Search Results (154)

The study of cultural landscapes has a tradition stretching back several decades. During this time, methods have been developed based on the geographical data and technological capabilities available. However, with new data becoming available, new methodological and conceptual challenges arise in linking different types of landscape data. In our article, we attempt to address these challenges. These include historical maps and remote sensing data, such as aerial and satellite images and LiDAR data. We illustrate these using examples of traditional heritage landscapes in Slovakia. We critically evaluated the informational value of historical maps and their connection with remote sensing data. Our case studies focused on using LiDAR data to identify overgrowing processes, historical trackways, agricultural terraces, catchworks and tree vegetation in wood pastures. Digital technology provides new and more accurate data, as well as new ways of evaluating it, thereby enriching existing landscape ecological methods of cultural landscape research. Full article

The conservation and intervention of heritage structures require a flexible, interdisciplinary environment capable of managing data throughout the building’s life cycle. Historic building information modeling (HBIM) has emerged as an effective tool for supporting these processes. Originally conceived for parametric construction modeling, BIM can also integrate historical transformations, aiding in maintenance and preservation. Historic buildings often feature complex geometries and visible material traces of time, requiring detailed analysis. This research proposes a methodology for documenting and assessing the envelope of historic buildings by locating, classifying, and recording transformations, deterioration, and structural deformations. The approach is based on semantic segmentation and classification using data from terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs), applied to the Palace of Miguel de Mañara—an iconic 17th-century building in Seville. Archival images were integrated into the HBIM model to identify previous restoration interventions and assess current deterioration. The methodology included geometric characterization, material mapping, semantic segmentation, diagnostic input, and temporal analysis. The results validated a process for detecting pathological cracks in masonry facades, providing a collaborative HBIM framework enriched with expert-validated data to support repair decisions and guide conservation efforts. Full article

With the rise of the sharing economy and the concept of the sharing city, the field of urban renewal is facing new opportunities and challenges. This paper innovatively explores built heritage renewal in central Shanghai from the perspective of the sharing economy, focusing on the evolution of plot morphology and associated design strategies. Six representative cases, selected within the framework of three urban renewal policies from 1999 to the present, are analyzed using a diachronic method based on the Conzen school and the street frontage index. Combined with historical maps, aerial photographs, and satellite images, the paper analyzes the changes in plot morphology from 1999 to 2024. The paper highlights how the introduction of sharing city principles significantly impacted plot morphology, facilitating the expansion and diversification of space use and driving the restructuring of plot boundaries, including physical, property, and activity boundaries. The study further reveals how the shared city concept has led to the emergence of privately owned public spaces. Additionally, the paper discusses the pursuit of flow, openness, and sharing in urban renewal, noting how these factors have shifted the focus from purely rentable and sellable areas to more efficient space resource allocation, optimizing spatial configurations. Finally, the paper introduces the concept of “sharing by transfer”, proposing that adjustments to plot boundaries under the sharing economy framework can foster more equitable, efficient, and sustainable urban renewal, providing new perspectives and strategic recommendations for built heritage renewal. Full article

(1) Background: This study aims to analyze the defoliation and boll opening performance of 123 upland cotton germplasm resources after spraying defoliant, using multispectral data to select relevant vegetation indices and identify germplasm resources sensitive to defoliants, providing methods for cotton variety improvement and high-quality parental resources. (2) Methods: 123 historical upland cotton germplasm resources from Xinjiang were selected, and the defoliation and boll opening of cotton leaves were investigated at 0, 4, 8, 12, 16, and 20 days after defoliant application. Simultaneously, multispectral digital images were collected using drones to obtain 12 vegetation indices. Based on defoliation rate, the optimal vegetation index was selected, and defoliant-sensitive germplasm resources were identified. (3) Results: The most significant difference in defoliation rate of cotton germplasm resources occurred 16 days after application. Cluster analysis grouped the 123 breeding materials into three categories, with Class I showing the best defoliation effect. Among the 12 vegetation indices, the Plant Senescence Reflectance Index (PSRI) has the highest correlation coefficient with the defoliation rate; and when the PSRI value is higher, the defoliation effect of the material is better. By comparing the traditional investigation method with the unmanned aerial vehicle multispectral technology, 15 cotton materials sensitive to defoliants were determined, with a defoliation rate of over 85%, a lint percentage ranging from 76.67% to 98.04%, and a PSRI value ranging from 0.1607 to 0.1984. (4) Conclusions: The study found that the vegetation index with sensitive response can be used as an effective indicator to evaluate the sensitivity of cotton breeding materials to defoliants. Using an unmanned aerial vehicle (UAV) equipped with vegetation indices for screening shows a high consistency with the manual investigation and screening method in screening excellent defoliation materials; it proves that it is feasible to screen cotton breeding materials with excellent defoliation effects using UAV multispectral technology. Full article

