Spatial Decision Research Articles

Storm Surge Risk Assessment in Coastal Communities in the Rio Grande Valley: An Application of GIS-Based Spatial Multicriteria Decision Analysis with Analytical Hierarchy Process

Kyne, D., 2023. Storm surge risk assessment in coastal communities in the Rio Grande Valley: An application of GIS-based spatial multicriteria decision analysis with analytical hierarchy process. Journal of Coastal Research, 39(3), 471–483. Charlotte (North Carolina), ISSN 0749-0208. Cameron County, which is located in the Rio Grande Valley, maintains records of storm surges associated with noticeable property damage, fatalities, and injuries. This study investigates storm surge inundation risk in Cameron County using storm surge hazard datasets from the National Oceanic and Atmospheric Administration, along with American Community Survey 2019 block group datasets. Using a GIS-based spatial multicriteria decision analysis with an analytical hierarchy process method, the study estimates that storm surge water levels could be above 6.1 m (20 ft) in category 4 and 5 hurricane events, whereas about 37% of the county's population (159,659 people) could be exposed to floodwater in the event of a category 5 hurricane. The inundation risk map shows that in the event of a category 4 or 5 hurricane, about 28 and 42%, respectively, of county's area could be exposed to a very high level of inundation risk. Because of the destructive power of such storms and their potential consequences, the findings suggest that storm surge risk should not be underestimated. All stakeholders should proactively prepare for potential storm surge events.

THE JOINT SPATIAL PLANNING DATA MODEL

Abstract. In modern times, spatial planning activities have been the process of determining projections for future land use. Spatial plans produce decisions about space in many different fields, from construction to transportation and environmental, natural, and cultural protection. The right, restrictions, and responsibilities (RRRs) to use the land pieces whose physical borders and legal status are registered with the cadastral process are determined by the spatial plans in line with the national purposes, public welfare, and healthy urbanization objectives.Land Administration Domain Model (LADM) is a general-purpose data model introduced in 2012 with International Organization for Standardization (ISO) standards. LADM proposes standards for many data infrastructures and land administration systems. In this context, although it does not have complete recommendations within the scope of spatial planning. It is essential to make additions to version II. As a result of gradual studies, spatial planning processes and decisions can be presented in a data model and the model can be associated with the LADM standard structure and integrated into land registration systems. Since LADM offers a conceptual model, newly created packages must be designed in a conceptual data model. The conceptual model is a product of several stages. This study focuses on how can produce a conceptual model in which countries can share spatial planning data. The requirements of the model that achieves this aim are revealed by considering the conceptual model production stages. By evaluating the findings, how can obtained data which helping to design the classes, class relations, and attributes of the data model were searched. With the conceptual data model to be prepared in line with the requirements, it is thought that land management processes can be strengthened by providing integration with spatial plans in LADM-based land administration systems.

A service-oriented collaborative approach to disaster decision support by integrating geospatial resources and task chain

The benefits of geospatial technologies in disaster management have reached a consensus in the international community. However, immediate integration and orchestration of the rich geospatial resources (data, algorithms, computing resources, etc.) in an emergency remain challenging due to the four gaps: encoding gap, source gap, knowledge gap, and network gap. Aiming to bridge the “resource islands”, we propose a service-oriented collaborative approach to disaster decision support by integrating geospatial resources and task chain as domain knowledge into a distributed environment. Data contributors, model contributors, GIS developers, and business experts collaboratively build a spatial decision support system (SDSS) that integrates various resources and knowledge. When disaster strikes, responders collaboratively perform emergency tasks to deliver the right information to the right person at the right time by leveraging the SDSS. The proposed approach is implemented as a Geospatial service platform for Disaster Response (GeoDR). Four joint exercises and the operation in relevant institutions in China demonstrate its capability to facilitate timely and effective responses to natural disasters.

