Multi-temporal Analysis Research Articles

An integrated approach for the assessment and monitoring of land degradation and desertification in semi-arid regions using physico-chemical and geospatial modeling techniques.

Land degradation (LD) and desertification are serious ecological, environmental, and social-economic threats in the world, and there is a demanding need to develop accountable and reproducible techniques to assess them at different scales. This study assesses LD and desertification with the help of remote sensing (RS) and geographical information system (GIS) in the study region for the period past 29 years, i.e., from 1990 to 2019. The severity of LD and desertification was assessed quantitatively by collecting twelve soil samples in the study region and analyzing the eleven soil physico-chemical parameters and these values have made correlated with digital number (DN) values with LANDSAT 8 OLI/TIRS satellite image. The land cover analysis of LANDSAT imagery revealed that the water body slightly increased from 0.29% in 1990 to 0.46% in 2019, and built-up-land increased from 2.87% in 1990 to 5.31% in 2019. Vegetation decreased from 52.03% in 1990 to 28.57%. Fallow land, degraded land, and desertified lands increased at alarming rates, respectively 13.71% to 26.35, 18.57% to 22.31%, and 12.53% to 17.00%. It is also established that the multi-temporal analysis of change detection data can provide a sophisticated measure of ecosystem health and variation, and that, over the last 29 years, considerable progress has been made in the respective research.

The protective role of mangroves in safeguarding coastal populations through hazard risk reduction: A case study in northeast Brazil

Coastal and estuarine ecosystems such as mangroves provide coastal protection services, safeguarding coastal communities and economies. However, sea-level rise can affect mangroves' protective role by increasing exposure to coastal hazards and economic costs. To better understand the role of mangroves as coastal protective barriers against hazards and their importance for conservation planning in the face of sea-level rise, we first analyzed temporal changes in the coastal landscape by measuring the erosion/accretion rates on the shoreline. We assessed coastal exposure to hazards with the presence and absence of mangroves. Finally, we estimated the economic losses and costs from the long-term retreat in the shoreline and mangrove loss. This study was carried out along the western coast of the South Atlantic, in the northeast Brazilian region. Coastal exposure indices were estimated using the Integrated Valuation of Environmental Services and Tradeoffs (InVEST) software, and the multitemporal analysis of shoreline was developed using the Digital Shoreline Analysis System (DSAS) software. Finally, the economic losses produced by those shoreline changes and social costs were estimated by predicting economic losses in terms of private property and by calculating societal costs in mangrove restoration and rockfill building. The results show that nearly a third of the shoreline is experiencing erosion and the coast could lose an additional 118 ha by 2030. In terms of the value of property loss, this translates to US$38,800 and would increase to US$72,000 under the maximum erosion rate scenario. Based on our coastal vulnerability assessment, almost 50 km of the coastline (20%) would transition to intermediate-high exposure levels if the current distribution of mangroves were to be lost. It is expected to cost about US$145 million in rockfill works and US$21 million in forest restoration to mitigate the impacts from human activities and sea-level rise on mangroves ecosystem services. At the national level, a total loss of mangroves in Brazil could mean mangrove forest restoration costs of nearly US$4000 million. More robust conservation policies are needed to conserve mangrove forests and safeguard the ecosystem-service co-benefits they provide. The latter is essential in low- and middle-income nations where the economic and welfare losses from coastal hazards are more challenging due to dependence on nature for livelihoods and well-being.

Using the VENµS Super-Spectral Camera for detecting moving vehicles

Monitoring transportation for planning, management, and security purposes has become a growing interest for various stakeholders. A methodology for detecting moving vehicles is based on the acquisition time gap between the pushbroom detector sub-arrays. However, this technique requires overcoming differences in ground sampling distance and/or spectral features of the sensor’s bands used for change detection.The current work demonstrates a proof of concept for the VENµS satellite’s capability to detect moving vehicles in a single pass with a relatively low spatial resolution. The VENµS Super-Spectral Camera has a unique stereoscopic capability because the two spectral bands, with the same central wavelength and width, are positioned at the extreme ends of the camera’s focal plane. This design enables a 2.7-sec difference in observation time. The normalized difference moving object index (NDMOI) has been designed to detect moving vehicles using these bands without image preprocessing for dimensionality reduction or geometric corrections, as other sensors require.Results show the successful detection of small- to medium-sized moving vehicles. Especially interesting is the detection of private cars that are, on average, 2–3 m smaller than the VENµS ground sampling distance. Vehicle movement was effectively detected in different backgrounds/environments, e.g., on asphalt and unpaved roads, as well as over bare soil and plowed fields. Furthermore, a multitemporal analysis of moving vehicles during the Covid-19 pandemic in 2020 shows the effectiveness of the proposed methodology.

