Fig 4 - uploaded by Amna Butt
Content may be subject to copyright.
Source publication
Ecological processes such as landslide disaster are primarily impacted by both geological and land use activities happening at different spatiotemporal scale. They specifically impact the socioeconomic development in the sub-Himalayan region of Pakistan. Ecological risk assessment and restrictive zonation mapping are therefore prerequisites for mit...
Context in source publication
Context 1
... i.e., topographic factors, physical factors and anthropogenic factors. Topographic factors included tilt direction, slope angle, and elevation. These factors were derived from the Shuttle Radar Topography Mission (STRM) Digital Elevation Model (DEM) of 30 m resolution. Area under study fell in the elevation range of 437 to 2053 m as shown in Fig. 4. Ten classes of Tilt direction were created, i.e., flat (-1), north (0-22.5), northeast (22.5-67.5), east (67.5-112.5), southeast (112.5-157.5), south (157.5-202.5), southwest (202.5-247.5), west (247.5-292.5), northwest (292.5-337.5), north (337.5-360) ( Fig. 5), whereas slope angle was divided into five intervals, i.e., 0°-45°, ...
Similar publications
Construction of dams has a significant impact on hydrological conditions of rivers. Eco-hydrology, as a sub-discipline of hydrology, focusses on ecological processes occurring within the hydrological cycle and strives to utilize them for enhancing the environmental sustainability. The aim of this study was to determine the stable and instable eco-h...
Construction of dams has a significant impact on hydrological conditions of rivers. Eco-hydrology, as a sub-discipline of hydrology, focusses on ecological processes occurring within the hydrological cycle and strives to utilize them for enhancing the environmental sustainability. The aim of this study was to determine the stable and instable eco-h...
Citations
... Their study in South Korea analyzed causative factors such as slope angle, altitude, soil texture, and forest density, validating our use of high-weighted factors particularly slope degree and lithology in assessing landslide hazard. Similarly, Saleem et al. (2020) highlighted that slope degree, lithology, land use/land cover, and precipitation are among the most influential factors for landslide susceptibility in the sub-Himalayan region, further confirming our results. In the context of flood hazard assessment, Dung et al. (2022) provided a comprehensive review of flood hazard zoning using AHP. ...
... Bioengineering techniques, such as planting deep-rooted vegetation, can further reinforce slopes and reduce erosion. This approach has been effective in landslide-prone regions of the Himalayas, where vegetation has been used to stabilize slopes and prevent soil erosion (Saleem et al. 2020). ...
... Participatory planning, which involves local communities in the development and implementation of risk mitigation strategies, can also improve the effectiveness and sustainability of these measures. This approach has been successfully applied in the sub-Himalayan region, where community input has led to more effective landslide mitigation strategies (Saleem et al. 2020). ...
Historic Cairo is particularly considered a UNESCO World Heritage site that is very vulnerable to natural disasters, such as flooding and landslides, which would threaten its cultural heritage. Multi-risk vulnerability assessments of heritage sites were investigated using remote sensing and GIS methods. Key factors were prioritized using the Analytic Hierarchy Process, and hazard maps were generated to identify areas at risk of floods and/or landslides. The investigation revealed that 54.1% of the study area falls within very low to moderate flood hazard zones, while 12.4% is classified as very high hazard, affecting 21 heritage sites. Additionally, 16% of the study area is in high-threat zones for landslides, impacting 13 cultural sites, with none in very high-risk zones. Considering both hazards, at least 30 sites are in high-risk areas, including 9 in very high-risk zones. The results highlight the urgent need to develop and implement targeted risk mitigation strategies, particularly for sites in central and eastern Historic Cairo, where flood and landslide risks overlap. The GIS-based database and hazard maps provide valuable tools for urban planners, policymakers, and stakeholders to formulate effective protection strategies for Historic Cairo’s cultural heritage.
