Landslide-prone Zones Research Articles

Investigation and monitoring of rotational landslides in El Mokkattam plateau Egypt, using integrated geological and geophysical techniques

Landslides are a rare but hazardous geological phenomenon in Egypt, with the El Mokattam plateau situated in the eastern part of Cairo covering approximately 64 km2 and ranging in elevation from 50 to 205 m. This study aims to identify and monitor landslides in the area using various geophysical methods. Twelve Electrical resistivity tomography (ERT) profiles,twenty-two P-wave Seismic Refraction profiles, twenty-two Refraction microtremors profiles, three ground penetrating radar (GPR) profiles and borehole data were utilized to analyze the occurrence of landslides in the El Mokattam Plateau. Additionally, we employed a relatively new geophysical method, studying high-frequency microtremor sounds emitted from landslide collapses at 22 stations. Our analysis identified steep slopes, jointed or fractured rocks, and irrigation water as primary factors contributing to landslides, with irrigation water acting as a lubricant for clays and promoting ground sliding. Examination of high-frequency microtremor sounds revealed a potential correlation between vertical high-frequency spectra at 100 Hz and landslide collapses, which aids in the identification of landslide-prone zones. Therefore, we conclude that seismological studies, particularly spectral analysis of high-frequency and low-amplitude sounds (microtremors) emitted from soil, offer a promising approach for investigating landslides.

Pemetaan Kerawanan Bencana Longsor Menggunakan Teknik UAV (Studi Kasus: Jalur Sitinjau Lauik Padang – Solok)

One of the most common natural disasters in Indonesia is landslides Heavy rains have caused several landslides in various regions, causing a large impact every year. Landslides caused by rainfall have also become a global problem in many regions, leading to large-scale landslides. Landslides that occur in Sitinjau Lauik, Padang City are influenced by high rainfall with very steep slopes (70˚-80˚), making this area very prone to landslides. One of the techniques used in mapping landslide vulnerability is the Unmanned Aerial Vehicle (UAV) technique, which is a flying machine controlled by a remote controller. The data obtained will be processed using ArcGIS with Weighted Overlay technique, and factors affecting landslides have been conditioned based on Multi Influencing Factor (MIF). This research aims to achieve: 1) the landslide vulnerability level of Sitinjau Lauik Padang-Solok, 2) determine the landslide prone zones in Sitinjau Lauik. The type of research used in this research is quantitative research with spatial approach. The data required are primary data and secondary data. Primary data consists of aerial photographs taken using drones and processed to produce slope, elevation, aspect, and TWI. The secondary data used is the Landsat 8 image in 2023 which is used to determine the vegetation index. This research resulted in 1) The landslide vulnerability level of Sitinjau Lauik is divided into four classes, namely, low landslide vulnerability level with an area of 4342m or 10.81%. Medium landslide vulnerability level with an area of 24575m or 61.16%. High landslide vulnerability level with an area of 11,294m or 28%. And very high landslide vulnerability level with an area of 14m or 0.03%. 2) Landslide vulnerability zonation based on slope condition is divided into 3 zones: Zone A with an area of 20,901m, Zone B with an area of 4642m. And Zone C with an area of 14,614m.

Multi - criteria analysis based on GIS and open data resources on the internet to establish the landslide susceptibility area of Lam Dong province

Evaluating the risk of landslides to implement preventative measures and aid in development planning is crucial, particularly in regions prone to such occurrences. Employing a landslide susceptibility map proves beneficial in managing land in landslide-prone zones. In this research, we introduce a GIS technology-based approach along with the multi-criteria analysis (MCA) method, incorporating the analytical hierarchy process (AHP) to determine optimal weight allocation for the criteria influencing landslide risk and compute landslide risk assessment indices. Eight criteria affecting landslide risk were chosen from publicly available data sources on the internet: elevation, slope, terrain moisture index (TWI), precipitation, land cover, normalized difference vegetation index (NDVI), soil type, and drainage density. Subsequently, overlaying simple maps facilitated the calculation of the Landslide Susceptibility Index (LSI), leading to the partitioning of the study area into five levels of landslide risk: very high, high, medium, average, low, and very low, covering approximately 8.6%, 24.3%, 32.0%, 23.9%, and 11.2% of the study area, respectively.

