Evolution of the Tazones Lighthouse slope (Cantabrian coast, N Spain). Multidisciplinary monitoring between 2018 and 2020

Abstract. The Tazones Lighthouse slope shows different active mass movements affecting an area of 70.000 m2 of the Cantabrian Coast (N Spain), characterized by almost vertical rocky cliffs developed on Jurassic rocks: alternating marl, sandstone and limestone with three main stratigraphic and structural discontinuity families. Between June 2018 and May 2020, 22 monthly monitoring campaigns have been carried out to measure the displacement of 38 control points, located between 95–110 masl. The total station monitoring has been complemented by ortophoto analysis and detailed digital terrain models (DTM) from two drone flights. Since the beginning of the 3D monitoring, about the 50 % of the markers moved more than 1 m, one of them exceeding 15 m. Detailed DTM has shown that the increased activity is controlled by the discontinuities. There is an extraordinary correlation between displacement acceleration and precipitation and soil moisture: the largest displacements have occurred after 2 periods of intense rain (January and October–November 2019, with a maximum 24-hour precipitation of 64.5 mm and 82.1 mm, respectively, and soil moisture values higher than 90 %). This represents an exceptional opportunity to analyse in real time the Jurassic cliffs retreat of the Cantabrian Coast, a question that remained not quantified.

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The fast evolution of the Tazones Lighthouse landslide (N Spain): multidisciplinary 3D monitoring between 2018 and 2019

10.5194/egusphere-egu2020-10175 ◽

2020 ◽

Author(s):

María José Domínguez-Cuesta ◽

Pelayo González-Pumariega ◽

Pablo Valenzuela ◽

Carlos López-Fernández ◽

Fernando Herrera ◽

...

Keyword(s):

Mass Movement ◽

Digital Terrain Models ◽

Digital Terrain ◽

Terrain Models ◽

Additional Control ◽

Vertical Displacements ◽

Cantabrian Coast ◽

Set Up ◽

Precipitation Records ◽

Fast Evolution

The Tazones Lighthouse landslide is an active mass movement affecting a stretch of the Cantabrian Coast (N Spain), characterized by the presence of almost vertical rocky cliffs developed on Jurassic rocks. The area is being monitored since 2018 when irreversible structural damages appeared in a building located in the surroundings of the lighthouse because of the fast evolution of the landslide.&#160;On June 2018, the first 24 topographic marks were installed by the COSINES Project researchers and 10 more were set up on December of that year, after the appearance of new cracks. Since then, monthly monitoring campaigns have been carried out by total station to gauge the displacement of the 34 mentioned marks and 4 additional control points. One of the control marks was lost, between January and February 2019, due to the fast evolution of the movement. Monitoring has been complemented by the elaboration of detailed digital terrain models through drone flights carried out in November 2018 and November 2019. In addition, precipitation data registered on the rainfall gauges of the surroundings have been collected.&#160;This contribution presents the recent fast evolution of the Tazones Lighthouse landslide, affecting an area about 70.000 m2 and characterized by relevant horizontal and vertical displacements. Since the beginning of the 3D monitoring, the 50% of the marks have moved more than 1 meter and 34% of them have moved more than 2 meters, one of them exceeding 14 meters of displacement.The detailed digital terrain models have allowed quantifying the volume of mobilized mass over a year from the main head of the movement, located 110 meters above sea level. Moreover, the comparison of these data with precipitation records has led to relate the evolution of the displacement with the rainfall, being able to establish a very good correlation between precipitation distribution and movement acceleration.

