Interpretation Of Aerial Photographs Research Articles

Intensively Cultivated Roman Villae Estates: Case Study of Medulin Bay (Istria, Croatia)

ABSTRACTOur image of the Roman landscape of Istria is characterised by large‐scale centuriation and architectural remains of Roman villae. Detection and mapping of other, less dramatic landscape features require systematic large‐scale prospection, but this faces significant difficulties in the Mediterranean environment. However, the developments in the field of airborne laser scanning offer the possibility to create archaeologically usable digital terrain models under water and under very dense and low maquis vegetation. This paper reports on the use of terrain models created using a green laser and a sophisticated archaeologically driven ground point filtering strategy. Combined with archaeological aerial photo interpretation, this provides the means for landscape mapping and interpretation that has revealed a wealth of archaeological structures hinting at Roman agricultural practices and landscape. Our case study is based on a laser scan of about 24 km2 of land and underwater terrain in Medulin Bay. Processed, visualised and interpreted for archaeological purposes, the data reveal not only features ranging from prehistoric hilltop settlements to modern military installations but also features a complex picture of the Roman land use. Of particular interest is the large number of planting pits, which extend over a total length of 4 km. They were laid on a regular grid of approximately 35 × 35 m, sometimes combined in contiguous parcels. They can be interpreted as remains of orchards or tree nurseries of Roman date, and the paper examines also the question of whether they can be linked to the associated Roman estates. The case study area presented here shows that the potential of remote sensing methods goes far beyond the mere finding of traditional sites but can open up new landscape‐scale perspectives on regions that have been archaeologically little explored.

A hierarchical, multi‐sensor framework for peatland sub‐class and vegetation mapping throughout the Canadian boreal forest

AbstractPeatlands in the Canadian boreal forest are being negatively impacted by anthropogenic climate change, the effects of which are expected to worsen. Peatland types and sub‐classes vary in their ecohydrological characteristics and are expected to have different responses to climate change. Large‐scale modelling frameworks such as the Canadian Model for Peatlands, the Canadian Fire Behaviour Prediction System and the Canadian Land Data Assimilation System require peatland maps including information on sub‐types and vegetation as critical inputs. Additionally, peatland class and vegetation height are critical variables for wildlife habitat management and are related to the carbon cycle and wildfire fuel loading. This research aimed to create a map of peatland sub‐classes (bog, poor fen, rich fen permafrost peat complex) for the Canadian boreal forest and create an inventory of peatland vegetation height characteristics using ICESat‐2. A three‐stage hierarchical classification framework was developed to map peatland sub‐classes within the Canadian boreal forest circa 2020. Training and validation data consisted of peatland locations derived from various sources (field data, aerial photo interpretation, measurements documented in literature). A combination of multispectral data, L‐band SAR backscatter and C‐Band interferometric SAR coherence, forest structure and ancillary variables was used as model predictors. Ancillary data were used to mask agricultural areas and urban regions and account for regions that may exhibit permafrost. In the first stage of the classification, wetlands, uplands and water were classified with 86.5% accuracy. In the second stage, within the wetland areas only, peatland and mineral wetlands were differentiated with 93.3% accuracy. In the third stage, constrained to only the peatland areas, bogs, rich fens, poor fens and permafrost peat complexes were classified with 71.5% accuracy. Then, ICESat‐2 ATL08 spaceborne lidar data were used to describe regional variations in peatland vegetation height characteristics and regional and class‐wise variations based on a boreal forest wide sample. This research introduced a comprehensive large‐scale peatland sub‐class mapping framework for the Canadian boreal forest, presenting the first moderate resolution map of its kind.