Spatial structure and influencing factors of regional city supply networks in manufacturing: A case study of Shandong, China

COVID-19 has driven the formation of regional supply chains. In addition, cities became the basic units of intra-regional supply chain organization under urban administrative economies. Based on the data mining of the buyer-supplier relationship of listed manufacturing firms, this study explores the spatial characteristics of city supply networks within Shandong by the indexes of degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, and a community detection algorithm using the social network analysis (SNA) method and ArcGIS software. It investigates the influencing factors of city supply networks by the correlation and regression of the quadratic assignment procedure (QAP). The results show the following: 1) Shandong has formed a multi-center city supply network with Jinan, Qingdao, Yantai-Weihai, and the distribution pattern of city centrality measured by different centrality indicators shows differences. 2) Cities belonging to the same network community show a coexistence of spatial proximity and “enclave” distribution. 3) Geographic proximity, convenient transportation links, administrative district economy, similarity of business environments represented by development zones, export-oriented or domestic market-oriented division of labor between cities, value chain division of labor between cities, and land price differences between cities promote the formation of regional city supply networks. Conversely, differences in local market size and wage levels between cities hinder the formation of city supply networks. This study attempts to apply the analysis results to regional planning from the perspective of regional industrial synergy development. Additionally, as it is based on typical Chinese provinces, it can provide policy references for national administrative regions and countries/regions at similar spatial scales for manufacturing supply chains, as well as for regional spatial layout decisions of manufacturing enterprises.

Ripples in macaque V1 and V4 are modulated by top-down visual attention

Sharp-wave ripples (SWRs) are highly synchronous neuronal activity events. They have been predominantly observed in the hippocampus during offline states such as pause in exploration, slow-wave sleep, and quiescent wakefulness. SWRs have been linked to memory consolidation, spatial navigation, and spatial decision-making. Recently, SWRs have been reported during visual search, a form of remote spatial exploration, in macaque hippocampus. However, the association between SWRs and multiple forms of awake conscious and goal-directed behavior is unknown. We report that ripple activity occurs in macaque visual areas V1 and V4 during focused spatial attention. The occurrence of ripples is modulated by stimulus characteristics, increased by attention toward the receptive field, and by the size of the attentional focus. During attention cued to the receptive field, the monkey's reaction time in detecting behaviorally relevant events was reduced by ripples. These results show that ripple activity is not limited to hippocampal activity during offline states, rather they occur in the neocortex during active attentive states and vigilance behaviors.

Meeting Human and Biodiversity Needs for 30 × 30 and beyond with an Iterative Land Allocation Framework and Tool

Spatial conservation prioritization does not necessarily lead to effective conservation plans, and good plans do not necessarily lead to action. These “science-action” gaps are pernicious and need to be narrowed, especially if the international goal of conserving 30% of the planet by 2030 is to be realized. We present the Earthwise Framework, a flexible and customizable spatial decision support system (SDSS) architecture and social process to address the challenges of these science-action gaps. Utilizing case study experience from regions within California, South Africa, and British Columbia, we outline the framework and provide the Little Karoo, South Africa SDSS data, code and results to illustrate five design strategies of the framework. The first is to employ an “open science” strategy for collaborative conservation planning and action. Another is that marginal value functions allow for the continuous accounting of element (e.g., habitat) representation in prioritization algorithms, allowing for an SDSS that is more automated and saves valuable time for stakeholders and scientists. Thirdly, we program connectivity modeling integrated within the SDSS, with an algorithm that not only automatically calculates all the least cost corridors of a region, but prioritizes among them and removes the ones that do not make ecological sense. Fourth, we highlight innovations in multi-criteria decision analysis that allow for both cost-efficient plan development, like representative solution sets, but also land-use planning requirements, like site specific valuation, in what appears to be a more transparent, understandable, and usable manner than traditional approaches. Finally, strategic attention to communicating uncertainty is also advocated. The Earthwise Framework is an open science endeavor that can be implemented via a variety of software tools and languages, has several frontiers for further research and development, and shows promise in finding a better way to meet the needs of both humans and biodiversity.

