A first assessment of the TanDEM-X DEMs over Brazilian territory is presented through a comparison with SRTM, ASTER GDEM and ALOS AW3D30 DEMs in seven study areas with distinct geomorphological ...contexts, vegetation coverage, and land use. Visual analysis and elevation histograms point to a finer effective spatial (i.e., horizontal) resolution of TanDEM-X compared to SRTM and ASTER GDEM. In areas of open vegetation, TanDEM-X lower elevations indicate a deeper penetration of the radar signal. DEMs of differences (DoDs) allowed the identification of issues inherent to the production methods of the analyzed DEMs, such as mast oscillations in SRTM data and mismatch between adjacent scenes in ASTER GDEM and ALOS AW3D30. A systematic difference in elevations between TanDEM-X 12 m, TanDEM-X 30 m, and SRTM was observed in the steep slopes of the coastal ranges, related to the moving-window process used to resample the 12 m data to a 30 m pixel size. It is strongly recommended to produce a DoD with SRTM before using ASTER GDEM or ALOS AW3D30 in any analysis, to evaluate if the area of interest is affected by these problems. The DoDs also highlighted changes in land use in the time span between the acquisition of SRTM (2000) and TanDEM-X (2013) data, whether by natural causes or by human interference in the environment. The results show a high level of detail and consistency for TanDEM-X data, indicate that the effective horizontal resolution of SRTM is coarser than the nominal 30 m, and highlight the errors in ASTER GDEM and ALOS AW3D30 due to mismatch between adjacent scenes in the photogrammetric process.
•TanDEM-X shows remarkable quality and consistency in all study areas.•TanDEM-X 30 m has a finer effective horizontal resolution compared to SRTM 30 m.•Results indicate some penetration of the TanDEM-X radar signal in open vegetation.•DoDs revealed artifacts in SRTM, ASTER GDEM and ALOS AW3D30.•DoDs highlighted changes in land use between the acquisition of SRTM and TanDEM-X.
This paper investigates differences between morphometric parameters (slope and aspect) derived from a resampled DEM and resampled morphometric data derived from a medium resolution DEM, with examples ...for three study areas in South America selected to represent flatlands, hilly terrain, and mountain ranges. Using a low resolution DEM for regional scale morphometric analysis is not an optimal choice, since attenuation of elevation will strongly affect the distribution of calculated parameters. Unless bounded by computational constraints, one should choose to derive basic morphometric parameters from higher resolution data, and resample it to a coarser resolution as needed.
•Averaging higher-resolution elevation data will strongly affect the distribution of calculated morphometric parameters.•It is best to derive basic morphometry from higher resolution data, and resample it to a coarser resolution as needed.•Slope derived from resampled elevation show a strong decrease in maximum values with coarser resolutions.•Resampled slopes are more correlated to the original ones, with less decrease in maximum values and with similar mean values.•Aspect changes less with resampling, but peaks and valleys in the density curve are intensified as resolution decreases.
Digital elevation models (DEMs) provide fundamental depictions of the three-dimensionalshape of the Earth’s surface and are useful to a wide range of disciplines. Ideally, DEMs record theinterface ...between the atmosphere and the lithosphere using a discrete two-dimensional grid, withcomplexities introduced by the intervening hydrosphere, cryosphere, biosphere, and anthroposphere.The treatment of DEM surfaces, affected by these intervening spheres, depends on their intendeduse, and the characteristics of the sensors that were used to create them. DEM is a general term,and more specific terms such as digital surface model (DSM) or digital terrain model (DTM) recordthe treatment of the intermediate surfaces. Several global DEMs generated with optical (visible andnear-infrared) sensors and synthetic aperture radar (SAR), as well as single/multi-beam sonars andproducts of satellite altimetry, share the common characteristic of a georectified, gridded storagestructure. Nevertheless, not all DEMs share the same vertical datum, not all use the same conventionfor the area on the ground represented by each pixel in the DEM, and some of them have variable dataspacings depending on the latitude. This paper highlights the importance of knowing, understandingand reflecting on the sensor and DEM characteristics and consolidates terminology and definitions ofkey concepts to facilitate a common understanding among the growing community of DEM users,who do not necessarily share the same background
Landslides have caused tremendous damage to human lives and property safety. However, the complex environment of mountain landslides and the vegetation coverage around landslides make it difficult to ...identify landslides quickly and efficiently using high-resolution images. To address this challenge, this article presents a feature-based constraint deep U-Net (FCDU-Net) method to detect rainfall-induced mountainous landslides. Usually, the vegetation in the landslide area is severely damaged, and the vegetation coverage can indirectly reflect the spatial extent of the landslide. Meanwhile, the texture features of high-resolution images can characterize the surface environment of landslide hazards to a certain extent. We first introduce auxiliary features of normalized difference vegetation index and gray-level co-occurrence matrix into the proposed method to further improve the detection performance. Then, to minimize the information redundancy of these features and the image, we combine Relief-F and Deep U-Net to screen the optimal features to effectively identify accurate and detailed landslide boundaries. Compared with traditional semantic segmentation methods, the FCDU-Net method can capture fine-grained details in high-resolution images and produce more accurate segmentation results. We conducted experiments by applying the proposed method and other most popular semantic segmentation methods to a high-resolution RapidEye image in Rio de Janeiro, Brazil. The results demonstrate that the FCDU-Net method can achieve better landslide detection results than the other semantic segmentation methods, and the evaluation measures of Precision, F1 score, and mean Intersection-over-Union are as high as 88.87%, 81.17%, and 83.19%, respectively. Furthermore, we quantitatively analyze the effect of the convolution input window size on the performance of FCDU-Net in detecting landslides. We believe that FCDU-Net can serve as a reliable tool for fast and accurate regional landslide hazard surveys.
