Geographies, Volume 4, Issue 3 (September 2024) – 10 articles

Geographic data quality is a complex issue requiring continuous operational improvements. Considering this to be one of the most topical research and technical issues in official statistics and environmental monitoring, this study re-connects the operational dimension of ‘geographic data quality’ with the broader issue of monitoring the quality of official statistics. By estimating the accuracy of public (spatially explicit) data, this study illustrates an operational framework with an exploratory exercise in estimating the geographic data quality characteristic of a specific information source within the official statistical system (i.e., building registry) in a given European country, namely, Italy. The results of this exercise provide a paradigmatic example of profound innovation in the activities of statistical services in Europe and specifically the Italian National Statistical Institute (Istat), transitioning from independent (and poorly connected) field surveys to an integrated system of registries. Since several studies are based on spatially explicit survey units, it is essential to estimate the quality of geographical data, especially those derived from information sources where space is topical information, such as (local, regional, or national) building registers. Thanks to the results of an empirical exercise applied to Italian building registers, the present article will discuss the issue of data accuracy, considered the main issue related to monitoring geographic data quality, from an official statistics’ perspective. Statistical indicators will be proposed for the assessment of systematic and random errors of spatially explicit measures, possibly enabling a quali-quantitative improvement in the semantic content of building registers that address the inherent requirements of official statistics. Such indicators have some positive implications for the entire system of official statistics in Italy and, for generalization, within the European Statistical System. Full article

Rapid urbanization and development have led to a significant number of Malaysians living in flood-prone areas, exacerbating the impact of natural disasters such as floods. This study aims to identify the factors influencing community resilience both before and after flood events in Temerloh, Pahang. Data were collected via questionnaires distributed to 350 flood victims. Key findings reveal that long-term residents exhibit higher resilience due to local knowledge and preparedness strategies. The study highlights the importance of integrating local experiences into flood management policies to enhance community resilience. The results reveal that large flood-prone areas experience frequent flooding, contributing to considerable community distress. This distress is somewhat alleviated by the support provided by government agencies and NGOs, which includes relief efforts, emergency services, and flood defense construction. Additionally, community involvement in flood management was found to have a statistically significant impact (p < 0.05). The study highlights the need for enhanced flood management strategies that address psychological aspects to reduce negative impacts on the community. Full article

As governments continue to address climate change when formulating policy, there remains a need to determine if such a change exists in the historical record to inform clear indices for monitoring the present climate for site-specific interventions. This study characterised trends and anomalies in rainfall and dry spells, providing local information often projected from satellites or regional data in data-scarce regions. From 1961 to 2007, daily rainfall records in Central Malawi were used to calculate indices for low-(Balaka), medium-(Bunda, Chitedze, KIA), and high-altitude (Dedza) sites, which were then subjected to Mann–Kendall’s, Cramer’s, and Spearman-Rho’s trend tests. Significant decreasing trends in terms of wet days and growing season length were evident across locations. Seasonal and extreme rainfall, dry spells, and inter-seasonal and near-decadal anomalies were not consistently or inevitably significant. Unexpectedly, rainfall anomalies were largest in Bunda and KIA, which have mild climatic regimes, while the lowest were in Balaka, a rainfall-averse zone. The relationship between El Niño-Southern Oscillation (ENSO) and extreme rainfall and dry spell events did not reach statistical significance. In conclusion, extreme precipitation and dry spell events show varied intensities and proportions rather than increased frequency. The disparate results largely justify the need for in-depth local-scale assessments for agroclimatic applications. Full article