The floodplain of a large river plays a crucial role in the river’s ecosystem and serves as an essential microhabitat for river fish to complete their life history events. Over the past four decades, the floodplain represented by the Jingjiang section in the middle reaches of the Yangtze River has experienced a significant reduction in area, complexity, and diversity of fish microhabitats. This study quantitatively analyzed the dynamic changes and geomorphological structure of the floodplain in the Jingjiang reach (JJR) of the Yangtze River using satellite remote sensing images and high-resolution unmanned aerial vehicle (UAV) optical images. We built an enhanced U-Net model incorporating both the CBAM and SE parallel attention mechanisms to classify these images and identify environmental structural units. The accuracy of the enhanced model was 16.39% higher compared to original U-Net model. At the same time, the improved normalized difference water index (mNDWI), enhanced vegetation index (EVI), and normalized difference vegetation index (NDVI) were utilized to extract the flood frequency of the floodplain and analyze the area changes of the floodplain in the JJR. The trend of the flood area in the JJR during the flood season was consistent with the overall trend of flood areas in the flood season, which generally exhibits a downward tendency. In 2022, the floodplain of the JJR underwent substantial anthropogenic disturbances, with 40% of its area comprising anthropogenic environmental units. Compared to historical periods, the impervious surface within the floodplain has increased annually, while ecological units such as riparian forests and trees have gradually diminished or even disappeared, leading to a simplification of structural complexity. These findings provide a critical background and robust data foundation for the protection and restoration of fish habitats and the formulation of strategies for fish population reconstruction in the Yangtze River. Full article

Understanding long-term coastal evolution requires historical data, yet accessing reliable information becomes increasingly challenging for extended periods. While vertical aerial imagery has been extensively used in coastal studies since the mid-20th century, and satellite-derived shoreline measurements are now revolutionizing shoreline change studies, ground-based images, such as historical photographs and picture postcards, provide an alternative source of shoreline data for earlier periods when other datasets are scarce. Despite their frequent use for documenting qualitative morphological changes, these valuable historical data sources have rarely supported quantitative assessments of coastal evolution. This study demonstrates the potential of historical ground-oblique images for quantitatively assessing shoreline position and long-term change. Using Conceição-Duquesa Beach (Cascais, Portugal) as a case study, we analyze shoreline evolution over 92 years by applying a novel methodology to historical photographs and postcards. The approach combines image registration, shoreline detection, coordinate transformation, and rectification while accounting for positional uncertainty. Results reveal a significant counterclockwise rotation of the shoreline between the 20th and 21st centuries, exceeding estimated uncertainty thresholds. This study highlights the feasibility of using historical ground-based imagery to reconstruct shoreline positions and quantify long-term coastal change. The methodology is straightforward, adaptable, and offers a promising avenue for extending the temporal range of shoreline datasets, advancing our understanding of coastal evolution. Full article

This study investigates the often-overlooked phenomenon of land drainage interventions as a means of climate change adaptation, focusing on a conceptual case study from Northern Bohemia, Czech Republic. The intensification of agriculture has led to extensive tile drainage systems, which have had significant environmental impacts, including disruption of water balance, nutrient leaching, and ecological degradation. With climate change expected to alter precipitation patterns and increase temperatures, these impacts are likely to intensify, leading to more frequent droughts and pollutant delivery from soil to water bodies. This study explores the options for the allocation and implementation of drainage-related measures such as controlled drainage, constructed wetlands, and partial drainage elimination to mitigate these effects, with the use of readily available archival data as well as aerial images, current as well as historical soil, land use, geomorphological and landowner-land user relationships. At two cadastral units with local potable water resources at the hilly Lovečkovicko case study, the paper proposes conceptual, practical approaches for integrating drainage-related measures into land consolidation processes. Here, eleven sites based on the cross-intersection of the above interventions’ criteria were selected, and twenty various drainage-related measures were tentatively designed. This study categorizes the implementation potential of the proposed measures into three levels: high, medium, and low, highlighting the feasibility and transferability of these interventions within the land consolidation or similar process. Full article

The present study aimed at identifying the transformations that occurred since the 1600s in a low-lying territory located east of the Venice Lagoon. The environmental modifications were examined in a GIS environment through the interpretation of multidisciplinary data. The analysis of historical maps realized from 1641 to 1943, as well as aerial photographs and satellite images taken in the last few decades, was fundamental to reconstruct the evolution of the study area mainly in relation to anthropogenic processes. Over the past few centuries, various attempts of land reclamation partially or totally failed. However, even if an overall general decrease in both the total pond surface area and the marsh extension has been observed since the 19th century, the territory appeared entirely dry back only in the 1940s owing to the efficacy of the main most recent works. Full article

