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(War) destruction of a city is not easily representable. Not only is the entirety of urban space hardly ever equally affected but also, within the damaged areas, there are different degrees of ruination. Along with photos and aerial photography, maps are one of the most common means of representing cities' war destruction. Despite their appearance, however, they are not an objective and impartial representation, but rather a narrative that can be deconstructed and interpreted in various ways. This paper inquires to what extent the Cottbus war damage map is a reliable testimony of the urban disaster, what its limitations are, and what story it tells. For all its precision, it was not made to serve utilitarian purposes, but rather as a mean of commemoration. This draws our attention to the fact that maps should not be only measured by their accuracy, but rather recognized and assessed on their own terms. [ABSTRACT FROM AUTHOR]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research examines the transformation of the Lake Pontchartrain coastal landscape, including the New Orleans shoreline. The paper addresses the critical need to understand long-term environmental change through a comprehensive geospatial analysis of historical cartographic representations. The study employs a methodology involving three key steps: (1) georeferencing maps using QGis v. 3.4.8., (2) vectorization using AutoCAD v. 2013, and (3) comparative spatial analysis to quantify coastal morphological changes. The quantitative results reveal significant coastal dynamics, with Lake Pontchartrain experiencing a total erosion balance of −36.42 km2, although the New Orleans coastal zone has experienced land reclamation. This loss can be attributed to the synergistic interaction of natural (e.g., subsidence, sea level rise, hurricanes) and anthropogenic (e.g., urban development, infrastructure, ecological fragmentation) processes that have accelerated coastal erosion in the study area. The research provides a critical historical analysis of the evolution of coastal landscapes in response to anthropogenic influences. However, the methodology is constrained when it comes to addressing the socioeconomic impacts. Nevertheless, the study considered the profound environmental and societal consequences of historical governmental and social decisions, thereby underscoring the intricate interplay between natural processes and human intervention in coastal ecosystems. These findings contribute to a more profound comprehension of the processes of coastal landscape transformation, underscoring the dynamic and fragile nature of coastal environments. [ABSTRACT FROM AUTHOR]

Historical aerial photographs from the early twentieth century have great interpretive potential for understanding the agricultural landscapes they record. In addition to building a chronology of farm layout, historical images can record particular crops and other agricultural activities, adding nuance to interpretations of historical agricultural space. Identifying particular crops and other activities requires practice and skill. This article presents a set of basic interpretive tools for understanding what is recorded in historical aerial photographs of farmland. An extended example is presented from Lunenburg County, Virginia. [ABSTRACT FROM AUTHOR]

Timely and accurate mastery of the spatial and temporal development process of landslides is crucial for emergency rescue work. In the early morning of July 5, 2022, under the influence of continuous heavy rainfall, the left embankment slope of a highway in Guangdong Province, slipped as a whole, and a truck fell and was buried, resulting in the interruption of highway traffic. In order to accurately carry out landslide analysis and management, and to provide information support for emergency rescue and relief work, whole-process survey and analysis of the landslide area was carried out based on unmanned aerial vehicle tilt photography, 3D reconstruction and spatial analysis technology. In situations where traditional surveying and mapping work is difficult to carry out, it is possible to accurately grasp the whole process of the development of landslides in space and time under the circumstances and construct corresponding realistic three-dimensional models to provide effective reference information for on-site rescue and relief work. At the same time, through the comprehensive analysis of the acquired information, it is inferred that the landslide is a traction landslide under the effect of continuous rainfall. [ABSTRACT FROM AUTHOR]

Quadrotor unmanned aerial vehicles (UAVs) operating in agricultural fields for aerial photography are susceptible to external disturbances. The disturbances result in trajectory deviation and irregular image overlapping that considerably degrade image quality. Disturbance observers (DOs) are commonly researched for counteracting these effects but may have delays and limitations in handling diverse and high-frequency disturbances. To this end, this work proposes a continuous high-order sliding mode-assisted DO (HSMDO) with limited time convergence characteristics for the estimation of disturbances in systems. The observer consists of a classical nonlinear DO (NDO) and a sliding mode-assisted system (SMAS). The NDO is used to estimate disturbances preliminarily. The SMAS is utilised to assist the NDO in estimating the high-frequency component of disturbances and ensure that the entire DO is finite-time convergent. Finally, the tracking controller is designed on the basis of the HSMDO, which enables UAVs to track the prescribed trajectories under disturbances stably. Simulation results show that the proposed HSMDO can accurately estimate various types of disturbances. Moreover, the tracking controller based on the HSMDO can improve the antidisturbance performance of systems and ensure the trajectory tracking accuracy of UAVs. [ABSTRACT FROM AUTHOR]