Monitoring and Identification of Agricultural Crops through Multitemporal Analysis of Optical Images and Machine Learning Algorithms.

The information about where crops are distributed is useful for agri-environmental assessments, but is chiefly important for food security and agricultural policy managers. The quickness with which this information becomes available, especially over large areas, is important for decision makers. Methodologies have been proposed for the study of crops. Most of them require field survey for ground truth data and a single crop map is generated for the whole season at the end of the crop cycle and for the next crop cycle a new field survey is necessary. Here, we present models for recognizing maize (Zea mays L.), beans (Phaseolus vulgaris L.), and alfalfa (Medicago sativa L.) before the crop cycle ends without current-year field survey for ground truth data. The models were trained with an exhaustive field survey at plot level in a previous crop cycle. The field surveys begin since days before the emergence of crops to maturity. The algorithms used for classification were support vector machine (SVM) and bagged tree (BT), and the spectral information captured in the visible, red-edge, near infrared, and shortwave infrared regions bands of Sentinel 2 images was used. The models were validated within the next crop cycle each fifteen days before the mid-season. The overall accuracies range from 71.9% (38 days after the begin of cycle) to 87.5% (81 days after the begin cycle) and a kappa coefficient ranging from 0.53 at the beginning to 0.74 at mid-season

REGIONAL MANAGEMENT AND DEVELOPMENT WITH FREE MULTI-TEMPORAL IMAGES: THE CASE OF HYDROELECTRIC POWER INSPECTION

The present research aims to analyze the case of the use of free satellite images in the inspection of works of hydroelectric plants and to propose its use in the management of regional development. The study performs a multitemporal analysis of CBERS-4 and Sentinel-2 data to assist the inspection process of the National Electric Energy Agency and proposes a reflection on this technology as a free tool for regional development management. The methodology observed inspection reports, images with different temporal and spatial resolutions and the ability of the images to integrate the inspection process of electricity generation in Brazil through photointerpretation. The results demonstrate that the processing of free images optimizes the human and financial resources, being able to verify three of the five stages of works supervised by the Agency to guarantee the schedule of implantation of the hydroelectric plants in any region of the country with the same capacity of use. In addition, remote sensing data are presented as an excellent tool in the management of regional development where the plants are implemented or other related management and monitoring applications, as they provide greater transparency and efficiency to the control over large areas, such as that exercised by the Agency, strengthening accountability and considerably reducing one of the most sensitive aspects to the regulatory body and the management of large areas: information asymmetry.

Assessment and characterization of sources of error impacting the accuracy of global burned area products

Understanding the sources of error that affect the accuracy of current coarse burned area products is crucial to identifying weaknesses and limitations of burned area (BA) algorithms. In this paper, we propose methods to analyse sources of errors of global BA products, which are applied to assess a widely used product, (FireCCI51), created under the ESA climate change initiative programme. The effect of several variables related to product accuracy are quantified by comparing the FireCCI51 BA product with a large global reference BA dataset for the years 2017–2019. These reference data were obtained from multitemporal analysis of Landsat-8 data. Error maps (commission and omission error layers) were generated for a sample of 316 units (100 km × 100 km) and associations between errors and potential explanatory sources of error were spatially analysed to provide a comprehensive error assessment of the FireCCI51 product. Active fire density, burned severity, burned patch size and land cover class were selected as explanatory variables for omission and commission errors. The results indicated that the largest contribution to the commission errors (70–80%) was related to the pixel size, particularly when pixels are only partially burned. Active fire densities were also associated to error distribution, with higher densities from products derived from the VIIRS sensors versus those generated from MODIS, indicating the potential benefit of the former as an alternative source in upcoming BA algorithms. Burn severity was also associated with error distribution, but this relation varied substantially across biomes. Land cover was also related to errors, with lowest accuracies for croplands with omission error percentages >85%. Fire size and, to a lesser extent, the shape of burned areas also played a crucial role in determining the accuracy of the BA products. BA accuracy increased for larger and more compact burned patches. Although our results suggest that further improvement of global BA products is possible, they also indicate that the ability of coarse spatial resolution BA sensors to meet the accuracy recommendations of the Global Climate Observing System (GCOS) programme is limited.