When rivers impinge on the steep bluffs of valley walls, dynamic changes stem from a combination of fluvial and mass wasting processes. This study identifies the geomorphic changes, drivers, and timing of a landslide adjacent to the Apalachicola River at Alum Bluff, the tallest natural geological exposure in Florida at ~40 m, comprising horizontal sediments of mixed lithology. We used hydrographic surveys from 1960 and 2010, two sets of LiDAR from 2007 and 2018, historical aerial, drone, and ground photography, and satellite imagery to interpret changes at this bluff and river bottom. Evidence of slope failure includes a recessed upper section with concave scarps and debris fans in the lower section with subaqueous features including two occlusions and a small island exposed from the channel bottom at lower water levels. Aerial photos and satellite images indicate that the failure occurred in at least two phases in early 2013 and 2015. The loss in volume in the 11-year interval, dominantly from the upper portion of the bluff, was ~72,750 m³ and was offset by gains of ~14,760 m³ at the lower portion of the bluff, suggesting that nearly 80% of the material traveled into the river, causing changes in riverbed morphology from the runout. Despite being along a cutbank and next to the scour pool of a large meandering river, this failure was not driven by floods and the associated lateral erosion, but instead by rainfall in noncohesive sediments at the upper portion of the bluff. This medium-magnitude landslide is now the second documented landslide in Florida. Full article

Deep learning-based super-resolution (SR) is an effective state-of-the-art technique for enhancing low-resolution images. This study explains a hierarchical dataset structure within the scope of enhancing grayscale historical aerial photographs with a basic SR model and relates it to non-reference image quality metric. The dataset was structured based on the hierarchy of photo interpretation elements. Images of bare land and forestry areas were evaluated as the primary category containing tone and color elements, images of residential areas as the secondary category containing shape and size elements, and images of farmland areas as the tertiary category containing pattern elements. Instead of training all images in all categories at once, which is the issue that any SR model with low number of parameters has difficulty handling, each category was trained separately. Test images containing the features of each category were enhanced separately, which means three enhanced images for one test image. The obtained images were divided into equal parts of 5 × 5 pixel size, and the final image was created by concatenating those that were determined to be of higher quality based on the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) metric values. Subsequently, comparative analyses based on visual interpretation and reference-based image quality metrics proved that the approach to the dataset structure positively impacted the results. Full article

Accurate and robust information on land cover changes in urban and coastal areas is essential for effective urban land management, ecosystem monitoring, and urban planning. This paper details the methodology and results of a pixel-level classification and change detection analysis, leveraging 1945 Royal Air Force (RAF) aerial imagery and 2011 Very High-Resolution (VHR) multispectral WorldView-2 satellite imagery from the broader area of Patras, Greece. Our attention is mainly focused on the changes in the coastline from the city of Patras to the northeast direction and the two major rivers, Charadros and Selemnos. The methodology involves preprocessing steps such as registration, denoising, and resolution adjustments to ensure computational feasibility for both coastal and riverbed change detection procedures while maintaining critical spatial features. For change detection at coastal areas over time, the Normalized Difference Water Index (NDWI) was applied to the new imagery to mask out the sea from the coastline and manually archive imagery from 1945. To determine the differences in the coastline between 1945 and 2011, we perform image differencing by subtracting the 1945 image from the 2011 image. This highlights the areas where changes have occurred over time. To conduct riverbed change detection, feature extraction using the Gray-Level Co-occurrence Matrix (GLCM) was applied to capture spatial characteristics. A Support Vector Machine (SVM) classification model was trained to distinguish river pixels from non-river pixels, enabling the identification of changes in riverbeds and achieving 92.6% and 92.5% accuracy for new and old imagery, respectively. Post-classification processing included classification maps to enhance the visualization of the detected changes. This approach highlights the potential of combining historical and modern imagery with supervised machine learning methods to effectively assess coastal erosion and riverbed alterations. Full article

