227 research outputs found

    LANDSLIDE SUSCEPTIBILITY MODELLING UNDER ENVIRONMENTAL CHANGES: A CASE STUDY OF CAMERON HIGHLANDS, MALAYSIA

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    Modeling landslide susceptibility usually does not include multi temporal factors, e.g. rainfall, especially for medium scale. Landslide occurrences in Cameron Highlands, in particular, and in Peninsular Malaysia, in general, tend to increase during the peak times of monsoonal rainfall. Due to the lack of high spatial resolution of rainfall data, Normalized Different Vegetation Index (NDVI), soil wetness, and LST (Land Surface Temperature) were selected as replacement of multi temporal rainfall data. This research investigated their roles in landslide susceptibility modeling. In doing so, four Landsat 7 Enhanced Multi Temporal Plus (ETM+) images acquired during two peak times of rainy and dry seasons were used to derive multi temporal NDVI, soil wetness, and LST. Topographic, geology, and soil maps were used to derive ‘static’ factors namely slope, slope aspect, curvature, elevation, road network, river/lake, lithology, soil geology lineament maps. Landslide map was used to derive weighting system based on spatial relationship between landslide occurrences and landslide factor using bivariate statistical method. A non-statistical weighting system was also used for comparison purpose. Different scenarios of data processing were applied to allow evaluation on the roles of multi temporal factors in landslide susceptibility modeling in terms of the accuracy of the landslide susceptibility maps (LSMs), the appropriate weighting system of the models, the applicability of the model, the ability to confirm the relation between landslide occurrences and rainfall. The results show that the average accuracy of LSMs produced by the developed models with inclusion of multi temporal factors is 49.1% on the overall. Addition of LST tends to improve the accuracy of LSMs. NDVI can be a suitable replacement for rainfall data since it can explain the relation between landslides occurrences and rainfall cycle. Statistical-based weighting system produced more accurate LSMs than non-statistical-based one and is applicable for landslide susceptibility modeling elsewhere. Significant causative factors were proven to produce more accurate LSMs

    Groundwater potential mapping in Ikorodu, Lagos State, Nigeria, using multi-criteria analysis and hydrogeophysics

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    The assessment of the potential groundwater recharge area is extremely important for water quality protection and proper management of ground water systems. The objective of this study was to evaluate systematic groundwater studies using the integration of remote sensing and geographic information systems (GIS) and hydrogeophysics as a tool to identify groundwater potential areas in Ikorodu, Lagos. In this study, various thematic maps (layers) derived from satellite image classification such as: Land use/ Land cover map, soil map, rainfall map, geological map, slope map derived from SRTM Digital Elevation Model, lineament density map obtained as a result if lineament analysis of the principal component of the image, were all integrated using the weighted overlay tool in the spatial analyst toolbox of ArcGIS 10.5. Ranks and weights of classes and sub-classes of the thematic layers were assigned based on their influences on groundwater occurrence. The vertical electrical sounding data obtained from the study area were used to validate the results of the groundwater potential map and also determine the areas with brackish water, saline water and freshwater and the most probable drillable depth for exploration. The results show that the groundwater potential zones of the study area could be classified into five zones with the following percentage for spatial distribution: “very high” potential zone (0.6%), “high” (4.2%), “moderate” (15.8%), “low” 71.7% and very low potential zone (7.7%). The South-Western region of Ikorodu, close to Oriwu has the highest concentration of groundwater. Imota is characterized with Moderate and Low ground water potentials. From the query results, the aquiferous layers were identified, their yield and potentials determined and the depths to which boreholes can be sunk for the drilling of fresh water were found to be between 20m and 120m respectively. Keywords: Groundwater, Remote sensing, GIS, Hydrogeophysics

    THE IMPACT OF LAND USE DYNAMICS ON THE SOIL EROSION IN THE PANCHNOI RIVER BASIN, NORTHEAST INDIA

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    Land use (LU) dynamics and its relation to the accelerated soil erosion phenomenon in two broad geomorphic divisions of the Panchnoi River basin of Northeast India have studied. The present study was based on the Revised Universal Soil Loss Equation (RUSLE). To measure the impact of the LU dynamics on soil erosion, the basin was divided into two broad geomorphic divisions, i.e., plain zone and hilly zone, and the rate of soil erosion has been estimated separately for both of the geomorphic divisions. It has been found that in the plain zone, LU dynamics significantly accelerated soil erosion—from 0.52 ton/ha/yr in 1990 to 0.94 ton/ha/yr in 2015. Similarly, the vegetation density decreased significantly in the mountainous and hilly zone as the mean Normalized Difference Vegetation Index (NDVI) value changed from 0.45 in 1990 to 0.35 in 2015, which accelerated soil erosion from 12.06 ton/ha/yr to 18.30 ton/ha/yr from 1990 to 2015. The study indicates that soil erosion may give rise to a severe environmental as well as economic problem in the Panchnoi river basin, which may trigger issues related to the soil fertility of the basin area