Event-based landslide inventories are essential sources to broaden our understanding of the causal relationship between triggering events and the occurring landslides. Moreover, detailed inventories ...are crucial for the succeeding phases of landslide risk studies like susceptibility and hazard assessment. The openly available inventories differ in the quality and completeness levels. Event-based landslide inventories are created based on manual interpretation, and there can be significant differences in the mapping preferences among interpreters. To address this issue, we used two different datasets to analyze the potential of U-Net and machine learning approaches for automated landslide detection in the Himalayas. Dataset-1 is composed of five optical bands from the RapidEye satellite imagery. Dataset-2 is composed of the RapidEye optical data, and ALOS-PALSAR derived topographical data. We used a small dataset consisting of 239 samples acquired from several training zones and one testing zone to evaluate our models’ performance using the fully convolutional U-Net model, Support Vector Machines (SVM), K-Nearest Neighbor, and the Random Forest (RF). We created thirty-two different maps to evaluate and understand the implications of different sample patch sizes and their effect on the accuracy of landslide detection in the study area. The results were then compared against the manually interpreted inventory compiled using fieldwork and visual interpretation of the RapidEye satellite image. We used accuracy assessment metrics such as F1-score, Precision, Recall, and Mathews Correlation Coefficient (MCC). In the context of the Nepali Himalayas, employing RapidEye images and machine learning models, a viable patch size was investigated. The U-Net model trained with 128 × 128 pixel patch size yields the best MCC results (76.59%) with the dataset-1. The added information from the digital elevation model benefited the overall detection of landslides. However, it does not improve the model’s overall accuracy but helps differentiate human settlement areas and river sand bars. In this study, the U-Net achieved slightly better results than other machine learning approaches. Although it can depend on architecture of the U-Net model and the complexity of the geographical features in the imagery, the U-Net model is still preliminary in the domain of landslide detection. There is very little literature available related to the use of U-Net for landslide detection. This study is one of the first efforts of using U-Net for landslide detection in the Himalayas. Nevertheless, U-Net has the potential to improve further automated landslide detection in the future for varied topographical and geomorphological scenes.
We present a practical approach to inter-compare a range of candidate digital elevation models (DEMs) based on pre-defined criteria and statistically sound ranking approach. The presented approach ...integrates the randomized complete block design (RCBD) into a novel framework for DEMs comparison. The method presented provides a flexible, statistically sound and customizable tool for evaluating the quality of any raster - in this case a DEM - by means of a ranking approach, which takes into account a confidence level, and can use both quantitative and qualitative criteria. The users can design their own criteria for the quality evaluation in relation to their specific needs. The application of the RCBD method to rank six 1" global DEMs, considering a wide set of study sites, covering different morphological and landcover settings, highlights the potentialities of the approach. We used a suite of criteria relating to the differences in the elevation, slope, and roughness distributions compared to reference DEMs aggregated from 1-5 m lidar-derived DEMs. Results confirmed significant superiority of CopDEM 1" and its derivative FABDEM as the overall best 1" global DEMs. They are slightly better than ALOS, and clearly outperform NASADEM and SRTM, which are in turn much better than ASTER.
The neotectonic evolution of the eastern edge of the Paraná Basin in the Santa Catarina State, Brazil was investigated using field data and detailed morphometric analysis along an east–west section. ...Analysis included generation of maps of isobase, hydraulic gradients, hypsometry, incision of drainage basins, drainage asymmetry and anomalous morphological features. All these maps generated results that agreed with field data and helped define recent faults in directions close to N–S and E–W, both probably reactivated faults of the Paraná Basin and the basement. Geomorphological features identified in topographic maps, possibly related to neotectonism, have a close agreement with our observations in the field. The asymmetry of basins as analysed by the T-Index method proved to be compatible with the influence of a E–W compressive tectonic regime and showed a movement from W to E. Application of the hypsometric integral technique helped establish a correlation between the younger basins with structures trending N–S (±30°). The N–S faults were related to a compressional stress field (SHmax) close to E–W and SHmin (stress minimum) around N–S, thereby establishing a tectonic context of structures developed in a transpressive regime. The compressional field was caused by the subduction of the Nazca tectonic plate below the South American plate, whereas the transcurrent component exploited pre-existent E–W structures when the Atlantic Ocean was opening.
