GIS-based Multi-criteria Analysis Research Articles

GIS-based multi-criteria land suitability analysis for sustainable agriculture in the northeast area of Tadla plain (Morocco)

Assessment of soil suitability for sustainable intensive agriculture is an appropriate tool to select the land suitable for agricultural production with the least economic and environmental costs. This study was conducted to evaluate the agricultural soil quality in the northeast area of Tadla plain (Morocco) using geographic information system (GIS) and analytical hierarchy process (AHP). Six soil quality indicators, i.e., pH, organic carbon, cation exchange capacity, texture, salinity and slope were considered and performed in 60 subsurface soil samples. AHP method was utilized to identify the weight of each indicator from the pairwise comparison matrix. The weighted sum overlay analysis was then used to generate the soil quality map in a GIS environment, by overlaying both indicator weights and sub-indicator weights. The studied area was classified into four soil quality categories, i.e., poor, medium, good, and excellent, the percentage of each category is 1.12, 20.98, 61.07 and 16.83%, respectively. The results indicated that 1.12% of the study area has poor suitability for sustainable intensive agriculture due to their unsuitable texture and low salinity, while about 77% of cultivated soils are adapted to agricultural production. The above results could be useful for the management of agricultural activity.

Land Suitability and Insurance Premiums: A GIS-based Multicriteria Analysis Approach for Sustainable Rice Production

The purpose of this research is to develop a land suitability model for rice production based on suitability levels and to propose insurance premiums to obtain maximum returns based on the harvest index and subsidy dependence factor for the marginal and moderately suitable lands in the northern part of Bangladesh. A multicriteria analysis was undertaken and a rice land suitability map was developed using geographical information system and analytical hierarchy process. The analysis identified that 22.74% of the area was highly suitable, while 14.86% was marginally suitable, and 28.54% was moderately suitable for rice production. However, 32.67% of the area, which was occupied by water bodies, rivers, forests, and settlements, is permanently not suitable; 1.19% is presently not suitable. To motivate low-quality land owners to produce rice, there is no alternative but to provide protection through crop insurance. We suggest producing rice up to marginally suitable lands to obtain support from insurance. The minimum coverage is marginal coverage (70%) to cover the production costs, while the maximum coverage is high coverage (90%) to enable a maximum return. This new crop insurance model, based on land suitability can be a rational support for owners of different quality land to increase production.

Planning the next-generation biofuel crops based on soil-water constraints

Widely blended in the transportation fuels, biofuels have been generally regarded as indispensable components in the U.S. national energy portfolio. Although the current production of cellulosic biofuels has been staggering at pilot scales, it is expected that large-scale cultivation of cellulosic biofuel crops may occur when techniques for cost-effective bioconversion of lignocellulosic biomass to ethanol are available. However, it is still unclear if enough land is in existence to accommodate potential large-scale lignocellulosic crops development without negative effects on the environment and food market. The appropriate land use for the next-generation biofuel crops should be planned and allocated in a manner that the competitive use of land dedicated to food and energy production and other side effects could be minimized. This research proposes an approach of identifying the potential available land for planting switchgrass in the U.S. Midwest using a GIS-based multi-criteria analysis that combines soil and water constraint factors. The results showed that land areas of approximately 13.6 million ha are unsuitable for profitable food crops but available for switchgrass cultivation in 7 U.S. Great Plains states. The findings can assist decision-makers in formulating land use policies and related environmental management strategies.

Site selection of urban wildlife sanctuaries for safeguarding indigenous biodiversity against increased predator pressures

Biodiversity loss in urban landscapes is a global challenge. Climate change is a major driving force behind biodiversity loss worldwide. Using Wellington, New Zealand as a research site, the aim of this research is to show how the most suitable patches of vegetation in urban landscapes can be identified, ranked, and prioritised as potential urban wildlife sanctuaries. This is in order to protect vulnerable indigenous fauna from some of the indirect impacts of climate change such as increased predator pressures and the spread of diseases among urban fauna caused by rising temperatures. A GIS-based multi-criteria analysis of spatial composition and configuration of patches of vegetation was undertaken with reference to eight factors affecting the quality of habitat patches and accordingly fauna behaviours in urban landscapes. Results show that Zealandia, the Wellington Botanic Garden, the Town Belt, and Otari-Wilton’s Bush are respectively the most important urban sites for establishing pest-free urban wildlife sanctuaries in the study area. This research reveals that patch size should not be considered as the single most important factor for the site selection of urban wildlife sanctuaries because the collective importance of other factors may outweigh the significance of patch size as a single criterion. Lessons learned in the course of this research can be applied in similar cases in New Zealand or internationally in order to facilitate the process of site selection for the establishment of urban wildlife sanctuaries in highly fragmented urban landscapes suffering from rising temperatures and other climatic changes.

