Search Results (5)

This study explores spiritual resilience as a mechanism for sustaining cultural landscapes, focusing on the UNESCO World Heritage Site of the Studenica Monastery (Serbia). By analysing the monastery’s sacred network, which includes monasteries, hermitages, and churches, the study demonstrates how material heritage (architecture, art), intangible practices (monastic life, liturgy, traditional crafts), and the natural environment (UNESCO MaB Golija–Studenica Biosphere Reserve) form a cohesive system of resilience. The concept of spiritual resilience is examined as a dynamic process that links sacred architectural structures and enduring religious practices with authentic land use preserved over centuries. We have utilised a methodological framework combining historical mapping, GIS viewshed analysis in spatial planning, and multidisciplinary data synthesis (historical, architectural, artistic, ecological, ethnographic) with resilience indicators aligned with the UNESCO’s Cultural Landscape approach. The findings reveal that Studenica’s sacred network operates as a coupled socio-ecological system. Spiritual practices, including annual processions and land stewardship rituals, have been identified as key factors in enhancing biodiversity conservation while mitigating land-use conflicts. Historical mapping has been used to highlight the overlap between sacred sites and protected ecological zones, reflecting traditional stewardship practices. By reframing heritage as an adaptive process where spirituality serves as a conduit between tradition and innovation, the study proposes replicable strategies for UNESCO sites worldwide. The concept of sacred landscapes as resilience hubs is furthered by alignment with SDG 11 (Sustainable Cities and Communities). Full article

Moving away from a static concept for the landscape that surrounds us, in this research article, we approach the visual landscape as a dynamic concept. Moreover, we attempt to provide an interconnection between the domains of landscape and cartography by designing maps that are particularly suitable for characterizing the visible landscape and are potentially meaningful for overall landscape evaluation. Thus, the present work mainly focuses on the consecutive computation of vistas along highways, incorporating actual landscape composition—as the landscape is perceived from an egocentric perspective by observers moving along highway routes in peri-urban landscapes. To this end, we developed an integrated method and a Python (version 2.7.16) tool, named “RouteLAND”, for implementing an algorithmic geoprocessing procedure; through this geoprocessing tool, sequences of composite dynamic geospatial analyses and geometric calculations are automatically implemented. The final outputs are interactive web maps, whereby the segments of highway routes are characterized according to the dominant element of the visible landscape by employing (spatial) aggregation techniques. The developed geoprocessing tool and the generated interactive map provide a cartographic exploratory tool for summarizing the landscape character of highways in any peri-urban landscape, while hypothetically moving in a vehicle. In addition, RouteLAND can potentially aid in the assessment of existing or future highways’ scenic level and in the sustainable design of new highways based on the minimization of intrusive artificial structures’ vistas; in this sense, RouteLAND can serve as a valuable tool for landscape evaluation and sustainable spatial planning and development. Full article

Settlement models help to understand the social–ecological functioning of landscape and associated land use and land cover change. One of the issues of settlement modeling is that models are typically used to explore the relationship between settlement locations and associated influential factors (e.g., slope and aspect). However, few studies in settlement modeling adopted landscape visibility analysis. Landscape visibility provides useful information for understanding human decision-making associated with the establishment of settlements. In the past years, machine learning algorithms have demonstrated their capabilities in improving the performance of the settlement modeling and particularly capturing the nonlinear relationship between settlement locations and their drivers. However, simulation models using machine learning algorithms in settlement modeling are still not well studied. Moreover, overfitting issues and optimization of model parameters are major challenges for most machine learning algorithms. Therefore, in this study, we sought to pursue two research objectives. First, we aimed to evaluate the contribution of viewsheds and landscape visibility to the simulation modeling of - settlement locations. The second objective is to examine the performance of the machine learning algorithm-based simulation models for settlement location studies. Our study region is located in the metropolitan area of Oyo Empire, Nigeria, West Africa, ca. AD 1570–1830, and its pre-Imperial antecedents, ca. AD 1360–1570. We developed an event-driven spatial simulation model enabled by random forest algorithm to represent dynamics in settlement systems in our study region. Experimental results demonstrate that viewsheds and landscape visibility may offer more insights into unveiling the underlying mechanism that drives settlement locations. Random forest algorithm, as a machine learning algorithm, provide solid support for establishing the relationship between settlement occurrences and their drivers. Full article

The number of satellites visible to a Global Navigation Satellite System (GNSS) receiver is important for high accuracy surveys. To aid with this, there are software packages capable of predicting GNSS visibility at any location of the globe at any time of day. These prediction packages operate by using regularly updated almanacs containing positional data for all navigation satellites; however, one issue that restricts their use is that most packages assume that there are no obstructions on the horizon. In an attempt to improve this, certain planning packages are now capable of modelling simple obstructions whereby portions of the horizon visible from one location can be blocked out, thereby simulating buildings or other vertical structures. While this is useful for static surveys, it is not applicable for dynamic surveys when the GNSS receiver is in motion. This problem has been tackled in the past by using detailed, high-accuracy building models and designing novel methods for modelling satellite positions using GNSS almanacs, which is a time-consuming and costly approach. The solution proposed in this paper is to use a GIS to combine existing, freely available GNSS prediction software to predict pseudo satellite locations, incorporate a 2.5D model of the buildings in an area created with national mapping agency 2D vector mapping and low density elevation data to minimise the need for a full survey, thereby providing savings in terms of cost and time. Following this, the ESRI ArcMap viewshed tool was used to ascertain what areas exhibit poor GNSS visibility due to obstructions over a wide area, and an accuracy assessment of the procedure was made. Full article

Infiltration-route analysis is a military application of geospatial information system (GIS) technology. In order to find susceptible routes, optimal-path-searching algorithms are applied to minimize the cost function, which is the summed result of detection probability. The cost function was determined according to the thermal observation device (TOD) detection probability, the viewshed analysis results, and two feature layers extracted from the vector product interim terrain data. The detection probability is computed and recorded for an individual cell (50 m × 50 m), and the optimal infiltration routes are determined with A* algorithm by minimizing the summed costs on the routes from a start point to an end point. In the present study, in order to simulate the dynamic nature of a realworld problem, one thousand cost surfaces in the GIS environment were generated with randomly located TODs and randomly selected infiltration start points. Accordingly, one thousand sets of vulnerable routes for infiltration purposes could be found, which could be accumulated and presented as an infiltration vulnerability map. This application can be further utilized for both optimal infiltration routing and surveillance network design. Indeed, dynamic simulation in the GIS environment is considered to be a powerful and practical solution for optimization problems. A similar approach can be applied to the dynamic optimal routing for civil infrastructure, which requires consideration of terrain-related constraints and cost functions. Full article