ESSI4.2 | Earth observation: opportunities and environmental applications towards resilient society
EDI

Earth observation (EO) technologies are valuable tools for providing the evidence necessary for decision making through the systematic monitoring, prediction and assessment of natural resources in a wide range of spatial and temporal scales, covering a range of multidisciplinary scientific communities and related applications.
Novel integrated systems can emerge by combining EO technologies with other sources of data and modeling tools that improve the availability, access and use of EO for a sustainable planet. With the access to EO data archives, past dynamics and trends can be identified and enable the training of dynamic models that can detect and predict various incidents. Both, monitoring and mapping are essential components of designing appropriate policies to prevent, for example, desertification and accelerate soil and water quality restoration.
The objective of this session is to explore the main challenges and the future directions of EO-driven approaches in two main pillars: environment and resilient society. A non-complete list of possible applications includes:
- develop decision making tools for improving agribusiness productivity, optimization of land and water management, explore the spatio-temporal dynamics of ecohydrological processes
- provide predictions of precipitation and monitor the meteorological drought using radar remote sensing
- investigate the interactions between atmospheric mechanisms and solar-related applications in a wide range of scales
- estimate the variations of sea surface levels with the use of satellite altimetry and tide gauge measurements
- monitor and model the evolution of aerosol and clouds in their natural environment using atmospheric remote sensing multi-platforms
- assess the risks to cultural heritage sites and critical infrastructure (CH/CI) due to natural hazards (i.e., fires, floods, earthquakes, etc.), propose preventive measures, integrate different sources of tools and data (e.g. EO imagery, machine learning, and geo-information data) for CH/CI and archaeolandscapes.
- Detect forest phenological changes and forest disturbances via various EO data (radar, multispectral, hyperspectral), identify possible abrupt changes in the forest phenology trend
- elaborate large amount of data using modelling tools for predicting and monitoring land, water and climate changes, and infer human origins and archaeological networks through the vast amount of EO data with the use of pattern recognition techniques.

Co-organized by GI3
Convener: Konstantinos PanagiotouECSECS | Co-conveners: Rodanthi-Elisavet Mamouri, Anis Chekirbane, Zampela PittakiECSECS, Zeinab ShirvaniECSECS
Orals
| Thu, 27 Apr, 14:00–15:40 (CEST)
 
Room 0.51
Posters on site
| Attendance Fri, 28 Apr, 10:45–12:30 (CEST)
 
Hall X4
Posters virtual
| Attendance Fri, 28 Apr, 10:45–12:30 (CEST)
 
vHall ESSI/GI/NP
Orals |
Thu, 14:00
Fri, 10:45
Fri, 10:45

Orals: Thu, 27 Apr | Room 0.51

Chairpersons: Konstantinos Panagiotou, Rodanthi-Elisavet Mamouri
14:00–14:10
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EGU23-2620
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ESSI4.2
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ECS
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On-site presentation
Christos Theocharidis, Ioannis Gitas, Chris Danezis, and Diofantos Hadjimitsis

Climate change can be described as the dominant factor all these decades concerning changes in forest phenology while, at the same time, temperature affects the development time (Barrett & Brown, 2021; X.Zhou et al., 2020; Suepa et al., 2016). Satellite image-time series data have proven their value regarding forest health and forest phenology observation. Monitoring continuous plant phenology is critical for the ecosystem at a regional and global level since the high sensitivity of vegetation life cycle to climate change; the so-called phenophases are essential biological indicators to comprehend how climate change has impacted these ecosystems and how this will change the ensuing years. (Buitenwerf, Rose, and Higgins 2015; Johansson et al. 2015).  

This study conducts a time-series analysis using the breaks for additive season and trend (BFAST) time-series decomposition algorithm, to detect possible abrupt changes in forest seasonality and the impacts of extreme climatic events on forest health, examining Sentinel-1 and Sentinel-2 data for the period 2017-2021. The backscatter coefficient from Sentinel-1, Normalised Difference Moisture Index (NDMI), Enhanced Vegetation Index (EVI), and Green Chlorophyll Index (GCI) were created by Sentinel-2 and assessed to find possible correlations between them. All the satellite time-series data derived through the Google Earth Engine platform.

The study area is the Paphos Forest, managed by the Department of Forest which could be described as a representative Mediterranean forest; thus, it is vital to monitor it because Mediterranean forests are expected to experience the first climate change in Europe. More specifically, the study focus on the Nortwest, West and Southwest areas of the Paphos Forest since the SAR images are from Ascending orbit. Moreover, Paphos forest has unspoiled vegetation, and a highly reduced number of forest wildfires have occurred in recent years, favouring the reliability of the research's results. 

 

 

Acknowledgements

The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

How to cite: Theocharidis, C., Gitas, I., Danezis, C., and Hadjimitsis, D.: Satellite times-series analysis and assessment of the BFAST algorithm to detect possible abrupt changes in forest seasonality utilising Sentinel-1 and Sentinel-2 data. Case study: Paphos forest, Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2620, https://doi.org/10.5194/egusphere-egu23-2620, 2023.