As a principal insulating component in power transmission systems, the integrity of the insulator is of paramount importance for ensuring the safe and reliable operation of transmission lines. While the deployment of aerial photography technology has markedly enhanced the efficacy of power facility inspections, the intricate backgrounds, multifarious viewpoint alterations, and erratic lighting circumstances inherent in the captured images present novel challenges for the algorithmic detection of insulator defects. To address these issues, this study proposes an enhanced version of the YOLOV7 detection algorithm. The introduction of the contextual transformer network (CoTNet) structure and an EMA attention mechanism enhances the model's capacity to perceive global contextual information in images and to model long-distance feature dependencies. Experiments based on a real aerial photography dataset demonstrate that the proposed algorithm outperforms the benchmark model in all key performance indicators, including accuracy, recall, and F1 score, which improved by 0.6%, 1.8%, and 0.8%, respectively. Additionally, the average precision (mAP@[0.5]) and mAP@[0.5:0.95] improved by 0.6% and 4.4%, respectively. The superiority of the algorithm in feature extraction and target localization is verified through Grad-CAM visual analysis, which provides a high-precision detection method for intelligent inspection of power transmission systems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The combination of global climate change and the urban heat island effect has given rise to a deterioration in the livability of residential districts within cities, posing challenges to enhancing the health quality of urban environments. Meanwhile, the intensification of daytime changes in temperature and humidity in residential districts has rendered the sensory representation of the urban heat island effect more pronounced. This study selects the residential districts in Fuzhou City as the research case area, which have witnessed a discernible warming trend in recent years, and acquires temperature and humidity parameter data at three time periods (early morning, noon, and evening) to represent the daytime temperature and humidity change phase. Through aerial photography and field research, three types of spatial morphological indicators (buildings I, vegetation II, and the combination of buildings and vegetation II) of residential districts are quantified to represent the three-dimensional spatial form of the case study area. The analysis results show the following: ➀ Residential districts experience two phases of daytime changes in temperature and humidity: a warming and drying phase (WDP) in the morning and a cooling and humidifying phase (CHP) in the afternoon. The characteristics of changes in temperature and humidity show a spatial correlation with each other. ➁ The impact of urban three-dimensional morphology on changes in temperature and humidity in WDP is minor, whereas, in CHP, it is influenced by Class II and Class III indicators. The two types of urban morphology exert a synergistic regulatory effect on changes in temperature and humidity. ➂ Vegetation has a significant regulatory effect on temperature and humidity variations in residential areas through changes in its three-dimensional form. Enlarging the area of individual trees while reducing their canopy volume can restrain the warming and dehumidification of residential districts and promote cooling and humidification. In contrast to only planting trees, a vegetation configuration combining trees, shrubs, and grass can bring a more obvious cooling effect to residential districts. The research results can provide a reference for urban planners in the planning and design of residential areas as well as the optimization and improvement of urban living environments. [ABSTRACT FROM AUTHOR]

For over a century, large-scale irrigation has been a cornerstone of Ancestral O'Odham (Hohokam) archaeological study. Along the lower Salt River, located in the Phoenix Basin, Arizona, a concerted effort has been made to understand Ancestral O'Odham agricultural production by reconstructing the histories of the largest irrigation systems. In this article, I will discuss an updated reconstruction of ancient irrigation along the lower Salt River. The article begins with an overview of previous Ancestral O'Odham irrigation. Next, the method used to create a new diachronic reconstruction of Ancestral O'Odham irrigation is provided. The method integrates canal signatures seen in historic aerial photography with excavation data and previous canal maps. Synthesized reconstructions of eight major irrigation systems are aggregated into an updated developmental history of irrigation in the lower Salt River Valley. Accompanying this update are discussions of a late Colonial/early Sedentary extremely large flood and standardized irrigation units (SIU). [ABSTRACT FROM AUTHOR]

In this article, a three-axis stable platform control method based on a lightweight, lowprecision global navigation satellite system (GNSS), inertial measurement unit (IMU) system, and proportion integration and differentiation (PID) algorithm is proposed to solve the stable imaging issues of a low-altitude unmanned airship aerial remote sensing system. The system utilizes a lightweight GNSS/IMU, which work with a dual global positioning system (GPS), connecting the camera system and flight platform through a three-axis stabilization platform, employing a PID control method with an open-loop control approach, and implementing stabilization control using a system-on-chip microcontroller for 32-bit (STM32) control chip circuit to address the camera attitude stabilization issue in the unmanned airship remote sensing system. The stability of the system is verified by a flight test, and the experimental results also show that the method can effectively isolate the effect of the instability of the unmanned airship attitude on the imaging system and effectively improve the imaging quality, which is of considerable significance for improving the accuracy of the unmanned airship aerial survey system. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) imaging provides the ability to obtain high-resolution images at a lower cost than satellite imagery and aerial photography. However, multiple UAV images need to be mosaicked to obtain images of large areas, and the resulting UAV multispectral image mosaics typically contain seam lines. To address this problem, we applied irradiance, vignette, and bidirectional reflectance distribution function (BRDF) filters and performed field work using a DJI Mavic 3 Multispectral (M3M) camera to collect data. We installed a calibrated reference tarp (CRT) in the center of the collection area and conducted three types of flights (BRDF, vignette, and validation) to measure the irradiance, radiance, and reflectance—which are essential for irradiance correction—using a custom reflectance box (ROX). A vignette filter was generated from the vignette parameter, and the anisotropy factor (ANIF) was calculated by measuring the radiance at the nadir, following which the BRDF model parameters were calculated. The calibration approaches were divided into the following categories: a vignette-only process, which solely applied vignette and irradiance corrections, and the full process, which included irradiance, vignette, and BRDF. The accuracy was verified through a validation flight. The radiance uncertainty at the seam line ranged from 3.00 to 5.26% in the 80% lap mode when using nine images around the CRT, and from 4.06 to 6.93% in the 50% lap mode when using all images with the CRT. The term 'lap' in 'lap mode' refers to both overlap and sidelap. The images that were subjected to the vignette-only process had a radiance difference of 4.48–6.98%, while that of the full process images was 1.44–2.40%, indicating that the seam lines were difficult to find with the naked eye and that the process was successful. [ABSTRACT FROM AUTHOR]

An improved EA‐YOLO object detection algorithm based on YOLOv5 is proposed to address the issues of drastic changes in target scale, low detection accuracy, and high miss rate in unmanned aerial vehicle aerial photography scenarios. Firstly, a DFE module was proposed to improve the effectiveness of feature extraction and enhance the whole model's ability to learn residual features. Secondly, a CWFF architecture was introduced to enable deeper feature fusion and improve the effectiveness of feature fusion. Finally, in order to solve the traditional algorithm's shortcomings it is difficult to detect small targets. We have designed a novel SDS structure and adopted a strategy of reusing low‐level feature maps to enhance the network's ability to detect small targets, making it more suitable for detecting some small objects in drone images. Experiments in the VisDrone2019 dataset demonstrated that the proposed EA‐YOLOs achieved an average accuracy mAP@0.5 of 39.9%, which is an 8% improvement over YOLOv5s, and mAP@0.5:0.95 of 22.2%, which is 5.2% improvement over the original algorithm. Compared with YOLOv3, YOLOv5l, and YOLOv8s, the mAP@0.5 of EA‐YOLOs improved by 0.9%, 1.8%, and 0.6%, while the GFLOPs decreased by 86.4%, 80.6%, and 26.7%. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The US-China balloon incident of February 2023 triggered the thought that stratospheric balloon technology (SBT) would be a useful addition to satellite observations for early warnings, disaster management and recovery systems in Australasia. Special properties of SBT are that balloons can hover over a disaster site for long periods of time; can operate closer to the ground, but out of the way of air traffic; can capture higher-resolution images and photographs; can use instruments similar to satellites and can gather images and data for modelling in real time. Currently, decision-makers rely on combinations of information sources such as satellites, aircraft 'line scans', command aircraft, drones, mapping systems and aerial photography to gather information and combine it. This is a lengthy process. SBT has made its way into disaster monitoring at official trials during active wildfires in the USA and into mobile communications during Hurricane Maria in 2017. No evidence was found that SBT has been used in early warnings or emergency and disaster management in Australasia, notwithstanding its potential advantages over satellite technologies, especially in the southern hemisphere where satellite coverage is relatively scarce. This study explored SBT by reviewing and analysing publicly available reports and secondary data. This paper concludes that it is an opportune time to re-evaluate the performance, properties and contributions that SBT can make to monitoring and early warnings. [ABSTRACT FROM AUTHOR]