DEVELOPMENT OF WEB GIS APPLICATIONS FOR MONITORING AGRICULTURAL ACTIVITIES IN SUNGAI KAKAP DISTRICT, KUBU RAYA REGENCY

<p>Good agricultural development planning requires an accurate and real-time database. This is very important to see the development and level of welfare of farmers as the spearhead of food security. Sungai Kakap Sub-district, Kubu Raya Regency is one of the sub-districts with the number of Gapoktan (23), Poktan (284), the number of members (6305) with Field Agricultural Extension Workers (PPL) since 2019 totalling 9 civil servants and 14 people helping themselves. The number of PPLs is not proportional to the number of farmer group members, making supervision of agricultural activities difficult. The presentation of information in the form of Web GIS is expected to be a solution so that assistance, guidance, and counselling carried out by the government through the agriculture office can be right on target. The purpose of this research is to build a Web GIS-based Agricultural Information System in Sungai Kakap District so that it can be used as a model for agricultural monitoring activities in other areas. The engineering method in this research uses Remote Sensing and Waterfall methods. Remote Sensing is a method of building spatial data using aerial photo interpretation techniques, while Waterfall is used to build a web GIS as a place to display spatial data. The result of this research is Software Engineering in the form of a Web GIS-based Agricultural Information System Application. This Web GIS application can then be used as a tool to monitor the agricultural activities of each farmer group member in each farmer group.</p>

Posidonia oceanica Cartography and Evolution of the Balearic Sea (Western Mediterranean)

The Balearic coastline presents an environmental and biological heterogeneity, which confers great complexity on the marine environment and treasures important biodiversity, both at the level of species and marine communities. The endemic phanerogam of the Mediterranean Sea, Posidonia oceanica, holds a pivotal role in maintaining high biodiversity, warranting protection as stipulated in the Posidonia Decree 25/2018. The purpose of this study is to provide quantitative criteria that will allow the delimitation of areas with Posidonia oceanica for conservation and to aid planning and management of this species, contributing to the reduction of biodiversity loss caused by anthropogenic impacts and global change. Utilizing a comprehensive approach, the study employs photo interpretation of aerial photographs taken at depths between 0 and 5 m, data from Side-Scan Sonar (SSS) campaigns, reprocessing information from the LIFE Posidonia project at depths between 20 and 30 m, and targeted sampling using Remote Operated Vehicles (ROV) and ocular recognition at strategic points. The research not only seeks to assess the present state of the phanerogam but also analyzes its evolution, establishing a technological database for consultation and integrated analysis. This database facilitates effective management by tracking habitat changes, representing a significant contribution to the understanding of the impact of global change on ecosystems through Geographical Information Technologies (TIGs).

Land Cover Trajectories and Their Impacts on Rainfall-Triggered Landslide Occurrence in a Cultivated Mountainous Region of Western Japan

Land cover changes in mountainous regions are potential precursors to landslide disasters. However, the effects of past long-term land cover changes on the characteristics of recent landslides remains underexplored. We studied land cover evolution over a 56-year period on Omishima Island in western Japan to examine the spatial relations of landslides in the July 2018 storm event based on rainfall, land cover trajectories, and topography. We generated land cover maps for 1962, 1981, and 2018 by aerial photo interpretation. We also identified 512 new landslides. Based on 47-year precipitation records, we estimated the return periods of 1- to 264-h rainfalls during the storm using the generalised extreme value (GEV) distributions. Return periods showed wide variation when the derived GEV distributions were applied to 1-km grid rainfall distributions. Despite such pronounced spatial variations in rainfall, we did not observe a clear correlation between rainfall intensity and landslide distribution. In contrast, land cover trajectories had a pronounced effect on landslide occurrence. Landslides were more concentrated on slopes that experienced land cover changes after 1962. A comparison of slopes on farmland developed between 1962 and 1981 (mainly citrus orchards) indicated that landslide density and area ratio were significantly lower on slopes that had reverted to forests than on those remaining as farmland. However, the values of the reforested slopes exceeded those of forests and farmlands that remained since before 1962. Our geospatial analysis revealed that even if the field had shifted to forests, the effects of reduced slope stability due to orchard development had remained for at least 37 years. This suggested that the impacts of converting forests to orchards last longer than harvesting in managed plantation forests.