... Zhou et al. [8] calculated the landslide hazard and vulnerability of the region based on the contribution weight model and used GIS technology to overlay the two to obtain the geological disaster risk zoning. Saleem et al. [9] used an analytical hierarchical process (AHP) to assign weights to the susceptibility factors of landslides in the sub-Himalayan region of Pakistan and obtained susceptibility zones using the weighted overlay method. Liu et al. [10] considered various factors that influenced landslide occurrence and used AHP combined with GIS technology to assess landslide susceptibility in the region. ...
... When using the failure value F D obtained from Equation (9) as the possibility of landslide occurrence, if the calculated failure value of the slope corresponds to the natural state, no conversion is required. If the calculated failure value of the slope results from the action of rainfall or an earthquake, it is necessary to consider the recurrence period of the rainfall or earthquake necessary, and the failure value calculated using Equation (9) should be divided by the return period to obtain the annual failure value of the slope [42]. where is the symbolic function. ...
... In the process of constructing the approximate structural performance function, 20 sampling sets within the parameter intervals were analyzed and the stability coefficient of each sampling combination under rainfall conditions was calculated, yielding an approximate structural performance function that considers rainfall conditions. According to the method described in Section 2.1, the non-probabilistic reliability index of the landslide under the first working condition was −0.0499, and the failure value was calculated as 0.5437 using Equation (9). To verify the accuracy of the non-probabilistic reliability calculation result, the Monte Carlo method was employed for comparison, with one million simulations performed. ...
Landslide risk assessment can quantify the potential damage caused by landslides to disaster-bearing bodies, which can help to reduce casualties and economic losses. It is not only a tool for disaster prevention and mitigation, but also a key step to achieve the coordinated development of the environment, economy, and society, and it provides important support for the realization of the global sustainable development goals (SDGs). In this study, a risk assessment method is proposed for an individual landslide based on the non-probabilistic reliability theory. The method represents an improvement to and innovation in existing risk assessment methods, which can obtain more accurate assessment results with fewer sample data points, refines the methods and steps of landslide risk assessment, and fully considers the destabilization mechanism of the landslide and the interaction with disaster-bearing bodies. A non-probabilistic reliability analysis of the slope was conducted, and the possibility of landslide occurrence was characterized by the failure value of the slope. Moreover, the influence range of the landslide was predicted using empirical formulas; space–time distribution probabilities of the disaster-bearing bodies were estimated by combining their location and activity patterns; and the vulnerability of the disaster-bearing bodies was calculated according to the landslide intensity and the resistance or susceptibility index of the disaster-bearing bodies. The method’s feasibility was verified through its application to the Xiatudiling landslide as a case study. In the process of performing slope stability calculations, it was found that the calculation results of the Monte Carlo method were consistent with those of the non-probabilistic reliability approach proposed in this paper, which was able to obtain more accurate results with less sample data. The personnel life and economic risks were 1.8499 persons/year and CNY 184,858/year (USD 25,448/year), respectively, under heavy rainfall conditions. The results were compared with the risk judgment criteria for geological disasters, and both risk values were unacceptable. After landslide treatment, the possibility of landslide occurrence was reduced, and the personnel life risk and economic risk of the landslide were also reduced. Both risk values then became acceptable. The effect of landslide treatment was obvious. The proposed method provides a new technique for assessing landslide risks and can help in designing mitigation strategies. This method can be applied to landslide risk surveys conducted by geological disaster prevention institutions, demonstrating enhanced applicability in data-scarce regions to improve risk assessment efficiency. It is particularly suitable for emergency management authorities, enabling rapid and comprehensive assessment of landslide risk levels to support informed decision making during critical response scenarios.
... Researchers found the factors most important for landslides to be geological and geomorphological conditions, precipitation, in addition to disturbances due to human activity playing an important role in the occurrence of landslides (Neamat & Karimi, 2020). Landslide disasters can result in loss of biodiversity, human lives, property, and damage to infrastructure (Saleem at al., 2020). Luwu Regency is one of the regencies that has the potential to be prone to landslides. ...
