scholarly journals LANDSLIDE SUSCEPTIBILITY MODELLING IN SELECTED STATES ACROSS SE. NIGERIA

2020 ◽  
Vol 4 (1) ◽  
pp. 23-27
Author(s):  
R. O. E. Ulakpa ◽  
V.U.D. Okwu ◽  
K. E. Chukwu ◽  
M. O. Eyankware
Keyword(s):  
Landslide Susceptibility ◽  
Landsat Imagery ◽  
Control Measures ◽  
Landslide Risk ◽  
Susceptibility Map ◽  
Landsat 8 ◽  
Aerial Photos ◽  
Anambra State ◽  
Digital Elevation ◽  
Elevation Model

Identification and mapping of landslide is essential for landslide risk and hazard assessment. This paper gives information on the uses of landsat imagery for mapping landslide areas ranging in size from safe area to highly prone areas. Landslide mitigation largely depends on the understanding of the nature of the factors namely: slope, soil type, lineament, lineament density, elevation, rainfall and vegetation. These factors have direct bearing on the occurrence of landslide. Identification of these factors is of paramount importance in setting out appropriate and strategic landslides control measures. Images for this study was downloaded by using remote sensing with landsat 8 ETM and aerial photos using ArcGIS 10.7 and Surfer 8 software, while Digital Elevation Model (DEM) and Google EarthPro TM were used to produce slope, drainage, lineament and elevation. From the processed landsat 8 imagery, landslide susceptibility map was produced, and landslide was category into various class; low, medium and high. From the study, it was observed that Enugu and Anambra state ranges from high to medium in terms of landslide susceptibility, Imo state ranges from medium to low.

scholarly journals Mapping of Landslide Susceptible Zones by Using Frequency Ratios at Bluncong Subwatershed, Bondowoso Regency

UKaRsT ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 126
Author(s):  
Didik Efendi ◽  
Entin Hidayah ◽  
Akhmad Hasanuddin
Keyword(s):  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Local Governments ◽  
Vegetation Index ◽  
Data Interpretation ◽  
Geographical Information ◽  
Landsat 8 ◽  
Digital Elevation ◽  
Elevation Model ◽  
Frequency Ratios

Landslides are the disasters that frequently happen in Bluncong sub-watershed. These incidents have caused damage and malfunction of road infrastructure, bridges, and irrigation buildings. Therefore, it is important to anticipate landslides through mapping of landslide-susceptibility areas The objective of this study is to map landslide susceptibility at Bluncong sub watershed, Bondowoso, by using Geographical Information System and remote sensing. The landslide susceptibility analysis and mapping are conducted based on landslide occurrences with the Frequency Ratio approach. The landslide sites are identified from field survey data interpretation. Digital Elevation Model maps, geological data, land uses and rivers data, and Landsat 8 images are collected, processed, and then built into the GIS platform's spatial database. The selected factors that cause landslide occurrences are land use, distance to river, aspect, slope, elevation, curvature, and the vegetation index (NDVI). The results show that the accuracy of the map is acceptable. The frequency ratio model gained the area under curve (AUC) value of 0.79. It is found that 9.08% of the area has very high landslide susceptibility. Local governments can use this study's mapping results to minimize the risk at landslidesusceptible zones

scholarly journals InSAR Monitoring of Landslide Activity in Dominica

2021 ◽  
Vol 13 (4) ◽  
pp. 815
Author(s):  
Mary-Anne Fobert ◽  
Vern Singhroy ◽  
John G. Spray
Keyword(s):  
Risk Mitigation ◽  
Disaster Mitigation ◽  
Aerial Images ◽  
Landslide Inventory ◽  
Landslide Risk ◽  
Susceptibility Map ◽  
Interferometric Synthetic Aperture Radar ◽  
Rainfall Events ◽  
Susceptibility Maps ◽  
Digital Elevation