GIS-based assessment of sustainable crop residues for optimal siting of biogas plants

The assessment of biomass at high spatial resolution is critical to manage supply risks and to identify optimal plant sites for producing sustainable biofuels and co-products. The spatial variabilities in soil type, topography, climate, and crop management practices further require vast computational time and resources to estimate the availability of sustainable biomass for a large study area. In this study, we developed a GIS-based integrated predictive modeling platform to assess the availability of sustainable crop residues at high spatial (30 m) and temporal (2010–2022) scales. A GIS-based multi-criteria inclusion-exclusion analysis and facility location-allocation models were used to identify suitable sites, and optimal siting of biogas plants respectively with biomass delivered cost. The Artificial Neural Network (ANN) based predictive models were well suited to predict sustainability indicators (soil erosion SE- R2 = 0.96, soil conditioning index, SCI R2 = 0.98 and organic matter factor, OMF- R2 = 0.83) for assessing sustainable removal rates of crop residues (corn stover and wheat straw). The GIS-based integrated model was applied to the State of Ohio and found that about 4–13 dry Tg of crop residues can be sustainably available to build 1–25 regional biogas plants. A typical optimal biogas plant with a feedstock capacity of up to 500 dry Gg could be drawn from a transport radius of about 19–35 km with a delivered cost of 40–46 $ dry Mg−1. The temporal and spatial variations in assessing the availability of biomass largely affected the supply chain decisions and its delivered costs.

Tsunami hazard and buildings vulnerability along the Northern Atlantic coast of Morocco \u2013the 1755-like tsunami in Asilah test-site

BackgroundThe Atlantic Coast of Morocco is prone to tsunami inundation. Therefore, in this region, earthquake-induced tsunami hazard has been intensively investigated leading to the development of a number of coastal inundation models. However, tsunami vulnerability remains not well understood to the same extent as the hazard. In this study, we use high-resolution numerical modeling, detailed field survey and GIS-based multi-criteria analysis to assess the building tsunami vulnerability and its sensitivity to the tide variations. Asilah located in the northwestern Atlantic coast of Morocco, where the impact from the 1755 tsunami is well documented, constitutes the area of this study.ResultsTo model the source-to-coast tsunami processes we used the COMCOT (Cornell Multi-grid Coupled Tsunami Model) numerical code on a set of bathymetric/topographic grid layers (640 m, 160 m, 40 m and 10 m resolutions) with an initial sea-surface perturbation generated using Okada’s formulae and assuming an instantaneous seabed displacement. The tsunami source models in this study correspond to four 1755-like earthquake scenarios. Results show that Asilah’s built environment is highly vulnerable to the tsunami impact that can range from 1.99 to 2.46 km2 of inundation area, depending on the source and the tidal level considered. The level of building vulnerability decreases considerably when moving away from Asilah’s coastline. Moreover, the variation in the tidal level introduces large change in the modeled tsunami impact and, therefore, affects the level of building vulnerability. ConclusionThus, we suggest considering the effect of the tide when simulating tsunami hazard and vulnerability, particularly, in coasts where tidal variations are significant. This study provides hazard and vulnerability maps that can be useful to develop the tsunami awareness of the Moroccan coastal population.

