High-resolution Elevation Data Research Articles

Surface Solar Radiation Resource Evaluation of Xizang Region Based on Station Observation and High-Resolution Satellite Dataset

Xizang boasts a vast and geographically complex landscape with an average elevation surpassing 4000 m. Understanding the spatiotemporal distribution of surface solar radiation is indispensable for simulating surface processes, studying climate change, and designing photovoltaic power generation and solar heating systems. A multi-dimensional, long-term, spatial, and temporal investigation of solar radiation in Xizang was conducted using three unique datasets, including the difference in surface solar radiation (SSR) between high-resolution satellite and ground station data, the annual and monthly distribution of SSR, and the interannual–monthly–daily variation and the coefficient of hourly variability. Combined with high-resolution elevation data, a strong linear correlation was shown between the radiation and the elevation below 4000 m. Furthermore, analysis reveals greater differences in data between east and west compared to the center, as well as between summer and winter seasons. SSR levels vary in steps, reaching the highest from Ngari to Shigatse and the lowest in a U-shaped area formed by southeastern Shannan and southern Nyingchi. In June, high monthly SSR coverage was the highest of the year. Since 1960, the annual mean SSR has generally exhibited a declining trend, displaying distinctive trends across various seasons and datasets. Owing to intricate meteorological factors, some regions exhibited double peaks in monthly SSR. Finally, we have introduced a solar resource assessment standard, along with a multidimensional evaluation of the resources, and categorized all townships. We offer a thorough analysis of Xizang’s solar radiation to provide a comprehensive understanding, which will help to prioritize recommendations for PV construction in Xizang.

Sunny-Day Flooding and Mortality Risk in Coastal Florida.

Sea-level rise is likely to worsen the impacts of hurricanes, storm surges, and tidal flooding on coastal access to basic services. We investigate the historical impact of tidal flooding on mortality rates of the elderly population in coastal Florida using administrative records of individual deaths, demographics, and residential location combined with tidal gauge and high-resolution elevation data. We incorporate data capturing storm and precipitation events into our empirical model to distinguish between disruptions from routine sunny-day flooding and less predictable tropical storm-induced flooding. We find that a 1-standard-deviation (20-millimeter) increase in tidal flooding depth increases mortality rates by 0.46% to 0.60% among those aged 65 or older. Our estimates suggest that future sea-level rises may contribute to an additional 130 elderly deaths per year in Florida relative to 2019, all else being equal. The enhanced risk is concentrated among residents living more than nine minutes away from the nearest hospital. Results suggest that tidal flooding may augment elderly mortality risk by delaying urgent medical care.

COMPARATIVE ANALYSIS BETWEEN GPS-BASED FIELD DIGITAL TERRAIN MODEL WITH TANDEM- X 90M, ASTER AND SRTM DIGITAL ELEVATION MODELS

This study compared the vertical accuracy of existing satellite’s Digital Elevation Model (STRM, ASTER) and the latest satellite remote sensing height data set TanDEM-90m. ASTER and STRM have vertical accuracies of ± 20m and ± 16m, respectively. TanDEMX-90m was processed before use, and the RMSE range of 19-20m was confirmed for TANDEM X 90m. The result of the study shows that ASTER DEM performed better than the rest of the global digital elevation models. The SRTM error of 4m between the first and second locations may be due to systematic error due to slightly different versions of SRTM used for processing. The TANDEM X 90m had the same resolution but performed poorer in positional fitness. The study found that digital elevation models have different resolutions and accuracy levels. Tandem-X90m has a resolution of up to 3 meters, while Aster and SRTM have 30 meters. GPS-based field digital terrain models provide higher accuracy, while Tandem-X90m has a 10 cm accuracy. The models cover a limited area, making them suitable for high-resolution elevation data. The data collection methods used by the models, such as SAR sensors, also affect their accuracy and resolution. Based on the above comparative analysis, it can be recommended that the GPS-based field digital terrain model is suitable for high-accuracy and high-resolution elevation data in a limited area. Tandem-X90m is suitable for high-resolution elevation data in a limited area but is expensive. Aster and SRTM are suitable for global-scale studies but have lower accuracy and resolution.