14:10–14:20
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EGU23-12887
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ESSI4.2
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ECS
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On-site presentation
Kyriaki Fotiou, Christos Theocharidis, Maria Prodromou, Stavroula Alatza, Alex Apostolakis, Athanasios V. Argyriou, Thomaida Polydorou, Constantinos Loupasakis, Charalampos Kontoes, Diofantos Hadjimitsis, and Marios Tzouvaras

In the last few years, the consequences of the active landslides that occurred in Cyprus have determined the necessity to provide a systematic displacement monitoring system of different areas using satellite-based techniques. Earth Observation and more specifically satellite remote sensing techniques using Synthetic Aperture Radar (SAR) imagery is the way forward exploiting the freely available Copernicus datasets that offer frequent revisit times and large spatial coverage. Moreover, Persistent Scatterer Interferometry (PSI) is among the most effective methods to monitor ground displacements, such as landslides, and assess their impact in residential areas. The purpose of this study is to showcase the use of advanced satellite image processing techniques, exploiting SAR satellite images to effectively identify ground displacements in different regions in Cyprus. The enhanced scientific and expertise skills of the ERATOSTHENES Centre of Excellence (ECoE) personnel on the application of PSI were acquired through a capacity building activity carried out by the National Observatory of Athens within the framework of EXCELSIOR project. The multi-temporal InSAR analysis in Cyprus revealed several deforming sites, which were also confirmed by the national authority responsible, i.e., the Geological Survey Department of the Ministry of Agriculture, Rural Development and Environment. ThCe villages of Pedoulas in Nicosia District and Pyrgos-Parekklisia in Limassol District are indicative deforming areas in Cyprus and were selected as test sites for further investigation. The ongoing implementation of additional InSAR techniques, fusion of remote sensing data and site visits for further validation, build a complete ground deformation monitoring system, aiming to migrate to a national scale project and serve as a valuable tool for natural hazards monitoring and risk reduction in Cyprus. 

 

Acknowledgements 

The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. 

How to cite: Fotiou, K., Theocharidis, C., Prodromou, M., Alatza, S., Apostolakis, A., Argyriou, A. V., Polydorou, T., Loupasakis, C., Kontoes, C., Hadjimitsis, D., and Tzouvaras, M.: Demonstrating the enhanced research capacity of the ERATOSTHENES Centre of Excellence for detecting ground displacements in Cyprus using advanced SAR satellite image processing techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12887, https://doi.org/10.5194/egusphere-egu23-12887, 2023.

14:20–14:30
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EGU23-13385
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ESSI4.2
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ECS
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On-site presentation
Maria Prodromou, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Dragos Ene, Ioannis Gitas, Kyriacos Themistocleous, Chris Danezis, and Diofantos Hadjimitsis

Fires are a widespread ecological factor since ancient times. It has a negative impact not only on the environment but on the economy, society and people. A forest fire can lead to a change in land surface, the destruction of large areas of vegetation and soil erosion. As a result, the economy is negatively affected, the balance of ecosystems is disturbed, and the flora, fauna and natural beauty are destructed. Also, biomass burning smoke affects air quality due to the large quantities of trace gases and aerosol particles that are emitted, leading to global climate change and playing a significant role in troposphere chemistry. A fundamental tool for forest fire management is the science of remote sensing. Remote sensing is commonly used for mapping burnt areas as well as for studying the effects of fire incidents and this statement is very well supported by the literature at local, regional and global levels. This study is mainly focused on burned area mapping and damage assessment on land surface and atmosphere for the case of the Arakapas fire in Cyprus. For the purposes of this study, the satellite images acquired from Sentinel-2 were used for the burnt area mapping and the fire severity estimation based on the dNBR (difference Normalized Burn Ratio) spectral index, and the Corine land cover was used for the assessment of the vegetation type that was disturbed. This event considered one of the largest in recent years is explored using data from Sentinel-5P, where carbon monoxide product is studied in the region affected by the fires. Furthermore, on the morning of the 5th of July, due to the change of wind direction, the smoke travelled from the centre of the island to the southwest, and it was detected by the multiwavelength Raman lidar, installed in Limassol. Thus, the optical properties of the smoke plume retrieved from the lidar are presented. The PollyXT-CYP lidar system of the ECoE, observed multiple layers between 500m and 2.5km with depolarization ratio of 5-8% and lidar ratio of 75sr for the upper layers.For the purposes of this study, the image processing was performed using custom scripts in the GEE (Google Earth Engine) platform with the JavaScript programming interface. The area affected by the fire was calculated to be ~40Km2. The spatial distribution map of the dNBR was classified according to the USGS fire severity levels, where high dNBR values indicate a more severe fire and values near zero and negative values indicate unburned and/or decreased vegetation after the fire.

 

Acknowledgements

The authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The 'EXCELSIOR' project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

How to cite: Prodromou, M., Mamouri, R.-E., Nisantzi, A., Ene, D., Gitas, I., Themistocleous, K., Danezis, C., and Hadjimitsis, D.: The synergy of Sentinel missions for fire damage assessment on land surface and atmosphere: the Arakapas village case study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13385, https://doi.org/10.5194/egusphere-egu23-13385, 2023.

