scholarly journals A Simplified, Object-Based Framework for Efficient Landslide Inventorying Using LIDAR Digital Elevation Model Derivatives

2019 ◽  
Vol 11 (3) ◽  
pp. 303 ◽  
Author(s):  
Michael Bunn ◽  
Ben Leshchinsky ◽  
Michael Olsen ◽  
Adam Booth
Keyword(s):  
Large Scale ◽  
Landslide Inventory ◽  
Sediment Delivery ◽  
Landslide Occurrence ◽  
Automated Method ◽  
Object Based ◽  
Digital Elevation ◽  
Input Parameters ◽  
Mapping Techniques ◽  
Elevation Model

Landslide inventory maps are critical to understand the factors governing landslide occurrence and estimate hazards or sediment delivery to channels. Numerous semi-automated approaches for landslide inventory mapping have been proposed to improve the efficiency and objectivity of the process, but these methods have not been widely adopted by practitioners because of the use of input parameters without physical meaning, a lack of transparency in machine-learning based mapping techniques, and limitations in resulting products, which are not ordinarily designed or tested on a large-scale or in diverse geologic units. To this end, this work presents a new semi-automated method, called the Scarp Identification and Contour Connection Method (SICCM), which adapts to diverse geologic settings automatically or semi-automatically using interventions driven by simple inputs and interpretation from an expert mapper. The applicability of SICCM for use in landslide inventory mapping is demonstrated for three diverse study areas in western Oregon, USA by assessing the utility of the results as a landslide inventory, evaluating the sensitivity of the algorithm to changes in input parameters, and exploring how geology influences the resulting landslide inventory results. In these case studies, accuracies exceed 70%, with reliability and precision of nearly 80%. Conclusions of this work are that (1) SICCM efficiently produces meaningful landslide inventories for large areas as evidenced by mapping 216 km2 of landslide deposits with individual deposits ranging in size from 58 to 1.1 million m2; (2) results are predictable with changes to input parameters, resulting in an intuitive approach; (3) geology does not appear to significantly affect SICCM performance; and (4) the process involves simplifications compared with more complex alternatives from the literature.

scholarly journals Object-Based Ensemble Learning for Pan-European Riverscape Units Mapping Based on Copernicus VHR and EU-DEM Data Fusion

2020 ◽  
Vol 12 (7) ◽  
pp. 1222 ◽  
Author(s):  
Luca Demarchi ◽  
Wouter van de Bund ◽  
Alberto Pistocchi
Keyword(s):  
Ensemble Learning ◽  
Large Scale ◽  
Accuracy Assessment ◽  
River System ◽  
River Network ◽  
Second Phase ◽  
Object Based ◽  
Digital Elevation ◽  
Recent Developments ◽  
Elevation Model

Recent developments in the fields of geographical object-based image analysis (GEOBIA) and ensemble learning (EL) have led the way to the development of automated processing frameworks suitable to tackle large-scale problems. Mapping riverscape units has been recognized in fluvial remote sensing as an important concern for understanding the macrodynamics of a river system and, if applied at large scales, it can be a powerful tool for monitoring purposes. In this study, the potentiality of GEOBIA and EL algorithms were tested for the mapping of key riverscape units along the main European river network. The Copernicus VHR Image Mosaic and the EU Digital Elevation Model (EU-DEM)—both made available through the Copernicus Land Monitoring Service—were integrated within a hierarchical object-based architecture. In a first step, the most well-known EL techniques (bagging, boosting and voting) were tested for the automatic classification of water, sediment bars, riparian vegetation and other floodplain units. Random forest was found to be the best-to-use classifier, and therefore was used in a second phase to classify the entire object-based river network. Finally, an independent validation was performed taking into consideration the polygon area within the accuracy assessment, hence improving the efficiency of the classification accuracy of the GEOBIA-derived map, both globally and by geographical zone. As a result, we automatically processed almost 2 million square kilometers at a spatial resolution of 2.5 meters, producing a riverscape-units map with a global overall accuracy of 0.915, and with per-class F1 accuracies in the range 0.79–0.97. The obtained results may allow for future studies aimed at quantitative, objective and continuous monitoring of river evolutions and fluvial geomorphological processes at the scale of Europe.

scholarly journals An inventory and morphometric analysis of British Columbia glaciers, Canada