Not another hillshade: alternatives which improve visualizations of bathymetric data

Increasing awareness of the importance of effective communication of scientific results and concepts, and the need for more accurate mapping and increased feature visibility led to the development of novel approaches to visualization of high-resolution elevation data. While new approaches have routinely been adopted for land elevation data, this does not seem to be the case for the offshore and submerged terrestrial realms. We test the suitability of algorithms provided by the freely-available and user-friendly Relief Visualization Toolbox (RVT) software package for visualizing bathymetric data. We examine the algorithms optimal for visualizing the general bathymetry of a study area, as well as for highlighting specific morphological shapes that are common on the sea-, lake- and riverbed. We show that these algorithms surpass the more conventional analytical hillshading in providing visualizations of bathymetric data richer in details, and foremost, providing a better overview of the morphological features of the studied areas. We demonstrate that the algorithms are efficient regardless of the source data type, depth range, resolution, geographic, and geological setting. The summary of our results and observations can serve as a reference for future users of RVT for displaying bathymetric data.

Telescopic Megafans on the High Plains, USA Were Signal Buffers in a Major Source-To-Sink System

Sediment routing systems transport sediment and environmental signals inefficiently. The storage and recycling of sediment buffers the responses of sedimentary systems to tectonic, climatic, and geomorphic changes. Long-term ( >106 a.) storage may occur in megafans—large, low-relief, hemiconical fluvial deposystems—but the behavior of these systems over such timescales is unclear. We examine late Neogene megafan deposits on the High Plains, USA that are stored in the catchment of the continental-scale Rocky Mountain-Gulf of Mexico source-to-sink system. Using high-resolution elevation data, we map numerous fluvial ridges (inverted channel relics) that can be differentiated into five, chronologically distinct groups. The oldest four groups comprise radial arrays with multiple channel divergences (avulsion nodes). The inferred fan apices and longitudinal intersection points are offset successively downgradient, indicating that fanhead entrenchment and fan-lobe deposition were approximately contemporaneous and strongly suggesting a telescopic morphology. The youngest group of channels, also the lowest in elevation, is confined to terraces along the modern valley of the South Platte River. We interpret this group as direct evidence for the abandonment of the megafan and the incision of the present valley. Uplift was the chief driving mechanism for early telescoping, but channel widening and uniform downcutting in the younger groups suggest that change in stream power was the primary driver of later telescoping and incision. The storage of sediment in the megafan effectively decoupled sources from downstream sinks. Some of this sediment was recycled during entrenchment, but much of it remains in storage as the Ogallala Group and Broadwater Formation. Emplacement of telescopic megafans should be considered as a long-term ( ≥106 years) buffer in other modern and ancient sediment routing systems.

Unveiling spatial variability within the Dotson Melt Channel through high-resolution basal melt rates from the Reference Elevation Model of Antarctica

Abstract. The intrusion of Circumpolar Deep Water in the Amundsen and Bellingshausen Sea embayments of Antarctica causes ice shelves in the region to melt from below, potentially putting their stability at risk. Earlier studies have shown how digital elevation models can be used to obtain ice shelf basal melt rates at a high spatial resolution. However, there has been limited availability of high-resolution elevation data, a gap the Reference Elevation Model of Antarctica (REMA) has filled. In this study we use a novel combination of REMA and CryoSat-2 elevation data to obtain high-resolution basal melt rates of the Dotson Ice Shelf in a Lagrangian framework, at a 50 m spatial posting on a 3-yearly temporal resolution. We present a novel method: Basal melt rates Using REMA and Google Earth Engine (BURGEE). The high resolution of BURGEE is supported through a sensitivity study of the Lagrangian displacement. The high-resolution basal melt rates show a good agreement with an earlier basal melt product based on CryoSat-2. Both products show a wide melt channel extending from the grounding line to the ice front, but our high-resolution product indicates that the pathway and spatial variability of this channel is influenced by a pinning point on the ice shelf. This result emphasizes the importance of high-resolution basal melt rates to expand our understanding of channel formation and melt patterns. BURGEE can be expanded to a pan-Antarctic study of high-resolution basal melt rates. This will provide a better picture of the (in)stability of Antarctic ice shelves.

