Geographies, Volume 3, Issue 1 (March 2023) – 11 articles

Hydrology is one of the most influential elements of geodiversity, where geology and geomorphology stand as the main values of abiotic nature. Hydrological erosion created by river systems destructing rock formations (eluvial process) from streams’ sources and then transporting and redepositing (alluvial process) the rock debris into the main river channels, make it an ongoing transformation element of the abiotic environment along channel networks. Hence, this manuscript demonstrates the influence of hydrological elements on geosite recognition, specifically for qualitative–quantitative assessment of geodiversity, which is based on a combination of geological and geomorphological values. In this concept, a stream system will be treated as an additional element. The basement area of the Manawatu Region has been utilized as the territory for the research of hydrological assessment. The region is in the southern part of the North Island of New Zealand and has relatively low geological and geomorphological values and diversity. The Strahler order parameter will be demonstrated as a hydrological element for geodiversity assessment. This parameter has been chosen as one of the most common and acceptable within geographical information system (GIS) environments. The result of this assessment compares the influences of Strahler order on qualitative–quantitative assessment of geodiversity and provides its drawbacks. Additionally, the places with high values will be considered for more accurate field observation to be nominated as potential geosites with an opportunity for geoeducational and geotouristic significance. Full article

Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This research presents the long-term time series maps from 2002 to 2021, with a comprehensive spatiotemporal depiction of inundation. In this paper, we bridged the research gap of space-time analysis for multi-season inundation dynamics, which is urgently needed for the Everglades wetland. Within a GIS-based framework, we integrated statistical models, such as Mann–Kendall and Sen’s Slope tests, to track the evolutionary trend of seasonal inundation dynamics. The spatiotemporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, presenting a warning regarding their vulnerability to sea level rise. Full article

Ethnogeology offers a longitudinal history of the formation of landscapes though the lens of First Nations Peoples. Significantly, it offers an insight into landscape change and geographical formation as consequence of geological events, climate shift (change), and consequential human resilience and adaptation strategies. This article considers a cultural landscape near Ballaarat (Ballarat) in Australia and its geological omnipresence in the eyes of the First Nations’ Wadawurrung People. The features, two extinct volcanoes—Bonan Youang (Mt Buninyong) and Terrinalum (Mt Elephant)—and a connection tract, offer high cultural values to the Wadawurrung People in addition to serving as key contemporary mental and orientation landmarks arising from their roles in the locality’s pastoral, goldmining, and suburbanisation colonisation phases. Full article

This paper aims to explore and evaluate aerial imagery and deep learning technology in pavement condition evaluation. A convolutional neural network (CNN) model, named PCIer, was designed to process aerial images and produce pavement condition index (PCI) estimations, which are classified into four scales of Good (PCI ≥ 70), Fair (50 ≤ PCI < 70), Poor (25 ≤ PCI < 50), and Very Poor (PCI < 25). In the experiment, the PCI datasets were retrieved from the published pavement condition report by the City of Sacramento, CA. Following the retrieved datasets, the authors also collected the corresponding aerial image datasets containing 100 images for each PCI grade from Google Earth. An 80% proportion of datasets were used for PCIer model training, and the remaining were used for testing. Comparisons showed using a 128-channel heatmap layer in the proposed PCIer model and saving the PCIer model with the best validation accuracy would yield the best performance, with a testing accuracy of 0.97, and a weighted average precision, recall, and F1-score of 0.98, 0.97, and 0.97, respectively. Moreover, future research recommendations are provided in the discussion for improving the effectiveness of pavement evaluation via aerial imagery and deep learning. Full article