Use of Spatial Data in Mapping Landslide Prone Areas in Luhurjaya and Surrounding Areas, Lebak Regency, Banten Province

Landslides are a natural process that occurs in a natural landscape on earth which can cause various environmental damage and can cause loss of life. An increase in the risk of landslides can be caused by uncontrolled land conversion due to the increasing population so that land development is necessary. The research was conducted in Luhurjaya and surrounding areas, Cipanas District, Lebak Regency, Banten with an area of 9 x 9 km. The spatial integration method was used to map landslide-prone zones using a scoring and weighting method, using five parameters, namely slope, rainfall, lineament density, rock type, and NDVI. Those five parameters are then overlaid to form a landslide susceptibility map. As a result of analyzing the research area based on these five parameters, it was found that this area has five slope classes, one rainfall class, five lineament density classes, three rock type classes, and four NDVI classes. After all the datas are scored and weighed, it was found that this research area can be classified to three zones, namely low landslide susceptibility zone, medium landslide susceptibility zone, and high landslide susceptibility zone. From the results of this analysis, disaster mitigation should be needed that can affect the community in the Lebak Regency area, Banten Province, namely in the form of providing provisions in the form of knowledge to the community regarding disaster management which is useful for minimizing the risk of the consequences of landslides

Mapping of Landslide Potential in Payung, Batu City, Indonesia, Using Global Gravity Model Plus (GGMplus) Data as Landslide Mitigation

Several areas in Batu City, Indonesia, often experience landslides when entering the rainy season; landslides occur at several points, including the Payung area on Jalan Trunojoyo. This area connects several districts in East Java, such as Malang Regency, Kediri City, and Jombang Regency. If this area experiences a landslide, the access road will be closed, forcing road users to look for another route that is further away. This study aims to map areas potentially prone to landslides on the Payung tourism road in Batu City, Indonesia. Gravity anomaly measurements were carried out using gravity data from the GGMplus satellite with a distance between data points of 220 m. The processing results are then correlated with the landslide hazard map made by InaRISK BNPB. Based on the residual anomaly map, the measured values are between -13.4 to -5 mgal (low), -5 to 5 mgal (moderate), and 5 to 12 mgal (high). Where the low zone shows the area with the lowest density, the low-density zone has a large enough landslide potential. So, the Trunojoyo road in the Payung area, Batu City, is a landslide-prone zone with very low rock density. The results of this study are expected to provide recommendations for mitigating landslides to the local government.

Landslide assessment through integrated geoelectrical and seismic methods: A case study in Thungsong site, southern Thailand

Many landslides can cause significant damage to infrastructure, property, and human life. To study landslide structure and processes, geophysical techniques are most productive when employed in combination with other survey and monitoring tools, such as intrusive sampling. Here, the integration of electrical resistivity tomography (ERT) and seismic refraction tomography (SRT) methods is used to assess landslides in Thungsong district, Nakhon Si Thammarat, the south of Thailand, where is a hilly and seasons of prolonged rainfall region. The 2D cross-plot analysis of P-wave velocity and resistivity values obtained by these two methods is introduced to identify potential landslide-prone zones in this region. The results of the 2D cross-plot model reveal detailed image of the subsurface conditions, highlighting areas of low P-wave velocity (lower than 600 m/s) and low resistivity (lower than 600 Ωm). These areas are indicative of weak zone and are potential to be sliding materials. Moreover, an intrusive sampling data from boreholes is also used for the calibration and validation geophysical data with geological data. This can improve the accuracy of landslide assessment and develop effective mitigation strategies to reduce the risk of landslides in this area. In addition of the 2D cross-plot, the volume of sliding material is also determined from the difference of the surface and slipping plane elevations. The volume calculation of sliding material is roughly 33447.76 m3. This approach provides a preliminary tool for landslide studies and monitoring landslides in this region, thus enabling an improved understanding of slope failure processes in this context, and the basis of a landslide mitigation strategy in the future.

