Photogrammetric Digital Elevation Models Research Articles

Flood Analysis Supported by Low‐cost Geometric Modelling

AbstractToday, it is increasingly clear that non‐stationarity hydrological and hydraulic variables and processes are occurring largely because of global warming. Accordingly, extreme hydrological events are becoming more common over time, and their effects are creating greater negative impacts on the environment (fluvial geomorphology and floodplains) and society (flood damage). Given this situation, the implementation of adaptation‐mitigation measures is vital, as well as an increased knowledge of the interaction between water and physical environments. In the binominal water‐terrain, having a reliable digital elevation model (DEM) is essential because of its important influence on fluvial modelling. However, this is frequently a technical‐economic problem. The aim of this paper is first to evaluate the compatibility between hydraulics and geometrics for fluvial applications and second to determine the quality of a novel DEM by robust estimators. This was obtained through the photogrammetric processing of digital aerial images acquired from a low‐cost camera mounted on an alternative aerial platform. Flood modelling and hydraulic parameters were obtained with the assistance of photogrammetric DEM (mesh size: 0.15 m, vertical accuracy: 0.102 ± 0.081 m, point density: ≈40 point/m2). Finally, our other goal is to develop a comparative analysis between light detection and ranging and digital photogrammetry on‐demand. This comparison revealed that flood modelling by photogrammetric DEM was considerably more detailed than that by light detection and ranging‐DEM, mainly because of higher point density and vertical accuracy. Consequently, flood analysis assisted by this novel geometric modelling approach qualifies as a reliable and competitive approach. Copyright © 2016 John Wiley & Sons, Ltd.

USE OF AERIAL IMAGES IN RESEARCH OF MASS MOVEMENTS – A CASE STUDY OF THE LACHOWICE LANDSLIDE (WESTERN CARPATHIANS, BESKID MAKOWSKI MTS)

The article presents the application of photogrammetric digital elevation models in the study of the Lachowice landslide. For this purpose, aerial photos taken in 1977, 2003, 2009 have been used. Digital terrain models (DTM) have been produced from the point cloud generated on the aerial images, using images matching. Generated models allowed calculating the volume of displaced rock masses. Zones of loss and accumulation of rock masses have also been identified. The presence of identifiable points on all images enabled the determination of the values and directions of horizontal displacement vectors.

Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction

Although digital elevation models (DEMs) prove useful for a number of hydrological applications, they are often the end result of numerous processing steps that each contains uncertainty. These uncertainties have the potential to greatly influence DEM quality and to further propagate to DEM-derived attributes including derived surface and near-surface drainage patterns. This research examines the impacts of DEM grid resolution, elevation source data, and conditioning techniques on the spatial and statistical distribution of field-scale hydrological attributes for a 12,000ha watershed of an agricultural area within southwestern Ontario, Canada. Three conditioning techniques, including depression filling (DF), depression breaching (DB), and stream burning (SB), were examined. The catchments draining to each boundary of 7933 agricultural fields were delineated using the surface drainage patterns modeled from LiDAR data, interpolated to a 1m, 5m, and 10m resolution DEMs, and from a 10m resolution photogrammetric DEM. The results showed that variation in DEM grid resolution resulted in significant differences in the spatial and statistical distributions of contributing areas and the distributions of downslope flowpath length. Degrading the grid resolution of the LiDAR data from 1m to 10m resulted in a disagreement in mapped contributing areas of between 29.4% and 37.3% of the study area, depending on the DEM conditioning technique. The disagreements among the field-scale contributing areas mapped from the 10m LiDAR DEM and photogrammetric DEM were large, with nearly half of the study area draining to alternate field boundaries. Differences in derived contributing areas and flowpaths among various conditioning techniques increased substantially at finer grid resolutions, with the largest disagreement among mapped contributing areas occurring between the 1m resolution DB DEM and the SB DEM (37% disagreement) and the DB-DF comparison (36.5% disagreement in mapped areas). These results demonstrate that the decision to use one DEM conditioning technique over another, and the constraints of available DEM data resolution and source, can greatly impact the modeled surface drainage patterns at the scale of individual fields. This work has significance for applications that attempt to optimize best-management practices (BMPs) for reducing soil erosion and runoff contamination within agricultural watersheds.