    LANDSLIDE SUSCEPTIBILITY MODELLING UNDER ENVIRONMENTAL CHANGES: A CASE STUDY OF CAMERON HIGHLANDS, MALAYSIA

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    Modeling landslide susceptibility usually does not include multi temporal factors, e.g. rainfall, especially for medium scale. Landslide occurrences in Cameron Highlands, in particular, and in Peninsular Malaysia, in general, tend to increase during the peak times of monsoonal rainfall. Due to the lack of high spatial resolution of rainfall data, Normalized Different Vegetation Index (NDVI), soil wetness, and LST (Land Surface Temperature) were selected as replacement of multi temporal rainfall data. This research investigated their roles in landslide susceptibility modeling. In doing so, four Landsat 7 Enhanced Multi Temporal Plus (ETM+) images acquired during two peak times of rainy and dry seasons were used to derive multi temporal NDVI, soil wetness, and LST. Topographic, geology, and soil maps were used to derive ‘static’ factors namely slope, slope aspect, curvature, elevation, road network, river/lake, lithology, soil geology lineament maps. Landslide map was used to derive weighting system based on spatial relationship between landslide occurrences and landslide factor using bivariate statistical method. A non-statistical weighting system was also used for comparison purpose. Different scenarios of data processing were applied to allow evaluation on the roles of multi temporal factors in landslide susceptibility modeling in terms of the accuracy of the landslide susceptibility maps (LSMs), the appropriate weighting system of the models, the applicability of the model, the ability to confirm the relation between landslide occurrences and rainfall. The results show that the average accuracy of LSMs produced by the developed models with inclusion of multi temporal factors is 49.1% on the overall. Addition of LST tends to improve the accuracy of LSMs. NDVI can be a suitable replacement for rainfall data since it can explain the relation between landslides occurrences and rainfall cycle. Statistical-based weighting system produced more accurate LSMs than non-statistical-based one and is applicable for landslide susceptibility modeling elsewhere. Significant causative factors were proven to produce more accurate LSMs

    Remote Sensing Approaches and Related Techniques to Map and Study Landslides

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    Landslide is one of the costliest and fatal geological hazards, threatening and influencing the socioeconomic conditions in many countries globally. Remote sensing approaches are widely used in landslide studies. Landslide threats can also be investigated through slope stability model, susceptibility mapping, hazard assessment, risk analysis, and other methods. Although it is possible to conduct landslide studies using in-situ observation, it is time-consuming, expensive, and sometimes challenging to collect data at inaccessible terrains. Remote sensing data can be used in landslide monitoring, mapping, hazard prediction and assessment, and other investigations. The primary goal of this chapter is to review the existing remote sensing approaches and techniques used to study landslides and explore the possibilities of potential remote sensing tools that can effectively be used in landslide studies in the future. This chapter also provides critical and comprehensive reviews of landslide studies focus¬ing on the role played by remote sensing data and approaches in landslide hazard assessment. Further, the reviews discuss the application of remotely sensed products for landslide detection, mapping, prediction, and evaluation around the world. This systematic review may contribute to better understanding the extensive use of remotely sensed data and spatial analysis techniques to conduct landslide studies at a range of scales

    Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

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    Landslides represent major natural hazards, which cause every year significant loss of lives and damages to buildings, properties and lifelines. In the last decades, a significant increase in landslide frequency took place, in concomitance to climate change and the expansion of urbanized areas. Remote sensing techniques represent a powerful tool for landslide investigation: applications are traditionally divided into three main classes, although this subdivision has some limitations and borders are sometimes fuzzy. The first class comprehends techniques for landslide recognition, i.e., the mapping of past or active slope failures. The second regards landslide monitoring, which entails both ground deformation measurement and the analysis of any other changes along time (e.g., land use, vegetation cover). The third class groups methods for landslide hazard analysis and forecasting. The aim of this paper is to give an overview on the applications of remote-sensing techniques for the three categories of landslide investigations, focusing on the achievements of the last decade, being that previous studies have already been exhaustively reviewed in the existing literature. At the end of the paper, a new classification of remote-sensing techniques that may be pertinently adopted for investigating specific typologies of soil and rock slope failures is proposed

    Application of Landsat-8 and ALOS-2 data for structural and landslide hazard mapping in Kelantan, Malaysia

