Evaluation of Approaches for Mapping Tidal Wetlands of the Chesapeake and Delaware Bays (original) (raw)
Related papers
Remote Sensing of Environment, 2008
Multi-temporal C-band SAR data (C-HH and C-VV), collected by ERS-2 and ENVISAT satellite systems, are compared with field observations of hydrology (i.e., inundation and soil moisture) and National Wetland Inventory maps (U.S. Fish and Wildlife Service) of a large forested wetland complex adjacent to the Patuxent and Middle Patuxent Rivers, tributaries of the Chesapeake Bay. Multi-temporal C-band SAR data were shown to be capable of mapping forested wetlands and monitoring hydroperiod (i.e., temporal fluctuations in inundation and soil moisture) at the study site, and the discrimination of wetland from upland was improved with 10 m digital elevation data. Principal component analysis was used to summarize the multi-temporal SAR data sets and to isolate the dominant temporal trend in inundation and soil moisture (i.e., relative hydroperiod). Significant positive, linear correlations were found between the first principal component and percent area flooded and soil moisture. The correlation (r 2 ) between the first principal component (PC1) of multi-temporal C-HH SAR data and average soil moisture was 0.88 (p = b .0001) during the leaf-off season and 0.87 (p = b .0001) during the leaf-on season, while the correlation between PC1 and average percent area inundated was 0.82 (p = b .0001) and 0.47 (p = .0016) during the leaf-off and leaf-on seasons, respectively. When compared to field data, the SAR forested wetland maps identified areas that were flooded for 25% of the time with 63-96% agreement and areas flooded for 5% of the time with 44-89% agreement, depending on polarization and time of year. The results are encouraging and justify further studies to attempt to quantify the relative SAR-derived hydroperiod classes in terms of physical variables and also to test the application of SAR data to more diverse landscapes at a broader scale. The present evidence suggests that the SAR data will significantly improve routine wooded wetland mapping.
Mapping and monitoring of vast coastal wetlands vulnerable to dynamic coastal erosion, sea-level rise, fire, and marsh succession require remote sensing approaches that capitalize on newly available sensors, advanced classification techniques, and combinations of multi-sensor and multi-date data. This pilot study assesses the feasibility and accuracy potential for mapping specific coastal wetlands of high priority for the National Wetland Inventory (NWI) in the Alligator River National Wildlife Refuge, North Carolina. Wetland classes of high mapping value owing to their ecological dynamics and extent include palustrine forests (swamp forests and pocosins), emergent estuarine marshes, irregularly-flooded shrub-scrub transition, and invasive Phragmites australis patches occurring along shores throughout the region. These classes selected to test input data and classification methodology using an array of multidate SAR imagery (ALOS PALSAR) and LiDAR-derived rasters (minimum elevation, vegetation canopy height, slope, and curvature) in combinations. Initial results illustrate strong potential for multidate SAR imagery and enhanced accuracy achievable by integration of vegetation canopy LiDAR for broad-scale mapping of coastal wetland vegetation change. Canopy structural changes over spring, early and late summer seasons were captured by PALSAR HH and HV polarization bands, yielding the highest overall accuracies multidate combination and with inclusion of LiDAR canopy and minimum elevation data. Field observations corroborated the remote sensing and offer useful calibration data for sea-level rise simulation models and invasive species monitoring. In concert with the historical continuity of Landsat for broader coastal land cover dynamics, these data and techniques offer significant enhancements for future monitoring of coastal change.
International Journal of Remote Sensing, 2019
Although regional wetland mapping studies have mostly relied on optical sensors, synthetic aperture radar (SAR) sensors are being increasingly applied. The aim of this study is to analyse the ability of the Phased Array type L-band Synthetic Aperture Radar on board of the Advanced Land Observing Satellite (ALOS/PALSAR-1) data to identify, delineate and monitor wetlands, and to evaluate the importance of scene selection in a highly unpredictable wetland. Three SAR scene sets (Year A, Year B and Inter-annual) were built for this purpose, considering the intra-annual and inter-annual hydrologic variability and the phenologic variability of the studied coastal wetland. Seven land cover types were defined, including three permanently flooded wetland classes, three temporarily flooded wetland classes and one non-wetland class. An object-based unsupervised classification approach was applied on each multi-temporal set. The obtained clusters were characterized by a temporal signature and assigned to the seven land cover types using a decision tree with user-defined thresholds. The accuracy assessment of each product was performed using a set of 258 data sites, including field collected data and data retrieved from Landsat 8 Operational Land Imager (OLI) imagery acquired during the dates of the field campaign. The Year B set showed the best accuracy (83.4% overall, 75% Kappa coefficient (κ)) and the lowest omission and commission mean errors (16.6% and 16.1% respectively). The classes that were best differentiated are permanently flooded wetlands (PFW) and non-wetlands (NW) in all sets.