Flood risk assessment in a coastal lagoon under present and future scenarios: Ria de Aveiro case study

Floods are one of the major threats to low-lying coastal lagoons, affecting people, socio-economic activities and ecosystem services. This work proposes a methodology to assess present and future flood hazard and risk in west-boundary low-lying coastal lagoons, using the Ria de Aveiro (Portugal) as case study. A multidisciplinary approach supported on Source–Pathway–Receptor–Consequence model combined with a GIS-based multi-criteria analysis was developed and applied. This comprised the following steps: (1) definition of present and future climate scenarios associated with oceanic, fluvial and combined events, combining sea levels and river discharges for different return periods; (2) characterization of flooding pathway through hydrodynamic modelling; (3) assessment of flood hazard combining flood depth and probability from hydrodynamic simulations; (4) assessment of flood risk calculating the adverse consequences on assets exposed to flood hazard. Results highlight that endangered regions are strongly dependent on the floods origin: oceanic floods threaten settlements and economic activities located along the margins of the lagoon main channels as well as habitats in the lagoon central area; fluvial floods endanger the river’s mouth adjacent areas causing damage in restricted settlements, economic activities and farmland habitats; the combined floods also threaten the margins adjacent to the transition zones. For future scenarios, it is predicted the flood risk increase/decrease for oceanic/fluvial events, as a consequence of mean sea level rise/river discharges reduction predicted for the region. Finally, this work demonstrated the value of the methodology proposed and its potential for flood risk analysis, supporting the decision-making process underlying the flood risk management.

GIS-based multi-criteria analysis and vulnerability method for the potential groundwater recharge delineation, case study of Manouba phreatic aquifer, NE Tunisia

Groundwater resources in semi-arid climate like Manouba region (North of Tunisia) have experienced deterioration of available water resources in terms of both quantity and quality. Managers and water engineers developed techniques to compensate for the high exploitation and remedy the poor quality of groundwater resources. One of the most important solutions is to focus on the recharge capacity of the aquifer. This paper aims to locate potential groundwater recharge areas using the multi-criteria approach. Delineation of groundwater potential recharge zones relies on physical parameters and groundwater vulnerability. Geographical information system can provide tools for handling multidisciplinary data used for each parameter. In this work, weighting coefficients attributed for parameters are assigned based on local conditions in the region, using the analytic hierarchy process by applying the intelligent decision system software. Results show that most of the study area has a groundwater recharge rate potentially moderate to high. Only 24% of the study area have low groundwater recharge rate located especially in Sebkhat Essijoumi and its vicinity, that mainly match to the least permeable and hilly areas. Considering both the vulnerability to pollution and the potential groundwater recharge capacity, the most suitable recharge sites are located in the North West of the study area.

GIS-based multi-criteria analysis modeling used to locate suitable sites for industries in suburban areas in Bangladesh to ensure the sustainability of agricultural lands

Land use changes significantly affect the sustainability of food security, environmental quality and the ecological balance in developing countries. Bangladesh is one such country, and it faces challenges caused by its limited resources of arable land. The urbanization of agricultural lands and urban developments in suburban areas add to these challenges. Therefore, the aim of this study is to characterize the land use changes that occur over time in suburban areas that have potential for industrial growth. This study also assesses potential locations for industrial development by using land suitability analysis (LSA) to emphasize both agricultural and industrial development in terms of sustainable growth. A geographical information system (GIS)-based multi-criteria analysis (MCA) model is developed for the LSA to distinguish compact parcels that are suitable for industrial economic zones. Nine criteria, including seven constraints and 23 factors, are evaluated using the spatial analysis tools in ArcGIS®. An analytical hierarchy process (AHP) is applied to prioritize these criteria based on experts opinion for the decision-making process of LSA. This study finds that the construction of densely clustered industrial areas has decreased the area of agricultural land by more than 10% in the last two decades. Furthermore, the results of the LSA show that only 4% of the land was highly suitable for industrial sites. On the other hand, four compact parcels that contain 16–10 ha of land and suitable for small industrial zones exist within the study area. Thus, the integrated GIS-MCA model can serve as a policy and planning tool for locating industrial economic zones while preserving agricultural lands and retaining environmental protections.

