Geographies, Volume 4, Issue 2 (June 2024) – 10 articles

This research assesses the environmental uses of Haleakalā Crater, and adjoining east Maui areas, by native Hawaiians during recent centuries, and evaluates the modern utilization of this volcanic depression. The study methods examine, and focus on, numerous historical and modern accounts and reports. Three historical periods were identified as follows: (1). A phase, from the ~1400s until contact with foreigners in 1778, characterized by the development of settlements, population expansion, the intensification of traditional agriculture, and the political consolidation of Maui. The construction of the Kiha-a-Pi‘i-lani trail across the crater enhanced travel between distant island areas. (2). Following the collapse of Maui’s human populations during the late 1700s, and until the 20th century, came a period distinguished by scientific exploration of the crater, and intentional or accidental introductions of animals, including goats, horses, cattle, and wild dogs. (3). After Haleakalā became a National Park in 1916, efforts to eradicate introduced animals and to encourage the reproduction of silverswords and other plants were initiated. Unfortunately, in retrospect, construction of a modern paved road, improvement of hiking trails, and building of facilities allowed swift access to the Park and substantially increased tourist numbers, up to ~2 million yearly visitors. Faced with such crowds, the long-term planning of Park resources appears to be a formidable task. Full article

Accurate flood prediction models and effective flood preparedness rely on thoroughly understanding rainfall–runoff dynamics. Similarly, effective rainfall–runoff models account for multiple interrelated parameters for robust runoff prediction. Process-based physical models offer valuable insights into hydrological processes, but their effectiveness can be hindered by data limitations or difficulties in acquiring specific data. Motivated by the frequent flooding events and limited data availability in the East Branch DuPage watershed, Illinois, this study addresses a critical gap in research by investigating effective discharge prediction methods. In this study, two significant machine learning (ML) models, artificial neural network (ANN) and support vector machine (SVM), were employed for discharge prediction. Historical data spanning from 2006 to 2021 were utilized to assess the performance of the models. Hyperparameter tuning was performed on the models to optimize their performance, and root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and the normalized root mean squared error (NRMSE) were used as evaluation metrics. Although both machine learning models demonstrated strong performance, the analysis revealed that the ANN model emerged as the more reliable option for predicting discharge in the watershed. Crucially, the ANN model surpassed the SVM model’s performance, achieving superior accuracy in predicting peak discharge events within the study area. Our findings have the potential to assist decision-makers and communities in implementing more dependable flood mitigation strategies, particularly in regions where hydrology data are limited. Full article

The Italian national territory is characterised by the widespread presence of cavities dating back to different periods, especially in urban areas. The lack of knowledge of the position of the entrances, planimetric developments and state of preservation contributes to accentuating the unknowns related to sinkhole risk, which are directly related to potential cavity collapses with the opening of surface chasms. To deepen knowledge with a view to risk mitigation, a method has been developed to employ surveys obtained from Unmanned Aerial Vehicles (UAVs) to locate entrances even in hard-to-access urban areas. These surveys, properly supported with GNSS stations, were then integrated with cavity surveys obtained from low-cost lidar mounted on iPhones. Comparisons were made with traditional surveying techniques to better understand the reliability of the surveys made with low-cost lidar. The 3D models obtained, combined with geomechanical surveys of the rock masses hosting the cavities, allowed the application of simplified and empirical methods for an initial stability assessment. This method was tested on a portion of the municipality of Grotte di Castro (Province of Viterbo—Italy). Full article

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously, there has been an increased use of uncrewed aerial systems (UASs) in remote sensing, as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UASs and the attention on agroecosystems, there is an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UASs to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and assembled accuracy assessments for each classification. The average overall accuracy (53.9%), though relatively low, was expected for such a diverse landscape with fine-resolution data. To bolster our understanding of the classifications, we interviewed farmers to understand their thoughts on how these maps may be best used to support their land management. After sharing imagery and land cover classifications with farmers, we found that while the prints were often a point of pride or curiosity for farmers, integrating the maps into farm management was perceived as impractical. These findings highlight that while researchers and government agencies can increasingly apply remote sensing to estimate land cover classes and ecosystem services in diverse agroecosystems, further work is needed to make these products relevant to diversified smallholder farmers. Full article

Global concern over optimizing transboundary water resources for residents is hindered by the lack of observational data, particularly in ungauged basins, mainly due to inaccessibility or security issues. Remote sensing and GIS technology provide a practical solution for monitoring and managing water resources in such basins. This research evaluates surface water resources in the Qaretikan ungauged transboundary basin using satellite products for precipitation, temperature, and evapotranspiration from 2005 to 2014. The accuracy of these datasets was assessed using statistical measures. The water balance components, i.e., precipitation and evaporation, were utilized to calculate runoff over the basin using the Justin method. Downstream environmental flow was estimated using the Lyon method, and available water was determined. This study identified a potential annual storage water of 11.8 MCM in the Qaretikan basin. The Analytic Hierarchy Process (AHP) integrated expert opinions to prioritize water usage decisions based on proposed decision options. The results revealed greenhouse cultivation water allocation as the top priority among the identified options, highlighting its importance in sustainable water resource management within the basin. Full article