2008 ◽  
Vol 54 (186) ◽  
pp. 551-560 ◽  
Author(s):  
Erik Schiefer ◽  
Brian Menounos ◽  
Roger Wheate
Keyword(s):  
British Columbia ◽  
Large Scale ◽  
Predictive Ability ◽  
Aerial Photographs ◽  
Automated Method ◽  
Digital Elevation ◽  
Length Width ◽  
Glacier Length ◽  
Regional Position ◽  
Elevation Model

AbstractWe describe an automated method to generate an inventory of glaciers and glacier morphometry from a digital topographic database containing glacier boundaries and a digital elevation model for British Columbia, Canada. The inventory contains over 12 000 glaciers with a total cumulative area that exceeds 25 000 km2, based on mapping from aerial photographs circa the mid-1980s. We use the inventory to examine dimensional characteristics among glaciers, namely the scaling relations between glacier length, width and area. Glacier length is a good predictor of glacier area, and its predictive ability improves when glaciers are stratified by the number of up-valley accumulation basins. The spatial pattern of glacier mid-range altitude parallels glaciation limits previously mapped for British Columbia and similarly reflects large-scale controls of orographic precipitation and continentality. The inventory is also used to refine models that relate glacier mid-range and terminus altitudes to regional position, aspect and, in the case of terminus altitudes, an index of glacier shape. Relations between glacier altitude limits and controlling spatial and topographic factors are used to make further climatic and mass-balance inferences from the glacier inventory.

scholarly journals Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster

2019 ◽  
Vol 11 (9) ◽  
pp. 1096 ◽  
Author(s):  
Hiroyuki Miura
Keyword(s):  
Debris Flow ◽  
Digital Elevation Model ◽  
Large Scale ◽  
Satellite Images ◽  
Erosion Depth ◽  
Digital Elevation ◽  
Elevation Model ◽  
Fusion Analysis ◽  
Optical Satellite Images ◽  
Debris Flow Disaster

Rapid identification of affected areas and volumes in a large-scale debris flow disaster is important for early-stage recovery and debris management planning. This study introduces a methodology for fusion analysis of optical satellite images and digital elevation model (DEM) for simplified quantification of volumes in a debris flow event. The LiDAR data, the pre- and post-event Sentinel-2 images and the pre-event DEM in Hiroshima, Japan affected by the debris flow disaster on July 2018 are analyzed in this study. Erosion depth by the debris flows is empirically modeled from the pre- and post-event LiDAR-derived DEMs. Erosion areas are detected from the change detection of the satellite images and the DEM-based debris flow propagation analysis by providing predefined sources. The volumes and their pattern are estimated from the detected erosion areas by multiplying the empirical erosion depth. The result of the volume estimations show good agreement with the LiDAR-derived volumes.

A new method for supporting interpretation of paleochannels in a large scale — Detrended Digital Elevation Model Interpretation

Geomorphology ◽  
2020 ◽  
Vol 369 ◽  
pp. 107374
Author(s):  
Shuyan Zhang ◽  
Yong Ma ◽  
Fu Chen ◽  
Jianbo Liu ◽  
Fulong Chen ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Large Scale ◽  
New Method ◽  
Model Interpretation ◽  
Digital Elevation ◽  
Elevation Model

scholarly journals A Semiautomatic Pixel-Object Method for Detecting Landslides Using Multitemporal ALOS-2 Intensity Images

2020 ◽  
Vol 12 (3) ◽  
pp. 561 ◽  
Author(s):  
Bruno Adriano ◽  
Naoto Yokoya ◽  
Hiroyuki Miura ◽  
Masashi Matsuoka ◽  
Shunichi Koshimura
Keyword(s):  
Disaster Response ◽  
Large Scale ◽  
Reference Data ◽  
Mass Movement ◽  
Recovery Planning ◽  
Additional Information ◽  
Digital Elevation ◽  
Before And After ◽  
Intensity Images ◽  
Elevation Model

The rapid and accurate mapping of large-scale landslides and other mass movement disasters is crucial for prompt disaster response efforts and immediate recovery planning. As such, remote sensing information, especially from synthetic aperture radar (SAR) sensors, has significant advantages over cloud-covered optical imagery and conventional field survey campaigns. In this work, we introduced an integrated pixel-object image analysis framework for landslide recognition using SAR data. The robustness of our proposed methodology was demonstrated by mapping two different source-induced landslide events, namely, the debris flows following the torrential rainfall that fell over Hiroshima, Japan, in early July 2018 and the coseismic landslide that followed the 2018 Mw6.7 Hokkaido earthquake. For both events, only a pair of SAR images acquired before and after each disaster by the Advanced Land Observing Satellite-2 (ALOS-2) was used. Additional information, such as digital elevation model (DEM) and land cover information, was employed only to constrain the damage detected in the affected areas. We verified the accuracy of our method by comparing it with the available reference data. The detection results showed an acceptable correlation with the reference data in terms of the locations of damage. Numerical evaluations indicated that our methodology could detect landslides with an accuracy exceeding 80%. In addition, the kappa coefficients for the Hiroshima and Hokkaido events were 0.30 and 0.47, respectively.