14:30–14:40
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EGU23-14742
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ESSI4.2
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ECS
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On-site presentation
Eleni Loulli, Johannes Bühl, Silas Michaelides, Athanasios Loukas, and Diofantos Hadjimitsis

Drought is a multidimensional phenomenon that is imperceptible at its early stages, it evolves slowly and cumulatively and results to adverse consequences, for example depletion of water volumes from rivers and reservoirs, decrease of carbon uptake in vegetation etc. Cyprus is characterized by semi-arid to arid climate conditions, experiencing extensive droughts that have a negative impact on the ecosystem, the economy and the agricultural production.

Existing research on drought events in Cyprus is limited to the usage of in-situ data, mainly temperature and precipitation measurements at meteorological stations. Polarimetric weather radars can offer more detailed information regarding precipitation phenomena, especially in areas with sparse network of meteorological stations or remote areas of interest.

This study compares reflectivity measurements from the two ground-based X-band dual polarization radars of the Department of Meteorology of the Republic of Cyprus with measurements obtained from NASA’s Global Precipitation Measurement (GPM) mission.

The DPR (Dual-frequency Precipitation Radar) aboard of GPM is employed in order to derive the radar reflectivity factor with a spatial resolution of 5-25 km for 120 km wide swath. The ground-based radars operate since 2017. They scan in PPI mode at eight (8) constant elevation angles, whereas their azimuth angle varies with a spatial resolution of 0.1° and the radius of each scan is 150 km. The radar stations are located in Rizoelia, Larnaca district, and Nata, Paphos district, providing a full coverage of the island.

Satellite-based radar reflectivity values are used to adjust the ground-based radar measurements. Consequently, the adjusted values of the ground-based radar reflectivity are used as input to modelling expressions for estimating the ground-based radar precipitation.

In order to ensure that the observations are spatially coincident, we have developed a collocated grid, hereafter called universal grid, on which both the ground- and satellite-based radar observations are interpolated at the same locations. The universal grid is a three-dimensional (3D) grid with grid cell size of approximately 2500 m along both horizontal directions, whereas the vertical resolution is set equal to the height resolution of GPM, i.e. 150 m. Regarding temporal resolution, GPM overpasses Cyprus approximately once a week. For the purposes of this study, we selected overflights after the beginning of the ground-based radar operation that coincide with precipitation events.

Additionally, statistical analysis of the reflectivity measurements has been conducted to understand the relationship between the ground-based and the satellite-based datasets and identify spatio-temporal patterns of precipitation.

Acknowledgements:

The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

The authors acknowledge also the Department of Meteorology of the Republic of Cyprus for the provision of the X-band radar data.

How to cite: Loulli, E., Bühl, J., Michaelides, S., Loukas, A., and Hadjimitsis, D.: Comparing reflectivity measurements between satellite- and ground-based radar observations: A case study for precipitation and drought monitoring in Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14742, https://doi.org/10.5194/egusphere-egu23-14742, 2023.

14:40–14:50
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EGU23-894
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ESSI4.2
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On-site presentation
Mahesh Kumar Jat, Ankan Jana, and Mahender Choudhary

Evapotranspiration (ET) is an important factor to calculate the water loss to the atmosphere and water demand for crops. Global and regional estimates of daily evapotranspiration are essential for our understanding of the hydrologic cycle. Remote sensing methods have many advantages in estimating daily ET for a large heterogeneous area.  In the present study, the sensitivity of ET with respect to different remote sensing-derived variables has been quantified while using the energy balance algorithm for land (SEBAL) method to estimate daily ET. The sensitivity of SEBAL-based ET has been determined for NDVI, LST, albedo, and SAVI using Extended Fourier Amplitude Sensitivity Test (eFAST) method. Relative changes in ET estimates for a range ± 20% of important parameters i.e., NDVI, albedo, SAVI, and LST have been determined and the sensitivity coefficient was estimated. Further, the sensitivity of SEBAL estimated ET has been investigated for different land cover and land use classes i.e., cropland, barren land, settlement, forest, and sparse vegetation. Results show that ET is significantly sensitive to the albedo and LST, however, other LULC classes have a different level of sensitivity. For cropland, ET is sensitive to NDVI. The sensitivity coefficient also indicates a significant effect of albedo and LST on the SEBAL estimated ET. For cropland, a 20% decrease in albedo and LST resulted in a 4.24% and 4.19% reduction in ET, and a 20% increase leads to an increase in ET by 13% and 5.53%, respectively. For sparse vegetation, a 20% reduction in albedo leads to an increase in ET by 7.46% while a 20% increase in albedo may reduce the ET by 15.70%. SAVI has an inverse relationship with ET for forest, barren land, settlement, and sparse vegetation as compared to other variables. The study concludes that SEBAL estimated ET is sensitive to albedo and LST significantly. The study helps in understanding the scope of uncertainty in remote sensing-based ET estimation.