INFORSAT: AN ONLINE SENTINEL-2 MULTI-TEMPORAL ANALYSIS TOOL SET USING R CRAN

Abstract. Remote sensing via orbiting satellite sensors is today a common tool to monitor numerous aspects related to the Earth surface and the atmosphere. The amount of data from imagery have increased tremendously since the past years, due to the increase in space missions and public and private agencies involved in this activity. A lot of these data are open-data, and academics and stakeholders in general can freely download and use it for any type of application. The bottle-neck is often not data availability anymore, but the processing resources and tools to analyse it. In particular multi-temporal analysis requires stacks of images thus digital space for storage and processing workflows that are tested and validated. Processing image by image is often not a viable approach anymore. Basic tools for multi-temporal analysis are provided via the same web interface, allowing the user to also apply parallel processing for a faster data extraction. A study case over burned areas in the north-eastern region of Italy are reported, to show how the multi-temporal analysis tools provided can be a valid source of data for further analysis. Multitemporal data consisting on the index values of each pixel inside user-defined areas can be downloaded in a spreadsheet that provides the values, the cell ids, the timestamp and the cloud and snow percentage. Also the full-resolution raster with index values that are rendered on screen can be downloaded as GeoTIFF at each specific date.

High Resolution Land Cover Mapping and Crop Classification in the Loukkos Watershed (Northern Morocco): An Approach Using SAR Sentinel-1 Time Series

Remote sensing has become more and more a reliable tool for mapping land cover and monitoring cropland. Much of the work done in this field uses optical remote sensing data. In Morocco, active remote sensing data remain under-exploited despite their importance in monitoring spatial and temporal dynamics of land cover and crops even during cloudy weather. This study aims to explore the potential of C-band Sentinel-1 data in the production of a high-resolution land cover mapping and crop classification within the irrigated Loukkos watershed agricultural landscape in northern Morocco. The work was achieved by using 33 dual-polarized images in vertical-vertical (VV) and vertical-horizontal (VH) polarizations. The images were acquired in ascending orbits between April 16 and October 25, 2020, with the purpose to track the backscattering behavior of the main crops and other land cover classes in the study area. The results showed that the backscatter increased with the phenological development of the monitored crops (rice, watermelon, peanuts, and winter crops), strongly for the VH and VV bands, and slightly for the VH/VV ratio. The other classes (water, built-up, forest, fruit trees, permanent vegetation, greenhouses, and bare lands) did not show significant variation during this period. Based on the backscattering analysis and the field data, a supervised classification was carried out, using the Random Forest Classifier (RF) algorithm. Results showed that radiometric characteristics and 6 days’ time resolution covered by Sentinel-1 constellation gave a high classification accuracy by dual-polarization with Radar Ratio (VH/VV) or Radar Vegetation Index and textural features (between 74.07% and 75.19%). Accordingly, this study proves that the Sentinel-1 data provide useful information and a high potential for multi-temporal analyses of crop monitoring, and reliable land cover mapping which could be a practical source of information for various purposes in order to undertake food security issues.

Multitemporal dual-pol Sentinel-1 data to support monitoring of forest post-fire dynamics

