Digital Elevation Model Datasets Research Articles

Simulating evolution of a loess gully head with cellular automata

This paper presents a new method for simulating the evolution of a gully head in a loess catchment with cellular automata (CA) based on the Fisher discriminant. The experimental site is an indoor loess catchment that was constructed in a fixed-intensity rainfall erosion test facility. Nine high-resolution digital elevation model (DEM) data sets were gathered by close range photogrammetry during different phases of the experiment. To simulate the evolution of the catchment gully head, we assumed the following. First, the 5th and 6th DEM data sets were used as a data source for acquiring the location of the catchment gully head and for obtaining spatial variables with GIS spatial analysis tools. Second, the Fisher discriminant was used to calculate the weight of the spatial variables to determine the transition probabilities. Third, CA model was structured to simulate the evolution of the gully head by iterative looping. The status of the cell in the CA models was dynamically updated at the end of each loop to obtain realistic results. Finally, the nearest neighbor, G-function, K-function, Moran’s I and fractal indexes were used to evaluate the model results. Overall, the CA model can be used to simulate the evolution of a loess gully head. The experiment demonstrated the advantages of the CA model which can simulate the dynamic evolution of gully head evolution in a catchment.

Google Earth's derived digital elevation model: A comparative assessment with Aster and SRTM data

This paper presents a statistical analysis showing additional evidence that Digital Elevation Model (DEM) derived from Google Earth is commendable and has a good correlation with ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) and SRTM (Shuttle Radar Topography Mission) elevation data. The accuracy of DEM elevation points from Google Earth was compared against that of DEMs from ASTER and SRTM for flat, hilly and mountainous sections of a pre-selected rural watershed. For each section, a total of 5,000 DEM elevation points were extracted as samples from each type of DEM data. The DEM data from Google Earth and SRTM for flat and hilly sections are strongly correlated with the R2 of 0.791 and 0.891 respectively. Even stronger correlation is shown for the mountainous section where the R2 values between Google Earth's DEM and ASTER's and between Google Earth's DEM and SRTM's DEMs are respectively 0.917 and 0.865. Further accuracy testing was carried out by utilising the DEM dataset to delineate Muar River's watershed boundary using ArcSWAT2009, a hydrological modelling software. The result shows that the percentage differences of the watershed size delineated from Google Earth's DEM compared to those derived from Department of Irrigation and Drainage's data (using 20m-contour topographic map), ASTER and SRTM data are 9.6%, 10.6%, and 7.6% respectively. It is therefore justified to conclude that the DEM derived from Google Earth is relatively as acceptable as DEMs from other sources.

Effects of terrain-induced shade removal using global DEM data sets on land-cover classification

Free access to global data sets of satellite images and digital elevation models (DEMs) such as Aster Global DEM (GDEM) and Shuttle Radar Topography Mission (SRTM) digital topography are expected to contribute to various study areas that deal with land cover and land use. To assess the capabilities of these global DEM data sets and to provide guidelines for performing shade removal under various terrain and illumination conditions, we evaluated the results of shade removal using the Minnaert correction and C-correction. These corrections were applied, using the GDEM (versions 1 and 2), SRTM, and a DEM derived from a local map (local DEM), to 30 sample images from 20 scenes of 10 path-rows in global land survey (GLS) Landsat-TM/ETM+ images, in terms of statistical indices and the accuracy of land-cover discrimination. The analysis indicated that the results of shade removal depended mainly on the correlation between the cosine of the sunshine incidence angle (cos(i)) and the radiance before shade removal, except in some cases with inferior illumination conditions. Of the three global DEMs, GDEM version 2 had the highest performance in shade removal. However, this study also indicated that successful shade removal was only one of the several factors that increased the accuracy of land-cover classification. In practical applications, shade removal can be recommended only for images where the terrain shade obviously disturbs the original spectral reflection characteristics of each land-cover type and no significant dependence of the land-cover distribution on the slope aspect is assumed. In such cases, also global DEMs evaluated in this study can be used for shade removal.