Landscape, as an important component of environmental quality, is increasingly valued by scholars for its visual dimension. Unlike evaluating landscape visual quality through on-site observation or using digital photos, the landscape visualization modeling method supported by unmanned aerial vehicle (UAV) aerial photography, geographic information System (GIS), and PixScape has the advantage of systematically scanning landscape geographic space. The data acquisition is convenient and fast, and the resolution is high, providing a new attempt for landscape visualization analysis. In order to explore the application of visibility modeling based on high-resolution UAV remote sensing images in landscape visual evaluation, this study takes campus landscape as an example and uses high-resolution campus UAV remote sensing images as the basic data source to analyze the differences between the planar method and tangent method provided by PixScape 1.2 software in visual modeling. Six evaluation factors, including Naturalness (N), Normalized Shannon Diversity Index (S), Contagion (CONTAG), Shannon depth (SD), Depth Line (DL), and Skyline (SL), are selected to evaluate the landscape vision of four viewpoints in the campus based on analytic hierarchy process (AHP) method. The results indicate that the tangent method considers the visual impact of the vertical amplitude and the distance between landscape and viewpoints, which is more in line with the real visual perception of the human eyes. In addition, objective quantitative evaluation metrics based on visibility modeling can reflect the visual differences of landscapes from different viewpoints and have good applicability in campus landscape visual evaluation. It is expected that this research can enrich the method system of landscape visual evaluation and provide technical references for it. [ABSTRACT FROM AUTHOR]

Objectives: To conduct an in-depth study on the spatial distribution of traffic conflicts in the continuous merging areas of cross-river bridges and ensure public transportation safety. Methods: First, we utilized drone aerial photography to collect videos of vehicle movements. Using the YOLOv7 object detection algorithm and the Strong SORT multi-object tracking algorithm, we extracted high-precision vehicle trajectory time-series data. Next, based on the motion characteristics of traffic entities, we proposed using Deceleration Rate (DR) to describe rear-end conflicts and Lane Change Speed (LCS) to describe lane-changing conflicts. Additionally, we employed the K-means clustering method to determine the threshold values for minor, moderate, and severe levels of rear-end and lane-changing conflicts. Finally, based on the obtained trajectory data, the values of traffic conflicts are calculated and their severity is classified. A heat map of the spatial distribution of vehicle conflicts in continuous merging zones is then created to study the spatial distribution patterns of traffic conflicts. Results: The threshold values for minor, moderate, and severe levels of rear-end conflicts are determined to be 3.06 m/s2, 5.36 m/s2, and 8.04 m/s2, respectively. For lane-changing conflicts, the thresholds are 1.13 m/s, 2.07 m/s, and 3.45 m/s. The spatial distribution of traffic conflicts exhibits a "first increase, then decrease, and then increase again" trend. Conclusions: The study identifies the critical areas of traffic conflicts in the continuous merging zones of cross-river bridges. The research results provide a novel approach for acquiring traffic data in these areas and offer a reliable quantitative method for assessing safety risks on these road segments. This provides a theoretical basis for proposing targeted traffic safety management strategies. [ABSTRACT FROM AUTHOR]

Tree height and vertical forest structure are important attributes in forestry, but their traditional measurement or assessment in the field is expensive, time-consuming, and often inaccurate. One of the main advantages of using remote sensing data to estimate vertical forest structure is the ability to obtain accurate data for larger areas in a more time- and cost-efficient manner. Temporal changes are also important for estimating and analysing tree heights, and in many countries, national airborne laser scanning (ALS) surveys have been conducted either only once or at specific, longer intervals, whereas aerial surveys are more often arranged in cycles with shorter intervals. In this study, we reviewed all freely available national airborne remote sensing data describing three-dimensional forest structures in Slovenia and compared them with traditional field measurements in an area dominated by uneven-aged forests. The comparison of ALS and digital aerial photogrammetry (DAP) data revealed that freely available national ALS data provide better estimates of dominant forest heights, vertical structural diversity, and their changes compared to cyclic DAP data, but they are still useful due to their temporally dense data. Up-to-date data are very important for forest management and the study of forest resilience and resistance to disturbance. Based on field measurements (2013 and 2023) and all remote sensing data, dominant and maximum heights are statistically significantly higher in uneven-aged forests than in mature, even-aged forests. Canopy height diversity (CHD) information, derived from lidar ALS and DAP data, has also proven to be suitable for distinguishing between even-aged and uneven-aged forests. The CHDALS 2023 was 1.64, and the CHDCAS 2022 was 1.38 in uneven-aged stands, which were statistically significantly higher than in even-aged forest stands. [ABSTRACT FROM AUTHOR]