Indonesia is one of the countries that often experiences landslides during the rainy season. The Palopo–Luwu main road is a landslide-prone area in North Bastem sub-district because it has a topographic condition with a very steep slope. Therefore, it is important to conduct research on the analysis of the potential for landslides in the area. The method used in this study is Weighted Overlay based on Geographic Information Systems (GIS) in making landslide-prone maps. Data processing with weighting or scoring on parameters such as slope, rainfall, rock type, soil type, and land cover. While the Finite Element Method (FEM) is used to model slope stability with input data on physical and mechanical properties of rocks and slope geometry data as a basis for calculating the slope safety factor (FK). The results of the study showed that almost 85% of the research area is a high landslide potential area which is the Palopo–Luwu main road area, this was validated from laboratory test data which was then analyzed for slope stability showing FK value <1.25, which is 0.936 and the actual condition of the slope in the field has collapsed. The mapping results can be used as a useful tool for land use planning and risk reduction in the research area.
... In this research, the To carry out a more comprehensive understanding of Halmahera Island, this research combines gravity data with geospatial data for lineament extraction. The use of geospatial data enables more accurate measurement and analysis of geological hazard patterns and distributions [16,17,18]. Zoning using a multi-criteria analysis is performed by several researchers, including Ambarwulan [19] for determining habitable areas in Sukabumi, Indonesia, Ameri [20] for fault identification in Kerman, Iran, Geçkin et al. [21] in Izmir, Turkey, Gunti et al. [22] for earthquake hazard impact analysis in Nepal, and Toma-Danila et al. [23] in Bucharest, Romania. ...
Halmahera Island is one of the Indonesian archipelagos that formed from the interaction among three major plates, Indo-Australian, Eurasia, and Pacific. This convergence causes Halmahera Island presumably to be a geological hazard susceptibility area. This study
used gravity data to delineate subsurface structure based on the Euler Deconvolution technique and further combined with various geospatial data, including lineament density extracted from Sentinel-1A imagery, rainfall rate, PGA, and vegetation index (NDVI) derived from optical
imagery processing, to generate a geological hazard potential zone map based on the Geographic Information System (GIS) implementation. Each thematic map is weighted using the Analytical
Hierarchy Process (AHP) approach, normalized by the Weighted Overlay Index (WOI) technique, and summed up to calculate the Hazard Potential Index (HPI). The calculated map is ranked and reclassified as the most and least dangerous zone of geological hazard vulnerability. HPI shows the most dangerous area is located in several places, including the north and south arms of Halmahera with an index of 0.63 and 0.51, respectively, while the lowest potential zone
is in the southeast arm (0.15). The outcome of this mapping is resumably to be used as a hazard mitigation reference henceforward.
... A compound multi-hazard susceptibility model was developed, including the landslide and flood susceptibility assessment. A GIS-AHP case study was conducted in the Himalayas region of Pakistan by (Akbar et al. 2022;Basharat et al. 2021;Maqsoom et al. 2021;Saleem, Ahmad, and Butt 2020). The element at risk due to the degree of exposure to disasters is known as vulnerability (Cannon 1994;Naudé, Santos-Paulino, and McGillivray 2009) and can be expressed through physical, social, economic, and environmental factors (Burton et al. 2022). ...