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    Identification of high potential risk and susceptible zones for natural hazards of geological origin is one of the most important applications of advanced remote sensing technology. Yearly, several landslides occur during heavy monsoon rainfall in Kelantan River basin, Peninsular Malaysia. Flooding and subsequent landslide occurrences generated significant damage to livestock, agricultural produce, homes and businesses in the Kelantan River basin. In this study, remote sensing data from the recently launched Landsat-8 and Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) on board the Advanced Land Observing Satellite-2 (ALOS-2) were used to map geologic structural and topographical features in the Kelantan River basin for identification of high potential risk and susceptible zones for landslides and flooding areas. The data were processed for a comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. The analytical hierarchy process (AHP) approach was used for landslide susceptibility mapping. Several factors such as slope, aspect, soil, lithology, normalized difference vegetation index (NDVI), land cover, distance to drainage, precipitation, distance to fault and distance to the road were extracted from remote sensing satellite data and fieldwork to apply the AHP approach. Directional convolution filters were applied to ALOS-2 data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ) in the west and Lebir Fault Zone in the east of the Kelantan state. The combination of different polarization channels produced image maps that contain important information related to water bodies, wetlands and lithological units. The N-S, NE-SW and NNE-SSW lineament trends and dendritic, sub-dendritic and rectangular drainage patterns were detected in the Kelantan River basin. The analysis of field investigation data indicates that many of flooded areas were associated with high potential risk zones for hydrogeological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topographic regions. Numerous landslide points were located in a rectangular drainage system that is associated with a topographic slope of metamorphic and quaternary rock units. Consequently, structural and topographical geology maps were produced for Kelantan River basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping and identification of high potential risk zone for hydrogeological hazards. Geohazard mitigation programs could be conducted in the landslide recurrence regions and flooded areas to reduce natural catastrophes leading to loss of life and financial investments in the Kelantan River basin. In this investigation, Landsat-8 and ALOS-2 have proven to successfully provide advanced Earth observation satellite data for disaster monitoring in tropical environments

    Identifying landslide hazards in a tropical mountain environment, using geomorphologic and probabilistic approaches

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    The objective of this study is the performance, assessing, comparison and validation of a set of three landslide hazard maps: The geomorphological, the multicriteria evaluation (MCE) and the probabilistic (weights of evidence); in order to evaluate its accuracy, advantages and limitations, and finally state its reliability. These approaches were tested in a tropical mountain environment located in the central Venezuelan Andes. The scale of this study is regional. A landslide inventory map was generated through aerial-photointerpretation and by the processing of two sets of Landsat imagery via contrast-widening color composite, given as result the outline of 493 landslide polygons, then given the main role played for a digital elevation model (DEM) as data input, a DEM for the study area was built through remotely sensed data obtained from the shuttle radar topographical mission (SRTM) and optical stereographic imagery provided by the advanced spaceborne thermal emission and reflection radiometer (ASTER) system. Because of the comparative nature of this study, these data was preliminary processed via density analysis in order to establish a common background on the landsliding process - passive factors relationship, which was used later to set up the criteria applied in the geomorphological and multicriteria evaluation (MCE) approaches. As a way of validation, the accuracy and error rate of the three landslide hazard maps were performed by its comparison to the landslide inventory map. It was concluded that although the geomorphological approach achieved a better landslide predictive power for this study area at a regional scale, the remaining procedures can play a complementary role, for example the MCE plays a crucial role in an early assessment of landslide hazard which highlights the needs and improving necessary to achieve a better probabilistic approach, which can be later incorporated in a more objective geomorphological assessment. Results also showed that any methodology can be improved and even empowered by the development of better and more integrated standards for factor maps collection rather that the simplification of them, in that way, further studies at regional scale must explore the remotely sensed imagery capacities for generation of data bases addressing regional susceptibility to landsliding process

    Ribbed moraines and subglacial geomorphological signatures of interior-sector palaeo-ice sheet dynamics

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    Transverse, subglacial bedforms (ribbed moraines) occur frequently in southern Keewatin, Nunavut, Canada, where they record a complex glacial history, including shifting centers of ice dispersal and fluctuating basal thermal regimes. Comprehensive mapping and quantitative morphometric analysis of the subglacial bedform archive in this sector reveals that ribbed moraines are spatially clustered by size and assume a broad range of visually distinct forms. Results suggest that end-member morphologies are consistent with a dichotomous polygenetic origin, and that a continuum of forms emerged through subsequent reshaping processes of variable intensity and duration. Translocation of mobile, immobile and quasi-mobile beds throughout the last glacial cycle conditioned the development of a subglacial deforming bed mosaic, and is likely responsible for the patchy zonation of palimpsest and inherited landscape signatures within this former core region of the Laurentide Ice Sheet. Comparison against field evidence collected from central Norway suggests that bedforming processes can be locally mediated by pre-existing topography
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