Fine-resolution Digital Elevation Model Research Articles

Geographically Comprehensive Assessment of Salt-Meadow Vegetation-Elevation Relations Using LiDAR

Salt meadows are thought to be vulnerable to habitat loss under future sea-level rise (SLR) due to inundation and compression of coastal environments (coastal squeezing). The extent of this threat is poorly understood due to the lack of geographically comprehensive impact assessments. Here, we linked vegetation data for Danish salt meadows to novel very fine-resolution digital elevation models. We developed statistical models relating plant species richness and average salt tolerance to elevation at different spatial scales. The best models were used to quantify potential impacts of SLR on Danish salt-meadow vegetation under five potential 21st-century scenarios. Overall, species richness increased with elevation (average r2 = 0.21), while average salt tolerance decreased (average r2 = 0.45). Fine resolution (≤10-m) topography was required to fully represent vegetation-elevation relationships. At >50-m resolutions only feeble links were found. Under the worst scenarios 67–74% of the Danish salt-meadow area was projected to be lost. Notably, the relatively species-rich upper meadows were predicted to shrink drastically. If realized, these impacts may have severe consequences for salt-meadow biodiversity. We note that sedimentation, not accounted for here, may allow some salt meadows to partly keep up with SLR but the extent to which this will occur and where is uncertain.

Extracting topographic characteristics of landforms typical of Canadian agricultural landscapes for agri-environmental modeling. I. Methodology

Li, S., Lobb, D. A., McConkey, B. G., MacMillan, R. A., Moulin, A. and Fraser, W. R. 2011. Extracting topographic characteristics of landforms typical of Canadian agricultural landscapes for agri-environmental modeling. I. Methodology. Can. J. Soil Sci. 91: 251–266. Soil and topographic information are key inputs for many agri-environmental models and there are linkages between soil and topography at the field scale. A major source of soil data is soil databases established based on field soil survey. Although both soil and topographic information are recorded in field soil surveys, the nominal nature of the topographic data has limited their use in agri-environmental models. In this study, we developed a methodology to extract various topographic derivatives and to classify the landscape into landform elements with distinctive topographic characteristics based on detailed analyses of fine resolution digital elevation models. Data obtained from these analyses were used to calculate a representative two-dimensional hillslope of five segments, each with a defined length and slope gradient. A set of modal hillslopes was developed to describe topographic variability. Additional topographic parameters, ratios and indices were calculated to reflect different aspects of topographic characteristics and also to build connections between different agri-environmental models. In particular, a topographic complexity index was developed as a quantitative measure of the degrees of divergence and convergence. This paper describes the methodology using one site as an example. Application of this methodology to other landforms in agricultural land of Canada is reported in a companion paper.

Evaluation of digital elevation models for delineation of hydrological response units in a Himalayan watershed

This study reports results from evaluation of the quality of digital elevation model (DEM) from four sources viz. topographic map (1:50,000), Shuttle Radar Topographic Mission (SRTM) (90 m), optical stereo pair from ASTER (15 m) and CARTOSAT (2.5 m) and their use in derivation of hydrological response units (HRUs) in Sitla Rao watershed (North India). The HRUs were derived using water storage capacity and slope to produce surface runoff zones. The DEMs were evaluated on elevation accuracy and representation of morphometric features. The DEM derived from optical stereo pairs (ASTER and CARTOSAT) provided higher vertical accuracies than the SRTM and topographic map-based DEM. The SRTM with a coarse resolution of 90 m provided vertical accuracy but better morphometry compared to topographic map. The HRU maps derived from the fine resolution DEM (ASTER and CARTOSAT) were more detailed but did not provide much advantage for hydrological studies at the scale of Sitla Rao watershed (5800 ha).