Earthquake risk management (ERM) needs proper planning and mitigation measures to minimise adverse impacts. In this context, we quantify the earthquake risk based on hazard, exposure, and vulnerability in the Northwestern Himalayas, Pakistan. A complete earthquake catalogue along with topographic, geo-environmental, seismic, and social causative factors were integrated into a geospatial environment for earthquake risk profiling. The integrated frequency ratio-analytical hierarchy process (FR-AHP) techniques were employed to measure the causative factor weights and historical earthquake distribution within the causative factor classes for hazard assessment. Simultaneously, AHP was utilised to calculate the vulnerability. The exposure was obtained by integrating the hazard and the land use map to estimate damage and loss. Finally, the risk was estimated and mapped across the study area at high resolution. The developed AHP model for vulnerability and hazard showed high accuracy for training and validation data sets (i.e. 98% and 93%, respectively). While there is an evident geographic disparity in the estimated risk, the results show that ∼25% of areas fall under the “very high-risk” zones where population and building density are high near active fault zones. The current study offers actionable insights for risk-reduction initiatives in the mapped high-risk zones.
... The slope facet is a more practical and reliable mapping unit compared to the grid, so the ultimate LHZ map will have better applicability compared to other methods. A number of authors have used the LHEF rating scheme for LHZ mapping at different scales [3,[20][21][22][23][24]. A noticeable gap was found in the quality of the input data, mainly due to the scale of the mapping. ...
The study aimed to utilize the capabilities of geospatial technology for landslide hazard evaluation factor (LHEF) scheme recorded in the Bureau of Indian Standard (BIS) code to prepare a landslide hazard zonation (LHZ) map of the Tehri reservoir rim area at the macro-scale. Multisource remote sensing data were visually and digitally interpreted to produces thematic layers and slope facet as recorded in BIS method. LHEF method is suited for meso and macro scale mapping thus, to broaden the scope of LHEF scheme, novel approaches were adopted namely, the mapping unit ‘slope facet’ was more precisely extracted through digital and visual interpretation of remote sensing data, the structural favorability map was extracted using photo-lineament density criteria. Additionally, two external factors, rainfall and seismicity were incorporated in LHEF rating scheme and used a matrix-based system to propose their combined rating. With the modified LHEF rating scheme, we have succeeded in identifying LHZ with reasonable accuracy. The bar chart method used to validate LHZ results that clearly indicated a high number of landslides falling in high to very high hazard zone conversely, very few landslides observed in low to very low hazard zone identified from current approach.
... The spatial analysis is fundamental for the evaluation of urban sustainability given that the evaluation is modeled using a group of indicators based on the space for map production (Khodakarami et al., 2023). Nowadays, different methods of spatial analysis with Geographical Information Systems (GIS) are used to explore urban situations of interest (Saleem et al., 2020), among which is the Spatial Decision Support System (SDSS). These SDSS combine spatial data, GIS analysis functions and visualization, and decision models to facilitate the evaluation of problem solving through specific procedures in GIS that adapt to the characteristics and necessities of each particular problem (Pignatelli et al., 2023). ...
... Landslides produce environmental issues in the hilly region including but not limited to soil degradation and deforestation (Van et al. 2017). This hazard has particularly affected the demographic trend of Sub-Himalayan region of Pakistan (Saleem et al. 2020). ...
Landslide is a chronic geohazard in hilly regions which affects the socioeconomic trends globally. Current study is conducted to apply three models including Information Value (IV), Frequency Ratio (FR) and Weights of Evidence (WoE) for Landslide Susceptibility Mapping (LSM) of Murree. Sentinel-2, Google Earth, and field surveys data were used to generate an inventory map of 102 landslides and these events were divided into two subsets i.e., 70% and 30% for LSM and model validation respectively. Eleven causative factors including soil erosion, elevation, slope, aspect, curvature, drainage, fault, road, precipitation, Land Use Land Cover (LULC), and lithology maps were prepared using Google Earth Engine (GEE). The final susceptibility maps were produced with the training datasets of landslide events and causative factors using IV, FR and WoE, whereas these maps were validated using the Receiver Operating Characteristic (ROC) technique. The Area Under Curve (AUC) illustrated the Success Rate Curve (SRC) of 69%, 78% and 79% for the IV, FR and WoE models, respectively, while Predicted Rate Curve (PRC) were 80%, 95% and 87% for the IV, FR and WoE models, respectively. The results of this study can be used by policymakers to plan some mitigation regarding soil erosion and landslides-prone region.