A lossless DEM compression for fast retrieval method using fuzzy clustering and MANFIS neural network

In this paper, we propose an integrated approach between fuzzy C-means (FCM) and multi-active neuro fuzzy inference system (MANFIS) for the lossless DEM compression for fast retrieval (DCR) problem, aiming to compress digital elevation model (DEM) data with the priority of fast retrieval from the client machine over the Internet environment. Previous researches of this problem either used the float wavelet transforms integrated with the SPIHT coding or constructed a predictor model using statistical correlation of DEM data in local neighborhoods; thus giving large-sized compressed data and slow transferring time of data between the server and the client. Based on the observation that different non-linear transforms for predictive values in the sliding windows may increase the compression ratio, we herein present a novel approach for DCR problem and validated it experimentally on the benchmark DEM datasets. The comparative results show that our method produces better compression ratio than the relevant ones.

A practical method for SRTM DEM correction over vegetated mountain areas

Digital elevation models (DEMs) are essential to various applications in topography, geomorphology, hydrology, and ecology. The Shuttle Radar Topographic Mission (SRTM) DEM data set is one of the most complete and most widely used DEM data sets; it provides accurate information on elevations over bare land areas. However, the accuracy of SRTM data over vegetated mountain areas is relatively low as a result of the high relief and the penetration limitation of the C-band used for obtaining global DEM products. The objective of this study is to assess the performance of SRTM DEMs and correct them over vegetated mountain areas with small-footprint airborne Light Detection and Ranging (Lidar) data, which can develop elevation products and vegetation products [e.g., vegetation height, Leaf Area Index (LAI)] of high accuracy. The assessing results show that SRTM elevations are systematically higher than those of the actual land surfaces over vegetated mountain areas. The mean difference between SRTM DEM and Lidar DEM increases with vegetation height, whereas the standard deviation of the difference increases with slope. To improve the accuracy of SRTM DEM over vegetated mountain areas, a regression model between the SRTM elevation bias and vegetation height, LAI, and slope was developed based on one control site. Without changing any coefficients, this model was proved to be applicable in all the nine study sites, which have various topography and vegetation conditions. The mean bias of the corrected SRTM DEM at the nine study sites using this model (absolute value) is 89% smaller than that of the original SRTM DEM, and the standard deviation of the corrected SRTM elevation bias is 11% smaller.

중/도시규모 기상모델을 이용한 고층건물군이 연안도시기상장에 미치는 영향 수치모델링

Modeling the effects of high-rise buildings on thermo-dynamic conditions and meteorological fields over a coastal urban area was conducted using the modified meso-urban meteorological model (Urbanized MM5; uMM5) with the urban canopy parameterization (UCP) and the high-resolution inputs (urban morphology, land-use/land-cover sub-grid distribution, and high-quality digital elevation model data sets). Sensitivity simulations was performed during a typical sea-breeze episode (4~8 August 2006). Comparison between simulations with real urban morphology and changed urban morphology (i.e. high-rise buildings to low residential houses) showed that high-rise buildings could play an important role in urban heat island and land-sea breeze circulation. The major changes in urban meteorologic conditions are followings: significant increase in daytime temperature nearly by due to sensible heat flux emitted from high density residential houses, decrease in nighttime temperature nearly by because of the reduction in the storage heat flux emitted from high-rise buildings, and large increase in wind speed (maximum 2 m ) during the daytime due to lessen drag-force or increased gradient temperature over coastal area.

Sensitivity of Coastal Flood Risk Assessments to Digital Elevation Models

Most coastal flood risk studies make use of a Digital Elevation Model (DEM) in addition to a projected flood water level in order to estimate the flood inundation and associated damages to property and livelihoods. The resolution and accuracy of a DEM are critical in a flood risk assessment, as land elevation largely determines whether a location will be flooded or will remain dry during a flood event. Especially in low lying deltaic areas, the land elevation variation is usually in the order of only a few decimeters, and an offset of various decimeters in the elevation data has a significant impact on the accuracy of the risk assessment. Publicly available DEMs are often used in studies for coastal flood risk assessments. The accuracy of these datasets is relatively low, in the order of meters, and is especially low in comparison to the level of accuracy required for a flood risk assessment in a deltaic area. For a coastal zone area in Nigeria (Lagos State) an accurate LiDAR DEM dataset was adopted as ground truth concerning terrain elevation. In the case study, the LiDAR DEM was compared to various publicly available DEMs. The coastal flood risk assessment using various publicly available DEMs was compared to a flood risk assessment using LiDAR DEMs. It can be concluded that the publicly available DEMs do not meet the accuracy requirement of coastal flood risk assessments, especially in coastal and deltaic areas. For this particular case study, the publically available DEMs highly overestimated the land elevation Z-values and thereby underestimated the coastal flood risk for the Lagos State area. The findings are of interest when selecting data sets for coastal flood risk assessments in low-lying deltaic areas.