FULL POLARIMETRIC TIME SERIES IMAGE ANALYSIS FOR CROP TYPE MAPPING

Abstract. Crop information and quality are not only fundamental for experts using spatial decision support systems but also have many applications in irrigation management, economic analysis for import or export, food safety, and achieving sustainable agriculture. Remote sensing is a cheap and fast way of reaching this goal. Full polarimetric SAR unlike optical sensors is an all-weather system providing geometrical and physical properties of the earth’s surface events. Due to the dynamic changes in crop properties through their phenological stages, crop type mapping has been challenging. As a result, accurate, reliable, and cost-effective crop type mapping using minimum data and processing has been the goal of the remote sensing and precision agriculture community. In this study, a new method based on time series analysis of full polarimetric SAR data combined with radar indices, polarimetric decompositions followed by the three αs extracted from H/A/α decomposition, and unsupervised H/α/Wishart classification bands as features generated from only 5 dates of RADARSAT CONSTELLATION MISSION 2 data were used for classification of crops. Applying random forest and cat boost algorithm as classifiers an accuracy of 87.4% and 75% was respectively achieved. indicating that both algorithms have promising results. Although the random forest algorithm had better results, the cat boost algorithm had less noise in each field and more homogenous farms were detected.

Herbestemming na de mijnsluiting. De ruimtelijke plangeschiedenis van Parkstad en het Emmaterrein, 1965-1997

Repurposing the Closed Coalmines. Spatial Planning in Parkstad and the Former State Mine Emma, 1965-1997. After the closing of the Dutch coal mines in the former Eastern Mining region in the south-eastern tip of the Netherlands, mining landscapes were wiped clean and industrial relics were all but completely demolished. The radical efficiency of this transition has, in current day, induced a public feeling of remorse over the lost physical proof of the mining period. This article traces how economic and programmatic parameters have guided spatial decision-making during the clean-up operation, and how was dealt with the possibility of preservation of mining relics. The article primarily analyses spatial planning documents responding to the closure of the mines, drawing forward the discourse underlying the restructuring of the region. Secondly, it discusses conceptualization, negotiation and problem solving targeted at the obsoleted mining infrastructure. Focusing on the terrain of former State Mine Emma, an intricate case in the light of this prevailing planning discourse, is put centre stage. The inflexible interdependence between a fixed spatial programme and a financial model is pinpointed as the key factor underlying the protracted redevelopment trajectory.

Spatial Perception Imperatives in Virtual Environments: Understanding the Impacts of View Usage Patterns on Spatial Design Decisions in Virtual Reality Systems

Spatial perception in virtual reality systems relies on a number of variables, including how users explore, observe and perceive the spatial factors of a virtual environment. In virtual reality systems, users can assume different types of views for spatial decision-making about the sizes and scales of and relationships among virtual spaces. This research explored the role of view usage patterns in spatial cognition and decision-making in a fully immersive virtual reality system and monitor-based virtual reality system. The focus of study was the impact of using the eye-level view as the only view type in a fully immersive virtual reality system on actual and perceived view usage patterns in a monitor-based virtual reality system. In addition, users’ spatial decision-making results were compared with regards to system usage sequence and view type. Quantitative and qualitative data, descriptive and inferential statistical comparisons, and testing of both systems were used to determine the participants’ performances concerning view usage patterns and the design outcomes. The results showed a moderate association between the view type utilized for spatial perception in a monitor-based virtual reality system and variations in system usage sequence. In addition, for both systems, variations in system usage sequence, space type, and other characteristics all affected the strength of the linear regressions of the sizes and scales of the design outcomes.

