This information is used to estimate flood inundation area for overbank flow. This paper introduces the two approaches and presents the results of their applications in the Murrumbidgee floodplain. The results are compared with the observed flow data and the hydrodynamic modelling results for two selected recent flood events. <s> BIB011 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Wetland and floodplain inundation is well-known for its hydrological, ecological and environmental importance. Satellite remote sensing provides an effective and efficient tool for detecting inundation extent. This study compares and validates inundation maps derived from NASA’s Moderate Imaging Spectroradiometer (MODIS) imagery. The comparison was performed between MODIS daily and 8-day composite products; and the validation was conducted using Landsat Thematic Mapper (TM) images. Two floodplain wetlands in the Murray-Darling Basin in Australia were selected as case studies, and inundation extents corresponding to the peak flows of significant flood events were extracted using the Open Water Likelihood (OWL) algorithm and the modified Normalised Difference Water Index (mNDWI) for MODIS and TM images, respectively. The accuracy of the inundation maps derived from different images were assessed spatially and statistically. The evaluation results show that both MODIS products may provide a reasonable estimate of the dynamic extent of floodplain inundation at the regional scale. The accuracy of inundation mapping is mainly due to the spatial and spectral characteristics of MODIS imagery and has nothing to do with the type of products chosen, thus the 8-day composite images can be used as a surrogate for daily images for the purpose of inundation delineation. <s> BIB012 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Abstract The Great Artesian Basin springs (Australia) are unique groundwater dependent wetland ecosystems of great significance, but are endangered by anthropogenic water extraction from the underlying aquifers. Relationships have been established between the wetland area associated with individual springs and their discharge, providing a potential means of monitoring groundwater flow using measurements of vegetated wetland area. Previous attempts to use this relationship to monitor GAB springs have used aerial photography or high resolution satellite images and gave sporadic temporal information. These “snapshot” studies need to be placed within a longer and more regular context to better assess changes in response to aquifer draw-downs. In this study we test the potential of 8 years of Moderate Resolution Imaging Spectroradiometer Normalised Difference Vegetation Index data as a long-term tracer of the temporal dynamics of wetland vegetation at the Dalhousie Springs Complex of the Great Artesian Basin. NDVI time series were extracted from MODIS images and phenologies of the main wetland vegetation species defined. Photosynthetic activity within wetlands could be discriminated from surrounding land responses in this medium resolution imagery. The study showed good correlation between wetland vegetated area and groundwater flow over the 2002–2010 period, but also the important influence of natural species phenologies, rainfall, and anthropogenic activity on the observed seasonal and inter-annual vegetation dynamics. Declining trends in the extent (km 2 ) of vegetated wetland areas were observed between 2002 and 2009 followed by a return of wetland vegetation since 2010. This study underlines the need to continue long-term medium resolution satellite studies of the GAB to fully understand variability and trends in the spring-fed wetlands. The MODIS record allows a good understanding of variability within the wetlands, and gives a high temporal-frequency context for less frequent higher spatial resolution studies, therefore providing a strong baseline for assessment of future changes. <s> BIB013 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> [1] Water is a precious resource since the lives and livelihoods of human societies depend on their ability to access this resource. This is particularly true in arid and semiarid regions like the Sahel where permanent surface waters are rare and hydrological solutions (e.g., accessing deep aquifers) are often not feasible. This work is devoted to the determination of the spatial and temporal variations of surface water extent at 250 m over 9 years (2003–2011) for the Soudan-Sahel region using visible and infrared imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) from both Terra and Aqua platforms. The methodology is automatic and could be applied to other regions and sensors. We utilized a combination of two MODIS spectral indices: the Normalized Difference Vegetation Index and the Modified Normalized Difference Water Index. Accuracy assessments carried out on 743 lakes across 37 Landsat images selected in Sahelian Africa on the basis of a stratified sampling show that the new product is (i) reliably able to detect surface water bodies of approximately 50 ha and larger, (ii) improves on existing surface water body products, and (iii) can be used to monitor the seasonal distribution of surface water in semiarid regions. <s> BIB014 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Semi-arid North-central Namibia has high potential for rice cultivation because large seasonal wetlands (oshana) form during the rainy season. Evaluating the distribution of surface water would reveal the area potentially suitable for rice cultivation. In this study, we detected the distribution