... India is rated ninth among countries with the biggest annual forest area change (2010)(2011)(2012)(2013)(2014)(2015) according to the Forest Survey Report, 2017. Because rapid erosion caused by poor land-use patterns in the India particularly Kashmir Himalaya contributes to deadly floods on the plains, sustainable land use is vital not only for the 115 million Himalayans who live there, but also for the millions more who dwell in the surrounding Indo-Gangetic lowlands (Rather & Farooq 2018;Yousuf et al. 2018;Meer & Mishra 2020;Saleem et al. 2020). ...
Land use changes in the Kashmir Himalayas must be mapped and monitored for long-term development and efficient planning. This work uses geospatial technologies such as remote sensing and geographic information system to track changes in land cover trends in four main watersheds in the Kashmir Valley's north-eastern Himalayas from 2003 to 2013. Land cover maps were created using images from the Landsat-5 Thematic Mapper. The watershed's land use/land cover (LULC) maps were created using supervised classification utilizing the maximum likelihood classifier (MLC). Over the previous decade, the LULC in the study watersheds has undergone a series of intricate changes as a result of deforestation, climate change, and agroforestry growth. A total of 11 major LULC classifications were discovered, indicating that forests are the most common land use in all four watersheds. Forest cover, river beds, water bodies, non-perennial snow, and glaciers have all decreased significantly, whereas scrubland, horticulture, rock mass, built-up areas, barren land, and agriculture have all increased significantly, except for Sindh watershed, where the scrubland class has decreased by 5.97% from 2003 to 2013. The study's methodology and conclusions point to crucial policy implications for long-term LULC management in the Kashmir Himalayas' Madhumati, Arin, Sindh, and Lidder watersheds.
HIGHLIGHTS
The current study makes use of the remote sensing and GIS approach, which is currently one of the most popular technologies for spatio-temporal analysis.;
As a result of deforestation, climate change, and agroforestry expansion, the LULC in the study watersheds has undergone a series of complex changes during the past decade.;
Forest cover has decreased drastically while agroforestry has shown an increasing trend.;
... Weighted overlay analysis is one of the most common spatial GIS operations (Kumar et al. 2021), that integrates remote sensing data with other GIS (raster) data layers. The weighted overlay method (WOM) is available in ArcMap (spatial analyst) tool which helps to produce a susceptibility/prediction map (Saleem et al. 2020) based on user input. It is commonly used to solve multi-criteria problems such as optimal/hazardous site selection (Lau and Zawawi 2021;Senouci et al. 2021) or suitability modeling. ...
The notion of this research is based on the two devastating earthquake events that happened on October 8, 2005, and September 24, 2019, in the regions of Azad Kashmir and Muzaffarabad. This study aims to (i) identification of the susceptible zones where landslides can occur in the future; (ii) preparation of landslide inventory maps using vector data, satellite imagery, Shuttle Radar Topographic Mission (STRM) and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) DEM; (iii) implementation of Analytical Hierarchy Process (AHP) model using weighted overlay analysis (WOA). For this purpose, key factors such as land use, faults, slope, contours, soil, and seismology maps are used to develop a landslide hazard zonation map. The output landslide susceptibility map has four susceptibility levels such as low, medium, high, and very high vulnerable zones. The results indicated that a highly susceptible landslide zone is found in the northwestern part of Muzaffarabad, which is a metropolitan region. Moreover, there are 127 active landslides are identified and collectively about 9% of the study area is very highly susceptible to future landslides. Furthermore, research findings are helpful in tactful thinking for future infrastructure development, and ecological protection in high-susceptible landslide regions in Muzaffarabad. It also helps the Government to make strategies based on any specific zones on a priority basis to reduce the casualties and destruction in future landslide events.
