Soil salinity mapping is essential for sustainable land development and water resources management. In situ sampling is time-consuming, laborious, and restricted by geographical conditions. Therefore, an efficient and accurate model is necessary to monitor and assess the spatio-temporal dynamic salinization at regional a scale. In this study, Shule River Basin (SLRB) is taken as an example to develop the soil salinity mapping model based on Landsat 8 OLI images using random forest (RF) algorithms. A series of extended soil salinity indexes (ESSIs) were generated by combining any two, three, or four spectral bands were combined in expressions that include one or more of the arithmetic operations: addition, subtraction, multiplication, division, square and rooting form. The features selected from ESSIs outperformed the features selected from soil salinity indexes (SSIs) used in references. The best selected indexes are (B7^2-B5^2)^0.5, (B4^2+B5^2-B6^2)^0.5, (B1*B5-B4*B6/(B1*B5+B4*B6))^0.5,(B2*B6-B3*B7/( B2*B6+B3*B7))^0.5. In addition, three partition sampling methods of the training set and validation set for long-tail distribution problems are compared. The results showed that the resampling method considering the long-tail distribution performs better than systematic resampling and random k-fold cross-validation. The regional soil salinity mapping results showed that most areas are seriously salt-affected in the whole basin, especially along the river and the southeast mountainous area, where the soil salinity classes are highly and even over-extremely saline. This study could have implications for agricultural schemes planning and salinization control.

How to cite: Zhang, T., Wang, Z., Tang, Y., and Shi, Y.: Mapping of Soils Salinity with Landsat 8 OLI Imagery and Random Forest Algorithm, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4057, https://doi.org/10.5194/egusphere-egu23-4057, 2023.

Unmanned Aerial Vehicle (UAV) can greatly improve the geological field mapping. However, applications of UAV in the investigations of the deposit still remain to be explored. The Liba gold deposit, located at the Li-Min gold belt to the western Qinling orogenic belt, is a typical open-pit gold deposit. The associated (local) landscape and geomorphology provide an excellent natural laboratory to explore the UAV in deposit field mapping. Here, UAV-based photogrammetry was performed to get the aerial photos across the mining area, as well asoutcrop information from the Liba gold mine. In the combination with a detailed field work, alteration zones with the regional faults can be efficiently interpreted and evaluated, both from the macro- to micro scale. According to the work, we established a general working flow of the usage of UAV deposit field exploration to improves the field work. By demonstrating the UAV-based technical applied in Liba, this work can strongly promote the understanding and interpretation of regional geology during the field work.

Key words: Open-pit Gold Deposit, Liba gold deposit, UAV-drone photogrammetry, Geological field mapping

How to cite: Wang, J., Qiu, K., and Fu, J.: An Application of UAV in Open-pit Gold Deposit Geological Field Mapping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4412, https://doi.org/10.5194/egusphere-egu23-4412, 2023.

Agroforestry, the association between trees/shrubs and crops, a widespread practice in West Africa, is presented as a lever for ecological intensification to optimize cereal yields in the face of strong population growth and the fight against climate change. Within the framework of the EU-DESIRA SustainSAHEL project, we aim to develop techniques to spatially assess the effect of trees on millet yields on an intra-field scale using imagery from an UAV equipped with a multispectral camera combined with geostatistical approaches. Indeed, recent advances in earth observation technologies position the UAV as an effective tool for evaluating the agronomic performance of agroforestry systems and for taking into account the intra-field variability of yields caused by environmental conditions, agricultural practices or the presence of trees (Roupsard and al., 2020 ; Leroux and al., 2022). The objective of this study was to estimate millet yields intra-field variability using UAV and up-to-date geostatistical approaches.

The study was carried out over the 2018-2022 cropping seasons in one representative Faidherbia parkland of the groundnut basin of Senegal. To that end, a Random Forest (RF) algorithm was first calibrated to estimate millet yield at sub-plot scale using a thresholding classification to eliminate non-vegetation elements and also to integrate texture data, in order to take into account the spatial relationships between pairs of pixels. Millet yields data and vegetation and textural index from aerial images at a flight height of 25 meters acquired in farmers’ plots were used to calibrate the RF model. The RF model was used to upscale yield at the whole field scale thus allowing to obtain a map of millet yield. Then Voronoï diagram, with Faidherbia as a reference, was applied to each yield map, considering each Voronoï region as a zone of influence of its included Faidherbia. We then applied a transformation and rotation matrix to overlay all the zones of influence of a population of 50 Faidherbia by putting all the trees at the same geographical position. Finally, we build an atlas, which is an average structure representative of a population and which makes possible to detect the patterns and properties of the evolution of the population considered, to evaluate the distance and directional effect of Faidherbia on vegetation index of the population and then on millet yield.

