Satellite Image Analysis Research Articles

Enhancement and analysis of hyperspectral satellite images for Soil Study and Behavior

Enhancement and analysis of hyperspectral satellite images for Soil Study and Behavior

Hazard evaluation framework for large yield explosions in urban environments: A case study of Beirut explosion

The Beirut explosion is one of the largest yield ammonium nitrate explosions in recent years, causing massive destruction and becoming a valuable case for explosion analysis. Compared with general post-disaster evaluation methods, e.g., on-site investigation and high-resolution satellite imagery, the numerical simulation approach can provide decision-makers and rescue workers with intuitive and visualized assessment results. Additionally, it can also serve as an effective tool to guide the architectural planning and blast-resistant design of building structures. However, due to the large dimension of urban numerical models, simulating explosions in complex urban blocks has low efficiency, often costing days to ensure accuracy. At present, based on the finite element analysis software AUTODYN, a framework to evaluate the post-explosion damage in city blocks is proposed, which is composed of the geospatial data, efficient numerical simulation approach, and damage evaluation principles. Subsequently, the detailed process of the numerical simulation approach is given, and it integrates the multi-stage method, symmetrical modelling, optimized graded mesh size, mapping, and mesh un-refinement technique, to reduce the number of mesh cells and increase the computational efficiency. Furthermore, the applicability of the numerical simulation approach in more complex environments is verified through two typical block explosion tests. Finally, the Beirut explosion is reproduced using the geospatial data obtained from OpenStreetMap, and the evaluation results are compared with field survey reports, satellite image analysis, and related numerical simulations. It is found that the proposed framework can quickly and effectively predict and evaluate the actual explosion accidents in the city environment.

Chronicle of a death foretold: The vanishing of an emblematic cultural landscape results in the loss of its unique plant communities

Badlands are peculiar geomorphological formations shaping landscapes of high ecological and cultural value. In the last decades, land reclamation for agricultural purposes and the cessation of traditional land use, such as sheep grazing, led to their decline in extent in many areas. To quantify the changes in badland-related plant communities, we resurveyed badland vegetation in a site of the Crete Senesi (Siena, central Italy) after 16 years (2006–2022), using 48 quasi-permanent vegetation plots and by means of uni- and multivariate analysis of variance. We found an increase in the total vegetation cover of plant communities growing in former bare soil and sparsely vegetated areas, in line with an overall decrease in the extent of bare soil surfaces in the study area, which we highlighted through the analysis of multitemporal satellite images. Pioneer vegetation characterized by the endemic plant Artemisia caerulescens subsp. cretacea changed into ruderal annual grasslands, while former bare soils were colonized by such pioneer vegetation. In contrast, perennial grasslands remained stable. Grasslands with shrubs became more similar to perennial grasslands in species composition. Species richness increased in former bare soils, and using the total vegetation cover as a proxy for successional stages, we found that Shannon diversity and evenness peaked at about 90% of total cover. In all the stages of colonization, short distance dispersal species prevailed, both therophytes (Avena sterilis, Parapholis strigosa) and perennials (Artemisia caerulescens subsp. cretacea, Bromopsis erecta). Long distance dispersal species (Galatella linosyris) started colonizing at about 60% of total vegetation cover, and at high vegetation cover all the functional groups coexisted. Our results confirm that the badland landscapes of southern Tuscany and specialist plant diversity adapted to badlands are vanishing after a diminishing of active land management, suggesting the current ineffectiveness of the Natura 2000 network in their conservation.

Evaluating the Land Use and Land Cover change of unprotected wetland situated in the Khultabad Tehsil of Aurangabad District, Maharashtra

The study investigated the effects of Land Use and Land Cover (LULC) change dynamics on the state and status of an unprotected wetland in semi-arid regions of India. The effects of the LULC shift on the wetland during a 15-year period were mapped and quantified using the long-term satellite image data collection. Using the supervised analysis approach, a multi-source satellite image analysis was carried out. The complete research area's Landsat data series were utilised to evaluate, map, and track LULC change over time. Wetland detection maps created for the 2007–2013–2016–2022 temporal periods were examined. According to the findings, the amount of agricultural land remained essentially constant during the comparative period, ranging from 29.71% to 31.43%. The percentage of waste land progressively grew from 14.29% to 22.86% between 2007 and 2016. By 2022, the plantation area will have shrunk from 15.43% in 2007 to 5%. Similarly, it is anticipated that the habitat would grow from 8.07% in 2007 to 12.93% in 2022. Farmland and fallow area figures are different because both land uses were determined using different season satellite pictures. But there is no obvious increase or decrease in the total agricultural area. These results may be used to create specialised wetland management plans and perhaps even a framework for restoring wetlands that are not currently under protection