of surface water with high spatial and temporal resolution by using two types of complementary satellite data: MODIS (MODerate-resolution Imaging Spectroradiometer) and AMSR-E (Advanced Microwave Scanning Radiometer–Earth Observing System), using AMSR2 after AMSR-E became unavailable. We combined the modified normalized-difference water index (MNDWI) from the MODIS data with the normalized-difference polarization index (NDPI) from the AMSR-E and AMSR2 data to determine the area of surface water. We developed a simple gap-filling method (“database unmixing”) with the two indices, thereby providing daily 500-m-resolution MNDWI maps of north-central Namibia regardless of whether the sky was clear. Moreover, through receiver-operator characteristics (ROC) analysis, we determined the threshold MNDWI (−0.316) for wetlands. Using ROC analysis, MNDWI had moderate performance (the area under the ROC curve was 0.747), and the recognition error for seasonal wetlands and dry land was 21.2%. The threshold MNDWI let us calculate probability of water presence (PWP) maps for the rainy season and the whole year. The PWP maps revealed the total area potentially suitable for rice cultivation: 1255 km2 (1.6% of the study area). <s> BIB015 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Abstract Flood inundation is crucial to the survival and prosperity of flora and fauna communities in floodplain and wetland ecosystems. This study tried to map flood inundation characteristics in the Murray-Darling Basin, Australia, utilizing hydrological and remotely sensed data. It integrated river flow time series and Moderate Resolution Imaging Spectroradiometer (MODIS) images to map inundation dynamics over the study area on both temporal and spatial dimensions. Flow data were analyzed to derive flow peaks and Annual Exceedance Probabilities (AEPs) using the annual flood series method. The peaks were linked with MODIS images for inundation detection. Ten annual maximum inundation maps were generated for water years 2001–2010, which were then overlaid to derive an inundation frequency map. AEPs were also combined with the annual maximum inundation maps to derive an inundation probability map. The resultant maps revealed spatial and temporal patterns of flood inundation in the basin, which will benefit ecological and environmental studies when considering response of floodplain and wetland ecosystems to flood inundation. <s> BIB016 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> In this article, passive microwave observations in synergy with optical data are exploited to monitor floods and estimate vegetation submerging. The selected site is Sundarban Delta, at the borders between India and Bangladesh. The area is subject to severe monsoon in summer, producing heavy floods and vegetation submerging. Because of their high spatial resolution, Moderate Resolution Imaging Spectroradiometer (MODIS) signatures are used to evaluate the coverage fractions of bare soil, vegetated fields, and permanent water. Multifrequency Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) signatures are used to monitor vegetation submerging during monsoon. Results are compared with ground measurements of water level and plant biomass in both agriculture areas and wetlands. Previous studies indicated that, during monsoon, there is a clear effect of brightness temperature decrease and polarization index increase in the C, X and Ka bands over the areas affected by floods. X band data pro... <s> BIB017 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Abstract Time-series remote sensing data, such as Moderate Resolution Imaging Spectroradiometer (MODIS) data hold considerable promise for investigating long-term dynamics of land use/cover change (LUCC), given their significant advantages of frequent temporal coverage and free cost. However, because of the complex ecological environment of wetlands, the applicability of these data for studying temporal dynamics of wetland-related land-cover types is limited. This is especially so for the Poyang Lake, China's largest freshwater lake, which has active seasonal and inter-annual dynamics. The primary objective of this study is to investigate the suitability of MODIS 250-m maximum value composite (MVC) vegetation indexes (VIs) for dynamics monitoring of the Poyang Lake. We applied a time-series 16-day MODIS NDVI from 2000 to 2012 and developed a method to classify wetland cover types based on timing of inundation. We combined techniques of applying iterative self-organizing data analysis (ISODATA) with varying numbers of clusters and a transformed divergence (TD) statistic, to implement annual classification of smoothed time-series NDVI. In addition, we propose a decision tree based on features derived from NDVI profiles, to characterize phenological differences among clusters. Supported by randomly generated validation samples from TM images and daily water level records, we obtained a satisfactory accuracy assessment report. Classification results showed various change patterns for four dominant land cover types. Water area showed a non-significant declining trend with average annual change rate 33.25 km 2 , indicating a drier Poyang lake, and emergent vegetation area had weak change over the past 13 years. Areas of submerged vegetation and mudflat expanded, with significant average annual change rate 23.51 km 2 for the former. The results suggest that MODIS' 250-m spatial resolution is appropriate and the classification method based on timing of inundation is useful for mapping general land cover patterns of Poyang