Potential of TerraSAR-X Imagery for Mapping Intertidal Coastal Wetlands
Proceedings of the …, 2011
This work presents preliminary results about the use of TerraSAR-X imagery for mapping intertidal habitats (oyster parks, seagrass meadows of Zostera noltii, sediments) along coastal lagoons (Arcachon lagoon, France). The combination of SAR and optical data appears to be useful to improve the discrimination of the various sediment and vegetation covers into classification schemes. Unlike optical imagery which may lead to misinterpret sediment type, the potential of the multi-polarization SAR data is assessed notably regarding its efficiency for separating intertidal (Z. noltii) from supratidal salt-marsh vegetation species (spartina, salicornia, and so on). TerraSAR-X imagery is also an excellent highlighter of areas colonized by oysters (both cultivated and invasive ones) due to their relevant roughness signature among neighbored facies. In contrast, mapping methods based on optical data alone often do not perform well because of the presence of algae on oyster shelves. Moreover, potential exists for discrimating unvegetated soils but biofilm-covered from low-vegetated ones. As a conclusion, TerraSAR-X imagery offers many tracks to increase the performance of thematic mapping products along intertidal environments, in complement of optical data.
Wetlands Ecology and Management, 2011
Detailed vegetation mapping of wetlands, both natural and restored, can offer valuable information about vegetation diversity and community structure and provides the means for examining vegetation change over time. We mapped vegetation at six tidal marshes (two natural, four restored) in the San Francisco Estuary, CA, USA, between 2003 and 2004 using detailed vegetation field surveys and high spatial-resolution color-infrared aerial photography. Vegetation classes were determined by performing hierarchical agglomerative clustering on the field data collected from each tidal marsh. Supervised classification of the CIR photography resulted in vegetation class mapping accuracies ranging from 70 to 92%; 10 out of 12 classification accuracies were above 80%, demonstrating the potential to map emergent wetland vegetation. The number of vegetation classes decreased with salinity, and increased with size and age. In general, landscape diversity, as measured by the Shannon’s diversity index, also decreased with salinity, with an exception for the most saline site, a newly restored marsh. Vegetation change between years is evident, but the differences across sites in composition and pattern were larger than change within sites over two growing seasons.
IEEE Transactions on Geoscience and Remote Sensing, 2000
Hydrology (i.e., inundation and soil moisture) is the most important abiotic factor controlling wetland function and extent, and scientists predict that wetland hydrology can be significantly altered over relatively short timescales due to climate change and anthropogenic impact. Whereas broadscale hydrology is difficult to monitor in forested wetlands with ground-based and optical remote sensing methods, C-band synthetic aperture radar (SAR) systems have the potential to improve the capability to monitor forested wetland hydrology. In this study, we examined the use of Environmental Satellite Advanced SAR (C-HH and C-VV) data for monitoring levels of inundation and soil moisture throughout the year in a typical Mid-Atlantic floodplain and some of the main limitations inherent to C-band data (i.e., polarization and plant phenology) in this environment. The relationships between the backscatter coefficient σ 0 and inundation, soil moisture, tree basal area, tree height, and forest canopy closure were examined. Significant differences in C-HH σ 0 were found between forested areas of varying hydrology (0%-60% area inundated) throughout the year and in C-VV σ 0 during the leaf-off season. As expected, C-HH SAR backscatter was better correlated with inundation and soil moisture than was C-VV SAR backscatter, and the correlations between both polarizations of backscatter and hydrology were stronger during the leaf-off season (C-HH leaf-off r 2 = 0.50, leaf-on r 2 = 0.39; C-VV leaf-off r 2 = 0.21, leaf-on r 2 = 0.19; all significant at p < 0.0001 level). Based on our findings, we concluded that the C-HH data are useful for monitoring hydrology beneath forest canopies throughout the year, whereas the C-VV data can be used during the leaf-off season. Our findings support previous studies that concluded that C-band imagery can be used to monitor forested wetland hydrology in large floodplains that are fully inundated. However, this study used detailed in situ measurements and demonstrated that C-band SAR data can also be used to monitor forested wetland hydrology in smaller partially inundated floodplains, which are more common in the Mid-Atlantic. She is currently working to assess the effect of conservation practices including wetland restoration on water quality and other ecosystem services. She specializes in monitoring forested wetlands using radar and other remotely sensed data. Eric S. Kasischke (A'85-M'88) received the B.S. degree in natural resources, the M.S. degree in remote sensing, and the Ph.D. degree in forest ecology/ remote sensing from the University
Water, 2014