•Neotectonic studies in a passive margin intraplate setting (South American Plate).•Evaluation of different morphometric techniques tested with field data.•Identification of the direction of the current SHmax in Santa Catarina State, Brazil.
Remotely Piloted Aircrafts (RPAs) are commonly used as a platform for collecting images which can be processed with Structure from Motion-Multi View Stereo (SfM-MVS) to generate 3D models. However, ...mobile applications for mapping planning are not designed for image acquisition of vertical surfaces, such as quarry walls or large cliffs, leaving the user to a manual flight operation, which does not ensure optimal overlap between images. Here we describe a workflow, based on the Litchi App, for automated RPA missions designed to acquire images of vertical surfaces or structures.•An easy-to-follow 8 steps method to survey vertical surfaces using a Remotely Piloted Aircraft.•It can be applied to outcrops, quarry walls, high cliffs and virtually any other type of vertical surface.•The workflow is flexible and can be adapted to a variety of target configurations and user-defined parameters.
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In this work, we analyze how variation in cell size influences the volume calculated from digital terrain models (DTMs) derived from a LiDAR (light detection and ranging) survey in two coastal Late ...Holocene dune fields in southern Brazil. Cell size varied from 1 to 100m. RMSE (root mean square error) of the resampled DTMs from the original LiDAR (with 0.5m resolution) increases linearly with cell size, while R2 (coefficient of determination) decreases following a second-order trend. The volume does not show simple linear or exponential behavior, but fluctuates with positive and negative deviations from the original DTM. This can be explained by a random factor in the position of the cell with regard to landforms and a relationship between cell and landform size, wherein a small change in cell size can lead to an under- or overestimation of volume. The ASTER GDEM (global digital elevation model) and X-SAR SRTM (Shuttle Radar Topography Mission) 1″ digital elevation models (DEMs) were not considered viable volume sources due to large deviations from the reference data, either as a consequence of noise in the SRTM X-SAR data or lack of bias elevation correction to a common reference base in the GDEM processing chain. Volumes from a 3-arcsec SIR-C SRTM deviated around ±5% from the reference data and are considered suitable input for numerical simulations of Quaternary dune field evolution models because these values should be within the expected range of sediment volume changes over hundreds to millions of years.
► Volumes calculated from DEMs fluctuate around a mean as cell size varies. ► Breaks in fluctuation pattern are interpreted as optimal cell sizes of landforms. ► Fluctuation is due to a random factor between cell and landform sizes. ► Volumes from SRTM (90m) presented small deviation from LiDAR. ► SRTM (90m) is considered a viable source of volume for coastal dune fields.
We present a new 52 m composite record (COL17c) composed of five sedimentary sequences retrieved from the Colônia basin (Southeastern Brazil). The COL17c record is composed of two main sub-units ...deposited under different regimes: a peatland above ~14 m and lacustrine sediments below. Sedimentary description and core scanning (MSCL and XRF) are first used to align individual cores in order to produce a nearly continuous composite record. We then established an original chronological framework based on radiocarbon, paleomagnetic, optically stimulated luminescence (OSL), post-infrared infrared stimulated luminescence at elevated temperature (pIRIR290°C) and authigenic 10Be/9Be dating. We describe the protocols used for each technique and discuss the positive and negative results, as well as their implications for proxy interpretation. In spite of negative results of some techniques, mainly due to the absence of adequate sample material, the multi-proxy approach used is essential to maximize the chances of obtaining a satisfactory age model for this unique continental sedimentary sequence. All valid chronological proxies, comprising three AMS 14C ages, one pIRIR290°C age, two paleomagnetic constraints and eight authigenic 10Be/9Be datum, are integrated within a Bayesian age-depth modeling to produce a 1.5 ± 0.1 Ma chronology for the whole COL17c sequence. This age model represents the first long-term chronological estimate of sediments deposition in the Colônia basin. The record allows to refine the age of the Colônia basin formation between 5.3 and 11.2 Ma, much older than previously estimated from short sedimentary cores.
•A 52 m composite record from the Colônia basin is built from 5 sedimentary cores•The 1.5 ± 0.1 Ma age-depth model is based on independent geochronometers•Paleomagnetic and authigenic 10Be/9Be dating used in a Bayesian age-depth modeling•XRF scanning of COL17c sediments reveal large-scale paleoenvironmental variations•The age of the Colônia basin formation is revised between 5.3 and 11.2 Ma
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