Approaches based on multitemporal analysis of optical-retrieved vegetation index time series were successfully applied to describe forest disturbances like forest fires; conversely, only few works make use of multitemporal Synthetic Aperture Radar (SAR) data. In this work, a multi-temporal approach based on Sentinel-1 data (S1) is proposed based on CR polarimetric index to monitor forest canopy along the considered period (2016–2019) preceding and following an important fire event occurred in the Piemonte Region (NW Italy) in November 2017. The Pettitt test, applied to the polarimetric index time series, was used for testing fire occurrence date and map burned areas (795 ha) resulting in user’s accuracy of burned area equal to 88%. A trend analysis was also conducted, on ‘burned’ pixels only, to describe tree canopy damage and strength of the consequent recovery process at pixel level using linear trend slope values of cross ratio polarimetric index time series. Finally, a k-means cluster analysis was applied to define classes having the same ecological behaviour with respect to two different criteria: one aimed at mapping type and intensity of damage and a second one aimed at describing the ecological behaviour in terms of resistance and resilience of burned patches. In the study area, the cluster layer called forest damage map classifies about the 22% of burned area as characterized by an early high severity whiled the residual by moderate-low severity levels. The second cluster layer called ecological response map defined the 61% of the burned area as resistant forests, the 20% as resilient forests and the 19% as increasing forest zones. All maps were generated with the aim of supporting post-fire assessment and management with free satellite SAR data.

Unfolding time, race and class inequalities to access leisure

The access to leisure activities is an important element to understand the potential participation and integration of individuals in the society. Despite its importance, urban planners in large urban centers in developing countries seek to prioritize access to mandatory activities. This study quantifies the accessibility to leisure and its inequalities in the municipality of São Paulo, considering the opening hours of leisure opportunities and racial and class population groups. Tracking data from buses and TomTom speed profile were used in the public and the private transport networks, respectively, to analyze and compare accessibility to parks and cultural equipment. A multitemporal analysis was performed to better understand the fluctuation of accessibility to leisure through different hours considering the opening hours of parks and cultural equipment. The population was stratified into four groups according to race and class (higher black, higher white, lower black, and lower white) to perform accessibility inequalities analysis. Results show that accessibility to leisure is higher for private transport users, it decreases from the central to the peripheral areas, and it changes significantly during the day due to traffic conditions, transit supply, and leisure opportunities opening hours. The Lorenz curves, Gini, and the Palma coefficients showed a highly unequal level of accessibility to leisure for different population groups, with the low-black population having the lowest level of leisure accessibility. Our findings may support policy makers in designing strategies to provide more spatial equity in the access to leisure opportunities.

Multi-temporal analysis of the dynamics of land use and vegetation cover in the Illangama River micro-basin

Esta investigación tuvo como objetivo realizar un análisis multitemporal de la dinámica de uso de suelo y cobertura vegetal de la microcuenca del Río Illangama durante el período 1996 - 2021, su incidencia social y ambiental, para el desarrollo sostenible de la misma. La metodología utilizada fue no experimental, tuvo un enfoque de estudio cualitativo con alcance descriptivo. Se realizó la clasificación supervisada de imágenes satelitales, con seis clases. Se empleó el Índice Diferencial Normalizado de Vegetación que evidenciando que en el año 1996 el valor bajo fue de -0,41 y el valor alto a 0,48, mientras que, en el año 2021 el valor bajo fue de -0,7 y el valor alto de 0,54. El área poblada en el 2021 en la microcuenca del Río Illangama disminuyó. Se determinó que, del año 1996 al 2021 ha crecido la zona de páramo sobre la cobertura denominada área sin cobertura vegetal en la zona alta de la microcuenca. Durante el lapso de 25 años se ha perdido en la microcuenca el tipo de vegetación densa y poco densa, sin embargo, han aumentado los reservorios de agua. La población principalmente se dedicaba a la agricultura, expandiendo sus cultivos y viviendas hacia la cuenca alta, no obstante, debido a mayores estrategias de conservación tanto de páramos como de bosques, se han ido controlando estas actividades.

Multitemporal Analysis of Urban Expansion in the Municipality of Madrid, Cundinamarca, between 1977 and 2020

Context: Given the increasing population concentration, both the proximity of the town of Madrid to the city of Bogotá and the growing metropolitan area around the latter have a significant influence on the increased urbanization and the change in land use in the town of Madrid, Cundinamarca. Objective: The objective of this study was to carry out a multitemporal analysis of the change in coverage and land use caused by urban expansion in the municipality of Madrid between 1977 and 2020. Methodology: Satellite images were observed through supervised classification, following the Corine Land Cover methodology, which was adapted for the Colombian context, and utilizing geographic information systems. Area variation analyses were performed for each classification in each of the evaluated years. Results: The data obtained show that the forest cover area and seminatural zones have been reduced by 86% in a period of 43 years, and that artificial territories have progressively become predominant in each of the years, even reaching a coverage greater than 50% of the municipality area. The agricultural territories have maintained 66,95% of the surface of the municipality, and they correspond the land use with the largest occupied area for the evaluated period, which shows the importance of the soil for the economic development of the population. Conclusions: This situation shows that population growth and urban expansion cause variations in coverage and land uses. Their valuation is an aspect that must be considered when elaborating development plans for municipal entities.