Rockfall hazard gains popularity nowadays among researchers in different scientific fields, decision-makers and urban planners. The assessment of rockfall hazard requires detection, mapping and estimating the maximum travel distance that rock boulders may reach, commonly known as “rockfall runout”. This latter can change significantly under the effects of different triggering factors such as soil conditions, chemical, physical and geological rock properties. However, comparing and analyzing these different effects represents, to the best of our knowledge, one of the newest scientific challenges that need to be addressed. This paper presents a complete methodologic approach aiming to assess the rockfall hazard through runout estimation in three different conditions: (i) gravity, (ii) earthquakes, and (iii) the presence of moisture along the slope. The “Mtein” Village and its surrounding areas in the Mount Lebanon region were chosen as the study area because there have been numerous historic rockfalls and various-sized rocks, such as cobbles and boulders, scattered throughout the area. Thus, three-dimensional simulations were conducted using the Rockyfor3D software and aerial photos for the year 1999 to assess the rockfall runout, the energy curves, and the number of deposited rocks. The results reveal that earthquakes have the highest triggering effect on rockfall and that moisture has a damping effect on RFs by decreasing the kinetic energy. The study shows the importance of taking into consideration the influence of triggering factors as well as rock density on rockfall runout and hazard. Full article

The present research aims at verifying whether there are significant differences between Land Use/Land Cover (LULC) classifications performed using Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data—abbreviated as L8 and S2. To comprehend the degree of accuracy between these classifications, both L8 and S2 scenes covering the study area located in the Basilicata region (Italy) and acquired within a couple of days in August 2017 were considered. Both images were geometrically and atmospherically corrected and then resampled at 30 m. To identify the ground truth for training and validation, a LULC map and a forest map realized by the Basilicata region were used as references. Then, each point was verified through photo-interpretation using the orthophoto AGEA 2017 (spatial resolution of 20 cm) as a ground truth image and, only in doubtful cases, a direct GPS field survey. MLC and SVM supervised classifications were applied to both types of images and an error matrix was computed using the same reference points (ground truth) to evaluate the classification accuracy of different LULC classes. The contribution of S2′s red-edge bands in improving classifications was also verified. Definitively, ML classifications show better performance than SVM, and Landsat data provide higher accuracy than Sentinel-2. Full article

Information on land use and land cover modification and their related problems for the streamflow and sediment yield are crucial for spatial planners and stakeholders to devise suitable catchment resources management plans and strategies. This research sought to assess the changes in land use and land cover (LULC) effects on the streamflow and sediment yield of the Koga watershed. Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data were used to create the land use and land cover maps. The LULC type identification analysis was performed by using ERDAS Imagine 2015. After the supervised classification, the land use and land cover maps for three distinct years (1991, 2008, and 2018) were generated, and the accuracy of the maps was reviewed. The LULC change analysis results were pointed out, as there was an appreciable LULC change in the study watershed. Agricultural land increased by 14.21% over the research period, whereas grassland decreased by 22.91%. The other LULC classes (built-up area, forest area, water body, and wetland) increased by 0.39%, 6.36%, 4.30%, and 0.46%, respectively. Contrarily, bushland decreased by 2.80%. Human activities were decisive in the significant land use alterations within the catchment. The flow rate of the river basin increased over the rainy season in the years 1991–2008 and declined in the drier months. The watershed’s sediment yield increased from 1991 to 2008 as a result of the extension of its agricultural area. Thus, the findings of this investigation demonstrated that the flow and sediment yield characteristics are changed because of the modifications within the LULC in the catchment. Some downstream and upstream parts of the area are exposed to comparatively high erosion, and the maximum amount of sediment is generated during the rainy season. Full article