At the turn of the 20th century, Christian and Catholic churches in Western nations established numerous mission hospitals in non-European regions. In China, mission hospitals represent a significant category of modern architectural heritage, symbolising advancements in healthcare and medical education while also serving as historical artifacts of early cultural interactions between China and the West. With ongoing developments in medical technology, these mission hospital structures no longer meet contemporary healthcare demands; many have been repurposed or temporarily abandoned. Preserving and effectively repurposing mission hospital heritage has thus emerged as a critical issue. In the present study, the Shantung Christian University Union Medical College was examined as a case study in addressing this challenge. The site retains the original Outpatient Building, Inpatient Building, Medical Teaching Building, and other architectural heritage and has preserved the original mixed Chinese and Western architectural styles. A combination of historical research, field investigation, and historic layering was adopted in the present study, drawing primarily on data from historical maps, satellite images from different periods, aerial photography from drones, architectural drawings, and other relevant historical data. Through case studies, methods for characterising and identifying the landscape and architectural heritage of mission hospitals were explored. Principles for the preservation and regeneration of the heritage of church hospitals were also proposed, with a view to providing a reference for the study and preservation of this type of heritage. Full article

The global rise in temperatures due to climate change has made it difficult even for specialised desert-adapted plant species to survive on sandy desert soils. Two of Namibia’s iconic desert-adapted plant species, Welwitschia mirabilis and the quiver tree Aloidendron dichotomum, have recently been shown to be under threat because of climate change. In the current study, three ecologically important Namibian Euphorbia milk bushes were evaluated for their climate change response. By comparing good-quality aerial photographs from the 1960s and recent 2020s high-resolution satellite images, it was determined by QGIS remote sensing techniques that very high percentages of the large succulents E. damarana, E. gummifera, and E. gregaria have died during the last 50 years in arid areas of Namibia. Areas like Brandberg (northern Namibia), Klein Karas (south-east), and Garub (south-west), with a high sandy-textured ground cover, have seen the loss of around 90% of E. damarana and E. gregaria and about 61% of E. gummifera in this period. This is alarming, as it could threaten the survival of several animal species adapted to feed on them, especially during droughts. This study focused on large succulent euphorbias, distinguishable in satellite images and historical photographs. It was observed that many other plant species are also severely stressed in arid sandy areas. The obtained results were ground-truthed and species identification was confirmed by the chemical analysis of remaining dead twigs using GC-MS and metabolomics. The ERA5 satellite’s 2 m above-ground temperature data show a 2 °C rise in annual average noon temperatures since 1950 at the three locations analysed. Annual daily temperatures increased by 1.3 °C since 1950, exceeding the global average rise of about 1.0 °C since 1900. This suggests that euphorbias and other plants on low-water-capacity sandy soils in Namibia face greater climate change pressure than plants globally. Full article

Unmanned aerial vehicle (UAV) remote sensing has found extensive applications in various fields due to its ability to quickly provide remote sensing imagery, and the rapid, even automated, geometric registration of these images is an important component of their time efficiency. While current geometric registration methods based on image matching are well developed, there is still room for improvement in terms of time efficiency due to the presence of the following factors: (1) difficulty in accessing historical reference images and (2) inconsistencies in data sources, scales, and orientations between UAV imagery and reference images, which leads to unreliable matching. To further improve the time efficiency of UAV remote sensing, this study proposes a fully automatic geometric registration framework. The workflow features the following aspects: (1) automatic reference image acquisition by using online map services; (2) automatic ground range and resolution estimation using positional and orientation system (POS) data; (3) automatic orientation alignment using POS data. Experimental validation demonstrates that the proposed framework is able to carry out the fully automatic geometric registration of UAV imagery, thus improving the time efficiency of UAV remote sensing. Full article

The visual evaluation and characteristic analysis of urban rivers are pivotal for advancing our understanding of urban waterscapes and their surrounding environments. Unmanned aerial vehicles (UAVs) offer significant advantages over traditional satellite remote sensing, including flexible aerial surveying, diverse perspectives, and high-resolution imagery. This study centers on the Haihe River, South Canal, and North Canal in Tianjin China, employing UAVs to capture continuous panoramic image data. Through immersive virtual reality (VR) technology, visual evaluations of these panoramic images were obtained from a cohort of young participants. These evaluations encompassed assessments of scenic beauty, color richness, vitality, and historical sense. Subsequently, computer vision techniques were utilized to quantitatively analyze the proportions of various landscape elements (e.g., trees, grass, buildings) within the images. Clustering analysis of visual evaluation results and semantic segmentation outcomes from different study points facilitated the effective identification and grouping of river visual features. The findings reveal significant differences in scenic beauty, color richness, and vitality among the Haihe River, South Canal, and North Canal, whereas the South and North Canals exhibited a limited sense of history. Six landscape elements—water bodies, buildings, trees, etc.—comprised over 90% of the images, forming the primary visual characteristics of the three rivers. Nonetheless, the uneven spatial distribution of these elements resulted in notable variations in the visual features of the rivers. This study demonstrates that the visual feature analysis method based on UAV panoramic images can achieve a quantitative evaluation of multi-scene urban 3D landscapes, thereby providing a robust scientific foundation for the optimization of urban river environments. Full article