Impact assessment of unsustainable airport development in the Himalayas using remote sensing: A case study of Pakyong Airport, Sikkim, India

Ground deformation is a widespread phenomenon that accelerates due to anthropogenic land development. Thus reclaimed/created land is more vulnerable to deformation and subsidence, especially in mountain areas. Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR) can be used to monitor such projects. The Pakyong Airport is an engineering feat, constructed by cutting a mountain and converting it into a tabletop in a landslide-prone zone and seismically active region of the Sikkim Himalayas. The cutting of hill slopes for airport construction and other anthropogenic activities has increased slope instability in the region. This paper studies the slow-moving landslides in the airport neighbourhood using A-DInSAR on Sentinel-1 time series data consisting of 64 images of ascending track and 82 images of the descending track. The time period of monitoring was from October 2014 to April 2018 (43 months). The images have been connected using the Minimum Spanning Tree graph for interferogram generation for estimating deformation. The atmospheric noise was removed, and the results enabled the identification of deformation (in line-of-sight) on the airstrip as well as in the neighbouring area, both the upslope and downslope of the airport. The deformation rates estimated were up to ±90 mm/year in Pakyong from both tracks. We could successfully capture such land movement associated with the Pakyong Airport construction and help assess the impacts of infrastructure construction on the slope stability of the area. The controlling factors such as precipitation, seismicity, geology and others were analysed with respect to the deformation obtained. This study helps in assessing the land deformation after construction (cutting and filling of the slope) in the area. The deformation detected in this study needs to be addressed for the safety of the residents as well as for the infrastructure present in the area.

Population Mitigation Strategies to Geomorphic Hazards in Limbe West Coast, South West Region of Cameroon

Environmental hazards are one of the main problems affecting humanity, especially human settlement in hazard prone zones. The study investigates the population strategies to mitigate geomorphic hazards in Limbe within the past 20 years. Data collected through a sample of 200 questionnaires and interview, were analyzed using both qualitative and quantitative statistical techniques. The results reveal that geomorphic hazards have been recurrent in Limbe particularly in the months of June, July and August where the average number of days for rainfall is 27 days in a month. The frequency of hazards occurrence is very often and is highly significant at P=0.000. It also reveals that mitigation measures such as raising foundation, use solid structures and embankments, vary from one area to another within the selected sample sites. Thus, the management strategies to mitigate geomorphic hazards are still lagging behind as there is lack of sensitization/education, good rehabilitation schemes on the part of the authorities to make population avoiding flood and landslide prone zones. Therefore, there is need of management plan for geomorphic hazards in particular and disaster risk management in general that should integrate all stakeholders for a co-management between the Limbe city council and the communities in risk prone areas.

GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India

Predicting landslides is becoming a crucial global challenge for sustainable development in mountainous areas. This research compares the landslide susceptibility maps (LSMs) prepared from five GIS-based data-driven bivariate statistical models, namely, (a) Frequency Ratio (FR), (b) Index of Entropy (IOE), (c) Statistical Index (SI), (d) Modified Information Value Model (MIV) and (e) Evidential Belief Function (EBF). These five models were tested in the high landslides-prone humid sub-tropical type Upper Tista basin of the Darjeeling-Sikkim Himalaya by integrating the GIS and remote sensing. The landslide inventory map consisting of 477 landslide locations was prepared, and about 70% of all landslide data was utilized for training the model, and 30% was used to validate it after training. A total of fourteen landslide triggering parameters (elevation, slope, aspect, curvature, roughness, stream power index, TWI, distance to stream, distance to road, NDVI, LULC, rainfall, modified fournier index, and lithology) were taken into consideration for preparing the LSMs. The multicollinearity statistics revealed no collinearity problem among the fourteen causative factors used in this study. Based on the FR, MIV, IOE, SI, and EBF approaches, 12.00%, 21.46%, 28.53%, 31.42%, and 14.17% areas, respectively, identified in the high and very high landslide-prone zones. The research also revealed that the IOE model has the highest training accuracy of 95.80%, followed by SI (92.60%), MIV (92.20%), FR (91.50%), and EBF (89.90%) models. Consistent with the actual distribution of landslides, the very high, high, and medium hazardous zones stretch along the Tista River and major roads. The suggested landslide susceptibility models have enough accuracy for usage in landslide mitigation and long-term land use planning in the study area. Decision-makers and local planners may utilise the study's findings. The techniques for determining landslide susceptibility can also be employed in other Himalayan regions to manage and evaluate landslide hazards.