The RF model is able to explain between 70 and 90 % of the millet yield variability. Then the analysis has shown that the tree has an influence on the millet stand density with a distance-decay effect from the tree. This stand density is about 60 % around the tree and 30 % at 15m from the tree.

Key words : Agroforestry, Uav, Machine learning, Image analysis, Geostatistics, Atlas

How to cite: Diene, S. M., Fernandez, R., Goze, E., Diack, I., Faye, M., Dabo, A. H., Bousso, P. O. B., Audebert, A., Roupsard, O., Leroux, L., Mbaye, M., Diouf, A. A., Diallo, M., and Sarr, I.: Assessment of the Faidherbia albida effect on millet yield using UAV images analysis and geostatistical techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7531, https://doi.org/10.5194/egusphere-egu23-7531, 2023.

In the Aeolian Archipelago (southern Tyrrhenian Sea), Panarea Island and the islets of Bottaro, Lisca Bianca, Lisca Nera and Dattilo, is undergoing sea level rise, land subsidence, coastal erosion and beach retreat that are posing continuous threats to coastal stability and infrastructures built along the coastal zone. With the aim to assess the coastal changes by the end of 2100 according to the IPCC climatic scenarios, that predict a global sea level rise even more than 1 m, a detailed evaluation of the potential coastal flooding has been estimated in the frame of the PANDCOAST project, funded by the INGV.

This work focuses on the use of Unmanned Aerial Vehicles (UAVs) imagery combined with multibeam bathymetry data collected in different years for the generation of the very  high-resolution Digital Terrain and Marine Model (DTMM) of the Panarea Island and its archipelago. Scenarios are based on the determination of the current coastline position, high resolution Digital Terrain and Marine Models, vertical land movements and climatic projections.  The data fusion of detailed topographic data, up to 2 cm/pixel for the subaerial sector with sea level rise projections released by the Intergovernmental Panel on Climate Change (IPCC) for the SSP2.6 and SSP5 climatic scenarios for this area, are used to map the expected multi-temporal sea level rise scenarios for 2050 and 2100.

In the analysis have been incorporated the effects of the vertical land movements (VLM) as estimated by the Global Navigation Satellite System (GNSS) network located in the archipelago. Assuming constant rates of VLM for the next 80 years, relative sea level rise projections provide values between 31±11 cm by 2050 and 104±27 cm by 2100 for the IPCC AR6 SSP8.5 scenarios and at 27±10 cm by 2050 and 73±24 cm by 2100, for the IPCC AR6 SSP2.6 scenario, with small variations in the individual islets of the archipelago. With these scenarios, the lowest elevated coasts of the islands are exposed to increasing marine flooding, especially during storm surges and high water levels particularly heavy from the north-western sectors.

How to cite: Anzidei, M., Doumaz, F., Esposito, A., Trippanera, D., Vecchio, A., Fabris, M., Bosman, A., and Alberti, T.: Ultra High-Resolution terrestrial and marine DEMs drive Relative Sea Level Rise projections and flooding scenario for 2100 A.D. for the Island of Panarea (Southern Tyrrhenian Sea, Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8617, https://doi.org/10.5194/egusphere-egu23-8617, 2023.

The use of unoccupied aerial systems (UAS) in geoscience has dramatically improved our ability to collect data at high resolution, minimal cost, and in rapid response to sudden events. The wide range of sensor and platform configurations gives scientists great flexibility in survey design and data collection. Satellite remote sensing data has exceptional spatial coverage and continues to increase its data acquisition to meter-level resolution. UAS data can image to the cm-level resolution but lacks the same spatial coverage as satellite. By combining and comparing UAS data with satellite and ground-based remote sensing data we can utilize the different strengths of these systems. Here we demonstrate various UAS applications in high-resolution topographic change, land use classification, and sub-surface geological mapping. We use UAS payloads such as RTK georeferenced RGB and multispectral images, lidar, and magnetic sensors to image surface changes and sub-surface structures. We demonstrate the need for post-processing (PPK) high precision GNSS rover locations over utilizing only RTK position information.