Dominica is a geologically young, volcanic island in the eastern Caribbean. Due to its rugged terrain, substantial rainfall, and distinct soil characteristics, it is highly vulnerable to landslides. The dominant triggers of these landslides are hurricanes, tropical storms, and heavy prolonged rainfall events. These events frequently lead to loss of life and the need for a growing portion of the island’s annual budget to cover the considerable cost of reconstruction and recovery. For disaster risk mitigation and landslide risk assessment, landslide inventory and susceptibility maps are essential. Landslide inventory maps record existing landslides and include details on their type, location, spatial extent, and time of occurrence. These data are integrated (when possible) with the landslide trigger and pre-failure slope conditions to generate or validate a susceptibility map. The susceptibility map is used to identify the level of potential landslide risk (low, moderate, or high). In Dominica, these maps are produced using optical satellite and aerial images, digital elevation models, and historic landslide inventory data. This study illustrates the benefits of using satellite Interferometric Synthetic Aperture Radar (InSAR) to refine these maps. Our study shows that when using continuous high-resolution InSAR data, active slopes can be identified and monitored. This information can be used to highlight areas most at risk (for use in validating and updating the susceptibility map), and can constrain the time of occurrence of when the landslide was initiated (for use in landslide inventory mapping). Our study shows that InSAR can be used to assist in the investigation of pre-failure slope conditions. For instance, our initial findings suggest there is more land motion prior to failure on clay soils with gentler slopes than on those with steeper slopes. A greater understanding of pre-failure slope conditions will support the generation of a more dependable susceptibility map. Our study also discusses the integration of InSAR deformation-rate maps and time-series analysis with rainfall data in support of the development of rainfall thresholds for different terrains. The information provided by InSAR can enhance inventory and susceptibility mapping, which will better assist with the island’s current disaster mitigation and resiliency efforts.

Influence of DEM spatial resolution on the susceptibility mapping with SHALSTAB in the Rio Garcia hydrographic basin, municipality of Blumenau/SC / Influência de la resolución espacial del MDE en la cartografía de susceptibilidad con SHALSTAB en la cuenca hidrográfica del Río García, municipio de Blumenau/SC

2021 ◽  
Vol 5 (3) ◽  
pp. 1475-1491
Author(s):  
Gisele Marilha Pereira Reginatto ◽  
Regiane Mara Sbroglia ◽  
Camilo Andrade Carreño ◽  
Bianca Rodrigues Schvartz ◽  
Pâmela Betiatto ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Landslide Susceptibility ◽  
Susceptibility Mapping ◽  
Hydrographic Basin ◽  
Susceptibility Maps ◽  
Digital Elevation ◽  
Stability Model ◽  
Elevation Model ◽  
Del Rio

In translational landslide susceptibility analysis with SHALSTAB (Shallow Landsliding Stability Model), the resolution of the digital elevation model (DSM) is determinant for defining the type of mapping generated (preliminary or not). In this study, in order to verify the influence of the SDM scale on the SHALSTAB stability classes, susceptibility maps were prepared at two scales: 1:50,000 and 1:10,000. The study area was the Garcia River watershed, belonging to the municipality of Blumenau, Santa Catarina, affected by landslides in the 2008 catastrophe, which enabled the validation of the simulations with the scars mapped in the field. Thus, the influence of scale on the distribution of the model's stability classes and on its performance was verified. SHALSTAB performed better at the 1:10,000 scale, predicting 70% of the instabilities in a percentage of unstable area approximately three times smaller than at the 1,50,000 scale.

scholarly journals Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A case Study in Kullu Valley, Himalayas

Geosciences ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 360 ◽  
Author(s):  
Sansar Raj ◽  
Thimmaiah
Keyword(s):  
Digital Elevation Model ◽  
Spatial Resolution ◽  
Landslide Susceptibility ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Mountainous Regions ◽  
Digital Elevation ◽  
Kullu Valley ◽  
Elevation Model ◽  
The Impact

Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.

scholarly journals Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2160
Author(s):  
Daniel Kibirige ◽  
Endre Dobos
Keyword(s):  
Soil Moisture ◽  
Expert Knowledge ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Regression Kriging ◽  
Environmental Covariates ◽  
Observatory Data ◽  
Digital Elevation ◽  
Elevation Model

Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.

scholarly journals Mapping Post-Earthquake Landslide Susceptibility: A U-Net Like Approach

2020 ◽  
Vol 12 (17) ◽  
pp. 2767
Author(s):  
Yu Chen ◽  
Yongming Wei ◽  
Qinjun Wang ◽  
Fang Chen ◽  
Chunyan Lu ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Environmental Influence ◽  
Landslide Susceptibility Mapping ◽  
Slope Aspect ◽  
Support Vector ◽  
Gis Technology ◽  
2008 Wenchuan Earthquake ◽  
Structure Information ◽  
Digital Elevation ◽  
Elevation Model