REFINEMENT OF STEREO IMAGE ANALYSIS USING PHOTOMETRIC SHAPE RECOVERY AS AN ALTERNATIVE TO BUNDLE ADJUSTMENT

Topographic mapping, e.g. the generation of Digital Elevation Models (DEM), is of general interest to the remote sensing community and scientific research. Commonly, photogrammetric methods, e.g. stereo image analysis methods (SIAM) or bundle adjustment methods (BAM), are applied to derive 3D information based on multiple images of an area. These methods require the detection of control points, i.e. common points within multiple images, which relies on a similarity measure and usually yields a sparse map of 3D points. The full spatial DEM is then obtained by interpolation techniques or imposed restrictions, e.g. smoothness constraints. Since BAM utilizes all images of the area, it is assumed to provide a more accurate DEM than SIAM which utilizes only pairs of images. Intensity-based shape recovery, e.g. shape from shading (SfS), utilizes the reflectance behavior of the object surface and thus provides a dense map of relative height changes, which provide the possibility to refine the photogrammetric DEMs. Based on Rosetta NavCam images of 67P/Churyumov-Gerasimenko we compare intensity-based DEM refinement methods which use DEMs obtained based on SIAM and BAM as a reference. We show that both the SIAM based DEM refinement and the BAM based DEM refinement are of similar quality. It is thus possible to derive DEMs of high lateral resolution by applying the intensity-based refinement to the less complex SIAM.

REFINEMENT OF STEREO IMAGE ANALYSIS USING PHOTOMETRIC SHAPE RECOVERY AS AN ALTERNATIVE TO BUNDLE ADJUSTMENT

Abstract. Topographic mapping, e.g. the generation of Digital Elevation Models (DEM), is of general interest to the remote sensing community and scientific research. Commonly, photogrammetric methods, e.g. stereo image analysis methods (SIAM) or bundle adjustment methods (BAM), are applied to derive 3D information based on multiple images of an area. These methods require the detection of control points, i.e. common points within multiple images, which relies on a similarity measure and usually yields a sparse map of 3D points. The full spatial DEM is then obtained by interpolation techniques or imposed restrictions, e.g. smoothness constraints. Since BAM utilizes all images of the area, it is assumed to provide a more accurate DEM than SIAM which utilizes only pairs of images. Intensity-based shape recovery, e.g. shape from shading (SfS), utilizes the reflectance behavior of the object surface and thus provides a dense map of relative height changes, which provide the possibility to refine the photogrammetric DEMs. Based on Rosetta NavCam images of 67P/Churyumov-Gerasimenko we compare intensity-based DEM refinement methods which use DEMs obtained based on SIAM and BAM as a reference. We show that both the SIAM based DEM refinement and the BAM based DEM refinement are of similar quality. It is thus possible to derive DEMs of high lateral resolution by applying the intensity-based refinement to the less complex SIAM.

Suitability of ground-based SfM–MVS for monitoring glacial and periglacial processes

Abstract. Photo-based surface reconstruction is rapidly emerging as an alternative survey technique to lidar (light detection and ranging) in many fields of geoscience fostered by the recent development of computer vision algorithms such as structure from motion (SfM) and dense image matching such as multi-view stereo (MVS). The objectives of this work are to test the suitability of the ground-based SfM–MVS approach for calculating the geodetic mass balance of a 2.1 km2 glacier and for detecting the surface displacement of a neighbouring active rock glacier located in the eastern Italian Alps. The photos were acquired in 2013 and 2014 using a digital consumer-grade camera during single-day field surveys. Airborne laser scanning (ALS, otherwise known as airborne lidar) data were used as benchmarks to estimate the accuracy of the photogrammetric digital elevation models (DEMs) and the reliability of the method. The SfM–MVS approach enabled the reconstruction of high-quality DEMs, which provided estimates of glacial and periglacial processes similar to those achievable using ALS. In stable bedrock areas outside the glacier, the mean and the standard deviation of the elevation difference between the SfM–MVS DEM and the ALS DEM was −0.42 ± 1.72 and 0.03 ± 0.74 m in 2013 and 2014, respectively. The overall pattern of elevation loss and gain on the glacier were similar with both methods, ranging between −5.53 and + 3.48 m. In the rock glacier area, the elevation difference between the SfM–MVS DEM and the ALS DEM was 0.02 ± 0.17 m. The SfM–MVS was able to reproduce the patterns and the magnitudes of displacement of the rock glacier observed by the ALS, ranging between 0.00 and 0.48 m per year. The use of natural targets as ground control points, the occurrence of shadowed and low-contrast areas, and in particular the suboptimal camera network geometry imposed by the morphology of the study area were the main factors affecting the accuracy of photogrammetric DEMs negatively. Technical improvements such as using an aerial platform and/or placing artificial targets could significantly improve the results but run the risk of being more demanding in terms of costs and logistics.