The INOVMineral Project’s Contribution to Mineral Exploration—A WebGIS Integration and Visualization of Spectral and Geophysical Properties of the Aldeia LCT Pegmatite Spodumene Deposit

Due to the current energetic transition, new geological exploration technologies are needed to discover mineral deposits containing critical materials such as lithium (Li). The vast majority of European Li deposits are related to Li–Cs–Ta (LCT) pegmatites. A review of the literature indicates that conventional exploration campaigns are dominated by geochemical surveys and related exploration tools. However, other exploration techniques must be evaluated, namely, remote sensing (RS) and geophysics. This work presents the results of the INOVMINERAL4.0 project obtained through alternative approaches to traditional geochemistry that were gathered and integrated into a webGIS application. The specific objectives were to: (i) assess the potential of high-resolution elevation data; (ii) evaluate geophysical methods, particularly radiometry; (iii) establish a methodology for spectral data acquisition and build a spectral library; (iv) compare obtained spectra with Landsat 9 data for pegmatite identification; and (v) implement a user-friendly webGIS platform for data integration and visualization. Radiometric data acquisition using geophysical techniques effectively discriminated pegmatites from host rocks. The developed spectral library provides valuable insights for space-based exploration. Landsat 9 data accurately identified known LCT pegmatite targets compared with Landsat 8. The user-friendly webGIS platform facilitates data integration, visualization, and sharing, supporting potential users in similar exploration approaches.

Automatically calculating the apparent depths of pits using the Pit Topography from Shadows (PITS) tool

AbstractPits, or pit craters, are near-circular depressions found in planetary surfaces, which are generally formed through gravitational collapse. Pits will be primary targets for future space exploration and habitability for their presence on most rocky Solar System surfaces and their potential to be entrances to sub-surface cavities. This is particularly true on Mars, where caves have been simulated to harbour stable reserves of ice water across much of the surface. Caves can also provide natural shelter from the high radiation dosages experienced at the surface. Since pits are rarely found to have corresponding high-resolution elevation data, tools are required for approximating their depths in order to find those which are the ideal candidates for follow-up remote investigation and future exploration. The Pit Topography from Shadows (PITS) tool has been developed to automatically calculate the apparent depth of a pit (h) by measuring the width of its shadow as it appears in satellite imagery. The tool requires just one cropped single- or multiband image of a pit to calculate a profile of h along the length of the shadow, thus allowing for depth calculation where altimetry or stereo image data is not available. We also present a method for correcting shadow width measurements made in non-nadir observations for all possible values of emission and solar/satellite azimuth angles. Shadows are extracted using image segmentation in the form of k-means clustering and silhouette analysis. Across 19 shadow-labelled Mars Reconnaissance Orbiter red-band HiRISE images of atypical pit craters (APCs) from the Mars global cave candidate catalogue (MGC3), PITS detected 99.6 per cent of all shadow pixels (with 94.8 per cent of all detections being true shadow pixels). Following this testing, PITS has been applied to 123 red-band HiRISE images containing 88 APCs, which revealed an improvement in the variation of the calculated h due to emission angle correction, and also found 10 APCs that could be good candidates for cave entrances on Mars due to their h profiles.

SCALING-UP DEEP LEARNING PREDICTIONS OF HYDROGRAPHY FROM IFSAR DATA IN ALASKA

Abstract. The United States National Hydrography Dataset (NHD) is a database of vector features representing the surface water features for the country. The NHD was originally compiled from hydrographic content on U.S. Geological Survey topographic maps but is being updated with higher quality feature representations through flow-routing techniques that derive hydrography from high-resolution elevation data. However, deriving hydrography through flow-routing methods is a complex process that needs to be tailored to different geographic conditions, which can lead to varying solutions. To address this problem, this paper evaluates automated deep learning and its transferability to extract hydrography from interferometric synthetic aperture radar (IfSAR) elevation data spanning a range of geographic conditions in Alaska.

Intersecting near-real time fluvial and pluvial inundation estimates with sociodemographic vulnerability to quantify a household flood impact index

Abstract. Increased interest in combining compound flood hazards and social vulnerability has driven recent advances in flood impact mapping. However, current methods to estimate event-specific compound flooding at the household level require high-performance computing resources frequently not available to local stakeholders. Government and non-governmental agencies currently lack the methods to repeatedly and rapidly create flood impact maps that incorporate the local variability in both hazards and social vulnerability. We address this gap by developing a methodology to estimate a flood impact index at the household level in near-real time, utilizing high-resolution elevation data to approximate event-specific inundation from both pluvial and fluvial sources in conjunction with a social vulnerability index. Our analysis uses the 2015 Memorial Day flood in Austin, Texas, as a case study and proof of concept for our methodology. We show that 37 % of the census block groups in the study area experience flooding from only pluvial sources and are not identified in local or national flood hazard maps as being at risk. Furthermore, averaging hazard estimates to cartographic boundaries masks household variability, with 60 % of the census block groups in the study area having a coefficient of variation around the mean flood depth exceeding 50 %. Comparing our pluvial flooding estimates to a 2D physics-based model, we classify household impact accurately for 92 % of households. Our methodology can be used as a tool to create household compound flood impact maps to provide computationally efficient information to local stakeholders.