Lake. <s> BIB018 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta’s general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas—namely the Yellow River Delta (China), the Mekong Delta (Vietnam), the Irrawaddy Delta (Myanmar), and the Ganges-Brahmaputra (Bangladesh, India)—as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013). A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid-latitude, subtropical, and polar deltas are illustrated, and the advantages and limitations of the approach for inundation derivation are discussed. <s> BIB019 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Wetlands provide a vital resource to ecosystem services and associated rural livelihoods but their extent, geomorphological heterogeneity and flat topography make the representation of their hydrological functioning complex. A semi automated method exploiting 526 MODIS (Moderate Resolution Imaging Spectroradiometer) 8-day 500 m resolution images was developed to study the spatial and temporal dynamics of the annual flood across the Niger Inner Delta over the period 2000–2011. A composite band ratio index exploiting the Modified Normalised Difference Water Index (MNDWI) and Normalised Difference Moisture Index (NDMI) with fixed thresholds provided the most accurate detection of flooded areas out of six commonly used band ratio indices. K-means classified Landsat images were used to calibrate the thresholds. Estimated flooded surface areas were evaluated against additional classified Landsat images, previous studies and field stage data for a range of hydrological units: river stretches, lakes, floodplains and irrigated areas. This method illustrated how large amounts of MODIS images may be exploited to monitor flood dynamics with adequate spatial and temporal resolution and good accuracy, except during the flood rise due to cloud presence. Previous correlations between flow levels and flooded areas were refined to account for the hysteresis as the flood recedes and for the varying amplitude of the flood. Peak flooded areas varied between 10 300 km2 and 20 000 km2, resulting in evaporation losses ranging between 12 km3 and 21 km3. Direct precipitation assessed over flooded areas refined the wetland’s water balance and infiltration estimates. The knowledge gained on the timing, duration and extent of the flood across the wetland and in lakes, floodplains and irrigated plots may assist farmers in agricultural water management. Furthermore insights provided on the wetland’s flood dynamics may be used to develop and calibrate a hydraulic model of the flood in the Niger Inner Delta. <s> BIB020 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Abstract We have, for the first time, developed a simple linear regression model based on PALSAR ScanSAR backscattering coefficients ( σ 0 ), water levels from Envisat altimetry, and MODIS Vegetation Continuous Field (VCF) product to generate water depth maps over flooded forest in the central Congo Basin. The water depth maps we generated are relative to the lowest water level from Envisat altimetry, which is assumed to be a base level with essentially zero depth. The predicted and observed water depths along the Envisat pass showed excellent agreements with RMS differences of 12.8 cm to 17.8 cm. The water depth maps were also independently validated with ∂h/∂t obtained from PALSAR interferometry, and storage anomalies estimated by multiplying inundation extents from PALSAR ScanSAR with spatially averaged water level anomalies from Envisat altimetry. The water storage volumes calculated from our water depth maps were calculated to be 11.3 ± 2.0 km 3 , 10.3 ± 2.3 km 3 , and 9.3 ± 1.8 km 3 for 12/05/2006, 12/08/2007, and 12/10/2008, respectively. It is expected that our method can be applied to other river basins that have flooded forest with satellite radar altimeter over-passes. The water depth maps can be directly used to calibrate and validate the spatial and temporal variation of inundation extent and water depth in the wetland derived from a 2-D hydrodynamic model. Furthermore, our water depth maps can be used as a “true” dataset to perform a pre-launch “virtual mission” study of the Surface Water Ocean Topography (SWOT) mission to be launched in 2020. <s> BIB021 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Asian countries strongly depend on rice production for food security. The major rice-growing season (June to October) is highly exposed to the risk of tropical storm related damage. Unbiased and transparent approaches to assess the risk of rice crop damage are essential to support mitigation and disaster response strategies in the region. This study describes and demonstrates a method for rapid, pre-event crop status assessment. The ex-post test case is Typhoon Haiyan and its impact on the rice crop in Leyte Province in the Philippines. A synthetic aperture radar (SAR) derived rice area map was used to delineate the area at risk while crop status at the moment of typhoon landfall was estimated from specific time series analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) data. A spatially explicit indicator of risk of standing crop loss was calculated as the time between estimated heading date and typhoon occurrence. Results of the analysis of pre- and post-event SAR images showed that 6500 ha were flooded in northeastern Leyte. This area was also the region most at risk to storm related crop damage due to late establishment of rice. Estimates highlight that about 700 ha of rice (71% of which was in northeastern Leyte) had not reached maturity at the time of the typhoon