Geodetic mass balance record with rigorous uncertainty estimates deduced from aerial photographs and lidar data – Case study from Drangajökull ice cap, NW Iceland

Abstract. In this paper we describe how recent high-resolution digital elevation models (DEMs) can be used to extract glacier surface DEMs from old aerial photographs and to evaluate the uncertainty of the mass balance record derived from the DEMs. We present a case study for Drangajökull ice cap, NW Iceland. This ice cap covered an area of 144 km2 when it was surveyed with airborne lidar in 2011. Aerial photographs spanning all or most of the ice cap are available from survey flights in 1946, 1960, 1975, 1985, 1994 and 2005. All ground control points used to constrain the orientation of the aerial photographs were obtained from the high-resolution lidar DEM. The lidar DEM was also used to estimate errors of the extracted photogrammetric DEMs in ice- and snow-free areas, at nunataks and outside the glacier margin. The derived errors of each DEM were used to constrain a spherical semivariogram model, which along with the derived errors in ice- and snow-free areas were used as inputs into 1000 sequential Gaussian simulations (SGSims). The simulations were used to estimate the possible bias in the entire glaciated part of the DEM and the 95 % confidence level of this bias. This results in bias correction varying in magnitude between 0.03 m (in 1975) and 1.66 m (in 1946) and uncertainty values between ±0.21 m (in 2005) and ±1.58 m (in 1946). Error estimation methods based on more simple proxies would typically yield 2–4 times larger error estimates. The aerial photographs used were acquired between late June and early October. An additional seasonal bias correction was therefore estimated using a degree-day model to obtain the volume change between the start of 2 glaciological years (1 October). This correction was largest for the 1960 DEM, corresponding to an average elevation change of −3.5 m or approx. three-quarters of the volume change between the 1960 and the 1975 DEMs. The total uncertainty of the derived mass balance record is dominated by uncertainty in the volume changes caused by uncertainties of the SGSim bias correction, the seasonal bias correction and the interpolation of glacier surface where data are lacking. The record shows a glacier-wide mass balance rate of Ḃ = −0.26 ± 0.04 m w.e. a−1 for the entire study period (1946–2011). We observe significant decadal variability including periods of mass gain, peaking in 1985–1994 with Ḃ = 0.27 ± 0.11 m w.e. a−1. There is a striking difference when Ḃ is calculated separately for the western and eastern halves of Drangajökull, with a reduction of eastern part on average ∼ 3 times faster than the western part. Our study emphasizes the need for applying rigorous geostatistical methods for obtaining uncertainty estimates of geodetic mass balance, the importance of seasonal corrections of DEMs from glaciers with high mass turnover and the risk of extrapolating mass balance record from one glacier to another even over short distances.

Performance of a photogrammetric digital elevation model in a tropical montane forest environment

