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Illegal waste is a global problem with negative impacts on human health and the environment. This article focuses on detection using remote sensing of sites of demolition and construction waste. We hypothesise that construction and demolition waste represent a human modification of terrain and, as a result, will be sensible to detection using visualisation models of terrain, specifically DEM (digital elevation model). To this effect, we start with a DEM of 0.25 m per pixel developed using data from the second iteration of the PNOA LiDAR project by the Spanish National Geographic Institute (IGN). We evaluate seven modelling tools of the Relief Visualisation Toolbox (RVT) for the visual detection of waste. The study area includes the city of Mérida (Extremadura, Spain). Our fieldwork identified 494 points of illegal waste in this area. These points were classified according to five categories in relation to land use, and we established a total of 14 areas with a surface area of 450 m by 450 m. Our results suggest that three of the seven models employed allow us to differentiate with clarity what is anthropic from the natural terrain and, in some scenarios, the location of construction and demolition waste. The LD model was the one with the best results, allowing an increase in the number of locations of illegal dumping of CDW in the study area.

The GIAHS-FAO program enhances the agricultural systems coevolved with humans through their dynamic conservation to guarantee the livelihood of future generations. The aim of this research was to assess, with a dynamic perspective, the terraced landscape’s integrity in a potential GIAHS-FAO site (Northwest Piedmont, Italy, 545 ha) characterized by a pergola caremiese vine-breeding technique. We developed a GIS-based approach to explore the main features that can affect the landscape’s integrity, starting from the changes of the land use. The aerial IGMI images (1954–1968) and the AGEA (2018) orthophoto were photo-interpreted using QGIS 3.16.2 “Hannover” (minimum mappable unit 100 m2). The results showed that 70.16% of the historical landscape was preserved, while the surface of vineyards decreased because of their abandonment. We observed that vineyards are the land use that requires more attention in future planning strategies, and that the landscape’s integrity is affected by the limited introduction of non-traditional vine-breeding techniques (espaliers) and new crops (olives groves). The methodology was able to assess the terraced landscape’s integrity in a dynamic perspective. The good integrity makes the study area a potential GIAHS-FAO site. Future planning strategies will have to lead the changing processes and preserve the landscape’s integrity.

The encroachment of wild boars into urban areas is a growing problem. The occurrence of wild boars in cities leads to conflict situations. Socio-spatial conflicts can escalate to a varied degree. Assessments of these conflicts can be performed by analyzing spatial data concerning the affected locations and wild boar behaviors. The collection of spatial data is a laborious and costly process that requires access to urban surveillance systems, in addition to regular analyses of intervention reports. A supporting method for assessing the risk of wild boar encroachment and socio-spatial conflict in cities was proposed in the present study. The developed approach relies on big data, namely, multimedia and descriptive data that are on social media. The proposed method was tested in the city of Olsztyn in Poland. The main aim of this study was to evaluate the applicability of data crowdsourced from a popular social networking site for determining the location and severity of conflicts. A photointerpretation method and the kernel density estimation (KDE) tool implemented in ArcGIS Desktop 10.7.1 software were applied in the study. The proposed approach fills a gap in the application of crowdsourcing data to identify types of socio-spatial conflicts involving wild boars in urban areas. Validation of the results with reports of calls to intervention services showed the high coverage of this approach and thus the usefulness of crowdsourcing data.

The paper describes the development of predictive equations of windthrow for five tree species based on remote sensing of wind-affected stands in southwestern New Brunswick (NB). The data characterises forest conditions before, during and after the passing of extratropical cyclone Arthur, July 4–5, 2014. The five-variable logistic function developed for balsam fir (bF) was validated against remote-sensing-acquired windthrow data for bF-stands affected by the Christmas Mountains windthrow event of November 7, 1994. In general, the prediction of windthrow in the area agreed fairly well with the windthrow sites identified by photogrammetry. The occurrence of windthrow in the Christmas Mountains was prominent in areas with shallow soils and prone to localised accelerations in mean and turbulent airflow. The windthrow function for bF was subsequently used to examine the future impact of windthrow under two climate scenarios (RCP’s 4.5 and 8.5) and species response to local changes anticipated with global climate change, particularly with respect to growing degree-days and soil moisture. Under climate change, future windthrow in bF stands (2006–2100) is projected to be modified as the species withdraws from the high-elevation areas and NB as a whole, as the climate progressively warms and precipitation increases, causing the growing environment of bF to deteriorate.

The aim of this article is to show geomorphological mapping of remote Antarctic locations using images taken by a fixed-wing unmanned aerial vehicle (UAV) during the Beyond Visual Line of Sight (BVLOS) operations. We mapped landform assemblages developed in forelands of Ecology Glacier (EGF), Sphinx Glacier (SGF) and Baranowski Glacier (BGF) in Antarctic Specially Protected Area No. 128 (ASPA 128) on King George Island (South Shetland Islands) and inferred about glacial dynamics. The orthophoto and digital elevation model allowed for geomorphological mapping of glacial forelands, including (i) glacial depositional landforms, (ii) fluvial and fluvioglacial landforms, (iii) littoral and lacustrine landforms, (iv) bodies of water, and (v) other. The largest area is occupied by ground moraine and glacial lagoons on EGF and BGF. The most profound features of EGF are the large latero-frontal moraine ridges from Little Ice Age and the first half of the 20th century. Large areas of ground moraine, frequently fluted and marked with large recessional moraine ridges, dominate on SGF. A significant percentage of bedrock outcrops and end moraine complexes characterize BGF. The landform assemblages are typical for discontinuous fast ice flow of tidewater glaciers over a deformable bed. It is inferred that ice flow velocity decreased as a result of recession from the sea coast, resulting in a significant decrease in the length of ice cliffs and decrease in calving rate. Image acquisition during the fixed-wing UAV BVLOS operation proved to be a very robust technique in harsh polar conditions of King George Island.

Recent increases in urbanization and tourism threaten the viability of UNESCO world heritage sites across the globe. The Angkor world heritage site located in southern Cambodia is now facing such a challenge. Over the past two decades, Angkor has seen over 300,000% growth in international tourist arrivals, which has led to uncontrolled development of the nearby city of Siem Reap. This study uses remote sensing and GIS to comprehend the process of urban expansion during the past 14 years, and has applied the CA-Markov model to predict future urban expansion. This paper analyzes the urban pressure on the Angkor site at different scales. The results reveal that the urban area of Siem Reap city increased from 28.23 km2 in 2004 to 73.56 km2 in 2017, an increase of 160%. Urban growth mainly represented a transit-oriented pattern of expansion, and it was also observed that land surfaces, such as arable land, forests, and grasslands, were transformed into urban residential land. The total constructed land area in the core and buffer zones increased by 12.99 km2 from 2004 to 2017, and 72% of the total increase was in the buffer zone. It is predicted that the built-up area in Siem Reap is expected to cover 135.09 km2 by 2025 and 159.14 km2 by 2030. The number of monuments that are most likely be affected by urban expansion is expected to increase from 9 in 2017 to 14 in 2025 and 17 in 2030. The urban area in Siem Reap has increased dramatically over the past decade and monuments continue to be decimated by urban expansion. This paper urges closer attention and urgent actions to minimize the urban pressure on the Angkor site in the future.