Topography and land suitability analysis in the integrated waste management site building (IWMB) at the University of Lampung

Slope class maps are products resulting from the topographical analysis process. The results of this topographical analysis can also be used as a basis for land suitability analysis, supported by land cover maps and indicative maps of built and undeveloped areas. The Integrated Waste Management Site Building (IWMB) at the University of Lampung was used as an AoI (Area of Interest) or a study area for making land suitability maps. The AoI in the Unila campus area was 4.11 hectares. This study aims to explore the capabilities of drones as a complementary vehicle for field survey data to find out topographical data and to analyze spatial suitability plans. The method used in this research was an interpretation of aerial photographs and analysis using the ArcGIS application. From the slope class analysis results, the research location is included in the flat class category to be safe for all buildings (0-8%). For classification in spatial suitability analysis, the area is divided into 8 development plans to provide sustainable green open spaces in the campus area. Based on the research results, information was found that drone technology can assist visual interpretation in an area’s development plan.

A step forward to understanding the development of volcanotectonic rifts: the structure of the Fremrinamar Fissure Swarm (Iceland)

We analysed all the Holocene structures defining the Fremrinamar Fissure Swarm (FFS), in the Northern Volcanic Zone of Iceland, through the interpretation of aerial photos, orthomosaics and Digital Surface Models (DSMs), and field surveys. We measured the strike, dip, length and kinematics of 761 normal faults and reconstructed the slip profile of 76 main faults (length >2 km), with the purpose of evaluating the overall direction of along-axis rift propagation. We also measured the strike of 146 eruptive fissures and 1,128 extension fractures. A total of 421 faults dip towards the east and 340 dip towards the west, mainly striking N0°-10°E. Maximum fault length is 14.2 km, and W-dipping faults are longer than E-dipping faults. The majority of eruptive fissures strike N10°-20°E, and are concentrated in the southern part of the FFS, around the Fremrinamar central volcano. Extension fractures mainly strike N0°-10°E, with a maximum length of 2,508 m. We evaluated the variation of strike, fracture density and spacing along the FFS, and observed a change of its trend from NNE-SSW in the central-southern part, to NNW-SSE in the northern part. We interpret this evidence as the effect of the intersection with the Grimsey Lineament. The tapering of fault slip profiles indicates a main northward propagation of the rift, and thus of the deformation, interpreted as the effect of lateral propagation of dykes from the magma chamber below the central volcano towards the north. Such interpretation is also supported by the distribution of normal faults, vertical offset and dilation values, and also by the rift width, which tend to decrease towards the north.

Rockfall Susceptibility Assessment and Landscape Evolution of San Nicola Island (Tremiti Islands, Southern Adriatic Sea, Italy)

San Nicola Island, pertaining to the Tremiti Archipelago (Southern Adriatic Sea, Italy), is widely affected by cliff retreat and gravitational phenomena which severely threaten its monumental historical and natural value. In this study, geomorphological features of the area were derived following a stepwise approach, combining multitemporal stereoscopic aerial photo interpretations with morphometric analyses and detailed field surveys. A rockfall susceptibility map was created following a heuristic approach based on morphometric and geothematic parameters, accounting for slope, slope aspect, outcropping lithologies, structural discontinuities density, distance from landslide scarps, and presence of anthropic caves. Cliff sectors set on dolomitic limestones feature the highest susceptibility values, especially along the southeastern sector; medium values, instead, are found along the island flanks and along scarps located within the inner sectors; and the lowest values are detected on summit tabular surfaces. The achieved results were compared with historical maps and seismic data derived from local and national archives and catalogues, respectively. These analyses allowed us to define the role played by litho-structural and tectonic features on landslide occurrence and distribution, and their interplay in driving landscape evolution over centuries. Finally, this work represents a valuable scientific tool to support geomorphological studies for landslide hazard assessment and proper territorial planning in any other small insular areas, showing similar geological–geomorphological features and landscape values.