How to cite: Jat, M. K., Jana, A., and Choudhary, M.: Remote Sensing based Evapotranspiration Estimation and Sensitivity Analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-894, https://doi.org/10.5194/egusphere-egu23-894, 2023.

14:50–15:00
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EGU23-3514
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ESSI4.2
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ECS
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On-site presentation
Alex Hamer, Sam Dixon, Christoph Kratz, Craig Dornan, Chris Miller, Michael Prince, Charlie Hart, Tom Hunt, and Andrew Webb

The world’s peatlands are our largest terrestrial carbon store whilst also providing a sustainable source of drinking water, a haven for wildlife and storing a record of our past. The England Peat Map aims to provide baseline maps for the extent, depth, and condition of peaty soils in England by 2024. This will enable targeting of future restoration, support nature recovery, improve greenhouse emissions reporting and natural capital accounting.

The maps will be created using a combination of multi-scale Earth observation imagery (satellite and airborne), existing and new ecological field survey data and machine/deep learning. Extent and depth mapping is implemented with random forest models and uses Sentinel satellite imagery and airborne LiDAR in combination with other ancillary datasets (e.g., geology and climate) for prediction. Assessment of peatland condition requires looking at these landscapes in different ways. Land cover mapping is used as a proxy for condition by targeting reflective classes for condition (e.g., Sphagnum, heather, and bare peat). Random forest and convolutional neural network (CNN) models are used in combination with Sentinel satellite imagery, aerial photography, and airborne LiDAR to produce national outputs. Mapping erosion/drainage features (grips, gullies and haggs) across the landscape is essential in understanding the underlying hydrological condition of the peatland and promising results have been achieved using CNNs with LiDAR and aerial photography. The final aspect of assessed condition is the movement of peat, also termed bog breathing, and is measured using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR). This opportunity is a result of novel in-situ peat movement cameras being installed across pilot sites to provide ground truth data.

The final maps will be released free of charge under an open UK government license, allowing wider application and new opportunities for use compared with currently available datasets. For example, these baseline maps have the potential to contribute towards national peatland monitoring to address further decline of peatland habitats and target restoration interventions to achieve cost effective results. Several challenges have occurred during the initial phase of the project such as the difficulty in licensing suitable training data and in defining what we are mapping when features lack a globally agreed definition (e.g., surface features). The talk will discuss these challenges as well as the future direction of the project and how these challenges can be overcome.

How to cite: Hamer, A., Dixon, S., Kratz, C., Dornan, C., Miller, C., Prince, M., Hart, C., Hunt, T., and Webb, A.: England Peat Map: The challenges of using Earth observation data and machine learning approaches at the national scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3514, https://doi.org/10.5194/egusphere-egu23-3514, 2023.

15:00–15:10
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EGU23-16794
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ESSI4.2
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Virtual presentation
Vinay Shivamurthy, Thokala Manoj, Kamera Arun Kumar, Maddela Harsha Vardhan, Sangannagari Lavanya, and Sankalamaddi Manasa

In the Anthropocene, with human centric planning, the landscapes are continually altered endangering the existence of biota, triggering climate changes, affecting the ecosystem services provided by the regional landscapes. However in special cases, meticulous planning and prioritized alterations of landscape has aided in improving the regional economy and the services provided by them. In the current communication we spatially evaluate the influence of irrigation projects on the lentic ecosystems and agrarian ecosystems at regional scale. Karimnagar, located in Telangana State India, along with 25km buffer from the city center was analyzed. Being in the semiarid zones, Karimnagar experience sever temperature during summer. Spatiotemporal variation in Zaid cropping pattern and water bodies were studied using Landsat series satellite data for the past 5 decades i.e., between 1973 to 2022. Indices based methods such as Normalized Difference Vegetation Index and modified Normalized Difference Water index were used followed by segmentation to determine the areas under Zaid cropping and extent of water. It was evident that during 1973 area under Zaid crops were as low as 231km2 with water bodies about 1.7km2. with commission of lower Manair in the year 1985, downstream regions of the reservoir showed large scale improvement i.e., the lakes were rejuvenated and the area under Zaid cropping improved significantly. Area under Zaid agriculture improved by four folds i.e., over 1000km2 and water bodies increased to 53km2. In the recent past, Mid Manair was commissioned in the year 2018 post which area under water has increase to 113km2 and area under Zaid cropping has increased to 1569km2. Post Lower Manair and Mid Manair Projects, most of the lentic ecosystems in the study area have become perennial catering to agrarian, domestic and environment. The Agriculture Ecosystem Service Value in the study area particularly due the Zaid Cropping has increased from 34 Million US$ in 1973 to ~128Million US$ after commission of Lower Manair and the same has increased to 235 Million US$ by 2022, like wise ecosystem services of lentic ecosystems have increased from 0.59Million US$ in 1973 to 39.57 Million US$ in 2022. The results indicates that with sensible planning and development, both society and regional environs get mutually benefitted thus ensuring superior wellbeing.