A GIS-Based Probabilistic Spatial Multicriteria Roof Water Inrush Risk Evaluation Method Considering Decision Makers’ Risk-Coping Attitude

A combination of geographic information system (GIS) and spatial multicriteria decision making (MCDA) in mine water inrush risk evaluation is widely used, but the randomness in the process of index weight determination and the risk-coping attitude of decision makers are not considered in the decision making process. Therefore, this paper proposes a probability-based roof water inrush risk evaluation method (GIS-MCDA) by combining the Monte Carlo analytic hierarchy process (MAHP) and ordered weighted averaging (OWA) operator. This method uses MAHP to determine the weight of the evaluation indicators, reducing the randomness of the analytic hierarchy process (AHP) to determine the weight of the evaluation indicators using the OWA operator to quantify the five risk-coping attitudes of decision makers and incorporate the risk attitude of decision makers into the evaluation process. Taking the Liangshuijing Coal Mine in northern Shaanxi as an example, the application of the GIS-MCDA method showed that the method makes the risk results of roof water inrush more objective and comprehensive and reduces or avoids the risk of decision making due to human subjective tendency change.

Enhanced Reactivation of Remapping Place Cells during Aversive Learning.

Study of the hippocampal place cell system has greatly enhanced our understanding of memory encoding for distinct places, but how episodic memories for distinct experiences occurring within familiar environments are encoded is less clear. We developed a spatial decision-making task in which male rats learned to navigate a multiarm maze to a goal location for food reward while avoiding maze arms in which aversive stimuli were delivered. Task learning induced partial remapping in CA1 place cells, allowing us to identify both remapping and stable cell populations. Remapping cells were recruited into sharp-wave ripples and associated replay events to a greater extent than stable cells, despite having similar firing rates during navigation of the maze. Our results suggest that recruitment into replay events may be a mechanism to incorporate new contextual information into a previously formed and stabilized spatial representation.SIGNIFICANCE STATEMENT Hippocampal place cells provide a map of space that animals use to navigate. This map can change to reflect changes in the physical properties of the environment in which the animal finds itself, and also in response to nonphysical contextual changes, such as changes in the valence of specific locations within that environment. We show here that cells which change their spatial tuning after a change in context are preferentially recruited into sharp-wave ripple-associated replay events compared with stable nonremapping cells. Thus, our data lend strong support to the hypothesis that replay is a mechanism for the storage of new spatial maps.

Determination of Optimized Locations for Modular Rice Paddy Aggregation Centres in Anambra State, Nigeria by GIS-Based Approach

In this study an attempt was made to appraise the adequacy of the existing number and Locations of Rice aggregation centres (RAC) in the state and propose optimal numbers and their locations in the eight agricultural zones of Anambra state, Nigeria using Geographic Information System (GIS) methodology. This method involves spatial decision, which deals with a large set of feasible alternatives through the use of remotely sensed data in providing the required spectral and spatial information for generating information layers for rice aggregation centres selection criteria. The study discovered thirteen sites fulfilling all sitting criteria for location of rice aggregation centres. The results propose that two locations be allotted to Ayamelum in addition to the 4 existing centres, thereby bringing it to a total of 6 aggregation centres with a mean distance of 2.8km. Anambra East which had one aggregation centre was allocated 2 aggregation centres with a mean distance of 2.65km from the rice farms. Anambra West which previously had no aggregation centre was allocated one aggregation centre with a mean distance of 2km. Awka North was also allocated two aggregation centres with a mean distance of 3.3km from the rice farms. Orumba South which previously had no centre was proposed one aggregation centre with a mean distance of 4.1km from the rice farms. Orumba North which previously had no centre was allocated two aggregation centres with a mean distance of 3.4km from the rice farms. Ihiala, had no aggregation centre but was allocated 1 aggregation centre which has a mean distance of 3.6km from the rice farms. Ogbaru previously had one aggregation centre but was allocated 1 more aggregation centre with a mean distance of 3.8km from the rice farms. These results have shown that GIS-based location modelling can be successfully used in locating agro-service centres such as products aggregation centres.