event and a further 8400 ha (84% of which was in northeastern Leyte) were likely to be not yet harvested. We demonstrated that the proposed approach can provide pre-event, in-season information on the status of rice and other field crops and the risk of damage posed by tropical storms. <s> BIB022 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> The mangrove ecosystem of Sundarbans region plays an important ecological and socioeconomical role in both India and Bangladesh. The satellite-based approach has been adopted for assessing the ecological disturbance caused by major cyclones. Moderate Resolution Imaging Spectroradiometer (MODIS) time-series (2001–2011) Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) products were used to compute the MODIS Global Disturbance Index (MGDI). The pre- and post-cyclonic changes in the EVI as well as LST were analyzed to study the impact of cyclones on the vegetation and surface temperature, respectively. In the present study, time-series MGDI was transformed to the percentage change in MGDI using temporal mean for each pixel, and its response toward cyclonic events was studied. The pre- and post-cyclonic Landsat data were analyzed to identify the affected areas discernible on the image and a threshold was decided to mark the “disturbed pixels.” The threshold for the instantaneous disturbance caused by cyclones was found to be more than 11 % of the temporal mean MGDI. The selected threshold was applied on the time-series MGDI images to delineate the disturbed pixels, and percent-disturbed area of each Island was computed. The classified disturbed area maps were able to characterize the impact of cyclones and effectively represent the distribution of the spatial intensity of the ecological disturbance in Sundarbans region. <s> BIB023 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> The understanding and assessment of surface water variability of inland water bodies, for example, due to climate variability and human impact, requires steady and continuous information about its inter- and intra-annual dynamics. In this letter, we present an approach using dynamic threshold techniques and utilizing time series to generate a data set containing detected surface water bodies on a global scale with daily temporal resolution. Exemplary results for the year 2013 that were based on moderate resolution imaging spectroradiometer products are presented in this letter. The main input data sets for the presented product were MOD09GQ/MYD09GQ and MOD10A1/MYD10A1 with a spatial resolution of 250 m and 500 m, respectively. Using the static water mask MOD44W, we extracted training pixels to generate dynamic thresholds for individual data sets on daily basis. In a second processing step, the generated sequences of water masks were utilized to interpolate the results for any missing observations, either ... <s> BIB024 </s> A Review of Wetland Remote Sensing <s> Review of Coarse Spatial Resolution Data for Wetland Studies <s> Accurate and up-to-date information on the spatial distribution of paddy rice fields is necessary for the studies of trace gas emissions, water source management, and food security. The phenology-based paddy rice mapping algorithm, which identifies the unique flooding stage of paddy rice, has been widely used. However, identification and mapping of paddy rice in rice-wetland coexistent areas is still a challenging task. In this study, we found that the flooding/transplanting periods of paddy rice and natural wetlands were different. The natural wetlands flood earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. We used this asynchronous flooding stage to extract the paddy rice planting area from the rice-wetland coexistent area. MODIS Land Surface Temperature (LST) data was used to derive the temperature-defined plant growing season. Landsat 8 OLI imagery was used to detect the flooding signal and then paddy rice was extracted using the difference in flooding stages between paddy rice and natural wetlands. The resultant paddy rice map was evaluated with in-situ ground-truth data and Google Earth images. The estimated overall accuracy and Kappa coefficient were 95% and 0.90, respectively. The spatial pattern of OLI-derived paddy rice map agrees well with the paddy rice layer from the National Land Cover Dataset from 2010 (NLCD-2010). The differences between RiceLandsat and RiceNLCD are in the range of ±20% for most 1-km grid cell. The results of this study demonstrate the potential of the phenology-based paddy rice mapping algorithm, via integrating MODIS and Landsat 8 OLI images, to map paddy rice fields in complex landscapes of paddy rice and natural wetland in the temperate region. <s> BIB025
Coarse spatial resolution remote sensing data used in wetland studies includes Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR data. MODIS instrument aboard NASA Aqua and Terra satellites provides nearly daily repeated coverage of the Earth's surface with 36 spectral bands and a swath width of approximately 2330 km. Seven bands are specifically designed for land remote sensing with a spatial resolution of 250 m (bands 1-2) and 500 m (bands 3-7) BIB004 . Of the 5719 wetland remote sensing papers, 331 papers used MODIS data and 127 used AVHRR data. Because of the combination of spectral, temporal, and spatial resolution compared to other global sensors, MODIS has been used in a variety of studies such as water body mapping and inundation  BIB015  BIB006 BIB005 BIB011 BIB012 BIB016 BIB017 BIB019 BIB020  , water depth mapping BIB021 , paddy rice planting area mapping BIB025 