Wetlands provide ecosystem goods and services vitally important to humans. Land managers and policymakers working to conserve wetlands require regularly updated information on the statuses of wetlands across the landscape. However, wetlands are challenging to map remotely with high accuracy and consistency. We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada's Radarsat-2 system to track within-season changes in wetland vegetation and surface water. We speculated, a priori, how temporal and morphological traits of different types of wetland vegetation should respond over a growing season with respect to four energy-scattering mechanisms. We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands. We found the traits of different types of vertical emergent wetland vegetation were detected well with the SAR data and corresponded with our anticipated backscatter
Remote Sensing, 2015
Methods using extensive field data and three-season Landsat TM and PALSAR imagery were developed to map wetland type and identify potential wetland stressors (i.e., adjacent land use) for the United States and Canadian Laurentian coastal Great Lakes. The mapped area included the coastline to 10 km inland to capture the region hydrologically connected to the Great Lakes. Maps were developed in cooperation with the overarching Great Lakes Consortium plan to provide a comprehensive regional baseline map suitable for coastal wetland assessment and management by agencies at the local, tribal, state, and federal levels. The goal was to provide not only land use and land cover (LULC) baseline data at moderate spatial resolution (20-30 m), but a repeatable methodology to monitor change into the future. The prime focus was on mapping wetland ecosystem types, such as emergent wetland and forested wetland, as well as to delineate wetland monocultures (Typha,
International journal of applied earth observation and geoinformation, 2018
Wetland maps currently in use by the Province of Nova Scotia, namely the Department of Natural Resources (DNR) wetland inventory map and the swamp wetland classes of the DNR forest map, need to be updated. In this study, wetlands were mapped in an area southwest of Halifax, Nova Scotia by classifying a combination of multidate and multi-beam RADARSAT-2 C-band polarimetric SAR (polSAR) images with spring Lidar, and fall QuickBird optical data using the Random Forests (RF) classifier. The resulting map has five wetland classes (open-water/marsh complex, open bog, open fen, shrub/treed fen/bog, swamp), plus lakes and various upland classes. Its accuracy was assessed using data from 156 GPS wetland sites collected in 2012 and compared to the one obtained with the current wetland map of Nova Scotia. The best overall classification was obtained using a combination of Lidar, RADARSAT-2 HH, HV, VH, VV intensity with polarimetric variables, and QuickBird multispectral (89.2%). The classified image was compared to GPS validation sites to assess the mapping accuracy of the wetlands. It was first done considering a group consisting of all wetland classes including lakes. This showed that only 69.9% of the wetland sites were correctly identified when only the QuickBird classified image was used in the classification. With the addition of variables derived from lidar, the number of correctly identified wetlands increased to 88.5%. The accuracy remained the same with the addition of RADARSAT-2 (88.5%). When we tested the accuracy for identifying wetland classes (e.g. marsh complex vs. open bog) instead of grouped wetlands, the resulting wetland map performed best with either QuickBird and Lidar, or QuickBird, Lidar, and RADARSAT-2 (66%). The Province of Nova Scotia's current wetland inventory and its associated wetland classes (aerial-photo interpreted) were also assessed against the GPS wetland sites. This provincial inventory correctly identified 62.2% of the grouped wetlands and only 18.6% of the wetland classes. The current inventory's poor performance demonstrates the value of incorporating a combination of new data sources into the provincial wetland mapping.
Temporal analysis of optical and SAR remote sensing for monitoring of intertidal salt marshes
2012
This study proposes a methodology in support of Integrated Coastal Zone Management, through analysis of the seasonal variations in intertidal habitats, as recorded in satellite remote sensing. Knowledge of seasonal and phenological cycles associated with different intertidal coastal habitats is critical for their identification and monitoring as part of an integrated remote analysis. This research seeks to improve understanding of the impact of external fluxes such as erosion, habitat loss and sea level rise. To achieve these aims, this research uses a multi-annual time series of both SAR data and medium/high resolution optical imagery (Landsat, ASTER) to develop vegetation products such as NDVI or FAPAR. The SAR data (airborne SAR, ASAR, ERS1/2) allows fluctuations in vegetation structure, standing biomass and flooding regimes to be examined. The combination of a multi-sensor and multi-temporal approach, with knowledge of habitat phenological cycles gives greater insight into the long-term dynamics of intertidal land cover and ecosystem functions and service associated with intertidal habitats. The temporal analysis of medium-resolution optical and SAR data can also be regarded as a precursor study for the upcoming Sentinel-1 and -2 missions, which will provide an unprecedented influx of satellite imagery.