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MASS MOVEMENTS' DETECTION IN HIRISE IMAGES OF THE NORTH POLE OF MARS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b4-383-2016 ◽

2016 ◽

Vol XLI-B4 ◽

pp. 383-384

Author(s):

L. Fanara ◽

K. Gwinner ◽

E. Hauber ◽

J. Oberst

Keyword(s):

Mass Movements ◽

High Resolution Imaging ◽

Detection Techniques ◽

The North ◽

Digital Terrain ◽

Terrain Models ◽

True Shape ◽

Imaging Science ◽

Resolution Imaging ◽

North Polar

We are investigating change detection techniques to automatically detect mass movements at the steep north polar scarps of Mars, in order to improve our understanding of these dynamic processes. Here we focus on movements of blocks specifically. The precise detection of such small changes requires an accurate co-registration of the images, which is achieved by ortho-rectifying them using High Resolution Imaging Science Experiment (HiRISE) Digital Terrain Models (DTMs). Moreover, we deal with the challenge of deriving the true shape of the moved blocks. In a next step, these results are combined with findings based on HiRISE DTMs from different points in time in order to estimate the volume of mass movements.

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Application of the SHALSTAB model for the identification of areas susceptible to landslides: Brazilian case studies.

Revista de Geomorfologie ◽

10.21094/rg.2017.015 ◽

2017 ◽

Vol 19 (1) ◽

pp. 136-144 ◽

Cited By ~ 1

Author(s):

MARTINS Tiago Damas ◽

VIEIRA Bianca Carvalho ◽

FERNANDES Nelson Ferreira ◽

OKAFIORI Chisato ◽

MONTGOMERY David R.

Keyword(s):

Shallow Landslides ◽

Light Detection And Ranging ◽

Economic Losses ◽

Mass Movements ◽

Digital Terrain ◽

Terrain Models ◽

Susceptibility Maps ◽

Mathematical Equations ◽

The 1960S ◽

Topographical Maps

Since the 1960s, catastrophic and generalized events of hazardous mass movements caused millions of dollars in economic losses and resulted in thousands of fatalities and homelessness in Brazil. To understand these processes and attempt to predict them, mathematical models have been utilized world-wide describing the physics of the process through mathematical equations. The objective of this study was to present two areas widely affected by shallow landslides where the SHALSTAB model was applied to understand the process and to predict potentially unstable areas in several hydrographic basins. Simulations utilized the types of distinct data that were available in each area. From both areas, geotechnical data collected in the field, topographical data from digital topographical maps and Digital Terrain Models (DTM) from Light Detection and Ranging (LiDAR) were utilized. Susceptibility maps were validated using two indexes, scar concentration (SC) and landslide potential (LP), based on landslides that occurred in 1985 and 2011. Both indexes showed satisfactory results given that the unconditionally unstable category described more than 45% of the landslide events, and the LP index displayed the highest values for the most unstable categories.

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Quality analysis of digital terrain models for the test area Zlatibor

Glasnik srpskog geografskog drustva ◽

10.2298/gsgd0301031b ◽

2003 ◽

Vol 83 (1) ◽

pp. 31-42 ◽

Cited By ~ 1

Author(s):

Branislav Bajat ◽

Dragoljub Strbac

Keyword(s):

Data Base ◽

Ground Truth ◽

Test Area ◽

Quality Analysis ◽

Control Points ◽

Digital Terrain Models ◽

Standard Methods ◽

Terrain Visualization ◽

Digital Terrain ◽

Terrain Models

Digital terrain models (DTM) have recently become products which substitute standard methods for the terrain relief presentation. As a part of a Geographic Information Systems (GIS) they represent not only a data base related to heights that are used for terrain visualization by the means of interpolation routines for the generation of contours, or terrain presentation by the 3D meshes, but also a useful data base in many GIS and other applications. Numerous users of DTMs should also be supplied with information of DTM quality. This is obtained by the statistical analysis of residuals between generated height and heights of the control points called ground truth. The results of this analysis might be compulsorily part of metadata base for all DTMs products.