The Disaster Protection System of Mountainous Rivers in Japan: The Example of the Akatani Watershed’s Reconstruction

On 5–6 July 2017, an unstable atmospheric condition caused an unusual concentration of rainfall above the Northern part of Kyushu Island, triggering a set of hydro-meteorological hazards. Within the affected area, the mountainous subwatershed of the Akatani River was significantly impacted by numerous landslides combined with debris flow and floods. National and local agencies deployed a plan of reconstruction to restore the floodplain and protect inhabitants. Regarding the hydrosystem in the Akatani watershed, this reconstruction project mainly focuses on the restoration of damaged protection systems and the construction of new infrastructures. Thus, this paper aims to explain the restoration plan of the Akatani River in terms of the strategic Japanese River System Sabo and then as a model of a national-scale spatial plan. It draws on (i) a literature review based on the historical evolution of Japanese protection systems and the River Sabo System; (ii) field surveys in 2019, 2022 and 2023, in conjunction with (iii) interviews with local, regional, and national officials; and (iv) a Geographical Information System analysis of previously and newly built protection systems through aerial photograph interpretation and geospatial data. Sabo works implemented in the Akatani watershed illustrate the engineering vision of Japanese river management. They also constitute a comprehensive system and include a downstream–upstream logic which echoes that of the River System Sabo. In addition, the disaster of July 2017 and the government’s response emphasize the continuous adaptation and improvement of the Japanese disaster management system, which mitigates severe disasters.

Construction of a deltaic strandplain during the Roman period in the Tavoliere di Puglia plain and palaeoclimatic implications

In response to the accidental exhumation of three ancient trees by farmers, we conducted a multidisciplinary study based on the stratigraphic analysis of boreholes, carbon-14 dating, aerial photo interpretation, and analysis of palaeobotanical and archaeological evidences. We reconstructed the formation and evolution during Roman times of a first “continuous” and then “discontinuous” deltaic strandplain at the mouth of the Carapelle Stream in the Tavoliere di Puglia Plain—the second-largest plain in Italy. Ttwo main phases can be recognised in the evolution of the Carapelle deltaic strandplain: 1) a first phase, lasted until ca. the birth of Christ, was characterised by a regular and continuous construction of sand ridges one leaning against the other; 2) a second phase, lasted more or less from the birth of Christ to the termination of the construction of the deltaic strandplain, was characterised by the discontinuous construction of sand ridges/coastal barriers with the isolation of lagoons/ponds, and by evidences of alluvial events. The most probable climatic–environmental scenario to have formed the Roman-period deltaic strandplain implied that: 1) the first phase was triggered by a higher total amount of precipitations, but with less extreme alluvial events; 2) the second phase was triggered by a total amount of precipitation lower than the previous period, but with higher occurrence of extreme alluvial events and/or by extreme alluvial events separated by longer period of low precipitations. This second phase was enhanced by the opening of vegetation. The passage between the first and second phase of the Carapelle deltaic strandplain coincides with the passage from overall negative NAO index to an overall positive NAO index.

Thematic interpretation of aerial photographs of forest areas based on conceptual modeling

Earth remote sensing (ERS) is one of the main sources of information about the earth's surface. With the development of unmanned aerial vehicles (UAVs), it became possible to take aerial photographs with high spatial resolution, which can be used to more accurately identify objects. The purpose of the study is to increase the reliability of aerial imagery interpretation by developing a methodology for automated image processing based on conceptual modeling. An analysis of the methods for thematic interpretation of images showed that none of them provides sufficient quality of segmentation without additional adjustment to the subject area. The technique of conceptual modeling of subject tasks is applied, which ensures the adequacy of syntactic representations (including various images) and makes it possible to control the logic of solving problems and reduce the number of errors at the stage of its software implementation. The description of the information system for thematic interpretation of images, which implements the developed methodology, is given. An assessment was made of the reliability of thematic interpretation of images of forest areas. It is shown that the developed technique allowed to improve the identification of forest objects on aerial photographs by 18.6%. The development of this technique can be carried out to determine the characteristics of identifiable trees: age, species, height, and wood stock.