Satellite image analysis of thermal comfort for a sustainable urban ecology of Winneba, Ghana

To mitigate thermal heat effects for a sustainable urban living environment through planning and interventions, studies on land surface temperature (LST) in urban settings are crucial. Thus, the relationship between LST and surface landscape must be established to accurately assess the impacts of surface temperature changes for planning purposes. This will help gain knowledge about the spatial concentration of the heat effects and to design practical needs of urban planning. The study aimed to analyse and reveal the spatial dynamics of LST and its statistical relationship with two normalised satellite indices using Landsat satellite data. The Landsat-derived LST is validated using the MODIS surface temperature data. It also mapped the heat spots (HS) and evaluated the ecological evaluation index and thermal comfort using the thermal field variance index (TFVI). The results showed spatial variation in LST even within the built-up areas due to heterogeneity in the surface characteristics. Thus, localised heat islands (HIs) exist within short distances. The analysis established an inverse correlation for LST-NDVI and a direct correlation for LST-NDBI. The vegetation and water surfaces served as important heat reduction sinks while heavily built-up areas and the hardened-clayey bare surfaces served as heat-enhancing sources. More than half (52.80%) of the study area enjoys an excellent (48.57%) and good (4.23%) ecological evaluation index, indicating excellent to good thermal comfort. Much of these areas are in the urban periphery. Also, more than one-third (38.96%) enjoy the worst (34.85%) and worse (4.11%) ecological evaluation index and thus high thermal discomfort. Identifying these HS areas and evaluating the thermal comfort will help the planners and decision-makers to fully evaluate the thermal consequences of different landuse or land development scenarios and therefore improve the scientific basis of future planning and regulations.

Changing Land Use and Urban Dynamics around an Industrial Zone in Bangladesh: A Remote Sensing Analysis

This article examines the adverse effect of rapid industrialization around Bangladesh’s Dhaka Export Processing Zone (DEPZ) by analyzing Landsat satellite images captured between 1989 and 2019. Image classification was performed to separate built-up areas with machine learning algorithms in Google Earth Engine. Image analysis was conducted using ArcMap and ArcGIS Pro. Field observations, interviews, and the literature review provided information for explanations about the phenomenon observed from satellite image analyses. The findings reveal that when DEPZ started its operation in 1993, there was hardly any built-up area in the vicinity. Within three decades, over 25% of the land within a 5 km radius of DEPZ has been converted into a built-up area, triggering an almost seven-fold increase in population. Industrial and urban growth in the DEPZ area has caused significant soil and water pollution in the broader region. As a result, the quantity and quality of agricultural land has degraded. In the long run, the planned industrial development initiative has contributed to unsustainable urban growth and environmental consequences. Insights drawn from this article can guide policymakers to re-evaluate their policy for rapid and large-scale industrialization.

Quantitative Evaluation of Suspended Solid Runoff from Large-Scale Landslide Areas Presumed to Be the Source of Turbid Water

In the uppermost stream of the Mimikawa River, in northern Miyazaki Prefecture, the contribution to river turbidity of a huge, collapsed slope alternating sandstone and mudstone layers was qualitatively shown in our previous study. In this study, the water level and turbidity were continuously observed, to obtain a quantitative estimation of this contribution. The conversion equation from the water level to the flow rate is required, but field measurements during the flooding term in the mountainous site are difficult. In this study, a high-resolution survey was conducted, and the relationship was determined via a small-scale hydraulic model shaped using a 3D printer from the survey results, to determine the relationship between the water level and the flow rate. The flow rate time series was reproduced with the distributed runoff model that is verified with the flow rate converted from the water level. The flow rate and turbidity load time series were also estimated from the long-term rainfall. The area of the bare soil surface of each small basin was obtained via satellite image analysis, and the soil yield from each surface condition was calculated. Furthermore, the amount of turbidity produced upstream of Kamishiiba Dam was calculated for each small basin. It was estimated that 24% of the turbidity was generated from the small basin covering 5.7% of the total catchment area. This study showed that it is possible to verify the hydrological model by obtaining the water-level–discharge relationship, even in the mountains, where it is difficult to observe the discharge on-site, via small-scale hydraulic model experiments.