Model of Priority Ranking of Cadastral Parcels for Planning the Implementation of Urban Consolidation

The paper proposes a Model of priority ranking of cadastral parcels for planning the implementation of urban consolidation, which is a continuation of the published research on the assessment of fragmentation and assessment bonitet values of cadastral parcels. The research deals with one segment of the Spatial Decision Support System and is one process in the planning of urban consolidation. Comparison criteria were identified for the evaluation and priority ranking of cadastral parcels. The subject of the research is private cadastral parcels in the area of large public project construction. The goal of the research is to find the optimal way to compare conflicting and incomparable criteria for the evaluation of private cadastral parcels and, at the same time, a way of fitting the opinions of stakeholders in the implementation planning process of urban consolidation. Due to the complexity of the task and realizing certain spatial criteria, unique models were developed. Special attention was paid to the participatory approach to problem-solving, in which all groups of stakeholders were identified, and the way of expressing their views was defined. The Complex proportional assessment (COPRAS) method and the Analytic Hierarchy Process method (AHP) methods were used to solve the problem. The defined models were tested in the field of construction of a large public project Campus at the University of Split.

Assessing the sustainability of spatial development decisions

Changing social and economic conditions justify a rethinking of the theory and practice of domestic spatial development and planning. Despite the progress made over the last thirty years, sustainability problems have emerged for some development projects following the exhaustion of budgetary resources. This paper presents a model developed by the authors for the ex-post and ex-ante assessment of the sustainability of spatial development decisions and suggests an aggregate index for quantifying the model, which can be used to support the preliminary analysis for spatial development decisions.

Climate Change and the Resilience of Collective Memories

Vernacular heritage sites encompass customs, practices, places, objects, artistic expressions, and values that are innate to a particular place and time. Climate knowledge of the particular place and time is embedded in vernacular settlements and lifestyles along with other environmental, cultural, and societal determinants of the place. Rebuilt, restored, and adapted, vernacular settlements evolved with changing climate, cultural practices, community aspirations, and a gradual influx of modernization and urbanization. However, its legacy —as represented by traditional houses from the pre-industrial period that were built by laypeople— is challenged by climate and disaster risks, e.g., loss of lands, food sources, water resources, intangible values, and displacement. Although the impacts of climate change combined with anthropic influences have been recognized as a threat to cultural heritage by scholars, this underappreciated form of cultural heritage has not been the focus of the integrated understanding risks of climate and disaster discussions. The aim of this dissertation, therefore, is to reveal the deteriorations caused by changing climate and anthropic interventions on vernacular heritage at both spatial planning decisions such as urban development projects and at local level practices such as maladaptation from the case of Fındıklı of Rize in Turkiye. The factors behind the deterioration of vernacular heritage sites under changing climate and the ways to achieve climate resilience are analysed through interviews with local people, the observations of on-site visits conducted in January and July 2019 in addition to mapping.