In September 2023, an unmanned aerial vehicle was used to conduct airborne laser scanning and aerial photography in the Makazhoy Basin, where the carbon testing ground of the A.A. Kadyrov Chechen State University is located. As a result, a highly accurate digital elevation model (DEM) was compiled for areas of about 170 hectares located on opposite macroslopes of the basin at comparable hypsometric levels (1700-2200 m). Subsequent processing of the DEM using ArcGis software allowed us to quantitatively characterize the microrelief of the test sites and identify, based on morphometric analysis and semi-automated interpretation, the terraces on the mountain slopes that were previously used for agriculture. It was found that the previously existing settlement and farming system in this area took into account the natural resource potential of the mountain slopes. In this regard, the northern macroslopes of the Makazhoy Basin are characterized by greater productivity of natural ecosystems compared to the southern ones. The consequence of these natural causes is that the terraces on the northern macroslope occupy 46% of the test site area, while on the southern one - 26%. [ABSTRACT FROM AUTHOR]

Understanding of the formation and evolution of supraglacial lakes in high mountain regions is crucial for accurately assessing their impact on glacier behaviour, hydrology, and potential hazards such as outburst floods. This article examines the annual spatio-temporal evolution of supraglacial lakes on the Belvedere Glacier between 2000 and 2023. Very high-resolution aerial photography and high-resolution satellite imagery were used to identify supraglacial lakes as small as 37 m² and narrow bands of ice-marginal lakes. The mapping revealed that the well-known Lake Effimero is stable in its position but unstable in size, with variations from 428 m² to 99.7 x 10³ m². These changes are potentially due to snowmelt or glacier dynamics. In 2002, the area of Effimero was at its largest extent observed during the study period. The first appearance of the Lake Effimero was revelated by the Landsat imagery on 27 May 2001, which differed from the findings of other studies. New lakes were observed to form in a manner independent of Effimero formation, exhibiting a consistent annual occurrence with nearly linear area growth up to 9.7 x 10³ m² in 2023. The formation of the lakes is shown to be influenced by their morphological characteristics. [ABSTRACT FROM AUTHOR]

[Objective] This study aims to explore the application of traditional mixed pixel decomposition method in drone remote sensing technology, and to propose a fast estimation method for vegetation cover and management factor (C factor) at a small scale. [Methods] Drone aerial photography was used to capture remote sensing imagery of land use in the Guli area of Jiangning, Nanjing. An object-oriented classification method was utilized to extract the coverage of various land types. The C value of the research area was computed based on the mixed pixel decomposition C factor model, and the method′s accuracy was evaluated by comparing it with previous research results. [Results] The object classification results (vegetation, bare land, and non-photosynthetic land) have an overall accuracy of over 95%. Based on the mixed pixel decomposition C factor model, the estimated C values for forestland, cultivated land, and grassland in the Guli area are 0.057, 0.176, and 0.043, respectively, which are close to existing research results. [Conclusion] Estimating C factor based on UAV remote sensing is feasible and more efficient compared to the traditional method of runoff plot observation. [ABSTRACT FROM AUTHOR]

Remote surveillance techniques from unmanned aerial vehicles (UAVs) equipped with thermal infrared cameras are a progressive platform for effective monitoring of hard-to-reach thermal objects. This paper presents the first results of UAV application to the research of five thermal objects on the Kuril Islands. Four of them (the Kipyashchaya River on Iturup Island, Lake Biryuzovoe on Simushir Island, Yankich Island, and the Yurieva River on Paramushir Island) are associated with active volcanoes. Heat maps with precise geographical reference have been obtained for all sections of gas hydrothermal discharge. Air thermometry for the Kipyashchaya River and Yankich Island were verified by ground data and real atmospheric attenuation coefficients were obtained for different flight altitudes under observed meteorological conditions. The first data on the parameters of the thermal plume from the hot Yurievа River flowing into the Sea of Okhotsk were obtained. [ABSTRACT FROM AUTHOR]

Major storms can cause significant changes to coastal and wetland environments. A series of storm events in 2020 resulted in closure of the historically open estuary at Cabbage Tree Basin, Port Hacking, New South Wales (NSW), Australia. Prolonged tidal impoundment (3 months) led to substantial changes in hydrological and sedimentological processes, resulting in widespread mangrove dieback. This study aimed to quantify the degree of impact and recovery for mangroves, identify factors contributing to dieback, and consider the implications for carbon sequestration. This was achieved using remotely piloted aircraft structure-from-motion approaches, aerial photography, and field-based assessments of vegetation health and above-ground biomass (AGB). Mangroves were classified as 'dead', 'partially dead', and 'live'. In October 2019, there was 10.8 ha of live mangroves, with this reduced to 6.6 ha by August 2022. Digital surface models (DSMs) were intersected with classified mangroves to assess the vertical distribution of each zone. All mangroves classified as 'dead' were distributed at elevations < 0.4 m with respect to the Australian Height Datum (AHD), suggesting these regions were persistently inundated, which was confirmed by water level loggers (inundated during logger deployment). Field data confirmed substrate elevation related to dieback with the proportion of 'live' mangroves greatest at elevations > 0.6 m AHD. Substrate elevation and distance to the estuary mouth were significantly correlated with species, with Avicennia marina located at lower tidal positions and closer to the entrance compared to Aegiceras corniculatum. The dieback event equated to a loss of 81.5 ± 48 Mg of above-ground biomass, 38.1 ± 22.5 Mg C, or 140 ± 82 Mg CO2 equivalence (CO2e). This study provides an important baseline for monitoring dieback events. Continued monitoring is crucial to assess recovery and to tailor management strategies. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mountain search and rescue (MSAR) seeks to assist people in extreme remote environments. This method of emergency response often relies on crewed aircraft to perform aerial visual search. Many MSAR teams use low‐cost, consumer‐grade unmanned aerial vehicles (UAVs) to augment the crewed aircraft operations. These UAVs are primarily developed for aerial photography and lack many features critical (e.g., probability‐prioritized coverage path planning) to support MSAR operations. As a result, UAVs are underutilized in MSAR. A case study of a recent mountain search and recovery scenario that did not use, but may have benefited from, UAVs is provided. An overview of the mission is augmented with a subject matter expert‐informed analysis of how the mission may have benefited from current UAV technology. Lastly, mission relevant requirements are presented along with a discussion of how future UAV development can seek to bridge the gap between state‐of‐the‐art robotics and MSAR. [ABSTRACT FROM AUTHOR]