Comparative analysis of freely available digital elevation models for applications in multi-criteria environmental modeling over data limited regions

Remotely sensed elevation data obtained from high-resolution Digital Elevation Models (DEMs) is one of the main sources of data required for environmental modeling and remediation especially when it has to do with identification of erosion sites and flood-prone areas. The focus of this study is to evaluate four recently improved and freely available high-resolution elevation data obtained from the Advanced Land Observing Satellite World 3D Digital Surface Model version 2.1 (ALOS W3D30), TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X 90), Multi-Error-Removed Improved-Terrain (MERIT) DEM and EarthEnv-DEM90 in order to determine the most suitable DEM that could be used as an input data in a multi-criteria environmental modeling to identify erosion sites and flood-prone areas in data limited regions such as Southeastern Nigeria. Intensive performance evaluation of these four DEMs was rigorously carried out using statistical and surface analyses tools (Root-Mean-Square Error (RMSE), Land Use/Land Cover, slope, and contour maps). The obtained RMSE range from 5.49 m to 19.79 m depending on the surface of contact. Slope values range from 0.00 to 89.49° depicting the complexity and ruggedness of the terrain. Analyses of the obtained RMSE showed that EarthEnv-DEM90 is more accurate (in terms of RMSE value) than the other three DEMs but further terrain analyses using slope and contour maps generated from each of the DEMs revealed that ALOS W3D30 represent the topography of the terrain (terrain variation) better than the other three DEMs. This study demonstrates the importance of carrying out rigorous and intensive performance evaluation of DEMs using many terrain parameters or attributes in order to avoid large errors that may be contributed by the use of a DEM in applications such as environmental modeling and remediation.

Resilience of U.S. coastal wetlands to accelerating sea level rise

Coastal wetlands provide a wide array of ecosystem services, valued at trillions of dollars per year globally. Although accelerating sea level rise (SLR) poses the long-term threat of inundation to coastal areas, wetlands may be sustained in two ways: by positive net surface-elevation change (SEC) from sediment and organic matter buildup and by accumulation, or horizontal migration into refugia—low-lying, undeveloped upland areas that become inundated. Using a simple model together with high-resolution elevation data, we provide, across the contiguous United States, analysis of the local effects of SLR, maximum SEC rates, and coastal development on the long-term resilience of coastal wetlands. We find that protecting current refugia is a critical factor for retaining wetlands under accelerating SLR. If refugia are conserved under an optimistic scenario (a high universal maximum SEC rate of 8 mm/yr and low greenhouse gas emissions), wetlands may increase by 25.0% (29.4%–21.5%; 50th, 5th–95th percentiles of SLR) by the end of the century. However, if refugia are developed under a more pessimistic scenario (a moderate universal maximum SEC rate of 3 mm/yr, high greenhouse gas emissions, and projections incorporating high ice-sheet contributions to SLR), wetlands may decrease by −97.0% (−82.3%–99.9%). These median changes in wetland area could result in an annual gain of ∼$222 billion compared to an annual loss of ∼$732 billion in ecosystem services in the US alone. Focusing on key management options for sustaining wetlands, we highlight areas at risk of losing wetlands and identify the benefits possible from conserving refugia or managing SEC rates.