Devonian-Mississippian faulting controlled by WNW-ESE-striking structural grain in Proterozoic basement rocks in Billefjorden, central Spitsbergen

In Billefjorden, central Spitsbergen, Devonian collapse and Carboniferous rift-related sedimentary strata were deposited unconformably over Proterozoic basement rocks displaying well developed N-S-trending Caledonian grain. Caledonian structures and fabrics are thought to have controlled the location and trend of subsequent Devonian and Carboniferous basin-bounding faults like the Billefjorden fault zone and Lemströmfjellet–Løvehovden fault. However, fieldwork and interpretation of aerial photographs in Proterozoic basement rocks reveal the existence of steep, abundant, WNW-ESE-striking brittle faults that are sub-orthogonal to known major Caledonian and post-Caledonian structures in Billefjorden, but that do not extend into adjacent-overlying, rift-related, Pennsylvanian rocks of the Gipsdalen Group. Structural analysis of field data and aerial photographs suggest that WNW-ESE-striking faults in basement rocks in Billefjorden formed as (sinistral) strike-slip and normal faults during Devonian-Mississippian extension in agreement with previously inferred models of sinistral transtension. The abundance of these faults suggest that their formation was controlled by analogously trending, preexisting structural grain (planar anisotropies) at depth, and their pronounced WNW-ESE strike suggest that the strike of preexisting anisotropies were comparable to recently identified, crustal-scale, WNW-ESE-striking Timanian thrust systems in Svalbard and the northern Barents Sea.

The Response of Sandstone Sea Cliffs to Holocene Sea-Level Rise by Means of Remote Sensing and Direct Surveys: The Case Study of Punta Licosa Promontory (Southern Italy)

Punta Licosa promontory is located in the northern part of the Cilento coast, in the southern Tyrrhenian basin. This promontory is bordered by sea cliffs connected to a wide shore platform sloping slightly towards the sea. This area has been considered stable at least since Late Pleistocene, as testified by a series of evidence well known in the literature. The aim of this research is to reconstruct the main coastal changes that have occurred in this area since the middle Holocene by means of the literature data, aerial photo interpretation, satellite images, GPS measurements, direct underwater surveys, GIS elaborations of high-resolution DTMs, bathymetric data and high-resolution orthophotos taken by UAV. Particular attention was paid to the wide platform positioned between −7.2 ± 1.2 m MSL and the present MSL, this being the coastal landform interpreted as the main consequence of sea cliff retreat. The elevation of this landform was compared with the GIA models calculated for the southern Tyrrhenian area, allowing establishing that it was shaped during the last 7.6 ± 1.1 ky BP. Moreover, the interpretation of archaeological and geomorphological markers led to the reconstruction of the shoreline evolution of this coastal sector since 7.6 ky BP. This research evaluates the cliff retreat under the effect of Holocene RSL variation on Cilento promontories, located in the western Mediterranean and characterised by the presence of monophasic platforms, and the applied method can be considered more effective and less complex and expensive if compared to other effective approaches such as those based on the usage of cosmogenic nuclides.

Mapping subsurface tile lines on a research farm using aerial photography, paper maps, and expert knowledge

AbstractAccurate maps of subsurface tile drainage lines are needed for agronomic and environmental research studies and the maintenance of current tile drainage systems. In this study, tile lines at the Purdue University Agronomy Center for Research and Education near West Lafayette, Indiana were located using a combination of visual aerial photo interpretation, expert knowledge, and paper construction drawings. The mapping accuracy was assessed at 27 locations where tile lines were located physically using a tile probe. Tile lines were correctly predicted 89% of the time with an average spatial accuracy of ±1.23 m of the true tile locations. This approach was better than a previous tile line location map prepared using an automated remote sensing method, which had an average spatial accuracy of ±2.12 m.