Copyright of Water Conservancy Science & Techonlogy & Economy is the property of Water Conservancy Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Climate change has intensified flooding and increased localized torrential rainfalls, leading to disasters such as landslides, infrastructure collapse, and urban floods. The extent and accuracy of flood damage information significantly impact recovery processes. While previous studies primarily utilized satellite and aerial imagery for broad flood assessments, they often lacked the precision needed for accurate damage analysis. This study addresses the gap between rapid assessment needs and precise damage quantification in flood inundation analysis. This research introduces a novel image-based investigation approach to enhance the speed and accuracy of flood inundation assessment. By leveraging unmanned aerial vehicles (UAVs) and image-based spatial data technology, aerial images of flooded areas are rapidly captured to construct three-dimensional disaster site terrain information. The proposed methodology employs advanced techniques in aerial photography, image processing, and geographic analysis to quantitatively analyze flood inundation scale using only aerial images and geographic information systems (GIS). The research yielded a calculated flood inundation area of 3,847.36 m2 and a flood volume of 13,895.13 m3. This methodology complements existing flood inundation assessment techniques and has the potential to significantly improve disaster management efforts by providing rapid, accurate, and actionable data for decision-makers. [ABSTRACT FROM AUTHOR]

Objectives: On August 3, 2024, a catastrophic flash flood and debris flow devastated Ridi Village in Guzan Town, Kangding City, Sichuan Province. This disaster led to the collapse of a bridge on the Yakang Expressway between the Ridi No. 1 and No. 2 tunnels and destroyed several homes in the village, resulting in 23 people missing and 4 confirmed fatalities. Methods: To gather critical information and support emergency rescue operations, an in-depth analysis of the Ridi Gully debris flow was conducted using drone aerial photography and on-site investigations. The study examined the formation processes and underlying causes of the debris flow, with key dynamic parameters being calculated. These data were then used to simulate the dynamic evolution of debris flow using FLO-2D software, and the verification accuracy (Ω) of simulation results reached 1.65. Results: The findings suggested that the debris flow was primarily triggered by internal factors, including the steep terrain of the watershed, the presence of weathered and fractured granite, and the abundance of loose material within the gully. External factors such as recent temperature increases, which accelerated snow and ice melt, along with sustained rainfall, created the conditions necessary for the debris flow to occur. The flow transported approximately 58×104 m³ of solid material, with the largest boulders measuring up to 6 m in diameter, while most ranged between 20 cm and 1 m. The flow velocity exceeded 8 m/s, and the impact force of individual boulders was over 500 kilonewtons, with the total impact force in the flow path surpassing 100 tons, resulting in significant destructive power. Conclusions: Critical insights into the formation and mechanics of the Ridi Gully debris flow offer valuable guidance for emergency response and disaster mitigation in regions with similar geological hazards in the mountainous areas of southwestern China. [ABSTRACT FROM AUTHOR]

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The January 1, 2024, Noto Peninsula earthquake left many devastated areas. Right after the event, aerial photography provided the initial assessment but covered only specific areas. Satellite images with optical sensors that are freely available are limited by spatial resolution and oftentimes covered by cloud. The Sentinel-1 Synthetic Aperture Radar (SAR) due to its all-weather sensing capability proved to be useful in mapping the extent of the affected areas. This study mapped Wajima City where earthquake aftereffects were severe as reported using coherence and intensity mapping. Pre- and post-event images were used to rapidly identify affected areas. Based on the result, taking the coherence of one pre- and one post-event images can give an impression of wide earthquake damage. The coherence of two post-event images compared with two pre-event images provides a better estimate of affected areas. Taking multiple pre- and post- event images improved the map because the large variation of the intensity is minimized through time-series averaging. Using a simple RGB composite, the affected areas were mapped. Threshold mapping was also used to extract collapsed buildings/houses using a training dataset. The mean coherence difference and mean intensity difference between pre- and post-event images were the two variables used. The computed minimum threshold for the mean coherence difference was 0.35. However, the average not the minimum of the mean intensity difference of 3.0 was used as initial value. Using mean coherence difference>=0.35 gave a high accurate prediction of collapsed buildings at 73.47% but also has false identification of 30.95%. To negate the overprediction, the mean intensity difference<=4.0 was integrated. The result lowered the overprediction to 20.75% but also lowered the accuracy to 64.97%. This assessment was only conducted in the fire-razed morning market in Wajima City. [ABSTRACT FROM AUTHOR]

During projects to build roads in China's mountainous areas, which are often characterized by the poor stability of rocky slopes, cases of deformation damage occur frequently. Because of the wide distribution of rocky landslides in the smooth layer, the unavoidable perturbation caused by engineering construction and the seriousness of landslide disasters, the destruction of this type of landslide and the research into prevention of the mechanism cannot be ignored. On 6 February 2023, a rock slide occurred in Yaoping village, Hubei Province, China. Using field investigations, Google satellite images, unmanned aerial vehicle photography, indoor testing and numerical simulations, we analysed the geological situation, deformation characteristics, damage process and triggering mechanism. The results show that the Yaoping landslide is a typical downward plane-sliding rock slide induced by the excavation of a highway. When strain softening occurs, the shear strength and friction coefficient of the slip zone soil are significantly reduced. Excavation caused the factor of safety of the slope to decrease substantially, with a maximum decrease rate of 60.7%. Excavation is considered to be the extrinsic factor that triggered the occurrence of the Yaoping landslide, while the reduction of landslide resistance caused by strain softening of the soil in the slip zone is the intrinsic direct factor that led to the occurrence of this type of landslide. The Yaoping landslide has obvious traction landslide characteristics. The landslide from deformation to destruction has four stages: creep at the leading edge of the landslide; traction deformation in the middle and back of the landslide; slip belt softening; and integral sliding. The prevention and control of this type of landslide requires a larger scope and depth of investigation, in order to identify in advance the possible soft surface in the rock layer, to speculate on the possible formation of landslide destruction mode, and to determine the support scheme and scope according to the geological conditions of the slopes on both sides of the highway. The slip zone soil of the Yaoping landslide was used to obtain the strength index of slip zone soil, which provides data support for the overall deformation characterization of the landslide. The results can provide a reference for the risk management and prevention of rock slides caused by human engineering activities during the excavation of roads. [ABSTRACT FROM AUTHOR]