Dynamic Modeling of Land Use and Coverage Changes in the Dryland Pernambuco, Brazil

The objective of this work was to carry out a multitemporal analysis of changes in land use and land cover in the municipality of Floresta, Pernambuco State in Brazil. Landsat images were used in the years 1985, 1989, 1993, 1997, 2001, 2005, 2009, 2014, and 2019, and the classes were broken down into areas: water, exposed soil, agriculture, and forestry, and using the Bhattacharya classifier, the classification was carried out for generating land use maps. The data was validated by the Kappa index and points collected in the field, and the projection of the dynamics of use for 2024 was constructed. The thematic maps of land use and coverage from 1985 to 2019 show more significant changes in the forest and exposed soil classes. The increase in the forest class and the consequent reduction in exposed soil are consequences of the interaction between climate and human activities and the quality of the spatial resolution of the satellite images used between the years analyzed.

Measurement of Water Soil Erosion at Sparacia Experimental Area (Southern Italy): A Summary of More than Twenty Years of Scientific Activity

The main purpose of this article is to give a general idea of the scientific activity that was carried out starting from the 2000s on the basis of the data collected in the plots installed at the Sparacia experimental station for soil erosion measurement in Sicily, South Italy. The paper includes a presentation of the experimental site, a description of the methods and procedures for measuring soil erosion processes both available in the literature and applied at the Sparacia station (sediment sampling and water level reading in the storage tanks for total erosion measurements; profilometer, and Structure from Motion technique for rill erosion measurements), and the main results obtained in the monitoring period in the experimental site. The latter concern the effects of plot size and steepness on soil loss, the measurement variability, the frequency analysis of soil loss, the rill erosion characterization, and the comparison between rill and interrill erosion rates. Each of these topics is addressed with multi-temporal analyses performed with increasing size of the available database, which allowed to draw robust conclusions. Soil loss did not vary appreciably with plot length in contrast with the assumption made in the USLE/RUSLE. The variability of the measurements of soil loss, runoff volume, and sediment concentration at the event scale in replicated plots decreased as the mean measured value increased. The normalized event soil loss was distributed according to a two-component distribution. A power relationship between rill volumes and lengths was established. The measurements also confirmed the morphological similarity between the channels of the rills and ephemeral gullies described by a power dimensionless relationship. Rill erodibility of the sampled clay soil varied over time, maintaining relatively low values. Finally, rill erosion was dominant relative to interrill erosion, and a more efficient sediment transport system through the rill network occurred as plot steepness increased.

Evaluation of Atmospheric Correction Methods of Sentinel-2 for Monitoring Paddy Rice Growth in Cianjur and Klaten Regency

Atmospheric correction is a critical pre-processing step required in quantitative remote sensing applications such as extraction of biophysical variables and multi-temporal analysis. The objective of this study was to evaluate surface reflectance of atmospheric correction methods base on scene-based empirical namely Dark Object Subtraction (DOS) and the radiative transfer methods namely the Second Simulation of Satellite Signal in the Solar Spectrum (6S). We applied these methods to Sentinel-2 images above rice fields in Cianjur and Klaten Regency, and compared surface reflectance from atmospheric correction methods with ground measured reflectance base on spectral response and vegetation indices (NDVI, EVI, SAVI and MSAVI). For that purpose, generative phase of rice growth was analysed by using statistical analysis. The result showed that the 6S method has better accuracy than DOS and varies on each bands.