Detecting trends in seagrass cover through aerial imagery interpretation: Historical dynamics of a Posidonia oceanica meadow subjected to anthropogenic disturbance

Over the last century, P. oceanica meadows have undergone significant regression along Mediterranean coasts due to anthropogenic disturbances. Using an integrated approach based on historical aerial photography interpretation in GIS environment and Bayesian modelling, we mapped the upper limits of a P. oceanica meadow and identified the most influential disturbance factors acting along the coast of Giglio Island, where several local human-mediated impacts have historically co-occurred from 1968 to 2013. Model selection based on the DIC criterion suggested that the presence of the impacts is suitable for describing the seagrass coverage variation. Similarities in P. oceanica cover within 13 investigated zones were highlighted when considering the most relevant impacts, such as harbour expansion, mining, and anchoring. The detected adverse effects indicate the need for implementing management actions focusing on the present and past sources of impact to reduce their effect on P. oceanica beds actively.

Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study

ABSTRACT Invasive alien plant species (IAPS) have negative impacts on ecosystems, including the loss of biodiversity and the alteration of ecosystem functions. The strategy for mitigating these impacts requires knowledge of these species’ spatial distribution and level of infestation. In situ inventories or aerial photo interpretation can be used to collect these data but they are labor-intensive, time-consuming, and incomplete, especially when dealing with large or inaccessible areas. Remote sensing may be an effective method of mapping IAPS for a better management strategy. Several studies using remote sensing to map IAPS have focused on single species detection and were conducted in relatively homogeneous natural environments, while other common, more heterogeneous environments, such as urban areas, are often invaded by multiple IAPS, posing management challenges. The main objective of this study was to develop a mapping method for three major IAPS observed in the urban agglomeration of Quebec City (Canada), namely Japanese knotweed (Fallopia japonica); giant hogweed (Heracleum mantegazzianum); and phragmites (Phragmites australis). Mono-date and multi-date classification approaches were used with WorldView-3 and SPOT-7 satellite imagery, acquired in the summer of 2020 and in the autumn of 2019, respectively. To estimate presence probability, object-based image analysis (OBIA) and nonparametric classifiers such as Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were used. Overall, multi-date classification using WorldView-3 and SPOT-7 images produced the best results, with a Kappa coefficient of 0.85 and an overall accuracy of 91% using RF. For XGBoost, the Kappa coefficient was 0.81 with an overall accuracy of 89%, whereas the Kappa coefficient and overall accuracy were 0.80 and 88% for SVM classifier, respectively. Individual class performances based on F1-score revealed that Japanese knotweed had the highest maximum value (0.95), followed by giant hogweed (0.91), and phragmites (0.87). These results confirmed the potential of remote sensing to accurately map and simultaneously monitor the main IAPS in a heterogeneous urban environment using a multi-date approach. Although the approach is limited by image and reference data availability, it provides new tools to managers for IAPS invasion control.

Combining unmanned aerial vehicles and satellite imagery to quantify areal extent of intertidal brown canopy‐forming macroalgae

AbstractBrown macroalgae habitats provide a range of ecosystem services, offering coastal protection, supporting and increasing biodiversity, and more recently have been recognized for their potential role as blue carbon habitats. Consequently, accurate areal estimates of these habitats are vitally important. Satellite imagery is often utilized for areal estimates of vegetated habitats due to their ability to capture vast areas but are disadvantaged by their lower resolution. In contrast, imagery collected by unmanned aerial vehicles (UAV) provide high‐resolution datasets but are unable to cover the necessary spatial scale required for calculating areal estimates at regional, national or international scales. This study successfully and accurately corrects the outputs from low‐resolution Sentinel 2 imagery to the standard of high‐resolution UAV imagery by using a novel brown algae index and a simple regression model to provide accurate spatial estimates. This model was applied to rocky shores across Wales, UK to predict a spatial extent of 6.2 km2 for three fucoid macroalgae species; Ascophyllum nodosum, Fucus vesiculosus and F. serratus. The regression model was validated in two ways. First, the data used to create the regression model was split to train and test (50:50) the model, with a root mean square error of ~8%–14%. Secondly, spatial estimates of fucoids in independent aerial imagery were assessed using aerial photography interpretation and compared to that of the regression model (7% difference). The carbon standing stock of fucoids calculated from the spatial estimate (6.2 km2) was found to be significantly lower than that of other marine carbon stores, indicating that fucoids do not significantly contribute as a blue carbon habitat based on biomass alone. This study produces a robust and accurate remote sensing technique to estimate spatial extent of macroalgae at large spatial scales, with possible worldwide applicability.