DEM Explorer: An online interoperable DEM data sharing and analysis system

Digital Elevation Model (DEM) data products are freely downloadable in tiled files from providers. But for most application needs, the area of interest does not exactly match the original spatial coverage of one DEM tile. After users obtain the files, they must mosaic, sub-set, and/or re-project them using geospatial software to generate the customized data that meet their requirements. It would be best if users could obtain the required DEM data directly. DEM Explorer is designed to share and explore the common DEM datasets in a publicly accessible online environment. It offers an intuitive and interoperable way to customize, download, visualize, and analyze DEM data in an Ajax-enabled Web interface. Via DEM Explorer, users are able to not only retrieve the original DEM files directly, but also obtain on-demand DEM data for any area of interest in a preferred format and projection. Deviations of terrain information are integrated as Web geoprocessing services in DEM Explorer to generate detailed terrain characteristics. DEM based hydrological models developed as Web services are aggregated to discover hydrological features. DEM Explorer has been adopted by the NASA Land Processes Distributed Active Archive Center to distribute the ASTER Global DEM to global users.

Risk of Inundation to Coastal Wetlands and Soil Organic Carbon and Organic Nitrogen Accounting in Louisiana, USA

Exceeding 1.2 million acres (4856 km(2)) since the 1930s, coastal wetland loss has been the most threatening environmental problem in Louisiana, United States. This study utilized high-resolution LiDAR (Light Detection and Ranging) and DEM (Digital Elevation Model) data sets to assess the risk of potential wetland loss due to future sea level rises, their spatial distribution, and the associated loss of soil organic carbon (SOC) and organic nitrogen (SON) estimated from the State Soil Geographic (STATSGO) Database and National Wetlands Inventory (NWI) digital data. Potential inundation areas were divided into five elevation scales: < 0 cm, 0-50 cm, 50-100 cm, 100-150 cm, and 150-200 cm above mean sea level. The study found that southeastern Louisiana on the Mississippi River Delta, specifically the Pontchartrain and Barataria Basins, are most vulnerable to sea-level rise induced inundation. Accordingly, approximately 42,264,600 t of SOC and 2,817,640 t of SON would be inundated by 2050 using an average wetland SOC density (203 t per hectare) for the inundation areas between 0 and 50 cm. The estimated annual SOC and SON loss from Louisiana's coast is 17% of annual organic carbon and 6-8% of annual organic nitrogen inputs from the Mississippi River.

Systematic morphometric characterization of volcanic edifices using digital elevation models

Quantitative characterization of the size and shape of volcanic edifices is an essential step towards the understanding of factors controlling volcano growth and morphology. The recent advent of digital elevation models (DEMs) with worldwide coverage offers the opportunity to systematically document the morphometry of all types of volcanoes using quantitative well-formalized methodologies. We present a methodology for the morphometric characterization of volcanic edifices. After reviewing previous studies on volcano morphometry and the various existing DEM sources, we describe an integrated procedure that uses a DEM and its derived products (slope, curvature) to extract a coherent set of morphometric parameters for a given volcanic edifice. Edifice boundaries are manually defined by searching for breaks in slope around the base. The parameters describe the overall size (basal and summit region area and widths, height, volume), planar shape (ellipticity and irregularity index of elevation contours), profile shape (height–width ratios) and slope of the edifice. Similar parameters for relatively large (depending on DEM spatial resolution) summit craters/calderas are also computed. Slope values and ellipticity and irregularity indexes are extracted for successive height intervals providing detailed information of volcano shape as a function of height. The number of secondary peaks is also estimated. The method is tested on thirteen composite volcanoes in Nicaragua using three DEM datasets (90 m SRTM, 30 m ASTER G-DEM and an 80 m topographic map-derived DEM) and the resulting parameters are evaluated in terms of boundary delineation and DEM source. Finally, the parameters obtained for the Nicaraguan volcanoes are discussed as an illustrative example of the type of data and information that can be extracted systematically for volcanoes worldwide.

Elevational patterns of species richness, range and body size for spiny frogs.