Owing to its unique physical and socio-economic characteristics, the Saint Louis region stands out as one of the most susceptible areas in Senegal to the adverse impacts of coastal erosion. The dynamics of erosion in this region are significantly influenced by the Langue de Barbarie (LB), a sand spit formed at the mouth of the Senegal River. Initially, in 2003, a 4 m wide artificial breach was strategically introduced to mitigate flooding; however, sediment dynamics expanded it to 6 km by 2020, thereby affecting the entire region. This study delves into the coastline change of the LB, specifically divided into three zones (LB-1, LB-2, and LB-3), spanning the period from 1994 to 2042. Leveraging Geographic Information System (GIS) and remote sensing techniques, our investigation reveals that, prior to the breach’s creation, the average dynamic coastline rates in zones LB-1, LB-2, and LB-3 were estimated at 4.4, 5.9, and 4.4 m/year, respectively. Subsequent to the breach, these rates shifted to −1.2, 8.4, and −2.7 m/year, with the most significant erosion observed alongshore of LB-3 at −6.6 m/year during the period 2002–2012. Projecting into 2032, LB-1 and LB-3 are anticipated to experience erosion rates of −11.5 and −26.8 m/year, respectively, while the LB-2 records an estimated accretion rate of 8.41 m/year. Eroded areas are expected to total 571,458 m², while accumulated areas are expected to total 67,191 m². By 2042, zones LB-1, LB-2, and LB-3 are expected to experience erosion rates of −23 and −53.6 m/year, resulting in the erosion of 1,021,963 m² and the accumulation of 94,930 m² with a dynamic rate of 168.2 m/year in zone LB-3. These results have significant implications for solving the urgent issue of coastal erosion in LB. Full article

Non-Representational Theory (NRT) emphasizes the significance of routine experience in shaping human geography. In doing so, the theory largely eschews traditional approaches that have offered area-based, longitudinal, and synoptic formalisms for geographic inquiry. Instead, NRT prioritizes the roles of individualized and often dynamic lived geographies as they unfold in the moment. To date, NRT has drawn significant inspiration from the synergies that it shares with philosophy, critical geography, and self-referential ethnography. These activities have been tremendous in advancing NRT as a concept, but the theory’s strong ties to encounter and experience invariably call for practical exposition. Alas, applications of NRT to concrete examples at scales beyond small case studies often prove challenging, which we argue artificially constrains further development of the theory. In this paper, we examine some of the thorny problems that present in applying NRT in practical terms. Specifically, we identify ten traps that NRT can fall into when moving from theory to actuality. These traps include conundrums of small geographies, circularity in representation, cognitive traps, issues of mustering and grappling with detail, access issues, limitations with empiricism, problems of subjectivity, methodological challenges, thorny issues of translation, and the unwieldy nature of process dynamics. We briefly demonstrate a novel observational instrument that can sidestep some, but not all, of these traps. Full article

There have been increasing calls in gentrification studies to examine the geography of gentrification in slums, as little is known about the patterns and processes of slum gentrification, especially in sub-Saharan African cities where slums house over 50% of the urban population. This study explored the spatiotemporal changes in slums in Lagos, Nigeria, between 1984 and 20 on the pattern and drivers of gentrification. Data were collected from 42 slums in Lagos through remote sensing (1984–2020) and a field survey (2020–2021). The study integrated geospatial analysis with quantitative and qualitative analysis to investigate the patterns and drivers of gentrification in Lagos slums. The findings show that between 1984 and 2020, all the sampled slums had undergone gentrification processes, apart from those that were completely cleared. However, many slums continue to have deprived areas as they continue to gentrify. Almost all the slum communities have experienced slum clearance in the past. Additionally, the current and new housing developments in the study have favored middle- to high-income groups, which has led to the displacement of previous slum residents. The study identified slum clearance, fires and floodings, the presence of palaces in the community, the proportion of deprived areas in 1984, government interest in the slum, and the size of the church as drivers of slum gentrification processes in Lagos. Finally, the findings show that the vulnerability of slum dwellers increases with slum gentrification. Therefore, this study recommended developing policies and programs, such as sustainable relocation and low-cost housing, to mitigate the negative consequences of slum gentrification, especially in cities with significant shares of low-income groups. Full article

In Japan, rural areas are grappling with population decline and aging, leading to a shortage of labor for farmland maintenance. This has resulted in the abandonment of farmland or its conversion for solar photovoltaic (PV) use. However, this unplanned conversion raises concerns about agricultural productivity decline, landscape degradation, biodiversity loss, water resource maintenance, and disaster prevention. This study focuses on the Kushida watershed, examining (1) accurate farmland classification using remote sensing data, (2) the geographical distribution of farmland converted to PV systems from 2016 to 2021 and concentrated along the river, especially on north-facing slopes, (3) the highest conversion rates in wheat fields, followed by legume fields, tea fields, and paddy fields, and (4) no clear correlation between farmland conversions and changes in the number of farmers, but associations with farmland geography and solar radiation levels. These findings contribute to a nuanced understanding of sustainable rural development in Japan, emphasizing the importance of considering geographical factors in the conversion of farmland to PV. Full article

Wind erosivity has an intermittent character due to complicated interactions between air streams, surface characteristics, and sediment particles. To experimentally investigate the effect of a sudden and local gust on sediment entrainment, a simple setup was installed in a mobile wind tunnel. One, three, and five consecutive gusts were applied and compared with standard test conditions with steady wind. The applied wind was characterized by total test duration (s), duration of gust (s), mean velocity, peak velocity (m s⁻¹), gust factor, and transport capacity based on sediment-specific threshold velocity. The eroded material was collected by sediment containers. The results suggest that 1. the application of gusts inside the mobile wind tunnel setup is feasible but related to uncertainty concerning the applied wind conditions, and 2. the horizontal transport rate increased with the number of applied gusts. While the highest rates were measured during five gusts on sand, the relative effect of gusts was most accentuated in the comparison of one gust to no gust on loam. The findings highlight how temporally and spatially limited gust impact causes extreme particle entrainment. These particles may subsequently either start erosion or enter vertical dust transport. Full article