To document the dynamics of biocultural heritage, we studied traditional uses of plants on a segment of the Andean Road System, or Qhapaq Ñan, within the central Andes of Ecuador, home of the Kichwa community of Nizag. Here, residents preserved a rich diversity of plants within their agricultural fields, or chakra, of the Andean landscapes, upholding a culture steeped in traditional knowledge. Wild and domesticated plants are a cornerstone for the community, prompting the development of ethnobotanical management strategies with a conservation approach. The diverse plant uses aim to revalue their culture, fortify their self-identification as an indigenous community, and ensure the transmission of ancestral knowledge. This research aims to ascertain the ethnobotanical applications of this venerable community. Employing participatory action research, semistructured interviews were conducted with 43 community informants to gather ethnobotanical data on the flora applied within their territory, spanning categories such as food, agriculture, crafts, living fences, construction, fuel, ornamental, environmental, technological, and medicinal services. The findings indicate that age, rather than educational level and gender, significantly influences the variation in plant usage knowledge. In total, 142 plant species were cataloged, comprising herbs (58%), shrubs (23%), trees (15%), and climbers (4%). The most represented families were Asteraceae, Fabaceae, Lamiaceae, and Poaceae. Notably, 96% of these species provide some type of environmental service or fulfill a niche within the socioecological system. Medicinal uses were reported for 89% of the plants, while 56% served agricultural purposes, primarily in fertilizer production and forage. Additionally, 44% of the plants are utilized as food, typically consumed fresh. Among the medicinal plants, leaves are the most used part (58%), prepared as infusions and poultices. The prevalent ailments addressed include respiratory and urinary system conditions, with Borago officinalis, Carica pentagona, Vasconcellea pubescens, and Origanum mejorana being the most frequently employed plants. Full article

Floods are among the most widespread and recurrent natural disasters globally. In the European region, climate change leads to an increase in the incidence and intensity of flooding. For effective management of the phenomenon, the European Union instituted Directive 2007/60/EC for the assessment and management of flood risks in order to reduce the negative consequences of flooding on human health, economic activities, the environment, and cultural heritage. Cyprus, as a member of the European Union, had to comply with the provisions of the directive. Within the second implementation of the directive, combined 1D/2D hydraulic models were conducted. These data served as a benchmark for the present research, in which the differences in the inundated area, depths, and simulation time are investigated using a full 2D hydraulic simulation. The present research examines two Areas of Potentially Significant Flood Risk, one in an urban and one in a rural area. Overall, the proposed 2D methodology was found to represent inundated areas to a good extent with almost zero deviation in comparison to the 1D/2D method. This study demonstrated the adequacy of the 2D hydraulic simulation method, which offers greater flexibility in modeling a variety of hydraulic scenarios, enabling planning and flood risk management that is vital for protecting communities, infrastructure and the environment from the devastating impacts of floods. Full article

Schmitt’s map was one of the outstanding survey products of the late 18th century, produced through Habsburg military mapping in the shadow of the Napoleonic Wars in the area of today’s southern Germany and some neighboring regions. The main geodetic basis for the map work was the series of surveys in Germany conducted by C.-F. Cassini de Thury in the 1760s. However, this was only a horizontal control for part of Schmitt’s map. The Cassini survey chains were linked in the 1790s by a complementary survey in the northern part of the map work: the Staržinsky-Sarret survey, which is the subject of this study. The authors have searched through the archive summary drafts of this survey. The georeferencing of the photographed sketches in the Cassini projection was feasible with surprisingly low error. By using the global SRTM elevation database, it was possible to identify the points/summits of the Staržinsky-Sarret survey between which visibility is possible. Thus, despite the fact that only one of the seven map sketches examined explicitly presents a triangulation structure, we present a possible triangulation pattern that could have been used to provide geodetic control in the northern part of the Schmitt map. The authors consider this survey as the basis for the assumption that georeferencing the Schmitt map in its own projection is possible in this area with relatively small residual errors. Full article

Despite increasing wildfire severity and range, rapid development in the fire-prone Wildland–Urban Interface (WUI) has continued, and many neighborhoods are at risk of a constrained wildfire evacuation due to a high ratio of houses to community road-network exits. In Texas, Hays County is prone to fire, and rapid population growth has created a substantial WUI. Despite this, there is not sufficient research addressing neighborhood-level evacuation risks. The goal of this research, then, is to search Hays County for neighborhoods that face the highest combined risk of wildfire and potential evacuation difficulty. This research provides a limited use case wherein local decision-makers can quantify the combined risk of wildfire and constrained evacuation at the neighborhood scale by making use of standard spatial analysis techniques and publicly available datasets. The results show an alarming trend of low-egress neighborhoods in fire-prone areas within Hays County which carry the risk of a very difficult evacuation in cases when wildfire warning time is short. By using publicly available datasets and standard techniques, this research provides methods for local decision-makers across the state to identify these at-risk neighborhoods within their own jurisdictions which may aid in emergency planning and mitigation. Full article