Quantifying spatial patterns of species richness is a core problem in biodiversity theory. Spiny frogs of the subfamily Painae (Anura: Dicroglossidae) are widespread, but endemic to Asia. Using spiny frog distribution and body size data, and a digital elevation model data set we explored altitudinal patterns of spiny frog richness and quantified the effect of area on the richness pattern over a large altitudinal gradient from 0–5000 m a.s.l. We also tested two hypotheses: (i) the Rapoport's altitudinal effect is valid for the Painae, and (ii) Bergmann's clines are present in spiny frogs. The species richness of Painae across four different altitudinal band widths (100 m, 200 m, 300 m and 400 m) all showed hump-shaped patterns along altitudinal gradient. The altitudinal changes in species richness of the Paini and Quasipaini tribes further confirmed this finding, while the peak of Quasipaini species richness occurred at lower elevations than the maxima of Paini. The area did not explain a significant amount of variation in total, nor Paini species richness, but it did explain variation in Quasipaini. Five distinct groups across altitudinal gradient were found. Species altitudinal ranges did not expand with an increase in the midpoints of altitudinal ranges. A significant negative correlation between body size and elevation was exhibited. Our findings demonstrate that Rapoport's altitudinal rule is not a compulsory attribute of spiny frogs and also suggest that Bergmann's rule is not generally applicable to amphibians. The study highlights a need to explore the underlying mechanisms of species richness patterns, particularly for amphibians in macroecology.

Simulating X-Band Interferometric Height in a Spruce Forest From Airborne Laser Scanning

The aim of this study is to use airborne laser scanning (ALS) data to simulate synthetic aperture radar interferometry (InSAR) elevation data [digital elevation model (DEM)] from the spatial distribution of scatterers. A Shuttle Radar Topography Mission X-band DEM data set and an ALS data set from a spruce-dominated forest area are used. A 3-D grid of voxels is made from the spatial distribution of ALS first echoes. The slant angle penetration rate of the SAR microwaves (PSAR) is simulated to be a function of the vertical ALS penetration rate (PALS), i.e., PSAR = PALS4. The InSAR DEM and heights above the ground are fairly well reproduced by the simulator. A total least squares regression model between the simulated and measured InSAR DEMs has an R2 value of 0.99 and a slope of 1 : 1. By subtracting the ALS-based terrain heights (digital terrain model), we obtained InSAR heights, which were reproduced with an R2 value of 0.78, a slope of 0.96, and a root-mean-square error of 2.3 m. With the simulator, it was demonstrated how a disturbance event would affect the InSAR height. Unfortunately, the relationship was curvilinear and concave, which means that the method is not very sensitive to weak disturbances. This might be partly overcome by using a more vertical incidence angle of the SAR microwaves. The simulator might be used for validation or ground truthing of the InSAR data, as well as gaining understanding of how vegetation changes affect the InSAR data.

A modified binary tree codification of drainage networks to support complex hydrological models

A new codification method (named a modified binary tree codification method) is developed for coding drainage networks. To express the inner topological structure of a drainage basin, it is necessary to delineate and code digital drainage networks from digital elevation model datasets. In this study, the established software TOPAZ is used to delineate river reaches, and the new codification method is applied, which is based on the application of binary-tree structures and hierarchical zones. A coded drainage network can then be stored in a relational database management system to achieve efficient manipulation of data items for topological operations. The utility of the new codification method is demonstrated by an example applied to the Digital Yellow River Model. The drainage network of the Middle Yellow River in northern China has been coded and the hydrological and soil erosion processes of its sub-basin, the Chabagou River basin, are simulated. Because more details of the drainage network can be efficiently and effectively described, the new codification method can support complex hydrological models and extract more information from hydrological simulations than ever before.

건물효과를 고려한 연안도시지역 고해상도 기상모델링

A meso-urban meteorological model (Urbanized MM5; uMM5) with urban canopy parameterization (UCP) was applied to the high-resolution simulation of meteorological fields in a complex coastal urban area and the assessment of urban impacts. Multi-scale simulations with the uMM5 in the innermost domain (1-km resolution) covering the Busan metropolitan region were performed during a typical sea breeze episode (4~8 August 2006) with detailed fine-resolution inputs (urban morphology, land-use/land-cover sub-grid distribution, and high-quality digital elevation model data sets). An additional simulation using the standard MM5 was also conducted to identify the effects of urban surface properties under urban meteorological conditions. Results showed that the uMM5 reproduced well the urban thermal and dynamic environment and captured well the observed feature of sea breeze. When comparison with simulations of the standard MM5, it was found that the uMM5 better reproduced urban impacts on temperature (especially at nighttime) and urban wind flows: roughness-induced deceleration and UHI (Urban Heat Island)-induced convergence.