Digital photogrammetry has advanced to the point where digital elevation models (DEMs) can be derived in full automation from stereo images, offering new opportunities in various fields including forestry. However, the performance and limitations of digital photogrammetry need to be carefully investigated in forest environments where both scientific studies and forest management depend on accurate information. We evaluated the performance of a photogrammetric digital surface model (photo-DSM) derived from small-format aerial photographs over approximately 2000 ha of tropical montane forest in northern Borneo, Malaysia. The accuracy of the photo-DSM was evaluated by using a reference dataset derived from airborne laser scanning (ALS) with an approximate density of 15 pulses/m2. The vertical accuracy over the total area (18,349,288 pixels) was represented by a mean error of 0.006 m and RMSE of 3.003 m, with 61.1% of all measured heights accurate to within ±1 m, 81.9% accurate to within ±2 m, and 88.7% accurate to within ±3 m. More detailed local accuracy evaluation was conducted at block level: 31 1-ha blocks and one 0.25-ha block located over different forest types and characterized by the mean canopy height (range=8.4-41.1 m) and standard deviation (range=2.0-9.8 m) of the ALS-canopy height model (ALS-CHM). RMSE of the forest blocks ranged from 1.01 to 4.19 m, and this variance in RMSE could be explained by 78.6% of standard deviation of the ALS-CHM. Canopy slope and dark areas also had an effect on the RMSE: in areas of higher canopy slope and in darker areas within the forest blocks, the RMSE increased by up to 8.6 and 5.8 m, respectively. No-data areas accounted for 3.24% in the forest blocks and were also influenced by canopy slope and darker areas. RMSE of non-forest areas was 0.39 m (n=5243 pixels). Research and development on image-matching algorithms (which achieved 86.1% successful alignment of the aerial photographs in our study), cameras, unmanned aerial vehicles, and flight parameters are ongoing; as a result, digital photogrammetry and its capacity for use in various forestry applications are also continuing to improve.

Spatially Explicit Rangeland Erosion Monitoring Using High-Resolution Digital Aerial Imagery

Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ±8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.

Scenario-Based Validation of Moderate Resolution DEMs Freely Available for Complex Himalayan Terrain

Accuracy of the Digital Elevation Model (DEM) affects the accuracy of various geoscience and environmental modelling results. This study evaluates accuracies of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM Version-2 (GDEM V2), the Shuttle Radar Topography Mission (SRTM) X-band DEM and the NRSC Cartosat-1 DEM V1 (CartoDEM). A high resolution (1 m) photogrammetric DEM (ADS80 DEM), having a high absolute accuracy [1.60 m linear error at 90 % confidence (LE90)], resampled at 30 m cell size was used as reference. The overall root mean square error (RMSE) in vertical accuracy was 23, 73, and 166 m and the LE90 was 36, 75, and 256 m for ASTER GDEM V2, SRTM X-band DEM and CartoDEM, respectively. A detailed error analysis was performed for individual as well as combinations of different classes of aspect, slope, land-cover and elevation zones for the study area. For the ASTER GDEM V2, forest areas with North facing slopes (0°–5°) in the 4th elevation zone (3773–4369 m) showed minimum LE90 of 0.99 m, and barren with East facing slopes (>60°) falling under the 2nd elevation zone (2581–3177 m) showed maximum LE90 of 166 m. For the SRTM DEM, pixels with South-East facing slopes of 0°–5° in the 4th elevation zone covered with forest showed least LE90 of 0.33 m and maximum LE90 of 521 m was observed in the barren area with North-East facing slope (>60°) in the 4th elevation zone. In case of the CartoDEM, the snow pixels in the 2nd elevation zone with South-East facing slopes of 5°–15° showed least LE90 of 0.71 m and maximum LE90 of 1266 m was observed for the snow pixels in the 3rd elevation zone (3177–3773 m) within the South facing slope of 45°–60°. These results can be highly useful for the researchers using DEM products in various modelling exercises.

Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.

Comparison of DEMS derived from USGS DLG, SRTM, a statewide photogrammetry program, ASTER GDEM and LiDAR: implications for change detection

Many digital elevation models (DEMs) now exist, enabling quantitative assessments of topographic change through DEM subtraction. However, many of these DEMs are inherently different – their source data, preprocessing, and interpolation procedures introduce varying amounts of error, which are partially correlated with the local topographic situation (e.g. slope, aspect, and elevation of any given location). Understanding of these differences and potential errors is necessary prior to change detection analysis in order to incorporate the inherent uncertainties into the analysis of topographic change. This study evaluated available DEMs in the Mud 7.5′ United States Geological Survey (USGS) topographic quadrangle in West Virginia, USA. We compare DEMs derived from the USGS digital line graphs (DLGs), the Shuttle Radar Topography Mission (SRTM), a statewide photogrammetric DEM, and the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global DEM v2, to a LiDAR DEM. Using the LiDAR data as a reference (RMSE 0.12 m), the USGS DLG and the SAMB showed low RMSE, while the SRTM and GDEM exhibited high RMSE and a systematic negative bias.