Multitemporal Analysis of the Water Mirror of the Jaburu I Reservoir Through Remote Sensing Tools in the Years 2013 to 2020

Resumo Em regiões com influência do clima semiárido é nítida a escassez hídrica, a qual é consequência, dentre outros fatores, de cenários negativos de precipitação que acarretam secas prolongadas. Tais características reverberam negativamente no desenvolvimento socioeconômico da sociedade envolvida. Nesse contexto, o armazenamento de água em açudes pode ser considerado uma alternativa estratégica importante que requer uma atenção especial em busca da mitigação do déficit hídrico nessas regiões. Dessa forma, o presente trabalho teve como objetivo realizar uma análise multitemporal do espelho d’água do Açude Jaburu, localizado nos municípios de Ubajara e Tianguá, Ceará, nos anos de 2013 a 2020. Para isto, foi aplicado o índice Normalizado por Diferença de água (NWDI), tendo sido utilizadas imagens do satélite Landsat 8, Coleção 1 Tier 1, LANDSAT/LC08/C01/T1_RT, calibrado para reflectância do Topo da Atmosfera (TOA), por meio das bandas 3 e 5, com uma resolução espacial original de 30 m. Os principais resultados mostram que os anos que apresentaram maior recuo foram 2014 e 2015 com 192,21 e 175,05 hectares de espelho d’água a menos, respectivamente. Os anos de 2018 e 2019 apresentaram expansão, com 130,86 e 295,65 hectares, respectivamente. Para avaliar os dados abordados neste trabalho em termos de correlação com a pluviosidade na área, utilizou-se o teste de correlação de Spearman, que apresentou valor de p igual a 0.9349, assumindo-se não haver relação entre a pluviometria e a área do espelho d’água. Sugerem-se estudos mais aprofundados na área para compreender quais fatores podem comprometer a disponibilidade hídrica no reservatório, bem como confirmar, por meio de séries maiores, se realmente não há correlação entre a área do espelho d’água e a quantidade de chuva na área. Por fim, verificou-se que as ferramentas de sensoriamento remoto se mostraram eficazes na análise do espelho d’água da área estudada, bem como guardam um potencial positivo para contribuir com o gerenciamento adequado dos recursos hídricos superficiais em região com clima semiárido.

ON THE APPLICATION OF REMOTE SENSING TIME SERIES ANALYSIS FOR LAND COVER MAPPING: SPECTRAL INDICES FOR CROPS CLASSIFICATION

Abstract. This study aims to introduce a semi-automatic classification workflow for the production of a land use/land cover (LULC) map of the island of Sardinia (Italy) following the CORINE legend schema, and a ground spatial resolution compatible with a scale of 1:25.000. The classification is based on free high-resolution satellite imagery from Sentinel-1 and Sentinel-2 collected in 2020, ancillary data derived from Sardinian Geoportal, Joint Research Centre (JRC) and OpenStreetMap. The LULC map production includes three steps: 1) pixel-based classification, realized with two different approaches, that use i) information derived from existing thematic maps eventually re-coded in case of incoherencies observed between datasets and/or satellite data products, and ii) spectral indices and parameter thresholds defined on the basis of multitemporal analysis; 2) segmentation of Sentinel-1 and 2 annual composites, and pre-labelling of segments with the pixel-based classified map, obtaining the preliminary map; 3) visual inspection procedure in order to confirm, or re-assign, classes to polygons. The accuracy of the preliminary map was tested in a sample area and on specific class of non-irrigated crops through ground truth data collected from a detailed photo-interpretation, estimating 97% of overall accuracy. The results show a great improvement from existing thematic maps in terms of detail, with the possibility of a yearly updating of the map via automatic processes. However, some limitations were found, due to the high fragmentation of Sardinian landscape and the high variety of crop types and agricultural practices, that could affect the efficiency of the classifier.

Multi-temporal analysis of submarine sand dunes morphodynamics (Bay of Brest, Brittany, France): A marker of sediment pathways in a macrotidal environment open to sea swells