A Multi-Criteria Decision Analysis (MCDA) Approach for Landslide Susceptibility Mapping of a Part of Darjeeling District in North-East Himalaya, India

Landslides are the nation’s hidden disaster, significantly increasing economic loss and social disruption. Unfortunately, limited information is available about the depth and extent of landslides. Therefore, in order to identify landslide-prone zones in advance, a well-planned landslide susceptibility mapping (LSM) approach is needed. The present study evaluates the efficacy of an MCDA-based model (analytical hierarchy process (AHP)) and determines the most accurate approach for detecting landslide-prone zones in one part of Darjeeling, India. LSM is prepared using remote sensing thematic layers such as slope, rainfall earthquake, lineament density, drainage density, geology, geomorphology, aspect, land use and land cover (LULC), and soil. The result obtained is classified into four classes, i.e., very high (11.68%), high (26.18%), moderate (48.87%), and low (13.27%) landslide susceptibility. It is observed that an entire 37.86% of the area is in a high to very high susceptibility zone. The efficiency of the LSM was validated with the help of the receiver operating characteristics (ROC) curve, which demonstrate an accuracy of 96.8%, and the success rate curve showed an accuracy of 81.3%, both of which are very satisfactory results. Thus, the proposed framework will help natural disaster experts to reduce land vulnerability, as well as aid in future development.

Comparison of two landslide hazard zonation methods in the volcanic terrain of Temanggung Regency, Central Java, Indonesia

Landslides are a recurring phenomenon that disrupts the natural environment and causes yearly property damage, economic losses, and fatalities. The damage is expected to increase due to deforestation rates, population growth, agriculture, slope-building infrastructure expansion, and global climate change. This study assesses the susceptibility to landslides through Weight of Evidence (WoE) and Frequency Ratio (FR) methods in the Temanggung Regency, Central Java Province, Indonesia, that located on the slopes of two active volcanoes. Initially, a landslide record and the input parameters of the landslide controlling factors were prepared from field surveys, remote sensing data, and secondary data and processed by a geographic information system (GIS). Six landslide parameters in thematic layer maps were selected to develop landslide susceptibility: slope, lithology type, geological structure density, land cover, and rainfall. According to the WoE and FR models, a landslide susceptibility zoning map was classified into four landslide-prone zones from low to very high. Finally, the success and predictive rate curves method confirmed the landslide susceptibility maps to check the model accuracy. The results showed that the landslide susceptibility map using the WoE method had better accuracy than the FR method, with a success rate of 78.48% and a prediction rate of 81.1%. In comparison, the FR method was 74.53% for the success rate and 78.48% for the prediction rate. These landslide susceptibility maps can be used as a guideline to develop land-use planning and landslide disaster mitigation.