A serious earthquake could trigger thousands of landslides and produce some slopes more sensitive to slide in future. Landslides could threaten human’s lives and properties, and thus mapping the post-earthquake landslide susceptibility is very valuable for a rapid response to landslide disasters in terms of relief resource allocation and posterior earthquake reconstruction. Previous researchers have proposed many methods to map landslide susceptibility but seldom considered the spatial structure information of the factors that influence a slide. In this study, we first developed a U-net like model suitable for mapping post-earthquake landslide susceptibility. The post-earthquake high spatial airborne images were used for producing a landslide inventory. Pre-earthquake Landsat TM (Thematic Mapper) images and the influencing factors such as digital elevation model (DEM), slope, aspect, multi-scale topographic position index (mTPI), lithology, fault, road network, streams network, and macroseismic intensity (MI) were prepared as the input layers of the model. Application of the model to the heavy-hit area of the destructive 2008 Wenchuan earthquake resulted in a high validation accuracy (precision 0.77, recall 0.90, F1 score 0.83, and AUC 0.90). The performance of this U-net like model was also compared with those of traditional logistic regression (LR) and support vector machine (SVM) models on both the model area and independent testing area with the former being stronger than the two traditional models. The U-net like model introduced in this paper provides us the inspiration that balancing the environmental influence of a pixel itself and its surrounding pixels to perform a better landslide susceptibility mapping (LSM) task is useful and feasible when using remote sensing and GIS technology.

scholarly journals Pluri-decadal (1955–2014) evolution of glacier–rock glacier transitional landforms in the central Andes of Chile (30–33° S)

2017 ◽  
Vol 5 (3) ◽  
pp. 493-509 ◽  
Author(s):  
Sébastien Monnier ◽  
Christophe Kinnard
Keyword(s):  
Feature Tracking ◽  
Central Andes ◽  
Image Feature ◽  
Rock Glacier ◽  
Aerial Photos ◽  
Surface Displacements ◽  
Digital Elevation ◽  
Elevation Changes ◽  
Elevation Model ◽  
Displacement Patterns

Abstract. Three glacier–rock glacier transitional landforms in the central Andes of Chile are investigated over the last decades in order to highlight and question the significance of their landscape and flow dynamics. Historical (1955–2000) aerial photos and contemporary (> 2000) Geoeye satellite images were used together with common processing operations, including imagery orthorectification, digital elevation model generation, and image feature tracking. At each site, the rock glacier morphology area, thermokarst area, elevation changes, and horizontal surface displacements were mapped. The evolution of the landforms over the study period is remarkable, with rapid landscape changes, particularly an expansion of rock glacier morphology areas. Elevation changes were heterogeneous, especially in debris-covered glacier areas with large heaving or lowering up to more than ±1 m yr−1. The use of image feature tracking highlighted spatially coherent flow vector patterns over rock glacier areas and, at two of the three sites, their expansion over the studied period; debris-covered glacier areas are characterized by a lack of movement detection and/or chaotic displacement patterns reflecting thermokarst degradation; mean landform displacement speeds ranged between 0.50 and 1.10 m yr−1 and exhibited a decreasing trend over the studied period. One important highlight of this study is that, especially in persisting cold conditions, rock glaciers can develop upward at the expense of debris-covered glaciers. Two of the studied landforms initially (prior to the study period) developed from an alternation between glacial advances and rock glacier development phases. The other landform is a small debris-covered glacier having evolved into a rock glacier over the last half-century. Based on these results it is proposed that morphological and dynamical interactions between glaciers and permafrost and their resulting hybrid landscapes may enhance the resilience of the mountain cryosphere against climate change.

scholarly journals Volume change of Jakobshavn Isbræ, West Greenland: 1985–1997–2007

2010 ◽  
Vol 56 (198) ◽  
pp. 635-646 ◽  
Author(s):  
Roman J. Motyka ◽  
Mark Fahnestock ◽  
Martin Truffer
Keyword(s):  
Sea Level ◽  
Climate Forcing ◽  
Similar Magnitude ◽  
Specific Mass ◽  
Aerial Photos ◽  
West Greenland ◽  
Digital Elevation ◽  
Speed Up ◽  
Elevation Model ◽  
Fast Flow