The dune systems in the Algiers region (Algeria) are scarce and often relict, making them highly vulnerable to disappearance. They face numerous pressures, mainly linked to human activities, and benefit from few effective protection measures. It is important to note that these habitats are at risk of disappearing due to both drastic natural conditions and human activities. The aim of this study is to evaluate alterations in vegetation status and the usefulness of airborne remote sensing, which is more cost-effective than very high-resolution satellite imagery, in studying these delicate environments, specifically in the region of El Kadous as a study area. The multi-temporal aerial imagery (1959, 1980, 2003, 2015 and 2019) is used to monitor the spatio-temporal dynamics of vegetation units. The methodology is based on a qualitative and quantitative analysis of diachronic mapping and field surveys. The results obtained are consistent with the Normalized Difference Vegetation Index (NDVI), extracted from the Quick Bird satellite images. Also, the Chi-Square Test of Independence is applied to demonstrate the effectiveness of aerial photography in monitoring and analyzing coastal dune vegetation. The findings indicate a decline in vegetation from the 1980s onwards, with an 87.14% reduction in overall plant cover and changes in the spatial structure. Additionally, there has been a decrease in key species such as the Oyat. It should be noted that the causes of this degradation are mainly attributed to climate change, coastal erosion, and human activity. [ABSTRACT FROM AUTHOR]

Small unmanned aerial rotorcrafts (SUARs) have garnered widespread attention in recent years due to their applications in various fields such as aerial photography, surveillance, search and rescue, and agriculture, with particular emphasis on the control issues associated with these rotorcrafts. Central to the discourse surrounding SUARs is the nuanced investigation of control methodologies pertinent to their operational dynamics. This paper contributes to this discourse by presenting a hierarchical-based self-triggered controller design approach for SUARs, aiming to reduce communication resource usage while ensuring system stability. The proposed hierarchical framework intends to optimize the self-triggered control structure wherein the upper layer serves as the trigger layer for triggering interval calculation and the lower layer as the control layer for determining control inputs. Within this hierarchical framework, a cyclic iterative solution method is introduced. After setting an initial inter-execution interval at the upper layer, the lower layer controller optimizes the specified performance index for the given triggering interval time domain to calculate the optimal control input, which is then fed back to the upper layer trigger for computing the next maximum triggering interval while ensuring system stability. Simulation results on the SUARs model validate the effectiveness and superiority of this method. [ABSTRACT FROM AUTHOR]

Structure from motion (SfM) photogrammetry coupled with multiview stereo (MVS) techniques are widely used for generating topographic data for monitoring change in surface elevation. However, study sites on remote glaciers and ice caps often offer suboptimal conditions, including large survey areas, complex topography, changing weather and light conditions, poor contrast over ice and snow, and reduced satellite positioning performance. Here, we provide a review of methodological considerations for conducting aerial photography surveys under challenging field conditions. We generate topographic reconstructions, outlining the entire workflow, from data acquisition to SfM-MVS processing, using case studies focused around two small glaciers in Arctic Canada. We provide recommendations for the selection of photographic and positioning hardware and guidelines for flexible survey design using direct measurements of camera positions, thereby removing the need for ground control points. The focus is on maximising hardware performance despite inherent limitations, with the aim of optimising the quality and quantity of the source data, including image information and control measurements, despite suboptimal conditions. [ABSTRACT FROM AUTHOR]

Chemically distinctive features such as high salinity, low nutrient contents, and extremes of pH can limit the development of a vegetation cover on soil-free bare ground. This study synthesises our previous work on the geoecology of numerous chemically distinctive bare sites in the South Island and adds a temporal component within the last century. The rates of development of surficial cover on decadal time scales have been traced from available historical aerial photography of varying but adequate quality. Rates are highly variable but range between zero and 2 metres per year laterally, with some sites showing localised expansion of bare ground at times. Cover evolution involves the development of a cm-scale proto-soil layer that is at least partially biologically mediated. Geochemical thresholds in surficial substrates control the biological components of encroaching cover. Dynamic surface environments, especially steep and actively eroding slopes, help to maintain bare ground and resist cover development. Some chemically distinctive bare ground, and evolving adjacent proto-soil areas, host specialist tolerant native plant communities and shrinkage of these areas threaten this biodiversity. In contrast, some bare ground sites have elevated arsenic and/or highly acidic pH, and the development of proto-soil and vegetation cover is environmentally positive from a human perspective. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive review of advancements in the detection; evaluation; and management of invasive plant species (IPS) using diverse remote sensing (RS) techniques and machine learning (ML) methods. Analyzing the high-resolution datasets received from drones, satellites, and aerial photography enables the perfect cartography technique and analysis of the spread and various impacts of ecology on IPS. The majority of current research on hyperspectral imaging with unmanned aerial vehicle (UAV) enhanced by ML has significantly improved the accuracy and efficiency of identifying mapping IPS, and it also serves as a powerful instrument for ecological management. The integrative association is essential to manage the alien species better, as researchers from multiple other fields participate in modeling innovative methods and structures. Incorporating advanced technologies like light detection and ranging (LiDAR) and hyperspectral imaging shows potential for improving spatial and spectral analysis approaches and utilizing ML approaches such as a support vector machine (SVM), random forest (RF), artificial neural network (ANN), convolutional neural network (CNN), and deep convolutional neural network (DCNN) analysis for detecting complex IPS. The significant results indicate that ML methods, most importantly SVM and RF, are victorious in recognizing the alien species via analyzing RS data. This report emphasizes the importance of continuous research efforts to improve predictive models, fill gaps in our understanding of the connections between climate, urbanization and invasion dynamics, and expands conservation initiatives via utilizing RS techniques. This study also highlights the potential for RS data to refine management plans, enabling the implementation of more efficient strategies for controlling IPS and preserving ecosystems. [ABSTRACT FROM AUTHOR]