MODELLING OF HERACLEUM SOSNOWSKYI MANDEN. AND HERACLEUM MANTEGAZZIANUM SOMMIER & LEVIER COENOPOPULATION AREA INCREASE RATE

On the basis of developed individual-based model and empirical data the importance of anemochory for the dispersal of giant hogweed mericarpia over long distances (up to 55 m from the parent plant) was proved. The use of cellular automate for modelling of the plant coenopopuation area increase allowed to reveal the influence of weather condition, number and spatial distribution of hogweed plants in the period of the beginning of introduction on the rate of invasion. Verification of the results of the cellular automaton work based on satellite images and field observations showed a significant level of compliance of theoretical calculations and observed results. The logistic functions parameters describing the change in the area of giant invasive hogweed stands were determined. A retrospective analysis of satellite images of model plots, starting from the 90s of the 20th century, showed an annual increase in the area of hogweed coenopopulations by 20% in the exponential population growth phase. A significant variability in the rate of invasion (from 5% to 70% per year) depended on the initial conditions and stage of invasion, usage modes and ecological capacity of the available sites.

Multi-annual and multi-decadal evolution of sediment accretion in a saltmarsh of the French Atlantic coast: Implications for carbon sequestration

Coastal marshes offer natural solutions for adapting to and mitigating the effects of climate change and sea level rise. However, the resilience of the marsh physical system and, with it, the ecosystem services that it provides, is largely site specific. This calls for the increase in the spatial cover of coastal marsh studies in order to assess the controlling factors of marsh evolution, and their long-term carbon storage capacities. Here, we study the spatio-temporal variations in sedimentation rates and organic carbon (OC) sequestration capacity of the macrotidal minerogenic saltmarshes in Aiguillon Bay, belonging to one of the largest French coastal marshes. Supported by aerial photographs and satellite image analysis, we first show that saltmarshes of the Aiguillon Bay have prograded at very high rates, up to 14 m yr−1 since 1950. Sediment accumulation rates (SAR) were estimated at both multi-annual to multi-decadal scales based on two approaches: (i) LiDAR-based digital elevation models from multiple acquisition dates (2010–2021); and (ii) depth profiles of 210Pb in excess and 137Cs in sediment cores collected along cross-shore transects in the saltmarshes. Long-term SAR range from 0.8 to 2.2 cm yr−1 and are among the highest reported worldwide for equivalent systems. The positive accretion balance (accretion rate minus local sea-level rise rate) provides important clues on marsh resilience suggesting that the Aiguillon Bay is currently able to adapt to rising sea level. Despite relatively low organic carbon content (1.3–6.0%), high SAR leads to high carbon sequestration rates (99–345 gC m−2 yr−1; or a mean value of 2.5 Mg C ha−1 yr−1). The isotopic signature of sediment OC reveals a significant and rapid decomposition of organic material in surface cores, while allochthonous sediment of marine origin dominates the signature of chemically-stable OC of marsh sediments. This implies that the carbon sequestration capacity of minerogenic saltmarshes, such as those of the Pertuis Charentais, also depends upon the wealth of adjacent coastal environments through high sediment supply and primary productivity.

Preliminary assessment of the suspended sediment dynamics in the Sikkim–Darjeeling Himalayan river

The Sikkim–Darjeeling Himalaya region receives the highest amount of rainfall along the whole southern Himalayan margin and is known for the occurrence of extreme hydrometeorological and geomorphological events. The massive amounts of water and sediment transported each year through the mountain part of the Teesta River drainage system (∼8,150 km2)––the largest river in the region––have been severely impacted by dam construction in recent decades. The aim of the current study was to determine, for the first time in this part of the Himalaya region, the dynamics of suspended sediment transfer at a number of points distributed through the mountainous part of the Teesta River catchment prior to dam construction and preliminarily assess the impact of dam operations on the suspended sediment. Sediment sources were identified using a database of landslide inventories from 1965 to 2019, combined with visual interpretation of satellite imagery from the U.S. Corona programme and Google Earth. Hydrological and sediment data up to the second half of the 1990s were used to reconstruct the discharge and suspended sediment dynamics before direct human intervention in the river channels. The beginning and end of the construction of the reservoirs was determined by analyzing satellite images. The impact of dam operations on the suspended sediment was compiled from the available literature. The results of the current study indicate that the primary sources of sediment are landslides caused by the interaction of rainfall and road undercutting of slopes as well as channel erosion. During extreme rainfall events, the influence of deforested areas in the mobilization and delivery of sediment to the river network increases. The current analysis reveals that reconstruction of the suspended sediment dynamics should take into account the course of extreme events responsible for supplying material to the river network, as well as the long-term remobilization of already deposited sediment in the river channel. It was found that the mean suspended sediment load (SSL) following extreme rainfall, flooding, and landslides in the Teesta River catchment can be up to four times higher than its average values for the same catchment unaffected by such an event, and the effects can be observed for more than a decade afterwards. Under these conditions, the mean suspended sediment yield can reach 12,000 and up to 20,000 t/(km2·y) in individual years, which is among the highest in the Himalaya region and, indeed, the world. The construction of 13 dams in the last 30 years has disrupted the hydrological regime and sediment transport in the Teesta River catchment along 70% of its main course and largest tributaries, and this has resulted in the selective retention of coarser material in the reservoirs and a reduction in the SSL in the Himalayan piedmont. The high density of the dams suggests that further transport of suspended sediment will depend on the efficiency of the water and sediment management at the reservoirs, which may be affected by irregular natural extreme events.