Recent advancements in deep learning have significantly improved the performance of remote sensing scene classification, a critical task in remote sensing applications. This study presents a new aerial scene classification model, the Multi-Scale Swin–CNN Aerial Classifier (MSCAC), which employs the Swin Transformer, an advanced architecture that has demonstrated exceptional performance in a range of computer vision applications. The Swin Transformer leverages shifted window mechanisms to efficiently model long-range dependencies and local features in images, making it particularly suitable for the complex and varied textures in aerial imagery. The model is designed to capture intricate spatial hierarchies and diverse scene characteristics at multiple scales. A framework is developed that integrates the Swin Transformer with a multi-scale strategy, enabling the extraction of robust features from aerial images of different resolutions and contexts. This approach allows the model to effectively learn from both global structures and fine-grained details, which is crucial for accurate scene classification. The model’s performance is evaluated on several benchmark datasets, including UC-Merced, WHU-RS19, RSSCN7, and AID, where it demonstrates a superior or comparable accuracy to state-of-the-art models. The MSCAC model’s adaptability to varying amounts of training data and its ability to improve with increased data make it a promising tool for real-world remote sensing applications. This study highlights the potential of integrating advanced deep-learning architectures like the Swin Transformer into aerial scene classification, paving the way for more sophisticated and accurate remote sensing systems. The findings suggest that the proposed model has significant potential for various remote sensing applications, including land cover mapping, urban planning, and environmental monitoring. Full article

This comprehensive review explores the ecological significance of the Argane stands (Argania spinosa) in southwestern Morocco and the pivotal role of remote sensing technology in monitoring forest ecosystems. Argane stands, known for their resilience in semi-arid and arid conditions, serve as a keystone species, preventing soil erosion, maintaining ecological balance, and providing habitat and sustenance to diverse wildlife species. Additionally, they produce an extremely valuable Argane oil, offering economic opportunities and cultural significance to local communities. Remote sensing tools, including satellite imagery, LiDAR, drones, radar, and GPS precision, have revolutionized our capacity to remotely gather data on forest health, cover, and responses to environmental changes. These technologies provide precise insights into canopy structure, density, and individual tree health, enabling assessments of Argane stand populations and detection of abiotic stresses, biodiversity, and conservation evaluations. Furthermore, remote sensing plays a crucial role in monitoring vegetation health, productivity, and drought stress, contributing to sustainable land management practices. This review underscores the transformative impact of remote sensing in safeguarding forest ecosystems, particularly the Argane forest stands, and highlights its potential for continued advancements in ecological research and conservation efforts. Full article

Land allotment was embraced by the U.S. Government in the late 1800s and early 1900s as part of a solution to the “Indian problem”, the goal of which was assimilation into the Euro-American cultural and economic system. As a progressivist program, it was imposed with enthusiasm and confidence, dividing reservations into rectangular land parcels (allotments) in the belief that the allotment recipients would become yeoman farmers of the Jeffersonian mold. Tribes were unable to thwart the imposition of allotment, despite their best efforts, and its devastating long-term effects are now well known. Much less is understood, however, about the efforts of various tribes, sometimes successful and sometimes not, to obtain modifications to the terms of allotment imposed on them. We describe how the people of the Standing Rock Reservation in North and South Dakota successfully advocated for modifications which worked to their significant advantage. We draw heavily from the outgoing correspondence and allotment records of the Special Allotting Agent, Carl Gunderson, along with contemporaneous records of legislative proceedings and other documents. The successful efforts of the people of Standing Rock resulted not only in equitable access to scarce timber, but in allotments to numerous individuals who otherwise would have been ineligible. The net impact was the additional allotment of nearly 400,000 acres (160,000 ha) to over 1800 individuals who otherwise would have received nothing. Full article