Landslide susceptibility and risk analysis in Benighat Rural Municipality, Dhading, Nepal

The complex geology and undulating terrain made Nepal vulnerable to natural disasters like landslides. Benighat-Rorang Rural Municipality (RM), in the Dhading district of Nepal's Bagmati province, has experienced several minor to massive landslides that have harmed both nature and civilization. This study examines the factors influencing landslides in the Benighat-Rorang RM by analyzing soil structure, geology, land cover, geomorphology (primarily slopes and aspects), fault lines, drainage density, weather data, and road density to generate a comprehensive Landslide Susceptibility Mapping (LSM). The LSM will help in identifying landslide-prone zones (high to low), which will, in turn, enable stakeholders to implement appropriate mitigation measures across the landslide-induced rural municipality. The current study intends to create Landslide susceptibility zonation mapping within and around the studied area by applying the AHP method while taking into account the optimal set of geo-environmental parameters to identify regions at risk of future landslides. Elevation, Slope, Aspect, Drainage, Geology, Soil Classes, Fault Line, Lineaments, Land-cover, Road Networks, Population, and climatic parameters (Rainfall, Temperature, Relative Humidity, Surface Pressure, and Wind Speed) are among the fourteen geo-environmental elements used for this research. Using the field verification approach, the results of this procedure have been validated, which can be observed in an estimated success rate curve. Meteorological factors, such as temperature, rainfall, relative humidity, surface pressure, and wind speed, have been examined regarding landslide susceptibility. Thus, an integrated assessment of landslide susceptibility was applied to the area to identify inhabited areas vulnerable to or at risk of landslides. Furthermore, the placement of public amenities throughout the research zone was considered while conducting the social vulnerability risk analysis. Finally, landslide susceptibility zonation, climatic factors influencing landslide susceptibility, and social vulnerability assessment results of the study area have been combined to generate a risk map identifying landslide-prone municipal facilities and vulnerable communities. This study will help in building resilient landslide communities through effective spatial urban planning that incorporates regional risks induced by landslides with infrastructure development and management strategies.

Identification of Landslide-Prone Areas in Sanggau Regency, West Kalimantan using GIS and Resistivity Method

Currently, the weather in Indonesia has been greatly affected by climate change. This is evidenced by extreme weather events in early 2020 which are predicted to occur more frequently in Indonesia. Bad weather in the form of high rainfall will potentially cause hydrometeorological disasters such as floods and landslides. To anticipate the occurrence of landslides that have the potential to disrupt regional development, it is important to conduct research to map landslide-prone areas in the province of West Kalimantan. This research is in line with UNTAN's strategic research plan to contribute to disaster management and climate change. This research combines overlay and measurement methods with geoelectric methods. The overlay method is used as a method to map landslide susceptibility based on scoring calculations from land parameters. The mapping is expected to produce a map of the landslide-prone zone which can then be studied further. Assessment of landslide potential through slip plane analysis using resistivity geoelectric method. From the mapping and direct observation, it is proved that the high landslide susceptibility values correlate with the landslide occurrence in Sabang Merah, Sanggau. Based on the resistivity measurement there found the potential landslide slip surface that is connected with the dip of rock layers in the area.

Elevation Angles, Soil Textures, Soil Settlements and WaterHolding Capacity on Landslides: An Experimental Case Study in the Province of Iloilo, Philippines

The soil textures, soil settlements, soil water-holding capacity, and elevation angles are parameters for landslides in the Province of Iloilo. They are usually triggered during heavy rainstorms, causing severe property damage and sometimes causing casualties. This experimental study aims to determine how these parameters are factors for landslides and flood monitoring and uses three methods to provide ease and continuity of measurements. The Fourier transforms infrared (FTIR)spectroscopy analysis for soil textures, the Imhoff cone for the settling and water-holding capacity of the soil, and an improvised apparatus to test how the slopes affect the transportation of soil materials. FTIR Soil analysis reveals that contents of clay and organic matter directly affect soil water-holding capacity due to the larger surface area. The smaller particle sizes, such as clay, have a larger surface area leading to a higher water-holding ability. A landslide-prone zone has a lesser settling time except for the sand that settles fastest due to larger masses. An angle of 20 degrees has more mass movement too much higher slopes like 55 and 85 degrees. The increase in height or angle of the elevation decreases stability, leading to less mass movement. Less mass movement leads to the conclusion that there are rare landslides in the very high slope range due to fewer vibrations or soil movements caused by human activities and being compact or stable. This study is crucial for forecasting and preventing geohydrological processes and developing better landslide warning strategies to mitigate risks and reduce socioeconomic damage.