How to cite: Shivamurthy, V., Manoj, T., Arun Kumar, K., Harsha Vardhan, M., Lavanya, S., and Manasa, S.: Evaluating the influence of human induced landscape alterations on ecosystem services in semiarid regions of India., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16794, https://doi.org/10.5194/egusphere-egu23-16794, 2023.

15:10–15:20
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EGU23-17144
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ESSI4.2
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On-site presentation
Sofia Fidani, Ioannis Maroufidis, Stavros Chlorokostas, Ioannis N. Daliakopoulos, Dimitrios Papadimitriou, Ioannis Louloudakis, Georgios Daskalakis, Betty Charalambopoulou, and Thrassyvoulos Manios

Fast and rigorous assessment of tree characteristics from earth observation products has many environmental applications, including monitoring of the canopy biomass available for pruning and utilisation as soil amendment or energy source. Here we explore the efficiency of three supervised classification algorithms in assessing canopy area of olive trees, the staple food crop of the Mediterranean that annually produces an estimated 2,82 Μt ha-1 of residual biomass (Velázquez-Martí et al., 2011) which is currently largely unexploited and often an environmental hazard due to on-site fires. The algorithms include (a) a thresholding algorithm (Daliakopoulos et al., 2009) processing Normalized Difference Vegetation Index values, (b) a supervised machine learning algorithm comprised on an Artificial Neural Network (ANN) with 4 hidden layers, and (c) the AdaBoost supervised deep learning algorithm. Following Yang et al. (2009), the latter two methods use image colour, texture, and entropy as inputs. Ground truth was developed by manually producing a binary mask where pixels depicting tree crown were marked with 1 and otherwise 0, and classification results were evaluated using the Dice similarity coefficient (DSC; Nisio et al., 2020). The three algorithms were tested on assessing olive tree crown projected surface area on a WorldView II image of resolution 0.5 × 0.5 m of a rural area of Heraklion, Crete, Greece, acquired on November 10, 2020. Masking was performed in 42 olive tree plots including a total of 1,080 olive trees, including on-site visual validation of the masking results. Results show that the ANN performed better than AdaBoost and NDVI thresholding, scoring 81.98%, compared to 75.06 and 70.03%, respectively. The trained ANN is currently used to provide olive tree canopy estimates, used as input to assess canopy biomass available for pruning for the CompOlive system, an online platform that facilitates matchmaking of olive tree farms, olive mills, and mobile composting equipment, to optimise on-farm compost production and utilisation.

Acknowledgements

This research is co-financed by the European Union and Greek national funds through the Operational Program CRETE 2014-2020, under Project “CompOlive: Integrated System for the Exploitation of Olive Cultivation Byproducts Soil Amendments” (KPHP3-0028773).

References

Daliakopoulos, I. N., Grillakis, E. G., Koutroulis, A. G., & Tsanis, L. K. (2009). Tree Crown Detection on Multispectral VHR Satellite Imagery. Photogrammetric Engineering and Remote Sensing, 75(10), 1201–1211. https://doi.org/10.14358/PERS.75.10.1201

Velázquez-Martí, B., Fernández-González, E., López-Cortés, I., & Salazar-Hernández, D. M. (2011). Quantification of the residual biomass obtained from pruning of trees in Mediterranean olive groves. Biomass and Bioenergy, 35(7), 3208–3217. https://doi.org/10.1016/J.BIOMBIOE.2011.04.042

Yang, L., Wu, X., Praun, E., & Ma, X. (2009). Tree detection from aerial imagery. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 131–137. https://doi.org/10.1145/1653771.1653792

 

How to cite: Fidani, S., Maroufidis, I., Chlorokostas, S., Daliakopoulos, I. N., Papadimitriou, D., Louloudakis, I., Daskalakis, G., Charalambopoulou, B., and Manios, T.: Comparison of three algorithms for tree crown area and available pruning biomass monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17144, https://doi.org/10.5194/egusphere-egu23-17144, 2023.

15:20–15:30
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EGU23-8315
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ESSI4.2
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On-site presentation
Anis Chekirbane, Constantinos F. Panagiotou, Aloui Dorsaf, and Stefan Catalin

Managed aquifer recharge (MAR) is a water resource management technique that involves the intentional recharge and storage of water into groundwater systems. MAR is considered an innovative nature-based solution for increasing water availability, improving water quality, and reducing surface water runoff. However, the feasibility of implementing MAR projects depends on several factors, for example recharge water availability, water demand, and the intrinsic site characteristics (e.g., geology, hydrogeology) of the area.

The current study proposes an adapted approach of MAR feasibility mapping through the integration of GIS and multi-criteria decision analysis (GIS-MCDA). The geospatial feasibility of MAR application is evaluated by considering the suitability maps of four thematic layers, namely intrinsic, water availability, non-physical and water demand.  The applicability of this approach is demonstrated in Enfidha plain (NE Tunisia), for which multiple types of spatial and temporal datasets have been collected.   The selection of the criteria is done based on literature studies and MAR experts’ opinions with respect to their relevance to MAR implementation, whereas the weights are determined using analytical hierarchy process (AHP). Hence, an intrinsic suitability map was established via the integration of ArcGIS software and MCDA in a web-based platform, called INOWAS (https://inowas.com/). The results suggest that more than 80% of the total plain area is considered intrinsically suitable for MAR implementation.  The potential MAR feasibility of the demonstration site is expected to be established by overlaying the suitability maps of the three thematic layers.