Recent contrasting behaviour of mountain glaciers across the European High Arctic revealed by ArcticDEM data

Abstract. Small land-terminating mountain glaciers are a widespread and important element of Arctic ecosystems, influencing local hydrology, microclimate, and ecology. Due to their relatively small ice volumes, this class of ice mass is particularly sensitive to the significant ongoing climate warming in the European sector of the Arctic, i.e. in the Barents Sea area. Archipelagos surrounding the Barents Sea, i.e. Svalbard (SV), Novaya Zemlya (NZ), and Franz Josef Land (FJ), host numerous populations of mountain glaciers, but their response to recent strong warming remains understudied in most locations. This paper aims to obtain a snapshot of their state by utilizing high-resolution elevation data (ArcticDEM) to investigate the recent (ca. 2011–2017) elevation and volume changes of 382 small glaciers across SV, NZ, and FJ. The study concludes that many mountain glacier sites across the Barents Sea have been in a critical imbalance with the recent climate and might melt away within the coming several decades. However, deviations from the general trend exist; e.g. a cluster of small glaciers in north SV has been experiencing thickening. The findings reveal that near-stagnant glaciers might exhibit contrasting behaviours (fast thinning vs. thickening) over relatively short distances, which is a challenge for glacier mass balance models but also an opportunity to test their reliability.

Use of Cartosat-1 elevation data for local-scale terrain studies in India: a case study

ABSTRACT The Cartosat-1 satellite provides relatively high-resolution elevation data, which is publicly available for free, for most parts of India. Yet, published works applying such data in the local geographical context are few. This paper illustrates the application of CartoDEM, an elevation dataset based on Cartosat-1, to develop a coarse geographic narrative of the terrain at the tehsil level. Kotra tehsil in Udaipur district of Rajasthan, India, was used as a case study. It was found that the data, along with the calibration and analysis methods used here, allows a fairly well-resolved understanding of the terrain of the tehsil, including identification of major landforms and quantification of terrain metrics such as elevation and roughness. The free and easy availability of such data shows offers the potential for such studies to be performed for any local area for which CartoDEM or similar data exists.

Issues in Replication and Stability of Least-cost Path Calculations

An important and frequently used tool in archaeological spatial analysis is least-cost path (LCP) analysis to compute routes connecting a set of targets. The outcome depends on the cost model chosen and the topographic data used. A slope-dependent cost model requires a digital elevation model (DEM) that should reflect the landscape in the past. It is often impossible to reconstruct the past terrain, and modern high-resolution elevation data results in problematic storage requirements and computation times. This article presents a case study that explores issues in replication and stability of LCP calculations for pairs of targets that are close to known old trade routes. A large number of cost models is tested based on two topographic data sets, including DEMs of two different resolutions (25 m and 50 m). The cost models use six different slope-dependent cost functions suggested by various authors for pedestrian movement. Moreover, a slope-dependent cost function is applied that results in LCPs including hairpin curves if the slope exceeds a predefined critical value. It is shown that the best-performing LCP sets for the two topographic data sets are closely related but not identical. Moreover, reasons for the failure of LCP reconstructions for some old route sections are discussed.

A REVIEW OF UAV PHOTOGRAMMETRY APPLICATION IN ASSESSING SURFACE ELEVATION CHANGES

Assessing large scale topography and surface elevation changes usually requires temporal remote sensing and aerial photogrammetrically-based data. Usually, very high resolution (VHR) elevation data, for instance, digital surface models (DSM) from light detection and ranging (LiDAR) and unmanned aerial vehicles (UAV), are used to visualise the changes in surface elevation. Therefore, this study attempts to review different case studies of assessing topography and surface elevation changes, specifically on geomorphological change detection (GCD) based on UAV photogrammetry data. The case study areas at Five Finger Strand (NW Ireland), Rosolina Mare (Italy) and Elbow River, Alberta (Canada) were discussed. This paper reviews the theory of UAV, surface elevation changes, and the summary of a related case study of surface elevation changes. The finding can provide a deep understanding of UAV applications in assessing surface elevation changes using UAV photogrammetry data.

The late Holocene Nealtican lava-flow field, Popocatépetl volcano, central Mexico: Emplacement dynamics and future hazards

Abstract Popocatépetl, one of the most hazardous volcanoes worldwide, poses significant threats for nearby populations in central Mexico. Therefore, it is important to reconstruct its eruptive history, including estimates of lava-flow emplacement times and their rheological properties. These studies define possible future eruptive scenarios and are necessary to mitigate the risk. Stratigraphic studies of the cal 350–50 B.C. Lorenzo Plinian pumice sequence indicate that effusive activity (Nealtican lava-flow field) occurred shortly after explosive activity, reflecting drastic changes in the eruptive dynamics. It was likely due to the efficient degassing of the magma during the Plinian phase and a decrease of magma ascent and decompression rates. Magma mixing, fractional crystallization, and a minor crust assimilation are the processes controlling the differentiation of the Nealtican lavas. We used lava chemical and mineralogical composition to estimate lava-flow viscosities, and used high-resolution elevation data to estimate emplacement times. Results indicate that lava viscosities of andesites and dacites ranged from 109 to 1012 Pa·s and emplacement durations were between ~1 and ~29 years, depending on the flow unit and morphological method employed. Considering the entire volume of emitted lava (4.2 km3) and a mean output rate of ~1 m3/s to ~15 m3/s, we estimated that the effusive phase that produced the Nealtican lava-flow field may have lasted ~35 years. This eruption had a considerable impact on pre-Hispanic settlements around the volcano, whose population exodus and relocation probably contributed to the rise of important cities in central Mexico, such as Teotihuacán and Cholula.