Dual-scale validation of a medium-resolution coastal DEM with terrestrial LiDAR DSM and GPS

The use of medium-resolution photogrammetric-derived Digital Elevation Models (DEMs) to model coastal inundation risk is commonplace in the geosciences. However, these datasets are often characterised by relatively large and loosely defined elevation errors, which can seriously limit their reliability. Post-processed and static RTK dual-frequency GPS data and very high-resolution Terrestrial Laser Scanning DSM data are used here to quantify the magnitude and spatial distribution of elevation error on a 10 km coastal section of a medium-resolution photogrammetric DEM. The validation data are captured at two scales and spatial-resolutions to minimise the risk of spatial bias in the validation results. The strengths and shortcomings of each validation dataset are assessed, and the complimentary value of GPS and Terrestrial Laser Scanning for external validation is demonstrated. Elevation errors highlighted in the photogrammetric DEM are found to be significantly larger than suggested by the data suppliers, with a tendency for the larger errors to occur with increasing proximity to the coastline. The results confirm the unsuitability of the DEM tested for the local spatial modelling of coastal inundation risk, highlighting difficulties that may be prone to occur when similar DEM datasets are used in coastal studies elsewhere.

Digital elevation models for research: UK datasets, copyright and derived products

Abstract The UK is served by a wide range of digital elevation models (DEMs) that have a variety of technical specifications from several different vendors. The abundance of data presents researchers with a complex range of choices dependent upon their application (and therefore ‘fitness-for-purpose’) and desired use of intellectual property rights (IPR). This paper explores current DEM datasets of the UK and presents their use within the context of claimed copyright and IPR. In particular, responsibilities placed upon grant holders for the lodgement of research outputs by UK Research Councils places new emphasis upon data access, derived data and data re-use. The complex interplay of rights between research output stakeholders (data suppliers, data creators, data users) presents a difficult scenario for both data repositories and data depositors.

Steepened channels upstream of knickpoints: Controls on relict landscape response

The morphology of a relict landscape provides important insight into erosion rates and processes prior to base level fall. Fluvial knickpoints are commonly thought to form a leak‐proof moving boundary between a rejuvenated landscape below and a relict landscape above. We argue that fluvial rejuvenation may leak farther upstream, depending on the rate and style of knickpoint migration. The outer margin of a relict landscape should therefore be used with caution in tectonic geomorphology studies, as channel steepening upstream of knickpoints could reduce the relict area. We explore the response of the Roan Plateau to knickpoint retreat triggered by late Cenozoic upper Colorado River incision. Multiple knickpoints (100‐m waterfalls) separate a low‐relief, upper landscape from incised canyons below. Two digital elevation model data sets (10‐m U.S. Geological Survey and 1‐m Airborne Laser Swath Mapping) indicate steeper channels above waterfalls relative to concave channels farther upstream. The steepened reaches are several kilometers long, correspond to doubling of slope, and exhibit channel narrowing and an increase in hillslope angle. We compare two mechanisms for generating steepened reaches. The first uses a recent model for erosion amplification due to flow acceleration at the waterfall lip. The second acknowledges that waterfall lips may be limited to the outcrop of a resistant formation. Subtle structural warping of the stratigraphy can lead to lowering of the waterfall lip as it retreats, thus lowering base level for upstream channels. Results of numerical modeling experiments suggest the latter mechanism is more consistent with our observations of long, mildly steepened reaches.