In addition to standardizing the process of MAR feasibility, the derived maps constitute an asset in the process of planning and implementing effective MAR projects that help to ensure the long-term sustainability of water resources in the Sahel region of Tunisia.

Acknowledgement

This work is funded by National Funding Agencies from Germany (Bundesministerium für Bildung und Forschung – BMBF), Cyprus (Research & Innovation Foundation – RIF), Portugal (Fundação para a Ciência e a Tecnologia – FCT), Spain (Ministerio de Ciencia e Innovación – MCI) and Tunisia (Ministère de l’Enseignement Supérieur et de la Recherche Scientifique – MESRS) under the Partnership for Research and Innovation in the Mediterranean Area (PRIMA). The PRIMA programme is supported under Horizon 2020 by the European Union’s Framework for Research and Innovation.

How to cite: Chekirbane, A., F. Panagiotou, C., Dorsaf, A., and Catalin, S.: A coupled GIS-MCDA approach to map the feasibility of Managed Aquifer Recharge, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8315, https://doi.org/10.5194/egusphere-egu23-8315, 2023.

15:30–15:40
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EGU23-16436
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ESSI4.2
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On-site presentation
Kyriacos Themistocleous, Kyriaki Fotiou, and Marios Tzouvaras

Monitoring natural hazards due to climate change and natural hazards at cultural heritage sites facilitates the early recognition of potential risks and enables effective conservation monitoring and planning. Landslides, earthquakes, rock falls, ground subsidence and erosion are the predominant natural hazards in Cyprus, which pose serious disadvantages to cultural heritage sites as well as potential danger to visitors. To identify and monitor natural hazards and environmental displacements Earth observation techniques, such as SAR, can be used in combination with in-situ methods.

The EXCELSIOR H2020 Widespread Teaming project under Grant Agreement No 857510 and the TRIQUETRA project Horizon Europe, Grant Agreement No. 101094818 will study the use of Earth observation techniques for examining cultural heritage sites. The TRIQUETRA project will examine Choirokoitia, Cyprus as a pilot project using these techniques. Choirokoitia is a UNESCO World Heritage Site and is one of the best-preserved Neolithic sites in the Mediterranean. The project will examine the potential risk of rockfall at the Choirokoitia site, as the topology of the site is vulnerable to movements as a result of extreme climate change as well as of daily/seasonal stressing actions. Rockfall poses a significant danger to visitor safety as well as damage to cultural heritage sites.

As well, the Choirokoitia site will be used to detect and analyse natural hazards induced ground deformation based on InSAR ground motion data and field survey techniques for cultural heritage applications. InSAR data, satellite positioning and conventional surveying techniques will be employed to measure micromovements, while other techniques such as UAVs and photogrammetry will be used for documentation purposes and 3D modelling comparisons. In order to identify and monitor natural hazards and their severity, a permanent GNSS station and corner reflector, as well as analysing multitemporal SAR satellite data will be used to estimate the rate of land movement. SAR monitoring provides the opportunity to identify deformation phenomena resulting from natural hazards for monitoring and assessing potential hazards using remote sensing techniques to measure and document the extent of change caused by the natural and/or geo-hazards. PSI (Persistent Scatterer Interferometry) analysis can be used in the wider area to determine potential displacements.

The study is expected to lead towards the systematic monitoring of geohazards, and more specifically those of ground deformation and rock falls to facilitate the early recognition of potential risks and enable effective conservation monitoring and planning. The methodology can be used to monitor cultural heritage sites worldwide which are vulnerable to natural hazards.

How to cite: Themistocleous, K., Fotiou, K., and Tzouvaras, M.: Monitoring natural and geo- hazards at cultural heritage sites using Earth observation: the case study of Choirokoitia, Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16436, https://doi.org/10.5194/egusphere-egu23-16436, 2023.

Posters on site: Fri, 28 Apr, 10:45–12:30 | Hall X4

Chairpersons: Konstantinos Panagiotou, Rodanthi-Elisavet Mamouri
X4.155
|
EGU23-11244
|
ESSI4.2
Afforestation in water scarce environment under Climate Change: Will trees survive and thrive?
(withdrawn)
Marinos Eliades, Christos Theocharidis, Stelios Neophytides, Christiana Papoutsa, Ioannis Varvaris, Zampela Pittaki, Athanasios Argyriou, Hakan Djuma, Adriana Bruggeman, and Diofantos Hadjimitsis
X4.156
|
EGU23-7269
|
ESSI4.2
Konstantinos Fragkos, Ilias Fountoulakis, Argyro Nisantzi, Kyriakoula Papachristopoulou, Diofantos Hadjimitsis, and Stelios Kazadzis

The visible part of the surface downward solar radiation (400 – 700 nm) known as Photosynthetically Active Radiation (PAR) is a key parameter for many land process models and terrestrial applications. More specifically, it is a critical ecological factor affecting agriculture productivity, ecosystem-atmosphere energy, CO2 fluxes, canopy architecture in forest ecosystems, and the growth of phytoplankton, among others. 