Florida, USA, is home to rapidly changing beaches and wetlands, which are highly susceptible to our changing climate and destructive storm events. We show examples from beaches and wetlands in Pinellas County, Florida, USA where we have a) imaged the emergence and development of a barrier island, b) developed automated land use classification using photogrammetry and multispectral data, c) evaluated the impacts of a major hurricane event on a recently renourished beach. Pacaya Volcano, Guatemala, is an active volcano with frequent lava flows and historical flank collapse events. Using a combination of satellite DEMs, ground-based Terrestrial Radar Interferometry data, and UAS RGB SfM-photogrammetry, we have imaged recent lava flows in high-resolution showing details of lava flow levees and other structures. By comparing our data to pre-eruption satellite DEMs we can evaluate the volume and morphology of recently emplaced lava flows. In addition, we have collected magnetic data over recent lava flows that allows us to image the sub-surface structure of the lava flows and model lava flow properties. UASs are a powerful tool for remote sensing, geodetic, and geophysical data collection. They augment satellite and ground-based methodologies and by combining multidisciplinary data from these platforms we can image the earth in greater spatial and temporal detail than ever before.  

How to cite: Rodgers, M., Malservisi, R., Van Alphen, R., Sadeghi Chorsi, T., Dixon, T., and Connor, C.: UAS applications in high-resolution topographic change, land use classification, and sub-surface geophysical mapping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10468, https://doi.org/10.5194/egusphere-egu23-10468, 2023.

Stromboli is one of the most visited volcanoes in the world due to its persistent activity consisting in mild strombolian explosions with a frequency up to 25-30 events per hour. This activity is punctuated by more energetic explosions named major explosions, paroxysms and lava flow. These types of eruption can change drastically the morphology of the affected areas and cause volcanic phenomena highly impacting for the island, including heavy fallout of blocks and bombs on the flanks of the volcano, pyroclastic flows and tsunami waves. Paroxysms are highly dangerous phenomena for the tourists that climb the volcano and can cause serious problems also to the local people living on the two villages on the coast of the island. In order to map the areas affected by morphological changes, the thickness of deposits and the associate volume estimation of erupted products, we propose a study based on two techniques of remote sensing. First, we reconstruct the Stromboli topography, before and after an event, elaborating stereo pairs of Pleiades satellite and using as base an airborne LiDAR data at spatial resolution of 50 cm. Then we map the morphological changes giving an estimation of the relative areas and volumes. These results, discussed and compared with available field data, can help to better understand the impact of the event and provide indications useful in a territory planning aimed to mitigate the effects of such calamitous events.

How to cite: Spinetti, C., Bisson, M., and Palaseanu-Lovejoy, M.: Stromboli surface changes from Pleiades high-resolution space data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12890, https://doi.org/10.5194/egusphere-egu23-12890, 2023.

This study presents an application based on UAS optical data for mapping at very high spatial resolution the ballistic projectiles erupted during an explosive volcanic eruption. The novelty consists in the development of a GIS-based automate procedure that, elaborating high spatial resolution UAV optical imagery (RGB) acquired within few days from the explosive event, is able to reproduce the boundary of each ballistic projectile as georeferenced polygon feature. This procedure, applied for the first time at Stromboli volcano (Aeolian Archipelago, Italy), has reconstructed in 2D digital format the shape of the ballistic spatter clasts emplaced on the East flank of the volcano during the paroxysm of the 3rd July, 2019. The dimensions of the clasts, reproduced as polygon features stored in WGS 84 UTM 33 metric coordinates, range from 0.03 m² (16 cm x 16 cm) to 4.23 m² (~2 m x 2 m). Respect to the classic field survey, the application here presented is able to generate, in efficient and rapid way, a large amount of data and information on ballistic deposits, covering also the areas inaccessible and/or dangerous as particularly affected by ballistic fallout. Such application allowed  to better understand the dynamic of ballistics emplacement, providing a useful contribution to volcanic hazard mitigation.

How to cite: Bisson, M., Spinetti, C., Gianardi, R., Strehlow, K., De Beni, E., and Landi, P.: An automated GIS procedure for mapping ballistic projectiles by using UAVs imagery: the case of the 3rd July, 2019 paroxysm at Stromboli, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16686, https://doi.org/10.5194/egusphere-egu23-16686, 2023.

Endemic pests are a fundamental part of forest ecosystems, they provide key ecosystem services such as nutrient cycling and support biodiversity. Still, massive outbreaks of these pests, triggered by events such as drought, windthrows, and snow breaks, can limit the provisioning of ecosystem services that are key for human populations such as water cycle regulation and, which can eventually trigger natural hazard events (e.g. landslides).

Unmanned Aerial Vehicles (UAVs) and miniaturized optical sensors can be used to support foresters in detecting, identifying, and quantifying pests and their diffusion by exploiting multispectral imagery at high resolution. Such platforms are especially suited for monitoring areas in mountain regions that are difficult to access.