A RECONNAISSANCE-SCALE GIS-BASED MULTICRITERIA DECISION ANALYSIS TO SUPPORT SUSTAINABLE BIOCHAR USE: POLAND AS A CASE STUDY

Although increasing numbers of research papers regarding biochar are being published worldwide, in some countries growing interest in biochar has only recently been observed; this is true of Poland. We analysed information on biochar research in Poland alongside lessons learned elsewhere in order to identify the significant opportunities and risks associated with biochar use. This data fed into a GIS-based multicriteria analysis to identify areas where biochar application could deliver greatest benefit. We found that 21.8% of agricultural land in Poland has at least moderate indication for biochar use (soil organic matter below 2% and ph below 5.5), while 1.5% was categorized as a priority as it also exhibited contamination. Potential barriers identified included biomass availability and associated risks of indirect land-use change due to possible national and transnational biomass production displacement. Biochar use could have positive global consequences as a climate change mitigation strategy, particularly relevant in a country with limited alternatives. Scaling up a mitigation technology that is viable on account of its co-benefits might be cost-effective, which could, in turn, adjust national perspectives and stronger involvement in developing mitigation policies at the regional level. Biochar has much promise in temperate conditions and further research should therefore be assigned to explore biochar’s environmental and socio-economic impacts.

Geographic origins of a War of 1812 skeletal sample integrating oxygen and strontium isotopes with GIS-based multi-criteria evaluation analysis

The oxygen and strontium isotope composition of human bones and teeth are used to investigate human geographic origins and mobility in the archaeological record. We measured the oxygen (18O/16O) and strontium (87Sr/86Sr) isotope ratios in 14 teeth and 22 bone sections from 19th century soldiers who died in the Battle of Stoney Creek, Ontario, and were buried in a commingled mass grave at Smith's Knoll. To spatially locate the tooth isotope data we generated overlay maps of the eastern United States and Great Britain based on regional 87Sr/86Sr and meteoric precipitation δ18O variation. To do this, we employed a new method to visualize the isotopic information using GIS-based Multi-Criteria Evaluation analysis (GIS-MCE), a computational algorithm yet to be applied to stable isotope migration research. Our data confirm historic information concerning the areas from which American and British soldiers originated or were recruited, namely from the mid- to northerly latitude United States and Great Britain. This approach revealed the probable identity of at least one British soldier, and possibly one American soldier within the Smith's Knoll assemblage, making it the first archaeological study to provide substantial evidence for the identity of individuals interred in a mass grave. Our analysis highlights a new way to integrate isotopic and geophysical data through GIS-MCE technology to locate the most likely place of origin of individuals in a skeletal sample.

A GIS-based multi-criteria analysis model for earthquake vulnerability assessment using Choquet integral and game theory

A GIS-based multi-criteria analysis model using the integration of the Choquet integral and game theory is proposed in this paper for seismic vulnerability assessment (SVA). The proposed SVA model is able to take into account the effects of complementary, redundant, and independent criteria. Moreover, the proposed model provides an insight into experts’ preferences using game theory parameters. The application of the proposed model is demonstrated by assessing the seismic vulnerability of Tehran city. Due to the limited accessibility to data, only nine contributing criteria are specified which are associated with physical, social, and systemic vulnerability. Five experts are asked to determine the seismic vulnerability degree of 100 randomly selected urban statistical units. Particle swarm optimization method is then applied to extract fuzzy measures from information provided by the experts. Game theory is also employed to compute the interactions among the criteria and to evaluate the role of each criterion in the decision-making process. Finally, a vulnerability map is produced based on the knowledge of the consensus of the five experts and the results are validated by comparing with the previous models using Spearman’s correlation coefficient method.

Satellite remote sensing and GIS-based multi-criteria analysis for flood hazard mapping

This work focuses on the exploitation of very high-resolution (VHR) satellite imagery coupled with multi-criteria analysis (MCA) to produce flood hazard maps. The methodology was tested over a portion of the Yialias river watershed basin (Nicosia, Cyprus). The MCA methodology was performed selecting five flood-conditioning factors: slope, distance to channels, drainage texture, geology and land cover. Among MCA methods, the analytic hierarchy process technique was chosen to derive the weight of each criterion in the computation of the flood hazard index (FHI). The required information layers were obtained by processing a VHR GeoEye-1 image and a digital elevation model. The satellite image was classified using an object-based technique to extract land use/cover data, while GIS geoprocessing of the DEM provided slope, stream network and drainage texture data. Using the FHI, the study area was finally classified into seven hazard categories ranging from very low to very high in order to generate an easily readable map. The hazard seems to be severe, in particular, in some urban areas, where extensive anthropogenic interventions can be observed. This work confirms the benefits of using remote sensing data coupled with MCA approach to provide fast and cost-effective information concerning the hazard assessment, especially when reliable data are not available.