Food Submergence Calculation and Analysis Using Digital Elevation Model and Geographical Information System

2014 ◽  
Vol 571-572 ◽  
pp. 792-795
Author(s):  
Xiao Qing Zhang ◽  
Kun Hua Wu
Keyword(s):  
Information System ◽  
Digital Elevation Model ◽  
Flood Control ◽  
Large Scale ◽  
Geographical Information ◽  
Economic Losses ◽  
Model Data ◽  
Digital Elevation ◽  
Elevation Model ◽  
Digital Elevation Model Data

Floods usually cause large-scale loss of human life and wide spread damage to properties. Determining flood zone is the core of flood damage assessment and flood control decision. The aim of this paper is to delineate the flood inundation area and estimate economic losses arising from flood using the digital elevation model data and geographic information system techniques. Flood extent estimation showed that digital elevation model data is very precious to model inundation, however, in order to be spatially explicit flood model, high resolution DEM is necessary. Finally, Analyses for the submergence area calculation accuracy.

scholarly journals Automated object-based classification of rain-induced landslides with VHR multispectral images in Madeira Island

2015 ◽  
Vol 3 (9) ◽  
pp. 5633-5664 ◽  
Author(s):  
S. Heleno ◽  
M. Matias ◽  
P. Pina ◽  
A. J. Sousa
Keyword(s):  
Support Vector ◽  
Multispectral Images ◽  
Madeira Island ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Digital Elevation ◽  
Landslide Event ◽  
Separate Source ◽  
Elevation Model

Abstract. A method for semi-automatic landslide detection, with the ability to separate source and run-out areas, is presented in this paper. It combines object-based image analysis and a Support Vector Machine classifier on a GeoEye-1 multispectral image, sensed 3 days after the major damaging landslide event that occurred in Madeira island (20 February 2010), with a pre-event LIDAR Digital Elevation Model. The testing is developed in a 15 km2-wide study area, where 95 % of the landslides scars are detected by this supervised approach. The classifier presents a good performance in the delineation of the overall landslide area. In addition, fair results are achieved in the separation of the source from the run-out landslide areas, although in less illuminated slopes this discrimination is less effective than in sunnier east facing-slopes.

scholarly journals Morphotectonic analysis of Kozani Basin (Western Macedonia, Greece)

2017 ◽  
Vol 47 (2) ◽  
pp. 657
Author(s):  
E. Simou ◽  
V. Karagkouni ◽  
G. Papantoniou ◽  
D. Papanikolaou ◽  
P. Nomikou
Keyword(s):  
Large Scale ◽  
Drainage Pattern ◽  
Tectonic Structure ◽  
Tectonic Structures ◽  
River Terraces ◽  
Digital Elevation ◽  
Combined Use ◽  
Digital Modelling ◽  
Elevation Model ◽  
Topographic Relief

Kozani Basin is located in northern-central Greece and constitutes the southernmost of the Plio-Pleistocene basins of western Macedonia. Quantitative and qualitative analysis of morphological slope values, as well as the analysis of the drainage pattern in Kozani Basin confirms that the current topographic relief reflects intense neotectonic activity. Synthetic Morphotectonic Map of the under study area was carried out by means of the combined use of: (a) Digital Elevation Model (DEM), (b) Slope Distribution Map, (c) Morphological Slope Map and (d) Drainage Pattern Map. The composition of the digital modelling in conjunction with the regional geological setting, allows the identification of the main morphological discontinuities and lineaments that result from morphotectonic interpretation. The high morphological slope values indicate well-defined morphotectonic features, which mainly trend NE - SW and, secondarily, NW - SE. Distinct tectonic structures are mostly recognized in the SE margin of Kozani Basin, which is characterized by intense topographic relief. The main large-scale tectonic structure trends NE - SW and corresponds to the major Aliakmonas marginal fault zone that bounds the Kozani basin to the south. On the other hand, the NW margin’s features are indiscernible; thus, the criteria for their recognition are based on the existence of the river terraces, which reflect the tectonic control. The results of our studies are presented on the Morphotectonic Map, which is followed by our 3D model of Kozani Basin.