AbstractFollowing three decades of relative stability, Jakobshavn Isbræ, West Greenland, underwent dramatic thinning, retreat and speed-up starting in 1998. To assess the amount of ice loss, we analyzed 1985 aerial photos and derived a 40 m grid digital elevation model (DEM). We also obtained a 2007 40 m grid SPOT DEM covering the same region. Comparison of the two DEMs over an area of ∼4000 km2 revealed a total ice loss of 160 ± 4 km3, with 107 ± 0.2 km3 in grounded regions (0.27 mm eustatic sea-level rise) and 53 ± 4 km3 from the disintegration of the floating tongue. Comparison of the DEMs with 1997 NASA Airborne Topographic Mapper data indicates that this ice loss essentially occurred after 1997, with +0.7 ± 5.6 km3 between 1985 and 1997 and −160 ± 7 km3 between 1997 and 2007. The latter is equivalent to an average specific mass balance of −3.7 ± 0.2 m a−1 over the study area. Previously reported thickening of the main glacier during the early 1990s was accompanied by similar-magnitude thinning outside the areas of fast flow, indicating that the land-based ice continued reacting to longer-term climate forcing.

scholarly journals Analisis Spasial Bencana Longsor Bukit Telogolele Kabupaten Banjarnegara Menggunakan Data Foto Udara UAV

2017 ◽  
Vol 1 (1) ◽  
pp. 77
Author(s):  
Ruli Andaru ◽  
Purnama Budi Santosa
Keyword(s):  
Spatial Data ◽  
3D Analysis ◽  
Geospatial Information ◽  
Aerial Photos ◽  
Vehicle Data ◽  
Digital Elevation ◽  
Before And After ◽  
Elevation Model ◽  
Digital Orthophoto ◽  
Map Data

Spatial data is a very important role in emergency command and disaster management, before, during or post disasters. When a disaster occurs, the currently geospatial information is very needed: where the center of the disaster, the area affected, the volumetric of the landslide, what facilities are damaged, and determine the location of temporary shelters. This study examines and analyze the landslide in Banjarnegara 2014 before and after the landslide using Peta Rupa Bumi Indonesia (RBI) and the UAV Aerial Photos (Unmanned Aerial Vehicle). Data before the landslide obtained from RBI, while data after landslide obtained by performing aerial photography using fixed-wing UAV in December 2014 and August 2015. These aerial photos processing with photogrammetry to produce digital orthophoto and DEM (Digital Elevation Model). Orthophoto and DEM data is used to perform geospatial analysis in both 2D and 3D. 3D analysis obtained from the extraction of DEM elevation map data values appearance of the earth (RBI) and the UAV Aerial Photo. Analysis was conducted on the four components: contouring, terrain profile/cross section, slope/gradient, and volumetric (cut and fill). Readiness management of geospatial data and information is necessary to minimize losses and speed up the process of rehabilitation and reconstruction in the areas affected by the disaster. With this spatial analysis, the estimated of volume of landslides, mapping the facility affected, and the manufacture of the soil profile (high landslide, landslide affected area) can be performed quickly and accurately.

scholarly journals A new approach in the development and analysis of the landslide susceptibility map of the hillslopes of Bujumbura, Burundi

2021 ◽  
pp. 26-34
Author(s):  
Desire Kubwimana ◽  
Lahsen Ait Brahim ◽  
Abdellah Abdelouafi
Keyword(s):  
Landslide Susceptibility ◽  
Slope Angle ◽  
Landslide Inventory ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Aerial Photos ◽  
Conditioning Factors ◽  
Mountainous Regions ◽  
Tropical Environments

As in other hilly and mountainous regions of the world, the hillslopes of Bujumbura are prone to landslides. In this area, landslides impact human lives and infrastructures. Despite the high landslide-induced damages, slope instabilities are less investigated. The aim of this research is to assess the landslide susceptibility using a probabilistic/statistical data modeling approach for predicting the initiation of future landslides. A spatial landslide inventory with their physical characteristics through interpretation of high-resolution optic imageries/aerial photos and intensive fieldwork are carried out. Base on in-depth field knowledge and green literature, let’s select potential landslide conditioning factors. A landslide inventory map with 568 landslides is produced. Out of the total of 568 landslide sites, 50 % of the data taken before the 2000s is used for training and the remaining 50 % (post-2000 events) were used for validation purposes. A landslide susceptibility map with an efficiency of 76 % to predict future slope failures is generated. The main landslides controlling factors in ascendant order are the density of drainage networks, the land use/cover, the lithology, the fault density, the slope angle, the curvature, the elevation, and the slope aspect. The causes of landslides support former regional studies which state that in the region, landslides are related to the geology with the high rapid weathering process in tropical environments, topography, and geodynamics. The susceptibility map will be a powerful decision-making tool for drawing up appropriate development plans in the hillslopes of Bujumbura with high demographic exposure. Such an approach will make it possible to mitigate the socio-economic impacts due to these land instabilities

Sign in / Sign up

Export Citation Format

Share Document