GIS-based multi-criteria analysis of breeding habitats for recolonising species: New Zealand sea lions

The New Zealand sea lion (Phocarctos hookeri) is a threatened endemic species, with only three breeding colonies in the sub-Antarctic islands. Since 1993, there has been evidence for recolonisation of mainland New Zealand. Yet the coast that the sea lion has returned to only has fragmented and unevenly distributed potential habitats due to coastal urbanisation and development. Therefore, the need to identify and protect potential breeding habitats for recolonisation is a priority for management.A GIS-based multi-criteria analysis was used to identify potential suitable habitats for a 1600 km length of the NZ South Island coast based on distance to anthropogenic disturbance (urban areas, roads), distance to desirable environmental features (beaches, estuaries) and presence of suitable habitat/land access. From this model, we identified preliminary suitable habitat for breeding sites on the Otago Peninsula (east coast) and Catlins Coast (south). We independently detected some of the current dominant areas used by recolonising sea lions as well as identifying some promising new sites.We discuss the limitation of the results of this case study and the need for further data to be added to the model in the face of limited data availability. Overcoming this data limitation will meet an increasing need for a New Zealand-wide study for determining potential habitat for NZ sea lions. The results of such a study would identify areas to allow real-world management (protection or restoration) of the limited potential breeding sites for New Zealand sea lions. This new method could also be used for other recolonising species and encourage management of areas most likely to be recolonized by them.

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world.

A decision support approach for the selection and implementation of water harvesting techniques in arid and semi-arid regions

Water harvesting techniques (WHTs) improve the availability of water, which is essential for growing crops, especially in arid and semi-arid areas. A decision support approach can help in the selection of WHTs suitable under site-specific bio-physical and socio-economic conditions. This paper describes a participatory approach for the selection of suitable WHTs in watersheds in (semi) arid regions. It builds on a database of suitability indicators for WHTs, which was developed by integrating worldwide knowledge on their suitability. Once developed, the approach was applied on a case study for WHTs in the upper Geba watershed in northern Ethiopia. First, based on evaluation criteria and participants’ scientific and local knowledge, a pre-selection of most promising WHTs took place in a multi-stakeholder workshop. Next, the suitability indicators and a GIS-based multi-criteria analysis (MCA) were used to identify suitable areas for these WHTs. The results of the MCA were presented to stakeholders during a second stakeholder workshop. At this workshop, a final selection of WHTs to test was made based on a participatory ranking of WHTs using economic, ecological and socio-cultural criteria. The MCA approach was validated by comparing the predicted suitable areas with the already existing WHTs in the watershed. This led to the result that 90% of the existing check dams and 93% of the percolation ponds were correctly identified by the approach. We conclude therefore that this approach can be successfully applied for the participatory selection of WHTs and the identification of suitable areas for their implementation. Given that this approach is based on the newly developed database of WHTs, it can be easily applied in other (semi) arid regions.

Applying spatial analysis to the agroecology-led management of an indigenous farm in New Zealand

In Aotearoa New Zealand Māori land is often owned by communities and managed by trusts. Under communal ownership, trust managers are expected to provide for their communities in culturally responsive ways, using alternative land-related paradigms. In the context of Māori trust rural land management, geographic information systems (GIS) are seen as a beneficial resource to plan and support important decisions that have community-wide implications. For example, it is much easier to demonstrate visually the putative outcomes of spatial change to large numbers of people with the help of a GIS than it is to verbalise the effects of change. This paper reports on one aspect of such an application to a Māori trust-owned South Island farm, where a GIS-based multi-criteria analysis of terrain and proximity was conducted using also local botanical knowledge input to indicate optimal areas of growth for traditional medicinal plants. The analysis yielded very useful results, with positive feedback received from the local community. As well as the need to verify the approach empirically, there are plans underway to apply GIS in this way to other similarly-managed farms in Aotearoa New Zealand. However, in order to build a more comprehensive decision support resource for farm management, further plant species need to be modelled, and informed by a wider data set that includes detailed soil data.