Relationships between morphological and sedimentological parameters in source‐to‐sink systems: a basis for predicting semi‐quantitative characteristics in subsurface systems

ABSTRACTThe study of source‐to‐sink systems relates long‐term variations in sediment flux to morphogenic evolution of erosional–depositional systems. These variations are caused by an intricate combination of autogenic and allogenic forcing mechanisms that operate on multiple time scales – from individual transport events to large‐scale filling of basins. In order to achieve a better understanding of how these mechanisms influence morphological characteristics on different scales, 29 submodern source‐to‐sink systems have been investigated. The study is based on measurements of morphological parameters from catchments, shelves and slopes derived from a ∼1 km global digital elevation model dataset, in combination with data on basin floor fans, sediment supply, water discharge and deposition rates derived from published literature. By comparing various morphological and sedimentological parameters within and between individual systems, a number of relationships governing system evolution and behaviour are identified. The results suggest that the amount of low‐gradient floodplain area and river channel gradient are good indicators for catchment storage potential. Catchment area and river channel length is also related to shelf area and shelf width, respectively. Similarly to the floodplain area, these parameters are important for long‐term storage of sediment on the shelf platform. Additionally, the basin floor fan area is correlative to the long‐term deposition rate and the slope length. The slope length thus proves to be a useful parameter linking proximal and distal segments in source‐to‐sink systems. The relationships observed in this study provide insight into segment scale development of source‐to‐sink systems, and an understanding of these relationships in modern systems may result in improved knowledge on internal and external development of source‐to‐sink systems over geological time scales. They also allow for the development of a set of semi‐quantitative guidelines that can be used to predict similar relationships in other systems where data from individual system segments are missing or lacking.

Another Fast and Simple DEM Depression-Filling Algorithm Based on Priority Queue Structure

AbstractSome depression cells with heights lower than their surrounding cells may often be found in Grid-based digital elevation models (DEM) dataset due to sampling errors. The depression-filling algorithm presented by Planchon and Darboux works very quickly compared to other published methods. Despite its simplicity and delicacy, this algorithm remains difficult to understand due to its three complex subroutines and its recursive execution. Another fast algorithm is presented in this article. The main idea of this new algorithm is as follows: first, the DEM dataset is viewed as an island and the outer space as an ocean; when the ocean level increases, the DEM cells on the island’s boundary will be inundated; when a cell is inundated for the first time, its elevation is increased to the ocean level at that moment; after the ocean has inun-dated the entire DEM, all of the depressions are filled. The depression-removing processing is performed using a priority queue. Theoretically, this new algorithm is a ...

Comparing alpine watershed attributes from LiDAR, Photogrammetric, and Contour‐based Digital Elevation Models

AbstractAs part of an alpine hydrological study in the Canadian Rocky Mountains, three digital elevation model (DEM) data sets were obtained for the purpose of watershed characterization. The data sources were: (1) archived public access BC TRIM (Terrain Resource Information Management) 1:20 000 contour vectors; (2) stereo aerial photography DEM with a derived point spacing between 5 m and 20 m; (3) airborne LiDAR (light detection and ranging) with point spacing from 1 m to 4 m. GIS layers of terrain and watershed attributes were created for each of the three DEM data sets at grid cell resolutions of 5 m and 25 m. Watershed attributes investigated were: DEM elevation, area, hypsometry, and stream network topology. In areas of lower relief and forest cover, the TRIM contour DEM contained topological errors at both 5 m and 25 m resolutions due to the poor representation of terrain from widely spaced contours. The photo DEM introduced obvious stream topology errors at 25 m due to the inability of the photo DEM to discern subtle terrain beneath forest canopies. The photo and TRIM DEMs overestimated basin hypsometry relative to the LiDAR watersheds at highest elevations due, in part, to their inability to represent the inside of gullies and steps associated with geological strata. In the case of the photo DEM, selectively digitizing break lines such as cliff edges, while missing shadowed areas, led to the creation of an interpolated surface that was biased towards the outer extremities of the terrain. Conversely, relative to the photo‐based datasets, the LiDAR DEM better captured the inside of gullies and steps while under‐sampling break line features, leading to a bias in the interpolated surface towards internal terrain extremities. As would be expected, the quality and resolution of the terrain data increased from BC TRIM to photo to LiDAR. If modelling watersheds within the Canadian Rockies at the meso scale and above, BC TRIM (or equivalent) 1:20 000 contour vectors would be most appropriate given availability and cost considerations. The benefits of LiDAR are apparent if higher resolution and more accurate watershed attribute information is needed detailing first‐order hydrological channel features on steep shadowed mountain slopes or zero‐order hill‐slope depressions beneath forest canopies. Such landscape features provide preferential storages for winter snowpack in mountainous watersheds, suggesting that in the future LiDAR might be a tool of choice for snowpack resource monitoring in these regions. Copyright © 2008 John Wiley &amp; Sons, Ltd.