Sediment structures including submarine banks and dune fields are ubiquitous on tide-dominated continental inner shelves such as in the Iroise Sea. These are of current interest to human activities in several respects: they constitute an obstacle to navigation, they are dredged for beach nourishment or exploited for marine aggregates. In addition, the morphodynamic characterising of these sedimentary structures improves the knowledge of the sediment transfers that occur in coastal areas. This study documents a submarine sand dune field located along the northern flank of the Goulet channel connecting the Bay of Brest to the Iroise Sea and the Bay of Biscay. Subject to a macrotidal regime with strong currents, and to large waves during storm events, this sedimentary system features large dunes with very high migration rates. The analysis of six bathymetric datasets (from March 2013 to October 2019) allows specifying the morphodynamic characteristics of this small dune field about 3.5 km in length and 500 m in width. These dunes have heights on the order of 0.5 m–3.7 m with migration rates that can vary significantly within the range from 10 m/yr to 70 m/yr. The results highlight that the ebb tidal current and slope of the channel are the main factors controlling the evolution of these biogenic sandy structures migrating offshore (SW). Furthermore, seasonal variations in coastal hydrodynamics forcing, driven by tidal currents, appear to affect the temporal and spatial evolution of the dunes at this shorter time scale. This paper proposes a model of sediment transport patterns at the mouth of the bay of Brest according dune field characteristic, strong ebb current and residual tidal gyre.

UAV-Based Multitemporal Remote Sensing Surveys of Volcano Unstable Flanks: A Case Study from Stromboli

UAV-based photogrammetry is becoming increasingly popular even in application fields that, until recently, were deemed unsuitable for this technique. Depending on the characteristics of the investigated scenario, the generation of three-dimensional (3D) topographic models may in fact be affected by significant inaccuracies unless site-specific adaptations are implemented into the data collection and processing routines. In this paper, an ad hoc procedure to exploit high-resolution aerial photogrammetry for the multitemporal analysis of the unstable Sciara del Fuoco (SdF) slope at Stromboli Island (Italy) is presented. Use of the technique is inherently problematic because of the homogeneous aspect of the gray ash slope, which prevents a straightforward identification of match points in continuous frames. Moreover, due to site accessibility restrictions enforced by local authorities after the volcanic paroxysm in July 2019, Ground Control Points (GCPs) cannot be positioned to constrain georeferencing. Therefore, all 3D point clouds were georeferenced using GCPs acquired in a 2019 (pre-paroxysm) survey, together with stable Virtual Ground Control Points (VGCPs) belonging to a LiDAR survey carried out in 2012. Alignment refinement was then performed by means of an iterative algorithm based on the closest points. The procedure succeeded in correctly georeferencing six high-resolution point clouds acquired from April 2017 to July 2021, whose time-focused analysis made it possible to track several geomorphological structures associated with the continued volcanic activity. The procedure can be further extended to smaller-scale analyses such as the estimation of locally eroded/accumulated volumes and pave the way for rapid UAV-based georeferenced surveys in emergency conditions at the SdF.

Land cover changes in coffee cultural landscapes of Pereira (Colombia) between 1997 and 2014

Understanding how and what land cover changes and transitions have occurred in a territory is crucial to planning and managing high-demand surfaces. At the landscape level, the challenge is determining the allocation and management of various land cover options. Therefore, for natural resources planning and management, a study characterizing and analysing the territory of interest should be included. This work aimed to analyse the changes and land cover patterns in the city of Pereira, Colombia, within the framework of the Colombian Coffee Cultural Landscape. The evaluated period was between 1997 and 2014, and a Geographic Information System, ENVI 4.8 programme and QGIS programme were used for multitemporal analysis. To describe the land cover transitions, two temporal moments were analysed with Landsat satellite images: one moment was for the year 1997, which was taken in August (Landsat 5), and the other moment was for the year 2014, which was taken in July (Landsat 8). At level 1 of CORINE (Coordination of information on the environment), the areas of land cover corresponding to agricultural areas, forests and semi-natural areas decreased most in the analysis period, while artificial surfaces increased. At level 3, the cover with the greatest decrease in territory was coffee crops, which showed a negative annual loss rate of -3.97%, followed by permanent crops (-2.67%). The continuous and discontinuous urban fabric showed the greatest growth with a positive annual rate of 4.14%. In conclusion, the land cover that lost the most territory was coffee crop, mainly due to political-economic factors, such as the dissolution of the International Coffee Agreement and the National Federation of Coffee Growers that discouraged coffee cultivation and permanent crops. Likewise, sociocultural factors, such as smallholder farmers have guided the changes in land cover and have stimulated productive styles to adapt and remain, increasing heterogeneous agricultural areas.