Геоинформационный анализ состояния и возможность агролесомелиоративного обустройства сельскохозяйственных ландшафтов южной части междуречья Тигра и Евфрата

For the first time, for the conditions of southern Iraq, a modified method for geoinformation assessment of the state of agricultural landscapes in southeastern Iraq was developed, characterized by a combined analysis of the relief, forest plantations, field structure and soil contours. Based on the photogrammetric analysis of satellite images in the GIS environment, actual thematic cartographic layers of agricultural landscapes in the southern part were developed between the Tigris and Euphrates. The theoretical significance of the work is determined by obtaining new data on the state of agricultural land, on the features of the geomorphological characteristics of the territory, and determining the possibility of their agroforestry for protection from natural impacts during economic use, as well as by modifying the method of geoinformation assessment of the state of agricultural landscapes in southeastern Iraq. It has been established that there is practically no agroforestry development in the study area of the Maysan province, which has an area of 1607.2 thousand hectares. The results of the research can become the basis for the application of forest reclamation in order to protect agricultural land from degradation in southern Iraq. This will help restore the soil fertility of agricultural land, which will reduce losses from the impact of natural and anthropogenic negative factors.

Building Footprint Extraction from LiDAR Data Using SVM Classification

Automatic detection of buildings from very high resolution (VHR) satellite images is a current research hotspot in remote sensing. In this work presents a novel approach to detect the buildings by atomization of the training area collecting stage for supervised classification. The classification method for the analysis of satellite image based on Normalized Difference Vegetation Index (NDVI). The method employs the multi-spectral remote sensing data technique to find spectral signature of different objects such as vegetation index, land cover classification, concrete structure, road structure, rural and urban areas, rocky areas and remaining areas presented in the image. In the experiments, the proposed SVM framework outperformed for the three (Linear SVM, Cubic SVM, Medium Gaussian SVM) methods tested. SVM is trained through supervised learning to classify each location in the image as “buildings” or “Non-buildings.” Finally, SVM algorithm to find the accuracy value, training time and receiver operating characteristic curves to evaluate detection performance, and compare the proposed algorithm with several existing methods.

Early detection of potential landslides along high‐speed railway lines: A pressing issue

AbstractEarly detection of landslides is important for prevention and mitigation of landslide disasters. Especially, accurately identifying potential landslides along high‐speed railway is becoming a pressing issue for operation safety of high‐speed railway. Here, 161 Sentinel‐1A satellite images from March 2017 to September 2022 were acquired to detect potential landslides along the Lanzhou‐Urumqi high‐speed railway (LUHR) in Qinghai. Results show that rainfall is the main cause for the transition from secondary creep (steady state) to tertiary creep (accelerated) at the Jiujiawan landslide. The hot spot analysis method was used to cluster the average line‐of‐sight deformation velocity along the LUHR, effectively extracting five deformation zones that may pose a threat. Optical satellite image analysis revealed four potential landslides and one unstable slope. Furthermore, the rescaled range analysis documented that the Hurst exponent is greater than 0.8 for all four potential landslide instability points, implying that the identified potential landslide areas are still in motion and may pose a threat to the operation of the LUHR. On this basis, we propose a framework for early identification and monitoring of landslides along the high‐speed railway lines that supports landslide hazard managing with the goal to reduce landslide risk.