Synergetic merging of Cartosat-1 and RAMP to generate improved digital elevation model of Schirmacher oasis, east Antarctica

Abstract. Available digital elevation models (DEMs) of Antarctic region generated by using radar altimetry and the Antarctic digital database (ADD) indicate elevation variations of up to hundreds of meters, which necessitates the generation of local DEM and its validation by using ground reference. An enhanced digital elevation model (eDEM) of the Schirmacher oasis region, east Antarctica, is generated synergistically by using Cartosat-1 stereo pair-derived photogrammetric DEM (CartoDEM)-based point elevation dataset and multitemporal radarsat Antarctic mapping project version 2 (RAMPv2) DEM-based point elevation dataset. In this study, we analyzed suite of interpolation techniques for constructing a DEM from RAMPv2 and CartoDEM-based point elevation datasets, in order to determine the level of confidence with which the interpolation techniques can generate a better interpolated continuous surface, and eventually improves the elevation accuracy of DEM from synergistically fused RAMPv2 and CartoDEM point elevation datasets. RAMPv2 points and CartoDEM points were used as primary data for various interpolation techniques such as ordinary kriging (OK), simple kriging (SK), universal kriging (UK), disjunctive kriging (DK) techniques, inverse distance weighted (IDW), global polynomial (GP) with power 1 and 2, local polynomial (LP) and radial basis functions (RBF). Cokriging of 2 variables with second dataset was used for ordinary cokriging (OCoK), simple cokriging (SCoK), universal cokriging (UCoK) and disjunctive cokriging (DCoK). The IDW, GP, LP, RBF, and kriging methods were applied to one variable, while Cokriging experiments were employed on two variables. The experiment of dataset and its combination produced two types of point elevation map categorized as (1) one variable (RAMPv2 Point maps and CartoDEM Point maps) and (2) two variables (RAMPv2 Point maps + CartoDEM Point maps). Interpolated surfaces were evaluated with the help of differential global positioning system (DGPS) points collected from study area during the Indian Scientific Expedition to Antarctic (ISEA). Accuracy assessment of the RAMPv2 DEM, CartoDEM, and combined eDEM (RAMPv2 + CartoDEM) by using DGPS as ground reference data shows that eDEM achieves much better accuracy (average elevation error 8.44 m) than that of existing DEM constructed by using only CartoDEM (13.57 m) or RAMPv2 (41.44 m) alone. The newly constructed eDEM achieves a vertical accuracy of about 7 times better than RAMPv2 DEM and 1.5 times better than CartoDEM. After using accurate DGPS data for accuracy assessment, the approximation to the actual surface of the eDEM extracted here is much more accurate with least mean root mean square error (RMSE) of 9.22 m than that constructed by using only CartoDEM (RMSE = 14.15 m) point elevation data and RAMPv2 (RMSE = 69.48 m) point elevation data. Our results indicate that, the overall trend of accuracy for the interpolation methods for generating continuous elevation surface from CartoDEM + RAMPv2 point elevation data, based on RMSE, is as follows: GP1 > IDW > GP2 > OK > LP2 > DK > LP1 > RBF > SK > UK. In case of cokriging interpolation methods, OCoK yields more accurate eDEM with the least RMSE of 8.16 m, which can be utilized to generate a highly accurate DEM of the research area.. Based on this work, it is inferred that GP2 and OCok interpolation methods and synergistic use of RAMPv2 and CartoDEM-based point elevation datasets lead to a highly accurate DEM of the study region. This research experiment demonstrates the stability (w.r.t multi-temporal datasets), performance (w.r.t best interpolation technique) and consistency (w.r.t all the experimented interpolation techniques) of synergistically fused eDEM. On the basis of average elevation difference and RMSE mentioned in present research, the newly constructed eDEM may serve as a benchmark for future elevation models such as from the ICESAT-II mission to spatially monitor ice sheet elevation.