This study focus on the pine processionary (Thaumetopoea pityocampa) and European bark beetle (Ips typographus) that affect many forests in the Province of South Tyrol, Italy. Here, we present an up-scale strategy that first identifies the presence of a pest at the centimeter level (ground and close-range scale) based on UAV-derived products on a plot level. We conducted three UAV-flight campaigns during the year corresponding to the insect-life cycle. Then, on the one hand, using simple RGB and NDVI mosaics the system delineates the trees, identifies nests (processionary) and quantifies their impact. On the other, using the NDVI time series collection the system classify healthy, infested or dead tree linked to the presence of bark beetle. The system classifies and quantifies its presence by presenting graduated symbol maps widely used by foresters. Then, we scale up to meter resolution (remote sensing scale) to detect changes due to certain conditions of stress that can link to the presence of the studied pests. The final aim is to create high-quality training datasets that will be exploited by remote sensing products (Sentinel) to study and cover wider areas.

How to cite: Mejia-Aguilar, A., Theofanidis, A., Dorigatti, E., Sonnenschein, R., Chuprikova, E., and Meng, L.: Up-scaling approach to monitor pests in Alpine forests: A case study in Vinschgau, South Tyrol, Italy., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14035, https://doi.org/10.5194/egusphere-egu23-14035, 2023.

The Field Spectroscopy Facility (Edinburgh, UK) is a Natural Environment Research Council public funded body which maintains and provides cutting edge spectroscopy instrumentation and expertise to UK and international researchers. The facility primarily focuses on the provision of ground based spectroscopic instrumentation, often in support of airborne spectroscopic surveys, but was awarded a UKRI capital fund in 2019 for the development of a UAV spectroscopic sensor suite to fill the spatial resolution gap between airborne and ground measurements.

Developed as the “NERC Field Spectroscopy Facility UAV Suite”, the new instrument pool consists of various UAV platforms and spectroscopic sensors which can be loaned to UK and international researchers. Instruments include multispectral cameras with sensors matched to Sentinel-2 and WorldView-3 centre wavelengths; thermal cameras covering the SWIR to MIR region; a custom designed UV-VIS spectrometer for measurements of solar induced fluorescence; and the flagship sensor of the suite, a lightweight hyperspectral imager with LIDAR attachment covering the UV-VIS-SWIR region (350 to 2500 nm range).

In this presentation, we discuss the development of the FSF UAV suite, discussing our “chain” concept of development – calibration of sensors at our optical laboratory; integration of sensors onto UAVs; logistical planning of flights with associated ground-based data acquisition; and the development of custom processing chains of UAV acquired data. We will highlight select campaigns on which the UAV suite has been used, including macro plastic detection as part of ESA HyperDrone, ecological surveying of large peatlands in Northern Scotland, and support for the ESA-FLEX (solar induced fluorescence sensing) mission. We will also discuss the challenges involved in sensor integration, and provide insight into the novel solutions which we have employed during the development of the UAV suite.  

How to cite: Ramsay, R., Merrington, A., Gillespie, J., and Hancock, S.: The NERC Field Spectroscopy Facility UAV Suite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15267, https://doi.org/10.5194/egusphere-egu23-15267, 2023.

Multi-vendor operations of uncrewed vehicles as part of the observations, surveillance and surveying are already daily practice in many fields. The popularity of the integration platforms that manage multiple, sometimes simultaneously, systems is also already proven by the integration platforms' popularity. With new European regulations for the drone industry and the growing popularity of various (ground, water surface, underwater, aerial) systems exploitations, the need for situation awareness and planning that will be flexible and vendor lock-in free is leveraged. However, despite several recent efforts and some popular specifications that aim at becoming de-facto standards, civil operations' interoperability challenge is unsolved. To assess whether a shared data model is suitable for multi-domain, multi-heterogeneous vehicle use, and challenge it with real applications and demonstrate the exchange of command and control information, OGC members started an Interoperability Experiment in 2022. IE is based on a data model developed by Kongsberg Geospatial and partners under the Standards-based UxS Interoperability Test-bed (SUIT). The IE considers those other standards and specifications which were used in the SUIT work as well as other Command and Control practices from the aviation and marine communities. The presentation depicts selected use cases and scenarios and outlines the information model of the localized situation awareness and mission planning and operations. Being specific for autonomous vehicle operations, they extend the needs of generic geospatial representations. Authors will explain relations to other similar models like (LSTS, MavLink, UMAA, STANAG 4586, JAUS, C2INav) and modern geospatial data exchange standards like OGC SensorThings, Features, Moving Features, GeoPose.

How to cite: Hanchevici, T., Zaborowski, P., Sullivan, D. V., and Robin, A.: Common mission planning and situation awareness model for UxS Command and Control systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16009, https://doi.org/10.5194/egusphere-egu23-16009, 2023.