Despite its high importance, PAR measurements are rather scarce and no relevant worldwide radiometric networks for this quantity, in contrast with other actinometric quantities (e.g., global horizontal irradiance), exist. For these reasons, PAR levels are mostly estimated by satellite observations and modeling techniques.   

In the current study, we present a 16-year PAR climatology over Cyprus, based on the combined use of radiative transfer (RT) models and satellite imagery. Copernicus Atmospheric Monitoring Service (CAMS) AOD and PWV, aerosol climatology of SSA and AE based on the MACv3 aerosol climatology, Ozone – OMI data for the period 2005 – 2021, are used as input to the RT model LibRadtran to obtain the clear sky PAR levels. Consequently, the CAMS Cloud Modification Factor based on MSG images will be used to derive the PAR under all sky conditions. The derived climatology has a spatial resolution of 0.05x0.05 degrees and a temporal variation of 15 minutes, as constrained by the availability of Seviri/MSG images. Finally, the quality of the retrieved climatology is assessed by comparison with ground-based PAR measurements and PAR retrievals from measurements of GHI through relevant conversion algorithms, from quantum sensors and pyranometers that are installed in selected stations of the Meteorological Service of Cyprus.

 

Acknowledgments: The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The Department of Meteorology of the Republic of Cyprus is acknowledged for providing ground-based data for validating the modelled quantities.

How to cite: Fragkos, K., Fountoulakis, I., Nisantzi, A., Papachristopoulou, K., Hadjimitsis, D., and Kazadzis, S.: Modelled-based Photosynthetically Active Radiation climatology for Cyprus: Validation with measurements and trends, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7269, https://doi.org/10.5194/egusphere-egu23-7269, 2023.

X4.157
|
EGU23-2551
|
ESSI4.2
|
ECS
|
Vanessa Streifeneder, Daniel Hölbling, and Zahra Dabiri

In the project HAGL (“Impact of hail events on agriculture: A remote sensing-based analysis of hail damage in the context of climate change”), we analyse the effects of hail damage on agriculture. In the context of climate change and the associated increased risk of extreme weather events to society and the economy, this project deals with a locally catastrophic natural hazard that causes high costs, namely hail. Hail, combined with severe storms, causes millions of Euros of damage to agriculture every year. The influence of climate change on local weather patterns (e.g. thunderstorms) is still relatively unexplored, but early evidence points to an increase in weather patterns causing hail and an increase in hailstone sizes. In Austria, especially southeastern Styria with its various crops is frequently affected by extreme hail events. Yield losses due to hail damage can be existence-threatening for farmers, which is why an effective damage assessment is of great interest.

We aim to develop an efficient method to determine the damage to agriculture caused by hail using various remote sensing data. Through a spatial hotspot analysis, we identify regions in southeastern Styria that are particularly affected by hailstorms to test and validate our method. We perform a combined analysis of Sentinel-2 optical and Sentinel-1 synthetic aperture radar (SAR) data using object-based image analysis (OBIA) methods and different vegetation indices derived from the multispectral data as well as radar backscatter signals to detect hail damage. Finally, we aim to create a damage categorisation that could support insurance work in the event of a disaster and make it more efficient by providing a first estimation of the damage before an on-side assessment is conducted. Especially for large agricultural fields, this would save time and resources by making it possible to prioritise areas with high damage and organise the fieldwork of insurance employees accordingly.

How to cite: Streifeneder, V., Hölbling, D., and Dabiri, Z.: Impact of hail events on agriculture: A remote sensing-based analysis of hail damage in the context of climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2551, https://doi.org/10.5194/egusphere-egu23-2551, 2023.

X4.158
|
EGU23-6396
|
ESSI4.2
Ilias Fountoulakis, Konstantinos Fragkos, Kyriakoula Papachristopoulou, Argyro Nisantzi, Antonis Gkikas, Diofantos Hadjimitsis, and Stelios Kazadzis

Solar ultraviolet (UV) radiation is only a very small fraction of the total solar radiation reaching the Earth's surface. Nevertheless, it is of exceptional significance for life on Earth. In the last two decades, significant trends in biologically effective doses have been reported over many mid-latitude sites, due to changes in total ozone, aerosols, and cloudiness. In the present study, reanalysis and satellite information for aerosols, clouds, and total ozone, from Copernicus Atmospheric Monitoring Service (CAMS), MIDAS (ModIs Dust AeroSol) dataset, Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard Meteosat Second Generation (MSG) satellite, and Ozone Monitoring Instrument (OMI) aboard Aura satellite respectively, for the period 2004 - 2021 are used as inputs to a radiative transfer model and UV spectra are simulated for the island of Cyprus on fine spatial (0.05° x 0.05°) and temporal (15 mins) resolution. Effective doses for the production of vitamin D in the human skin, erythema, and DNA damage are calculated from the produced spectra. There is also an effort to attribute the changes in the UV biological doses to the corresponding changes in total ozone, aerosols, and cloudiness. The significant role of dust in the changes in UV doses over the island is also discussed.