다방향 흐름 분배와 실시간 보정 알고리듬을 이용한 분포형 강우-유출 모형 개발(I) - 이론 -

본 연구에서는 다방향 흐름 분배 알고리듬과 실시간 보정 알고리듬을 개발하여 분포형 강우-유출 모형에 적용하였다. 개발된 알고리듬의 적용과 분포형 모형 적용상의 약점인 계산시간 개선을 위해 비교적 간단한 수문과정 지배 방정식들을 이용하여 분포형 강우-유출 모형을 작성하였다. DEM(Digital Elevation Model)를 이용하여 공간해상도 변화에 따른 지형정보와 흐름정보의 변동성을 파악하였다. 모의수행 전처리 과정으로 가용한 고해상도 DEM 자료를 사용하여 공간해상도 변화에 따른 흐름정보의 손실을 최소화하고 상세흐름정보를 저해상도 흐름정보에 반영시키는 다방향 흐름분배 알고리듬을 개발하였다. 또한 실시간으로 유역상태량을 보정하는 실시간 보정 알고리듬을 개발하다. 개발된 모형은 저해상도 모의에서 유출 과정의 실제적 거동 정보를 유지할 수 있다. 그러므로 예측 정확도 향상 및 계산시간의 개선이 기대된다. In this study, a distributed rainfall-runoff model is developed using a multi-directional flow allocation algorithm and the real-time runoff updating algorithm. The developed model consists of relatively simple governing equations of hydrologic processes in order to apply developed algorithms and to enhance the efficiency of computational time which is drawback of distributed model application. The variability of topographic characteristics and flow direction according to various spatial resolution were analyzed using DEM(Digital Elevation Model) data. As a preliminary process using fine resolution DEM data, a multi-directional flow allocation algorithm was developed to maintain detail flow information in distributed rainfall-runoff simulation which has strong advantage in computation efficiency and accuracy. Also, a real-time updating algorithm was developed to update current watershed condition. The developed model is able to hold the information of actual behavior of runoff process in low resolution simulation. Therefore it is expected the improvement of forecasting accuracy and computational efficiency.

Effects of DEM Source and Resolution on WEPP Hydrologic and Erosion Simulation: A Case Study of Two Forest Watersheds in Northern Idaho

The recent modification of the Water Erosion Prediction Project (WEPP) model has improved its applicability to hydrology and erosion modeling in forest watersheds. To generate reliable topographic and hydrologic inputs for the WEPP model, carefully selecting digital elevation models (DEMs) with appropriate resolution and accuracy is essential because topography is a major factor controlling water erosion. Light detection and ranging (LIDAR) provides an alternative technology to photogrammetry for generating fine-resolution and high-quality DEMs. In this study, WEPP (v2006.201) was applied to hydrological and erosion simulation for two small forest watersheds in northern Idaho. Data on stream flow and total suspended solids (TSS) in these watersheds were collected and processed. A total of six DEMs from the National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and LIDAR at three resolutions (30 m, 10 m, and 4 m) were obtained and used to calculate topographic parameters as inputs to the WEPP model. WEPP-simulated hydrologic and erosion results using the six DEMs were contrasted and then compared with field observations. For the study watersheds, DEMs with different resolutions and sources generated varied topographic and hydrologic attributes, which in turn led to significantly different erosion simulations. WEPP v2006.201 using the 10 m LIDAR DEM (vs. using other DEMs) produced a total amount of as well as seasonal patterns of watershed discharge and sediment yield that were closest to field observations.

Towards accurate determination of surface height using modern geoinformatic methods: possibilities and limitations

Over recent decades several modern geoinformatic height-finding methods have emerged, including global positioning system (GPS), interferometric radar, and airborne laser scanner (ALS) or lidar. In conjunction with the conventional survey and photogrammetric method, they have found wide applications that demand varying levels of accuracy. In this paper, the principles of each method are briefly summarized. The discussion then concentrates on the accuracy level achievable with each method. The factors that affect the accuracy, wherever possible, are comprehensively evaluated. This review has revealed that the highest accuracy achievable is still with the levelling method, followed by the photogrammetric method. This situation is likely to change in light of real-time kinematic GPS coupled with ALS. In contrast to the imaging methods that are suited to obtain highly accurate, fine-resolution digital elevation models (DEMs) at a local scale, GPS is the most efficient at obtaining heights at spots or along lines accurately. ALS is the only method applicable to acquisition of subsurface heights in vegetated areas. These airborne methods are complementary to their space-borne counterparts, such as Shuttle Radar Topographic Mapping and Shuttle Laser Altimeter, both being ideal in obtaining DEMs at the regional and global scales. The synergistic use of GPS with lidar offers the best hope in obtaining cm-level accuracies essential for monitoring ground subsidence and tectonic uplift. Height measurements accurate to subcentimetres needed for national levelling surveys are possible only after the tropospheric path delay is externally calibrated using Raman lidar data during GPS data analysis.