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MASS MOVEMENTS' DETECTION IN HIRISE IMAGES OF THE NORTH POLE OF MARS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b4-383-2016 ◽

2016 ◽

Vol XLI-B4 ◽

pp. 383-384

Author(s):

L. Fanara ◽

K. Gwinner ◽

E. Hauber ◽

J. Oberst

Keyword(s):

Mass Movements ◽

High Resolution Imaging ◽

Detection Techniques ◽

The North ◽

Digital Terrain ◽

Terrain Models ◽

True Shape ◽

Imaging Science ◽

Resolution Imaging ◽

North Polar

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ANALYSIS OF MULTI-YEAR DYNAMICS OF THE NDVI GROWING INDEX IN THE IREMEL NATURAL PARK FOR LOCAL FOREST MANAGEMENT USING DIGITAL TERRAIN MODELS

Астраханский вестник экологического образования ◽

10.36698/2304-5957-2020-19-3-140-149 ◽

2020 ◽

Vol 19 (3) ◽

pp. 140-149

Author(s):

Inber Yaparov ◽

◽

Ildar Vildanov ◽

Elza Bashirova ◽

Rinat Gumerov ◽

...

Keyword(s):

Forest Management ◽

Digital Terrain Models ◽

Digital Terrain ◽

Natural Park ◽

Terrain Models

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Lidar-Based Morphometry of Conical Hills in Temperate Karst Areas in Slovenia

Remote Sensing ◽

10.3390/rs13142668 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2668

Author(s):

Tamás Telbisz

Keyword(s):

Empirical Distribution ◽

Inverse Gaussian ◽

Digital Terrain ◽

Terrain Models ◽

Starting Point ◽

Significant Difference ◽

Karst Areas ◽

Hill Area ◽

The Hill ◽

Comprehensive Study

Conical hills, or residual hills, are frequently mentioned landforms in the context of humid tropical karsts as they are dominant surface elements there. Residual hills are also present in temperate karsts, but generally in a less remarkable way. These landforms have not been thoroughly addressed in the literature to date, therefore the present article is the first attempt to morphometrically characterize temperate zone residual karst hills. We use the methods already developed for doline morphometry, and we apply them to the “inverse” topography using LiDAR-based digital terrain models (DTMs) of three Slovenian sample areas. The characteristics of hills and depressions are analysed in parallel, taking into account the rank of the forms. A common feature of hills and dolines is that, for both types, the empirical distribution of planform areas has a strongly positive skew. After logarithmic transformation, these distributions can be approximated by Inverse Gaussian, Normal, and Weibull distributions. Along with the rank, the planform area and vertical extent of the hills and dolines increase similarly. High circularity is characteristic only of the first-rank forms for both dolines and hills. For the sample areas, the the hill area ratios and the doline area ratios have similar values, but the total extent of the hills is slightly larger in each case. A difference between dolines and hills is that the shapes of hills are more similar to one another than those of dolines. The reason for this is that the larger, closed depressions are created by lateral coalescence, while the hills are residual forms carved from large blocks. Another significant difference is that the density of dolines is much higher than that of hills. This article is intended as a methodological starting point for a new topic, aiming at the comprehensive study of residual karst hills across different climatic areas.

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IMG2nDSM: Height Estimation from Single Airborne RGB Images with Deep Learning

Remote Sensing ◽

10.3390/rs13122417 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2417

Author(s):

Savvas Karatsiolis ◽

Andreas Kamilaris ◽

Ian Cole

Keyword(s):

Deep Learning ◽

State Of The Art ◽

Aerial Imagery ◽

Aerial Images ◽

Surface Model ◽

Large Area ◽

Digital Terrain ◽

Terrain Models ◽

Architectural Features ◽

Rgb Images

Estimating the height of buildings and vegetation in single aerial images is a challenging problem. A task-focused Deep Learning (DL) model that combines architectural features from successful DL models (U-NET and Residual Networks) and learns the mapping from a single aerial imagery to a normalized Digital Surface Model (nDSM) was proposed. The model was trained on aerial images whose corresponding DSM and Digital Terrain Models (DTM) were available and was then used to infer the nDSM of images with no elevation information. The model was evaluated with a dataset covering a large area of Manchester, UK, as well as the 2018 IEEE GRSS Data Fusion Contest LiDAR dataset. The results suggest that the proposed DL architecture is suitable for the task and surpasses other state-of-the-art DL approaches by a large margin.

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