Identifikasi Zona Rawan Longsor Menggunakan Metode Geolistrik Resistivitas Di Desa Pao Kecamatan Tombolo Pao Kabupaten Gowa

This research aims to identify landslide-prone zones using the geoelectric resistivity method in Pao Village, Tombolo Pao District, Gowa Regency. The configuration used for data collection in the field is the Wenner-Schlumberger configuration using four the number of lines. The result of research indicates that the first line average is founded in each layer which is suspected to occur in a layer of soil and igneous rock in the form of lava with 2.10 Ωm- 12.7 Ωm in resistivity value. In the second line, the average is founded wet soil, dry soil and igneous rock with 1.26 Ωm – 11.1 Ωm in resistivity value. The third line average is an established layer of soil and lava with 2.18 Ωm – 6.51 Ωm in resistivity value. The fourth line is suspected to occur layer of soil and lava with 1.59 Ωm – 8.50 Ωm in resistivity value and 1.25 m – 15.9 m in depth. It can be concluded that the first and fourth lines, based on the resistivity value, are generated to occur in a layer of soil. Igneous rocks are supported by topography, slup reaching 30o – 35o. Meanwhile, the second and third lines do not happen landslide potential because the resistivity results contain igneous rock. Still, the topography, vegetation, and slup are not the landslide-prone category.

Application of statistical and machine learning techniques for landslide susceptibility mapping in the Himalayan road corridors

Abstract Landslides are frequent geological hazards, mainly in the rainy season along road corridors worldwide. In the present study, we have comparatively analyzed landslide susceptibility by employing integrated geospatial approaches, i.e., data-driven, knowledge-driven, and machine learning (ML), along the main road corridors of the Muzaffarabad district. The landslide inventory of three road corridors is developed to evaluate landslide susceptibility, and eleven landslide causative factors (LCFs) were analyzed. After statistical significance analysis, these eleven LCFs generated susceptibility models using WoE, AHP, LR, and RF. Distance from roads, landcover, lithological units, and slopes are considered more influential LCFs. The performance matrix of different LSMs is evaluated through the area under the curve (AUC-ROC), overall accuracy, Kappa index, F1 score, Mean Absolute Error, and Root Mean Square Error. The AUC-ROC for WoE, AHP, LR, and RF techniques along Neelum road is 0.86, 0.82, 0.91, and 0.97, respectively, along Jhelum Valley road is 0.83, 0.81, 0.93, and 0.95, respectively, while along Kohala road is 0.89, 0.88, 0.89, and 0.92, respectively. The produced LSMs through ML (i.e., RF and LR) showed better prediction accuracies than WoE and AHP along these three road corridors. The LSMs are categorized into very high, high, moderate, and low susceptible zones along these roads. The LSM generated through hybrid models can facilitate the concerned local agencies to implement landslide mitigation policies for the landslide-prone zones along road corridors.

SLIP SURFACE IDENTIFICATION FOR LANDSLIDE HAZARD MITIGATION WITH ELECTRICAL RESISTIVITY TOMOGRAPHY

Pidada area, Panjang sub-district, Bandar Lampung city, located on Barisan Hill complex, has been affected by the Sumatran fault movement and the Lampung-Panjang fault so that the morphological condition is hilly with steep slopes, which causes the risk of natural disasters such as landslides. In this article, the identification of subsurface rock lithology and sliding plane in the landslide-prone zone is carried out using the Wenner-Schlumberger configuration geoelectric method. Based on the Wenner-Schlumberger configuration, the top layer has lithology clay tuff and sandy tuff, which predicted a weathered rock with a resistivity of 1 - 133 ohm.m. Coarse-grained tuff and fine-grained tuff with resistivity values of 135 - 250 ohm.m in the middle. The bottom layer has a resistivity of more than 250 ohm.m, that predicted to have a lithology breccia (igneous rock) Tarahan Formation. The sandy clay layer (81 - 90 ohm.m) predict as a sliding plane in this area at depths of 8.2 to 16 m. The type of landslide developed in the research area is a crawling soil landslide with very steep slope characteristics (80 – 350).