scholarly journals Global analysis of the slope of forest land

2020 ◽  
Author(s):  
Mikael Lundbäck ◽  
Henrik Persson ◽  
Carola Häggström ◽  
Tomas Nordfjell
Keyword(s):  
Large Scale ◽  
Forest Cover ◽  
Global Analysis ◽  
Forest Area ◽  
Forest Land ◽  
Digital Elevation ◽  
Total Forest Area ◽  
Cent Point ◽  
Elevation Model ◽  
Country Specific

Abstract Forests of the world constitute one-third of the total land area and are critical for e.g. carbon balance, biodiversity, water supply and as source for bio-based products. Although the terrain within forest land has a great impact on accessibility, there is a lack of knowledge about the distribution of its variation in slope. The aim was to address that knowledge gap and create a globally consistent dataset of the distribution and area of forest land within different slope classes. A Geographic Information System (GIS) analysis was performed using the open-source QGIS, GDAL and R software. The core of the analysis was a digital elevation model and a forest cover mask, both with a final resolution of 90 m. The total forest area according to the forest mask was 4.15 billion hectares whereof 82 per cent was on slope < 15°. The remaining 18 per cent was distributed over the following slope classes, with 6 per cent on a 15–20° slope, 8 per cent on a 20–30° slope and 4 per cent on a slope > 30°. Out of the major forestry countries, China had the largest proportion of forest steeper than 15° followed by Chile and India. A sensitivity analysis with 20 m resolution resulted in increased steep areas by 1 per cent point in flat Sweden and by 11 per cent points in steep Austria. In addition to country-specific and aggregated results of slope distribution and forest area, a global raster dataset is also made freely available to cover user-specific areas that are not necessarily demarcated by country borders. Apart from predicting the regional possibilities for different harvesting equipment, which was the original idea behind this study, the results can be used to relate geographical forest variables to slope. The results could also be used in strategic forest fire fighting and large-scale planning of forest conservation and management.

Sentinel-1 InSAR data by LiCSAR system

2021 ◽  
Author(s):  
Milan Lazecky ◽  
Yasser Maghsoudi Mehrani ◽  
Scott Watson ◽  
Yu Morishita ◽  
John Elliott ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Atmospheric Correction ◽  
East African ◽  
Digital Elevation ◽  
African Rift ◽  
Earth Observation Satellites ◽  
Elevation Model ◽  
Data Coherence ◽  
Standard Frame

<p>Looking Into the Continents from Space with Synthetic Aperture Radar (LiCSAR) is a system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR automatically produces geocoded wrapped and unwrapped interferograms combining every acquisition epoch with four preceding epochs, and complementary data (coherence, amplitude, line-of-sight unit vectors, digital elevation model, metadata, and atmospheric phase screen estimates by the Generic Atmospheric Correction Online Service, GACOS).</p><p>The LiCSAR products are generated in frame units where a standard frame covers ~220x250 km, at 0.001° resolution (WGS-84 coordinate system). Frames are continuously updated for tectonic and volcanic priority areas. In 2020, the LiCSAR system covered about 1,500 global frames in which we have processed over 89,000 Sentinel-1 acquisitions and generated over 300,000 interferograms. Among these, 470 frames cover 1,024 global volcanoes. We aim to cover the global seismic mask defined by the Committee on Earth Observation Satellites (CEOS), but focus initially on the Alpine-Himalayan belt and East African Rift.</p><p>We serve the products as open and freely accessible through our web portal: https://comet.nerc.ac.uk/comet-lics-portal and aim to provide them to shared infrastructures as the European Plate Observing System (EPOS). We also generate rapid response coseismic interferograms for earthquakes with moment magnitude (Mw)> 5.5  a few hours after the postseismic data become available, and we update frames covering active volcanoes twice per day.</p><p>Our products can be directly converted to displacement time series and velocities using  the LiCSBAS time series analysis software. We present solutions implemented in LiCSAR, and show several case studies that use LiCSAR and LiCSBAS products to measure tectonic and volcanic deformation.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.1c122b867cff59390830161/sdaolpUECMynit/12UGE&app=m&a=0&c=02895a62108de9393057db6a355e3b06&ct=x&pn=gnp.elif&d=1" alt=""></p>

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