BIB022 , ecological disturbance analysis BIB023 , wetland area monitoring BIB013 BIB018 BIB008 , peatland mapping BIB004 , and habitat mapping  . Satellite remote sensing data provide an effective and efficient tool for detecting water body areas and flood inundation extent on a large area. Because of the high temporal resolution and large coverage, MODIS has significant advantages for mapping the wetland extent and dynamics at a coarse spatial resolution BIB006 . Cai et al.  used MODIS data to map the water body areas of the Poyang Lake in China and obtained the lake surface area with an error of approximately 6.19%. They also analyzed the possibility of monitoring the height of the water surface using a radar altimeter. The surface water distribution was identified by Mizuochi et al. BIB015 using the modified normalized difference water index (MNDWI) of MODIS and normalized difference polarization index (NDPI) of the multi-frequency Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) in North-Central Namibia. Takeuchi and Gonzalez  proposed a new model by combining 2 km MODIS NDWI and 16 km AMSR-E NDPI to predict daily land surface water coverage and obtained a result similar to that of MODIS. Using visible and infrared channels of MODIS data, Kaptué et al. BIB014 monitored the spatiotemporal variations of surface water from 2003 to 2011 in the Soudan-Sahel region of Africa and argued that MODIS could effectively characterize open water bodies larger than 50 ha. They also concluded that MODIS could be used to monitor the seasonal changes of surface water in semiarid regions. Based on time series MODIS data, Klein et al. BIB024 presented a new method using dynamic threshold techniques to map daily water body in global scale and concluded that the new method could obtain intra-annual changes of open water effectively. Prigent et al. BIB010 used AVHRR visible and near-infrared reflectance and the derived NDVI and other satellite data to estimate the area and monthly distribution of land surface water at global scale. They found that the declines of open water and the increases of population often occurred in the same region. Carroll et al. BIB009 produced a new water mask map globally at 250 m spatial resolution based on MODIS and radar based water body dataset. Their result improved the former water mask product at 1 km spatial resolution and could be freely download from http://landcover.org. Ogilvie et al. BIB020 combined MNDWI and the normalized difference moisture index (NDMI) of MODIS imagery to monitor the flood areas. To monitor flood and estimate vegetation submerging in the Sundarban Delta, at the borders between India and Bangladesh, MODIS was used to evaluate the coverage fractions of bare soil, vegetated fields, and permanent water and AMSR-E was used to monitor the submerging vegetation BIB017 . Chen et al. BIB012 and Huang et al. BIB016 derived a flood inundation map from MODIS data in Murray-Darling Basin in Australia. Chen et al. BIB012 also used TM as the validation data and concluded that the accuracy of inundation mapping is mainly due to the spatial and spectral characteristics of MODIS imagery. Huang et al. BIB016 revealed spatial and temporal patterns of flood inundation in the study region. Dutta et al. BIB011 used the same method to derive inundation maps from MODIS daily imagery in Murrumbidgee Floodplain of Australia and then built a flood inundation model. Ordoyne and Friedl BIB006 used MODIS data to predict the surface inundation in Everglades of the United States and found that the inundation patterns correlate with the tasseled cap wetness index derived from MODIS. They also suggested that MODIS is a useful sensor for monitoring flood dynamics, especially in sparse tree wetlands. Kuenzer et al. BIB019 analyzed the dynamics of inundation using MODIS data in four river deltas of Asia and demonstrated that MODIS data have potential to depict distinct inundation patterns. Compared to MODIS data, AVHRR data have been sparsely used for wetland studies because of the lower spectral resolution and coarse spatial resolution (8 by 8 km) of AVHRR normalized difference vegetation index (NDVI) data and also because of the natural fragmentation of wetlands BIB007 BIB003  BIB001 BIB002 . Ewiii et al. BIB001 used NDVI from AVHRR images to monitor the damage of forested wetland by hurricanes in Louisiana, USA. They compared NDVI changes at three impacted sites with undamaged forest and confirmed the direct impact of hurricanes on the forested wetland. Ewiii et al. BIB002 used AVHRR NDVI and thematic maps classified based on Landsat TM to determine the relationship between forest type and hurricane impact severity and made conclusions useful for resource managers. AVHRR NDVI has also been used by Moreau et al.  to assess the spatial and temporal changes of biomass in wetland grasses of Bolivian Northern Altiplano; the authors found that NDVI is sensitive to green vegetation biomass. Time series of AVHRR NDVI have also been used to analyze the seasonal and annual changes of wetland and it was reported that NDVI time series can provide useful information for large area of wetlands BIB007 . Based on spectral mixture analysis, AVHRR images were used to estimate CH 4 emissions from wetland in West Siberia. According to the CH 4 emission rate of each wetland ecosystem from field observations and the fraction of each wetland ecosystem in each AVHRR pixel, Takeuchi et al. BIB003 determined the total and mean CH 4 emission of the study region to be 9.46 × 10 6 kg CH 4 day −1 and 59.3 mg CH 4 m −2 day −1 , respectively.