Radargrammetry for Digital Elevation Model Generation Using Envisat Reprocessed Image and Simulation Image

The digital elevation model (DEM) is one of the most important sources used for Earth surface analysis because of its various applications and its usability in subsequent studies. A DEM can be generated with interferometric synthetic aperture radar (InSAR) and radargrammetry techniques from synthetic aperture radar (SAR) images with orbital separation between them as the baseline. The on-board radar imaging system records both phase and intensity information of the backscattered signals. Radargrammetry is based on the disparity between two intensity images which is less affected by temporal and atmospheric decorrelation while InSAR uses the phase differences between two images. However, SAR intensity images may have low spatial resolution compared to optical images that are used in the photogrammetric DEM generation and the original SAR image is degraded by speckle noise. This leads to low accuracy of radargrammetric DEMs. It is necessary to develop methods focusing on original SAR images to improve the accuracy of radargrammetric DEM generation. In this letter, we propose that the single look complex (SLC) SAR image reprocessing method can be utilized to improve the image quality of radargrammetric DEMs. Simulated noise-free SAR images are used to generate radargrammetric DEMs for the purpose of comparison. Three SLC SAR images are selected for image quality improvement in each track. Other images in the same track are matched and processed to one reference image. The SAR simulation images are generated based on the reference image in each track. Therefore, the products in the same track have the same meta-information. Each DEM product is compared with conventional radargrammetric DEMs. This study shows that DEMs generated from re-processed SAR images are more accurate than radargrammetric DEMs from single-pair SAR images. Also, the accuracy of radargrammetric DEM produced with the proposed method is close to DEMs generated with noise-free simulated SAR images.

Validation of SRTM X Band DEM over Himalayan Mountain

Abstract. The present research study assesses the accuracy of the SRTM X band DEM with respect to high accuracy photogrammetric Digital Elevation Model (DEM) for parts of the Himalaya. The high resolution DEM was generated for Manali and nearby areas using digital aerial photogrammetric survey data of 40 cm Ground Sampling Distance (GSD) captured through airborne ADS80 pushbroom camera for the first time in Indian Himalayan context. This high resolution DEM was evaluated with Differential Global Positioning System (DGPS) points for accuracy assessment. The ADS80-DEM gave root mean square error (RMSE) of ~<1m and linear error of 1.60 m at 90 % confidence (LE 90) when compared with the DGPS points. The overall RMSE in vertical accuracy was 73.36 m while LE 90 was 75.20 m with regard to ADS80 DEM. It is observed that the accuracy achieved for part of Himalayan region is far less as compared to the values officially claimed. Thus, SRTM X band DEM should be used with due care in mountainous regions of Himalaya.

Topographic correction of ALOS-PALSAR images using InSAR-derived DEM

Topographic corrections of synthetic aperture radar (SAR) images over hilly regions are vital for retrieval of correct backscatter values associated with natural targets. The coarse resolution external digital elevation models (DEM) available for topographic corrections of high resolution SAR images often result into degradation of spatial resolution or improper estimation of backscatter values in SAR images. Also, many a times the external DEMs do not spatially co-register well with the SAR data. The present study showcases the methodology and results of topographic correction of ALOS-PALSAR image using high resolution DEM generated from the same data. High resolution DEMs of Jaipur region, India were generated using multiple pair SAR images acquired from ALOS-PALSAR using interferometric (InSAR) techniques. The DEMs were validated using differential global positioning system measured elevation values as ground control points and were compared with photogrammetric DEM (advanced spaceborne thermal emission and reflection radiometer – ASTER) and SRTM (Shuttle Radar Topography Mission) DEM. It was observed that ALOS-PALSAR images with optimum baseline parameters produced high resolution DEM with better height accuracy. Finally, the validated DEM was used for topographic correction of ALOS-PALSAR images of the same region and were found to produce better result as compared with ASTER and SRTM-DEM.

LiDAR in extreme environment: surveying in Antarctica

Abstract. This study was performed under the patronage of the Italian National Research Programme in Antarctica (PNRA) with the aim to realize a high resolution Digital Elevation Model (DEM) of the moraine named "Boulder Clay" which insists approximately 7 km far from the Italian Research Base "Mario Zucchelli Station" in the Terra Nova Bay area. The DEM will be included in the project for the construction of two runways to be used as support facilities for the scientific research campaigns which take place on regular basis each year. Although the research efforts to realize a detailed cartography of the area is on-going, for the specific aim and urgency of this project it was decided to perform a laser scanning survey in this extreme environment in order to obtain contour lines describing the terrain elevation each 50 cm and volume analysis. The final result will be super imposed on a photogrammetric DEM with contour lines each 2.5 m and satellite images. This paper focus both on the final scientific data and on all the challenges have to be faced in such extreme and particular environment during the laser scanning survey.