Mapping land use competition in the rural–urban fringe and future perspectives on land policies: A case study of Meknès (Morocco)

The geographical and socio-economic characteristics of peri-urban areas make them particularly vulnerable to land use competition. They are transitional zones, in continuous transformation, where various economic activities attempt to co-exist in equilibrium. Peri-urban agriculture plays a key role in this dynamic, functioning in a complex system that includes a large and diverse set of stakeholders which act to provide environmental and economic services to cities. The work described in this paper was undertaken to develop a methodology to map land use competition in terms of vulnerability to urbanization of agricultural lands, based on explicit spatial indicators set up in a GIS-based multi-criteria analysis (hereafter GIS-MCDA). The applied indicators are generated from an analysis of existing drivers of land use competition within the peri-urban area of Meknes (Morocco). This area is particularly interesting because of its agricultural characteristics, and because of recent changes in the dynamics of land use and tenure. This case study indicates a high risk of land competition in 37% of the area examined, and a very high risk in 16% of the area. The highest risk areas are located in the southern part of the peri-urban region, which is also considered the most valuable in terms of agricultural production. The map we have developed can be considered a preliminary tool for improving new planning strategies to manage land resource competition in rural–urban fringe zones. The approach presented is particularly useful as a simplified methodology to obtain spatialized indicators for the drivers of land use competition when data are limited, as often found in developing countries.

Design of a GIS and multi-criteria based land evaluation procedure for sustainable land-use planning at the regional level

Designof comprehensive, standardized land evaluation tools is challenged by constraints of scale, data availability, validity, and mathematical translation and combination of diagnostic indicators. This study aims to design a GIS-based multi-criteria land suitability analysis that integrates agro-ecological aptitude, environmental impact and socio-economic feasibility criteria in a step-wise procedure combining recent advances in indicator selection, evaluation and weighing – exploiting information from various data sources – with functional mathematical combination procedures. The procedure involves: (1) selection of diagnostic land characteristics, (2) design of the corresponding evaluation criteria and consequent scoring of the diagnostic characteristics, (3) arithmetic combination of the scored characteristics into partial performance indices for agro-ecological aptitude, environmental impact and socio-economic feasibility, and (4) classification of the performance indices into aptitude, impact, and feasibility classes and determination of the overall land suitability class of the proposed land use. The tool’s performance and applicability proved successful in a case study, identifying expansion zones for rubber in Quang Tri province, Vietnam. Local expert knowledge, relevant literature sources, factor-yield relationships and the discriminating power of different land characteristics within the given environment were successfully integrated to select, score and weigh diagnostic land characteristics. Explicit distinction between factors and constraints depending on the fuzziness of their spatial patterns, and between limiting and non-limiting factors depending on their impact and interaction, furthermore allowed to apply the most relevant arithmetic combination procedures.

Mapping landslide susceptibility using satellite data and spatial multicriteria evaluation: the case of Helwan District, Cairo

Landslides are one of the critical geological hazards which cause damage to civil engineering structures such as roads, railways, bridges, dams, and houses and may lead to loss of life. During the last two decades, Cairo region has experienced several landslides and land subsidence events causing destruction at many locations. In this paper, satellite data and a GIS-based multicriteria analysis were used to assess the landslide susceptibility of East Cairo-Helwan region. Such area has been subjected to geohazard events that were accelerated by anthropogenic activities such as quarrying and blasting. The area encompasses seven new cities that have been partially constructed during the last decades. The cities are 10th Ramadan, El Ebour, New Cairo, El Amal, El Sherouk, 15 May, and Badr. Seven factors triggering landslides; slope angles, rock type, faults, elevation, seismic intensity zones, stream density and land cover were input to the model to produce a landslide susceptibility map. Such a map was used to examine the susceptibility of the locations of the seven new cities. The result revealed the high vulnerability of the locations of El Amal and 15 May cities and few zones including south of Cairo city. For verification, high-resolution image and a fine-scale geological map were used. Earlier field investigations were also compared to the result. We believe that the resultant landslide susceptibility map provides some guidelines to land use management and planning in the investigated area.