基于生态系统多维特征的粤港澳大湾区国土空间生态保护修复分区研究

PDF HTML阅读 XML下载 导出引用 引用提醒 基于生态系统多维特征的粤港澳大湾区国土空间生态保护修复分区研究 DOI: 10.5846/stxb202202260447 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家社科科学基金项目（20CGL063） Ecological protection and restoration zoning of territorial space in Guangdong-Hong Kong-Macao Greater Bay Area based on multidimensional ecosystem features Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:我国国土空间生态保护修复已进入"山水林田湖草"系统治理和建设阶段。开展生态保护修复的分区研究，正确认识生态系统的地域组合特征及其分异规律，可以为落实系统治理理念提供空间指导。当前生态保护修复分区研究逐渐重视生态系统的完整性，但对于生态系统表征维度相对单一，导致对国土空间系统性综合认知受限。基于此，基于生态安全理论以及生态系统综合评估框架，构建生态保护修复分区的多维度指标体系，以提升对国土空间的系统性综合认知。以流域为基本单元，在评估粤港澳大湾区生态现状本底和退化特征的基础上，采用空间聚类方法划分两级生态保护修复分区。结果表明：（1）各流域生态现状质量和退化程度空间分异较为明显。生态现状质量呈现出外部高、中部低的圈层式分异特征。而生态退化空间分布则相对分散。（2）以生态现状综合指数与一级分区指标数据的空间异质性为基础，可将研究区划分为5个在空间上连续的生态保护修复一级区。以生态退化综合指数与二级分区指标数据的空间异质性为基础，可在一级区内部划分出11类29个生态保护修复二级区。研究方案可为国土空间的"山水林田湖草"系统治理提供生态分区优化路径。同时也为研究区生态保护修复提供了空间决策支持。 Abstract:The ecological protection and restoration of China's national land space has entered the stage of systematic management and construction of "mountains-rivers-forests-farmlands-lakes-grasslands". A comprehensive zoning study on the ecological protection and restoration can provide spatial guidance for the implementation of the concept of systemic governance by correctly understanding the characteristics of the geographical combination of ecosystems and their differentiation. The current zoning research on ecological protection and restoration is gradually focusing on the integrity of ecosystems, but the dimension of ecosystem characterization is relatively single, leading to a limited comprehensive cognition of the spatial systemic nature of the country. This study constructs a multidimensional index system for the ecological protection and restoration zoning based on ecological security theory and a comprehensive ecosystem assessment framework, in order to improve the systematic and comprehensive cognition of territorial space. Using watershed as the basic unit, this study adopts a spatial clustering approach to delineate two levels of ecological protection and restoration zones based on the assessment of the current ecological background and degradation characteristics of the Guangdong-Hong Kong-Macao Greater Bay Area. The results show that:(1) The current ecological quality and degradation of each watershed vary greatly, and the spatial differentiation is also relatively obvious, but the current ecological quality shows a circled differentiation with high quality in the outer part and low quality in the middle. In contrast, the spatial distribution of ecological degradation is relatively dispersed. (2) Based on the spatial heterogeneity of the comprehensive ecological status index and first grade zoning index data, the study area can be divided into five spatially continuous first grade zones of ecological protection and restoration. Based on the spatial heterogeneity of the composite index of ecological degradation and second grade zoning index data, the study area can be divided into 11 categories and 29 secondary zones of ecological protection and restoration within the first grade zone. The research scheme of the study can provide an ecological zoning optimization path for the systematic management of "mountains-rivers-forests-farmlands-lakes-grasslands" on territorial space. It also provides spatial decision support for ecological protection and restoration in the study area. 参考文献 相似文献 引证文献

A Spatial Decision Support System for Prioritizing Repair Interventions on Power Networks

The business continuity of services provided by Critical Infrastructures is vital in order to ensure the security, the economy and the public’s health of a Nation. Delays and bad recovery strategies after disasters or failures can lead to impairing impacts in terms of injury to people, environmental pollution and loss of time, money and resources. In such a context, the adoption of a spatial Decision Support System (DSS) might play a crucial role in order to help operators to adopt the best recovery strategy in the shortest possible time frame. Current approaches do not consider the problem of assigning an intervention location to a maintenance crew and do not account for the effective time needed for emergency intervention. In this paper we develop a novel spatial multi-criteria DSS methodology for prioritizing repair interventions on power networks. The multi criteria strategy is solved by the adoption of Incomplete Analytic Hierarchy Process (AHP) which computes holistic assignment costs as the result of the combination of multiple and possibly conflicting metrics of cost.Then, we use the holistic costs as the basis for a task assignment phase that is based on the Hungarian algorithm. The proposed strategy has been implemented as a module in the Decision Support System, namely Critical Infrastructure Protection Risk Analysis and Forecast (CIPCast), whose outputs are represented on a web-based Geographic Information System (GIS) platform. The effectiveness of the proposed multi-criteria strategy has been validated via a real case study on the Rome City electrical distribution network.