A two-stage semi-supervised object detection method for SAR images with missing labels based on meta pseudo-labels

Recently, deep learning has been applied to analyze satellite images. However, applying fully supervised object detection (FSOD) is impractical because it is challenging to detect and annotate objects that are relatively small in high-resolution satellite images. In addition, most data owned by public institutions, such as military reconnaissance videos, do not contain sufficient object class label information. Therefore, the application of semi-supervised objection detection (SSOD) is more practical. The SSOD performance is often determined by generated pseudo-labels. Therefore, this study proposes a 2-stage SSOD model to generate accurate pseudo-labels. In the first stage, annotations, including the location information of unlabeled data, are detected using a modified faster R-CNN model. In the second stage, pseudo-labels of objects are additionally suggested through the meta pseudo-label method. Finally, reliable pseudo-labels are generated by comparing and combining the pseudo-labels generated in each stage, improving the SSOD model performance. Extensive experiments were conducted using the xView3 dataset provided by the U.S. Defense Innovation Unit (DIU). The proposed method performed approximately 11% better than the FSOD model, which does not learn pseudo-labels for datasets with missing labels according to the evaluation metrics proposed by the DIU covering both object detection and classification performance.

Accurate dating of tropical secondary forests using wood core Δ14C in Malaysia

Following the widespread loss and degradation of old-growth forests throughout the tropics, the area of secondary forests has expanded significantly in the past few decades. Understanding the history of vegetation modification is necessary for the proper maintenance and management of tropical secondary forests. Although satellite image analysis is an effective method for evaluating such changes, observations in tropical regions are limited by dense cloud coverage, and it is difficult to estimate the timings of forest disturbances based on annual rings because the climate is aseasonal and trees do not form clear annual rings near the equator in Southeast Asia. In this study, we developed a new, highly accurate technique for dating tropical secondary forests after disturbances such as shifting cultivation and forest fire in Malaysia based on Δ14C content of trees. We established 29 plots (20 m × 20 m) in secondary forests in six areas of Malaysia, mainly in Sarawak, and used time-series satellite images to determine the most recent disturbance with temporal accuracy of <6 years. We collected wood core samples from one or two trees with the largest diameter in each plot and measured the Δ14C content of their pith to estimate tree ages. We detected a significant positive correlation between tree age estimated by Δ14C dating and the period since the latest disturbance according to the time-series satellite images. The Δ14C-based age estimates were approximately five years younger than those obtained by satellite image dating. This difference is considered to indicate the time required for land use shifts after clear cutting or forest fire, and for tree species invasion after land abandonment. Together, our results revealed that the Δ14C method may be used to date tropical secondary forests after disturbance with high accuracy, even in aseasonal tropical rainforest areas.

Triggers for multiple glacier detachments from a low-angle valley glacier in the Amney Machen Range, eastern Tibetan Plateau

Large-scale ice avalanches initiated from low-angle glaciers (also known as glacier detachment) remain a scarcely studied and poorly understood phenomenon. Here we re-evaluated the repeat glacier detachments of a low angle (~14°) surging valley glacier in the Amney Machen Range, eastern Tibetan Plateau. Four glacier detachments recorded over a 15-year period (2004–2019) are described in detail based on the combination of satellite image analyses, additional terrain profile analyses and field data. To identify what triggered these high magnitude events, the glacier fluctuations, seismicity, lithology, and regional climate were examined. We find that the factors favouring glacier detachments were anomalous warming, subglacial hydrology, repeated glacier surging, a soft glacier bed, and ice-rock loading from the glacier headwall, though the relative influence of each factor varied in the four events we studied. We confirmed the observation of Paul (2019) that additional ice-rock debris loadings from the headwall were the most important factor for all events. The 2004 event probably was a delayed response to ice-rock loading during the preceding months. The latter three events may have been affected by short-term climate anomalies. The events of 2007 and 2016 were associated with anomalously high temperature: abrupt warming preceded the 2007 event and 2016 was the warmest year on record. The 2019 event followed sustained precipitation and high summer temperatures. Based on the spatial patterns in glacier change, we suggest that climate warming played a limited role in initiation.

Urban sprawl analysis of Akhmim city (Egypt) and its risk to buried heritage sites: insights from geochemistry and geospatial analysis

The present study employs a multidisciplinary approach to highlight the risks of urban expansion on buried cultural heritage sites. The buried temple of Ramses II in Akhmim city was chosen as a case study to assess the impact of urban expansion on its preservation. Support Vector Machine (SVM) classification was utilized to analyze satellite images from multiple sensors and evaluate the extent of urban growth surrounding the temple. The study also incorporated petrographic and mineralogical analyses of statues discovered in the temple, along with calculations of saturation indices, to assess the potential interactions between groundwater and archaeological materials. The findings indicate that urban development is encroaching upon the temple, posing potential risks to its preservation. Saturation indices for minerals in groundwater indicate a high tendency to dissolve dolomite (a common mineral in limestone) and to precipitate halite (sodium chloride). This is a concern because the artifacts unearthed from the temple are primarily composed of limestone. Consequently, there is a risk to the artifacts due to erosion and disintegration caused by mineral crystallization and expansion, as evidenced by the analysis of the rock and mineral characteristics of the statues discovered in the temple. The study proposes protective measures for the temple, including defining its dimensions beneath the urban area and establishing a dedicated protection zone around it.