An improved YOLOv7 aerial image object detection algorithm is proposed to solve the problems of low detection accuracy caused by mesoscale changes, small targets and dense occlusion in UAV aerial images. Firstly, a weighted sampling module with joint dynamic convolution is designed to capture features from multiple dimensions and improve the feature extraction ability of the model. Secondly, add a shallow feature detection head to retain more detailed information and enhance the ability to utilize small target features. Then, a multi- scale feature aggregation module (C2-Res2Block) with residual structure is constructed in the feature fusion part to make the model fuse rich multi-scale information. Finally, the MPDIoU measure is used to replace the traditional IOU to calculate the boundary regression loss and improve the localization ability of the model to the densely occluding target. Experiments on UAV aerial photography data set VisDrone2019 show that the improved algorithm is 4.3 percentage points higher than the original model on mAP@0.5, 2.4 percentage points on mAP@0.5: 0.95, the number of parameters is reduced by 6.81x106, and the detection accuracy is higher than the current mainstream object detection algorithms. It effectively improves the detection accuracy of UAV aerial images, and obviously improves the false detection and missing detection of aerial objects. [ABSTRACT FROM AUTHOR]

Landslides are the main gravitational phenomena in the Neogene basins of Algeria. This feature is mainly favored by the lithological nature of the fill materials, the climate, and the slope morphology. They are known for their high residential concentration and urban development. For better management and planning of future projects in landslide-prone areas, the use of Landslide Susceptibility Maps (LSMs) is indispensable. This study proposes a combined statistical and limit equilibrium method for the analysis of slope stability and for the production of LSMs using GIS in the Aomar Neogene basin (Bouira, Algeria). For this purpose, different work steps were carried out. Initially, a landslide inventory map was prepared based on existing studies, high-resolution aerial photography and satellite imagery analysis, as well as on detailed fieldwork. Besides, the geotechnical characterization of each geological formation was determined from the physical and mechanical parameters of recent and old geotechnical studies conducted in the region. A total, 169 landslides were compiled and randomly divided into training (70%) and validation (30%) datasets. Furthermore, eight factors influencing landslide occurrence (including slope angle, lithology, slope aspect, elevation, drainage density, distance to the rivers, distance to the roads, and rainfall) were selected and applied for the analysis. Moreover, the inventoried landslide and their associated factors were taken into account when mapping landslide susceptibility in the Aomar Neogene basin using Frequency Ratio (FR) models in GIS. On the other hand, a two-dimensional limit equilibrium (LE) model was used to determine the landslide-prone zones with a distinctive stability factor for each slope and the failure surface depth. Then, we have been able to verify and validate the obtained results for the statistical method using the Area Under the Curve (AUC) value of the Receiver Operating Characteristics Curves (ROC) method. For the frequency ratio models, the AUC is 83.23%, and for the limit equilibrium method, the safety factor is less than one for a slope greater than 16°. Based on these findings, we draw the conclusion that the maps may be exploited as practical instruments for land use planning and risk reduction in the Aomar Neogene basin. [ABSTRACT FROM AUTHOR]

Landslide inventories are crucial for evaluating susceptibility, hazards, and risks, and for devising resilience strategies in mountainous regions. This importance is amplified in the context of climate change, as existing inventories might not adequately reflect changing stability conditions. In May 2023, the Emilia-Romagna region of Italy was hit by two major rainfall events, leading to widespread flooding and the triggering of thousands of landslides. Predominantly, these were shallow debris slides and debris flows, occurring on slopes previously deemed stable based on historical data with no prior landslides recorded. Our team supported the Civil Protection Agency through field surveys and mapping efforts to pinpoint and record these landslides, prioritizing areas critical to immediate public safety and focusing on thorough mapping for future recovery planning. The outcome is a detailed map of all landslides induced by these events, manually identified using high-resolution aerial photography (0.2 m pixel resolution, RGB+NIR four bands) and categorized with the help of a 3D viewer. This comprehensive landslide inventory, comprising 80997 polygons, has been made openly accessible to the scientific community. [ABSTRACT FROM AUTHOR]

In the early hours of June 24, 2017, a major landslide event occurred in Xinmo Village, Sichuan Province, China. The landslide instantly devastated the whole village. Ten people died and 73 were missing in this major landslide event. The study area has suffered from several strong earthquakes in the past 100 y. Present studies have reported that the cumulative damage effect of the Xinmo landslide induced by earthquake is obvious. In this study, we conducted a shaking table test based on the detailed geological survey, historical seismic data, satellite optical image, unmanned aerial vehicle photography. The test result presents the characteristics of multistage seismic damage and progressive deformation process of the Xinmo landslide model, and shows that the historical earthquakes have caused serious damage to the interior of rock mass in the source area. The test also shows that the cumulative damage of the model increases with an increase in duration of earthquake loading. When the excitation intensity increases to a certain value, the damage accumulation velocity of the model suddenly increases. It reveals that frequent historical earthquake loads can be regarded as a main reason for the damage and deterioration of landslide rock mass. Damage accumulation and superposition occur in the slope. Under a long-term gravity, deformation of the slope gradually increases until catastrophic failure is triggered. The progressive deformation process of slope is summarized. Firstly, under strong earthquakes loading, a tensile fracture surface forms at the rear edge of the wavy deformation high and steep bedding slope. It reaches a certain critical depth and expands along the interlayer structural plane. Meantime, damaged fissures perpendicular to the structural plane also appear in the steep-gentle turning area of the slope. Secondly, under a coupling action of seismic loading and gravity, the interlaminar tensile crack surface at the rear edge of the slope extends to depth continuously. Meanwhile, rock fracture occurs in the steep-gentle turning area. The "two-way damage propagation" mode of the inter-layer tensile crack surface occurs until the sliding surface is connected. However, due to the "locking section" effect of rock mass at the slope foot, it can still maintain a short-term stability. Thirdly, under the influences of the heavy rainfall before a landslide and the long-term gravity of the upper sliding mass, rock mass in the steep section at the slope foot breaks outward. Finally, a catastrophic landslide occurs. [ABSTRACT FROM AUTHOR]