The Accuracy and Consistency of 3D Elevation Program Data: A Systematic Analysis

The 3D Elevation Program (3DEP) has created partnership opportunities to increase the collection of high-resolution elevation data across the United States, eventually leading to complete coverage of high-resolution, three-dimensional (3D) information from light detection and ranging (lidar) data across the entire country (interferometric synthetic aperture radar in Alaska). While 3DEP data are collected at different times and by varying producers, the assumption is that the use of the 3DEP Lidar Base Specification will provide standardized and consistent data across data collections. Another assumption is that the integration of lidar data into the seamless digital elevation models increases the accuracy of the derived products. This study tests these assumptions and updates some of the accuracy metrics that were done on previous versions of the standard products.

Applying Airborne LiDAR to Map Salt Marsh Inland Boundaries

The determination of rates and stocks of carbon storage in salt marshes, as well as their protection, require that we know where they and their boundaries are. Marsh boundaries are conventionally mapped through recognition of plant communities using aerial photography or satellite imagery. We examined the possibility of substituting the use of 1 m resolution LiDAR-derived digital elevation models (DEMs) and tidal elevations to establish salt marsh upper boundaries on the New Brunswick coasts of the Gulf of St. Lawrence and the Bay of Fundy, testing this method at tidal ranges from ≤2 to ≥4 m. LiDAR-mapped marsh boundaries were verified with high spatial resolution satellite imagery and a subset through field mapping of the upland marsh edge based upon vegetation and soil characteristics, recording the edge location and elevation with a Differential Geographic Positioning System. The results show that the use of high-resolution LiDAR and tidal elevation data can successfully map the upper boundary of salt marshes without the need to first map plant species. The marsh map area resulting from our mapping was ~30% lower than that in the province’s aerial-photograph-based maps. However, the difference was not primarily due to the location of the upper marsh boundaries but more so because of the exclusion of mudflats and large creeks (features that are not valued as carbon sinks) using the LiDAR method that are often mapped as marsh areas in the provincial maps. Despite some minor limitations, the development of DEMs derived from LiDAR can be applied to update and correct existing salt marsh maps along extensive sections of coastlines in less time than required to manually trace from imagery. This is vital information for governments and NGOs seeking to conserve these environments, as accurate mapping of the location and area of these ecosystems is a necessary basis for conservation prioritization indices.

Quantifying Slopes as a Driver of Forest to Marsh Conversion Using Geospatial Techniques: Application to Chesapeake Bay Coastal-Plain, United States

Coastal salt marshes, which provide valuable ecosystem services such as flood mitigation and carbon sequestration, are threatened by rising sea level. In response, these ecosystems migrate landward, converting available upland into salt marsh. In the coastal-plain surrounding Chesapeake Bay, United States, conversion of coastal forest to salt marsh is well-documented and may offset salt marsh loss due to sea level rise, sediment deficits, and wave erosion. Land slope at the marsh-forest boundary is an important factor determining migration likelihood, however, the standard method of using field measurements to assess slope across the marsh-forest boundary is impractical on the scale of an estuary. Therefore, we developed a general slope quantification method that uses high resolution elevation data and a repurposed shoreline analysis tool to determine slope along the marsh-forest boundary for the entire Chesapeake Bay coastal-plain and find that less than 3% of transects have a slope value less than 1%; these low slope environments offer more favorable conditions for forest to marsh conversion. Then, we combine the bay-wide slope and elevation data with inundation modeling from Hurricane Isabel to determine likelihood of coastal forest conversion to salt marsh. This method can be applied to local and estuary-scale research to support management decisions regarding which upland forested areas are more critical to preserve as available space for marsh migration.