An Unsupervised Saliency-Guided Deep Convolutional Neural Network for Accurate Burn Mapping from Sentinel-1 SAR Data

SAR data provide sufficient information for burned area detection in any weather condition, making it superior to optical data. In this study, we assess the potential of Sentinel-1 SAR images for precise forest-burned area mapping using deep convolutional neural networks (DCNN). Accurate mapping with DCNN techniques requires high quantity and quality training data. However, labeled ground truth might not be available in many cases or requires professional expertise to generate them via visual interpretation of aerial photography or field visits. To overcome this problem, we proposed an unsupervised method that derives DCNN training data from fuzzy c-means (FCM) clusters with the highest and lowest probability of being burned. Furthermore, a saliency-guided (SG) approach was deployed to reduce false detections and SAR image speckles. This method defines salient regions with a high probability of being burned. These regions are not affected by noise and can improve the model performance. The developed approach based on the SG-FCM-DCNN model was investigated to map the burned area of Rossomanno-Grottascura-Bellia, Italy. This method significantly improved the burn detection ability of non-saliency-guided models. Moreover, the proposed model achieved superior accuracy of 87.67% (i.e., more than 2% improvement) compared to other saliency-guided techniques, including SVM and DNN.

Deep-Seated Gravitational Slope Deformations in Molise region (Italy): novel inventory and main geomorphological features

ABSTRACT This paper focuses on Deep-Seated Gravitational Slope Deformations (DSGSDs) identified in the Molise region (Italy), along the central-southern sector of the Apennines chain. These phenomena were detected and mapped through a combination of aerial-photo interpretation, morphological analyses, and field surveys, integrated through satellite SAR interferometry (InSAR). The obtained general map is organized in different sections: inventory map with identification of DSGSDs and main geological and orographic features, geostructural scheme, representative cross sections, list and characteristics of DSGSDs, geomorphometric maps, landslides map, and seismotectonic setting. This study allowed us to realize a complete inventory of DSGSDs in the Molise region and define the main characteristics of each phenomenon. Through this research, it was possible to establish a general correlation between the analyzed deformations and the geological and geomorphological setting of the region as well as with its geodynamic context.

Computational Machine Learning Approach for Flood Susceptibility Assessment Integrated with Remote Sensing and GIS Techniques from Jeddah, Saudi Arabia

Floods, one of the most common natural hazards globally, are challenging to anticipate and estimate accurately. This study aims to demonstrate the predictive ability of four ensemble algorithms for assessing flood risk. Bagging ensemble (BE), logistic model tree (LT), kernel support vector machine (k-SVM), and k-nearest neighbour (KNN) are the four algorithms used in this study for flood zoning in Jeddah City, Saudi Arabia. The 141 flood locations have been identified in the research area based on the interpretation of aerial photos, historical data, Google Earth, and field surveys. For this purpose, 14 continuous factors and different categorical are identified to examine their effect on flooding in the study area. The dependency analysis (DA) was used to analyse the strength of the predictors. The study comprises two different input variables combination (C1 and C2) based on the features sensitivity selection. The under-the-receiver operating characteristic curve (AUC) and root mean square error (RMSE) were utilised to determine the accuracy of a good forecast. The validation findings showed that BE-C1 performed best in terms of precision, accuracy, AUC, and specificity, as well as the lowest error (RMSE). The performance skills of the overall models proved reliable with a range of AUC (89–97%). The study can also be beneficial in flash flood forecasts and warning activity developed by the Jeddah flood disaster in Saudi Arabia.