Many climate change “solution” plans include net-zero goals, which involve balancing the anthropogenic greenhouse gas emissions (GHG) with their removal. Achieving net-zero goals is particularly problematic for soils because they are often excluded from GHG inventories and reduction plans. For example, Maryland’s Climate Solutions Now Act (Senate Bill 528) put forward the goal of lowering emissions of GHG to 60% under 2006 quantities by 2031 and with a _target of net-zero emissions by 2045. To achieve these goals, the state of Maryland (MD) needs to quantify GHG emissions from various sources contributing to the state’s total emissions footprint (EF). Soils are currently excluded from MD’s GHG assessments, which raises a question about how the soil impacts the net-zero goal. This study examines the challenges in meeting net-zero goals using an example of carbon dioxide (CO₂) as one of the GHG types (net-zero CO₂ emissions). The current study quantified the “realized” social costs of CO₂ (SC-CO₂) emissions for MD from new land developments in the period from 2001 to 2016 which caused a complete loss of 2.2 × 10⁹ kg of total soil carbon (TSC) resulting in $383.8M (where M = million, USD = US dollars). All MD’s counties experienced land developments with various emissions and SC-CO₂ monetary values. Most of the developments, TSC losses, and SC-CO₂ occurred near the existing urban areas of Annapolis and Baltimore City. These emissions need to be accounted for in MD’s GHG emissions reduction plans to achieve a net-zero _target. Soils of MD are limited in recarbonization capacity because 64% of the state area is occupied by highly leached Ultisols. Soil recarbonization potential is further reduced by urbanization with Prince George’s, Montgomery, and Frederick counties experiencing the highest increases in developed areas. In addition, projected sea-level rises will impact 17 of MD’s 23 counties. These losses will generate additional social costs because of migration, costs of relocation, and damages to infrastructure. The state of MD has a high proportion of private land ownership (92.4%) and low proportion of public lands, which will limit opportunities for relocation within the state. Net-zero _targets are important but meeting these _targets without specific and integrative approaches depending on the source and type of emissions may result in failure. These approaches should also focus on the social costs of emissions, which raises the need for a new concept of integrating net-zero emissions and social costs. Full article

The interdependence of biological and cultural diversity is exemplified by the new conservation paradigm of biocultural heritage. We seek to clarify obsolescent notions of nature, whereby cultural construction and identity markers of mountain communities need to reflect localized, situated, and nuanced understanding about mountainscapes as they are developed, maintained, managed, and contested in spatiality and historicity. Using the nexus of socioecological theory, we question whether a convergent approach could bridge montological knowledge systems of either different equatorial and temperate latitudes, western and eastern longitudes, hills and snow-capped mountain altitudes, or hegemonic and indigenous historicity. Using extensive literature research, intensive reflection, field observation, and critical discourse analysis, we grapple with the Nagoya Protocol of the Convention of Biological Diversity (COP 10, 2010) to elucidate the benefit sharing and linkages of biocultural diversity in tropical and temperate mountain frameworks. The result is a trend of consilience for effective conservation of mountain socioecological systems that reaffirms the transdisciplinary transgression of local knowledge and scientific input to implement the effective strategy of biocultural heritage conservation after the UN Decade of Biological Diversity. By emphasizing regeneration of derelict mountain landscapes, invigorated by empowered local communities, promoted by the Aspen Declaration, the UN Decade of Ecological Restoration, and the UN International Year of Mountain Sustainable Development, montological work on sustainable, regenerative development for 2030 can be expected. Full article

The Amazon basin, the world’s largest river basin, is a key global climate regulator. Due to the lack of an extensive network of gauging stations, this basin remains poorly monitored, hindering the management of its water resources. Due to the vast extension of the Amazon basin, hydrological modeling is the only viable approach to monitor its current status. Here, we used the Soil and Water Assessment Tool (SWAT), a process-based and time-continuous eco-hydrological model, to simulate streamflow and hydrologic water balance in an Amazonian watershed where only a few gauging stations (the Jari River Basin) are available. SWAT inputs consisted of reanalysis data based on orbital remote sensing. The calibration and validation of the SWAT model indicated a good agreement according to Nash-Sutcliffe (NS, 0.85 and 0.89), Standard Deviation Ratio (RSR, 0.39 and 0.33), and Percent Bias (PBIAS, −9.5 and −0.6) values. Overall, the model satisfactorily simulated water flow and balance characteristics, such as evapotranspiration, surface runoff, and groundwater. The SWAT model is suitable for tropical river basin management and scenario simulations of environmental changes. Full article