Penerapan Sistem Informasi Geografis (SIG) Dalam Mengidentifikasi Potensi Kelongsoran

The primary objective of this study was to enhance the community's understanding and awareness of landslide risks and mitigation strategies by employing Geographic Information Systems (GIS) to identify landslide-prone areas in the Magetan District, East Java. The initiative unfolded in several stages, which included: (1) emphasizing the importance of mapping areas susceptible to landslides; (2) consolidating data through satellite image analysis and GIS; (3) developing GIS-based maps that depict landslide-prone areas; and (4) circulating these maps among the local community and governing bodies. In conclusion, this study demonstrates that a participatory approach, combined with advanced technologies such as GIS, can play a pivotal role in disaster mitigation. Early identification of landslide risks and appropriate mitigation strategies using GIS and community education can significantly enhance community preparedness and resilience to landslides. The potential applicability of this method to other regions with similar topographical and geological conditions underscores its relevance in improving community readiness and resilience against landslide disasters.

Shoreline Delineation from Synthetic Aperture Radar (SAR) Imagery for High and Low Tidal States in Data-Deficient Niger Delta Region

Satellite image analysis is a potentially powerful tool for monitoring coastal shoreline positions. This study explores the use of multi-temporal, dual-polarised Sentinel-1 GRD synthetic aperture radar (SAR) imagery with a spatial resolution of 10 m for delineating shorelines. It was conducted in a data-deficient and complex environment (the Niger delta of Nigeria), in a developing country with a cloud-heavy climate. The study focuses on exploring and testing the capability of using multitemporal waterlines from SAR images to derive shoreline positions at high and low tidal states. From 54 Sentinel-1 images recorded in 2017, the study selected 12 images to represent both high and low tidal states. These were spread across the wet and dry seasons in order to account for seasonal differences. Shoreline positions were obtained by identifying the land–water boundary via segmentation using histogram-minimum thresholding, vectorizing and smoothing that boundary, and averaging its position over multiple waterlines. The land–water segmentation had an overall accuracy of 95–99%. It showed differences between wet and dry season shoreline positions in areas dominated by complex creek networks, but similarities along open coasts. The SAR-derived shorelines deviated from the reference lines by a maximum of 43 m (approximately four pixels), and often less than 10 m (one pixel) in most locations (open coast, estuarine, complex creek networks) at high and low tides, except low tide lines in areas with extensive inter-tidal flats at shorelines 70 m to 370 m from the reference lines. However, for applications such as coastal vulnerability assessment, the high tide shoreline is of greater importance. Thus, depending on the application of interest, problems with low tide shoreline delineation may be irrelevant. Despite limitations, notably the relatively small number of images available that were recorded at high or low tide, the method provides a simple, objective, and cost-effective approach to monitoring shorelines at high and low tide.

Mapping Apennines river paths along different hydrological conditions from satellite images: A description of the method and potential applications

AbstractClimate change is producing large impacts on rivers, amplifying hydrological extremes. Prolonged drought periods result in dramatic stress for river biota and associated processes due to low discharge, reducing the interactions between rivers and their lateral environments or leading to hydrological intermittency. New quantitative methods are needed, to correlate discharge with the available riverine habitats. In this work we have mapped the wet surface and paths of two stretches of the Taro and Trebbia Apennine rivers, analyzing satellite images from periods with contrasting discharge. The considered stretches are critical due to different human pressures (large water withdrawals for agriculture and industrial use) and are particularly vulnerable to further, climate‐driven discharge reductions. The produced images offer multiple possibilities to extract qualitative and quantitative information at the whole stretch scales, including habitat reduction along with decreasing discharge, threshold discharge limiting lateral interactions, or the evaluation of longitudinal river continuity. We discuss the limitation and the potentialities of the method and the maps produced in terms of possible application in the field of river geomorphology, ecology, the definition of ecological river flow, risk assessment, and river management.