Identification of landslide-prone zones using a GIS-based multi-criteria decision analysis and region-growing algorithm in uncertain conditions

Landslides are considered to be one of the most significant natural hazards. Detection of landslide-prone zones is an important phase in landslide hazard assessment and mitigation of landslide-related losses. AHP as one of the most effective methods for GIS-based multi-criteria decision analysis is increasingly being used in susceptibility mapping. However, its weights have some degree of uncertainty that interval comparison matrix (ICM) method can be used to deal with this problem. The importance of this study is to propose an interval number distance-based region-growing (IDRG) method based on ICM for the identification of landslide-prone zones in the Urmia lake basin, Iran. To assess the capability of the proposed IDRG method, a landslide susceptibility map was produced using common AHP, too. To generate the maps, the weights of nine conditioning factors were determined using both traditional pairwise comparison matrices of the AHP method and ICM. The accuracy of the produced maps was assessed through ROC (receiver operating curve) and using a dataset of known landslide occurrences. The results indicate an improvement in accuracy of about 11% by identifying the landslide-prone zones using the IDRG method. This improvement was achieved by minimizing the uncertainty associated with criteria ranking/weighting in a traditional AHP and identifying the prone zones as areas instead of pixels. Finally, the robustness of the proposed method was demonstrated by sensitivity analysis.

Spatio-Temporal Assessment of Land use / Land cover using Normalized Difference Vegetation Index (NDVI) of Satellite Imageries and its relationship with Landslide-prone Zones in Kodaikanal Hill Station of Tamil Nadu, India

The land use exercises at last influence the land cover briefly as well as spatially. The primary consideration liable for the adjustment in land cover is to satisfy the developing requests of expanding populace through horticultural increase for nourishment and clearing of typical land covers like the forests and sparsely inhabited regions for settlement and business activities. The adjustment in land cover additionally upsets the other characteristic parts like soil ripeness, soil disintegration, environment, biodiversity, air quality and water system of the upset area. Remote sensing and GIS have been deployed to examine the changes in land use and land cover of the zone at spatial and transient scales. In the present study, the NDVI-based grouping explored a significant change in land use- land cover between 2009 and 2016. A significant change has been found in the forest cover area where around (3.34%) of the forest was occupied between 2009 and 2016. A comparison between the land use/land cover and landslide hazard zones was carried out which indicated the excessive anthropogenic activities (of construction and mechanized agriculture) as identified by built-up land and crop-land by NDVI studies need to be monitored and planned to maintain the safety, stability and popularity of this precious and geo-climatically strategic region.

FOSS (Free Open Source Software) Integration to Implement WebGIS-Based Information System of Kelud Volcano

The purpose of this research is to establish a webGIS-based disaster information system. WebGIS application is used as a dissemination strategy of geospatial information of the data obtained from the surrounding area of Kelud Volcano. This application utilizes the Free Open Source Software (FOSS) standardized by the Open Geospatial Consortium (OGC). The initial step in the development of this system includes providing a database for geospatial data storing consisting of landslide-prone zones, land suitability, and tourism which were the focus of this research. The second step is the GeoJSON data conversion and Web Mapping Service (WMS) creation. This study has several results in the form of; 1) the establishment of a web-based GIS application system using FOSS standardized by OGC provides benefits in terms of cost efficiency in the development and provides convenience for the application because it is widely used by the community; 2) the development of information systems built in two directions between community participation and disaster web managers shows effective results; 3) the results of the two system tests show that the system built has no functional problems but, the version of the web browser used needs to be considered. This application is expected to build a communication aspect between policymakers and the community concerning an integrated disaster information management.