Mapping contemporary magnetic mineral concentrations in peat soils using fine-resolution digital terrain data

Small-scale spatial variability in the concentration of magnetic minerals in peat soils has been explained by differences in the deposition and interception of magnetic minerals at the soil surface and the retention of magnetic minerals within the soil. Each of these processes is controlled by topographic conditions. Recent advances in the field of digital terrain analysis and the availability of fine-resolution digital elevation models means that the relationship between the concentration of magnetic minerals in peat soils and topography can be explored using quantitative methods. Alport Moor is an ombrotrophic peat moorland in the Peak District National Park, UK. 24 peat cores were collected from Alport Moor covering an area of 0.1 km 2. Each core was analysed for mass specific magnetic susceptibility. Three topographic attributes (topographic wetness index, difference from mean elevation and elevation as a percentage of elevation range) were extracted from a high resolution LiDAR digital elevation model of Alport Moor. Stepwise multiple regression analyses show that topographic wetness index and difference from mean elevation are excellent predictors of variation in peak magnetic susceptibility and total magnetic susceptibility inventories for peat soils of this upland area. The results demonstrate that the contemporary concentration of magnetic minerals in the peat soils of Alport Moor is controlled by micro- and local-scale variations in water table position. The results also suggest that the contemporary level of magnetic minerals in the peat soils of Alport Moor is controlled by the retention of such particles in the soil environment. Differences in the deposition and interception of magnetic minerals play a secondary role in controlling magnetic mineral concentrations. Spatial maps of magnetic susceptibility reveal that peat soils adjacent to gully edges at Alport Moor have the highest concentration of magnetic minerals. The mapping approach used in this study could be applied to other peatland environments.

Improvements in large‐scale drainage networks derived from digital elevation models

This paper presents an improved algorithm for deriving drainage networks for coarse‐gridded distributed hydrological models based on relatively fine resolution digital elevation models. The proposed algorithm aims to reproduce actual drainage networks more closely when applied in regions with meandering rivers running in parallel and for cell sizes of the order of 10 kilometers. To achieve this goal, the COTAT algorithm of Reed (2003) was improved, introducing another parameter related to the minimum upstream flow path into the cell besides the area threshold. The proposed algorithm was tested by applying it to the catchments of the rivers Tapajos (530,000 km2) and Grande (145,000 km2) in South America. Results show that drainage networks are generally improved by the proposed algorithm, needing only minor manual corrections.

Automated analysis and classification of landforms using high-resolution digital elevation data: applications and issues

This paper describes recent efforts to use fine spatial resolution digital elevation model (DEM) data, including, but not limited to, lidar DEM data, for automated analysis and classification of geomorphic and hydrologic terrain features. The example applications presented are based on a 3-m horizontal resolution lidar DEM for a 6 km by 8 km agricultural watershed in Alberta and on a similar 5-m horizontal resolution conventional DEM for two forested areas of 14 km by 12 km in the Cariboo Forest Region of British Columbia. The applications illustrate efforts to produce meaningful classifications of ecological and landform spatial entities and to automatically extract hydrological spatial entities required for input into the WEPP water erosion model. Fine spatial resolution DEMs present some unique problems for which solutions are still lacking or are insufficient. Errors of apparently minor extent or degree can seriously affect some forms of analysis, especially analyses that involve hydrological calculations of paths of surface water flow. A need is recognized for improved methods and tools for interpolating and editing fine spatial resolution DEMs to remove or reduce localized errors.

Comparison between computed balance velocities and GPS measurements in the Lambert Glacier basin, East Antarctica

AbstractComparisons between computed balance velocities, obtained from two different computing schemes, and global positioning system (GPS)-derived velocities were made in the Lambert Glacier basin region, East Antarctica. The two computing schemes used for the balance-velocity computations (a flowline (FL) scheme (Remy and Minster, 1993) and a finite-difference (BW) scheme (Budd and Warner, 1996; Fricker and others, 2000)) were first evaluated and compared. One of the key issues studied was the spatial resolution of the digital elevation model (DEM), representing the surface topography of the ice sheet, and the sensitivity of the balance velocities to the length of smoothing applied to the DEM. Comparison with the GPS velocities validated the two schemes to within 5–25% but showed the high sensitivity of the flowline method to the length scale of the smoothing. The finite-difference scheme was found to be robust to the chosen smoothing scale, but the balance-velocity values increased when a finer-resolution DEM was used. Both FL and BW computing schemes tended to overestimate the balance velocities in comparison with the GPS values; some of this discrepancy can be attributed to ice-sheet sliding.

Aggregation of digital terrain data using a modified fractal interpolation scheme

A modified fractal interpolation scheme that can be used to produce consistent digital terrain models at different spatial resolutions is introduced in this paper. The focus of the paper is on the aggregation of fine resolution terrain data to coarser scales (up-scaling), although the algorithm is equally useful for disaggregation purposes (down-scaling). Applications with digital elevation models (DEMs) for California and for Pennsylvania are used to illustrate the methodology. Comparisons with alternative approaches such as sampling of fine resolution DEMs, the use of mean and envelope orography representations, and the Cressman-type objective analysis are presented. The modified fractal interpolation scheme preserves well both the spatial structure of the elevations and orographic gradients and performed consistently better than other algorithms, especially for high level aggregation (coarse discretization).