Evaluation and Comparison of Multi Resolution DEM Derived Through Cartosat-1 Stereo Pair – A Case Study of Damanganga Basin

The study evaluates and compares Digital Elevation Model (DEM) data of various grid spacing derived using high resolution Cartosat 1 stereo data for hydrologic applications. DEM is essential in modeling different environmental processes which depend on surface elevation. The accuracy of derived DEM varies with grid spacing and source. The CartoDEM is the photogrammetric DEM derived from stereo pairs. Damanganga basin lying in the Western Ghats was analysed using 11 Carto stereo pairs. The process of triangulation resulted in RMSE of 0.42. DEM was extracted at 10 m, 20 m, 30 m, 40 m, 50 m and 90 m grid spacing and compared with ASTER GDEM (30 m) and SRTM DEM (90 m). DEM accuracy was checked with Root Mean Square Error (RMSE) statistic for random points generated in different elevation zones. Extracted stream networks were compared based on Correctness Index and Figure of Merit index, calculated for all the Digital Elevation Models at varying cell sizes. In order to further evaluate the DEM’s, a simple flood simulation with no water movement and no consideration of real time precipitation data was carried out and relationship between heights of flood stage and inundation area for each Digital Elevation Model was also established.

A Simplified Close‐Range Photogrammetric Technique for Soil Erosion Assessment

Surface reconstruction using digital photogrammetry offers a great advantage for soil erosion research. The technology can be cumbersome for field application because it relies on the accurate measurement of control points, often using a survey‐grade instrument. Also, even though digital photogrammetry has been used in much soil erosion research, its sensitivity in detecting soil elevation changes has rarely been assessed. This study aimed at simplifying the digital photogrammetric procedure for soil erosion research and assessing the sensitivity of this technology to detect soil erosion. To simplify the technology, we propose to combine a photogrammetric procedure for control point generation in a first step, followed by a conventional photogrammetric digital elevation model (DEM) extraction procedure. The performance of the method was assessed in the laboratory and tested in the field to digitize ephemeral gullies. In the accuracy test of photogrammetric survey step, we found that the maximum length measurement error was 3.4 mm, while the maximum angular deviation from the vertical or horizontal axes was 0.93°. The maximum error between control point coordinates generated by photogrammetry and those generated by a survey‐grade total station was 26 mm on the horizontal axes and 10 mm on the vertical axis. We also found that the sensitivity of digital photogrammetry in detecting soil surface elevation changes was similar to that of a laser scanner when the detection was performed on smooth soil surfaces and when the standard deviation of the elevation changes was approximately three times the precision of the photogrammetric DEM.

Quantitative analysis of the 1981 and 2001 Etna flank eruptions: a contribution for future hazard evaluation and mitigation

Lava flows produced during Etna flank eruptions represent severe hazards for the nearby inhabited areas, which can be protected by adopting prompt mitigation actions, such as the building of diversion barriers. Lava diversion measures were attempted recently during the 1983, 1991-93, 2001 and 2002 Etna eruptions, although with different degrees of success. In addition to the complexity of barrier construction (due to the adverse physical conditions), the time available to successfully slow the advance of a lava flow depends on the lava effusion rate, which is not easily measurable. One method to estimate the average lava effusion rate over a specified period of time is based on a volumetric approach; i.e. the measurement of the volume changes of the lava flow over that period. Here, this has been compared to an approach based on thermal image processing, as applied to estimate the average effusion rates of lava flows during the 1981 and 2001 Etna eruptions. The final volumes were measured by the comparison of pre-eruption and post-eruption photogrammetric digital elevation models and orthophotographs. Lava volume growth during these eruptions was estimated by locating the flow-front positions from analyses of scientific papers and newspapers reports, as well as from helicopter photographs. The analyses of these two eruptions contribute to the understanding of the different eruptive mechanisms, highlighting the role of the peak effusion rate, which represents a critical parameter for planning of mitigation actions and for hazard evaluation.