Optimal Location to Use Solar Energy in an Urban Situation

This study conducted in Lima, Peru, a combination of spatial decision making system and machine learning was utilized to identify potential solar power plant construction sites within the city. Sundial measurements of solar radiation, precipitation, temperature, and altitude were collected for the study. Gene Expression Programming (GEP), which is based on the evolution of intelligent models, and Artificial Neural Networks (ANN) were both utilized in this investigation, and the results obtained from each were compared. Eighty percent of the data was utilized during the training phase, while the remaining twenty percent was utilized during the testing phase. On the basis of the findings, it was determined that the GEP is the most suitable network for predicting the location. The test state’s Nash-Sutcliffe efficiency (NSE) was 0.90, and its root-mean-square error (RMSE) was 0.04. Following the generation of the final map based on the results of the GEP model, it was determined that 9.2% of the province’s study area is suitable for the construction of photovoltaic solar power plants, while 53.5% is acceptable and 37.3% is unsuitable. The ANN model reveals that only 1.7% of the study area is suitable for the construction of photovoltaic solar power plants, while 66.8% is acceptable and 31.5% is unsuitable.

Spatial clustering-based method for Italian marginal areas toward the sustainable regeneration

In Italy, there is a clear disparity between cities and villages located in marginal areas. The progressive depopulation of inland areas and the urban polarization represent consolidated dynamics difficult to adapt to the new paradigm of sustainable development. The post-Covid-19 pandemic scenario offers the opportunity to redefine new parameters of intervention and new visions for the regeneration of villages in accord with the new challenges of decentralization and distancing. The project «Renaissance of villages for the revitalization of marginal areas» (2021) aims to create the conditions to repopulate and rebalance shrinking territories by establishing new centres of attractiveness. This project envisages the active involvement of municipalities to implement multi-sectoral analysis and spatial assessment approaches in planning processes. It intends to develop an interactive web dashboard for local authorities and spatial planners to create both a learning environment and a participative spatial decision support system for future local policy actions toward sustainable local development. This study presents the project’s preliminary phase which aims to create the general framework of the web dashboard. A reconstruction of the village definition and the spatial selection of villages throughout Italy are presented as innovative aspects since the absence of an agreed definition of the village in the national and international level documents. Moreover, this study provides a quantitative spatial multivariate analysis cluster that analyzes, and groups Italian territories based on socioeconomic dynamics. The result of this analysis allows us to divide the territory into archetypes and to structure a framework that supports the definition of future scenarios for the regeneration of small urban areas considering the diversified needs and potential of the villages belonging to specific archetypes analyzed in the study.

Effect landslide hazard mitigation using an integrated of Analytical Hierarchy Process and Multi Criteria Evaluation: A case study the Jeneberang watershed

Jeneberang watershed has an important role in maintaining environmental stability, especially for the surrounding area. In 2004 a landslide occurred in the Jeneberang watershed which caused casualties and material losses. This study aims to determine the distribution and level of vulnerability to landslides in the Jeneberang watershed and to formulate an effective scenario to reduce the level of vulnerability. This research is located the Jeneberang watershed, South Sulawesi Province. The data used include data on the weight of each parameter and criteria for determining landslide susceptibility obtained from expert interviews, land use maps obtained from analysis of Landsat 8 OLI satellite imagery in 2020, slope maps, rainfall maps, forest area status maps, and map type. soil. The method used is the integration of AHP and MCE for landslide hazard assessment, GIS analysis and spatial decision-making for scenario simulation. The results of the analysis show that the rainfall parameter has the highest weight in determining the level of landslide susceptibility with a value of 0.327, the results of the MCE analysis for assessing the level of landslide susceptibility in the Jeneberang watershed show an area of 18.829 ha. or 18% of the Jeneberang watershed area which is classified as high hazard. The results of the analysis show that the use of an effective scenario reduces the landslide hazard at a high level of hazard. In the optimistic scenario, it can reduce the high vulnerability level by 9.14%, while in the moderate scenario it is effective in reducing the high vulnerability level by 8.72%.