Coastal erosion and sea level rise has become a significant threat to coastal heritage due to climate change. Management bodies are monitoring the risks posed by undertaking studies, ranging from Rapid Coastal Zone Assessments to much larger government and research council funded studies. These studies have incorporated varying techniques and datasets such as environmental sampling, LiDAR, GPS, and UAV surveys. However, these approaches rarely combine study of historic shoreline change with physical susceptibility modeling. This paper presents a combined methodology, utilizing LiDAR and survey data collected by the Climate, Heritage, Environments of Reefs, Islands and Headlands (CHERISH) project, along with historic mapping and aerial photography to produce a risk assessment for the heritage assets located on Ynys Enlli (Bardsey Island), North Wales. By constructing an Historic Erosion Model and an Erosion Susceptibility Model using ESRI's ArcGIS 10.5.1. with the DSAS Plugin and combining them with the LiDAR-derived spatial extents of archaeological features on the island, this project has shown that using both methodologies alongside each other can create a more complete overview of coastal environment change for the creation of vulnerability indexes. [ABSTRACT FROM AUTHOR]

We present new data of White Sea Coast dynamics within NE of the Gorlo Strait that were generated by satellite images, geomorphological and ground penetrating radar (GPR) profiling, aerial photography, and topographic surveys of coastal terraces and dunes. Our paleogeomorphological studies, supported by laboratory findings (diatom analysis and 14C dating), allowed us to reconstruct the morphodynamics of coastal and aeolian landforms. The obtained reconstruction enabled the evaluation of relative sea level (RSL) changes and the evolution of coastal landforms over the past ~ 3.7 cal ka BP. According to our research, sand was supplied to coastal zone and coastal dunes through scarp erosion (0.5–3.7 m/year) as well as from the shoreface, while the role of alluvial runoff is insignificant. The largest dune massifs were formed in the areas of longshore drift (from NE to SW) discharge. At the mouth of the Maida River, the barrier spit and foredune plain have been evolving from the end of the Holocene transgression (∼3.7–2.3 cal ka BP). The mean high water at this time was slightly higher (up to ∼2.5 m a.s.l.), and coastal processes were significantly more intense than current ones. Then, against a decrease in sea level and weakening sediment flows, the growth of the spit slowed. The ancient foredunes were stabilized by vegetation. Aeolian processes were activated ∼2.1 and after ∼0.8–0.7 cal ka BP. [ABSTRACT FROM AUTHOR]

[Objective] Severe gully erosion in the black soil region of Northeast China is continuously eroding arable land resources, posing a threat to the country's food security. The development of unmanned aerial vehicle (UA V) technology provides an effective way for monitoring gully erosion, but the higher the resolution of data obtained, the longer it takes. The challenge lies in configuring UA V parameters to simultaneously meet accuracy requirements and enhance aerial photography efficiency. _Methods］ The Hebei catchment in the rolling hills region of Northeast China was chosen as the study area. Using actual cross-section measurement data as a validation value, the accuracy of gully parameters extracted from UA V data at different resolutions, flight directions, and types was assessed to explore the suitable conditions for various UAV parameter configurations. Results] (1) Compared with field measurement data, data at a 1 cm resolution extracted the gully parameters with the highest accuracy, the average percentage error for all parameters was less than 5.0%, suitable for monitoring typical gully development processes. Data extracted at 3 cm and 5 cm resolutions had an average percentage error of less than 1().()% for gully width, and the average error increased as gully depth decreased. For gullies deeper than 1 m, the average percentage error was less than 1().()%，suitable for rapid regional sampling surveys. Data extracted at resolutions of 8 cm and 10 cm had average percentage errors greater than 4().()% for gully depth and cross-sectional area, suitable for extracting gully distribution locations and planar parameters. (2) Although fixed-wing UAV obtaining data slightly outperformed in extracting two-dimensional gully features, multirotor UAV using oblique photogrammetry were better in extracting three-dimensional gully features. (3) The average percentage errors for gully depth and cross-sectional area extracted from single-direction oblique photogrammetry data were 1.7 and 1.9 times those from cross-direction data. UAV data obtained from cross-direction flights provided higher accuracy in gully parameter extraction and richer details. _ Conclusion H Setting UA V parameters to a resolution of less than 5 cm and obtaining cross-direction oblique aerial photography data can meet the accuracy requirements for monitoring gully morphology in the black soil region of Northeast China. [ABSTRACT FROM AUTHOR]

The increasing use of drone technology to produce high-resolution digital imagery and elevation models has been associated with a growing interest in developing quantitative morphometric analysis (QMA). QMA analysis is an invaluable part of creating detailed topographic models in landslide scars that are still highly unstable and prone to erosion. This paper presents the results of a research that aims to create a topographic model in a landslide scarred area where the slope configuration is still varied. The study area was located in the landscape of the Cretaceous-Tertiary volcanic transition where many landslides have occurred. Three landslides were selected on the basis of different soil material characteristics that affect the topographic condition of the landslide scar. Aerial photography was recorded using a UAV with a flying height of 80 m, with an orthomosaic resolution of 1 cm. In detail, three morphometric variables (slope, plan curvature, topographic position index) were selected and calculated with the output evaluated based on visual-spatial interpretation. The results showed that morphometric variables performed well in modeling land surface topography. Steep slopes and surfaces with convex curvature are abundant at the ledges and landslide heads that allow water runoff to disperse as the initiation of gully erosion. The multidimensional gully erosion network is concentrated at relatively low elevations and surfaces with concave curvature. The undulating micro-relief of the land surface as a result of the process of material disposition builds up on each other to a gentle slope. Finally, the topographic model of the landslide surface can be used as a base material in implementation of both physical and vegetative land conservation strategies. [ABSTRACT FROM AUTHOR]