Acknowledgments: The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. The Department of Meteorology of the Republic of Cyprus is acknowledged for providing the ground-based data for the validation of the modelled quantities. 

How to cite: Fountoulakis, I., Fragkos, K., Papachristopoulou, K., Nisantzi, A., Gkikas, A., Hadjimitsis, D., and Kazadzis, S.: Evolution of biologically active ultraviolet doses in Cyprus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6396, https://doi.org/10.5194/egusphere-egu23-6396, 2023.

X4.159
|
EGU23-10910
|
ESSI4.2
Seonghun Pyo, Kwonho Lee, and Seunghan Park

Emission sources, meteorology, and topography are the major factors that make it difficult to predict aerosols in space and time. In this study, the moderate resolution imaging spectro-radiometer (MODIS) aerosol optical thickness (AOT) and the surface meteorology observed in Korea have been used to predict spatio-temporal AOT by using the machine learning with spatial analysis techniques. This method enables timeseries based prediction and spatial distribution modeling, and allows modeling values where there are no observation points. The model results show root mean square error (RMSE) 0.33 which is smaller than the standard deviation of the observed value 0.43. Using this technique, the trend of aerosol change in the future was estimated, and it was found that the aerosol in the area of interest decreased by about 7.4%. The methodology will be useful to analyze the regional scale aerosol evaluations, air quality, and climate study.

 

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF-2019R1I1A3A01062804)”

How to cite: Pyo, S., Lee, K., and Park, S.: Spatio-temporal prediction of aerosol optical thickness using machine learning and spatial analysis techniques, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10910, https://doi.org/10.5194/egusphere-egu23-10910, 2023.

X4.160
|
EGU23-12336
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ESSI4.2
|
ECS
Ilja Vuorinne, Janne Heiskanen, Ian Ocholla, Rose Kihungu, and Petri Pellikka

Invasive alien plant species are a major global problem threatening biodiversity and livelihoods and their mapping is needed for understanding their distribution dynamics, and for facilitating control and eradication measures. Prosopis spp., a fast-growing woody species native to South America, have been widely introduced into the tropics to restore degraded areas, but they have spread uncontrollably. For example, in East Africa, Prosopis spp. have invaded rangelands and thus decreased plant diversity and affected the livelihoods of pastoral communities. Remote sensing instruments mounted on an aircraft can be used to map such species and especially a combination of different sensors holds a potential for accurate detection.

The objective of this study was to test how a combination of airborne light detection and ranging (LiDAR), hyperspectral, and fine resolution multispectral data can be used to map Prosopis spp. in a semi-arid environment in Kenya. The remotely sensed spectral, structural, and textural features were used in a one-class machine learning algorithms to detect these species in a complex landcover. The results provide information on the use of different airborne remote sensing instruments and their combination in mapping woody alien invasive species and offer insights on the distribution of Prosopis spp. in the study area.

How to cite: Vuorinne, I., Heiskanen, J., Ocholla, I., Kihungu, R., and Pellikka, P.: Assessment of airborne remote sensing data for high-resolution mapping of invasive Prosopis spp. in a semi-arid environment in Kenya, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12336, https://doi.org/10.5194/egusphere-egu23-12336, 2023.

X4.161
|
EGU23-12958
|
ESSI4.2
Rosa Coluzzi, Francesco Di Paola, Vito Imbrenda, Maria Lanfredi, Letizia Pace, Elisabetta Ricciardelli, Caterina Samela, and Valerio Tramutoli

Agricultural areas of Mediterranean regions host an extraordinary wealth of biodiversity and represent the source of income for a large population often living below the average economic conditions of the most advanced regions of Europe. In these areas, the semi-arid climates, the impact of climate change, the parcelization of land property, and the poor soils, contribute to create widespread conditions of low profitability of agricultural areas. This is likely to have an impact on the increasing occurrence of land abandonment phenomena and on growing hydrogeological risk linked to the lack of land maintenance.

The productivity estimation of these agricultural areas represents a crucial information to detect hotspots of degradation helping policy makers in taking specific actions to increase productivity and reduce migration fluxes.

In this work, realized in the framework of the ODESSA (On DEmand Services for Smart Agriculture) project (financed by the European Regional Development Fund Operational Programme 2014-2020 of Basilicata Region), the procedure adopted involves the use of climate and vegetation geospatial data, including both direct observational data (temperature, rainfall, etc.) and satellite-derived vegetation indexes. For the climatic component, we exploited a database of daily temperature and rainfall data (2000-2021) acquired by the agrometeorological network of ALSIA (Lucana Agency for Development and Innovation in Agriculture) and the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) dataset providing rainfall data (1981-2020) at a spatial resolution of 0.050 to produce different diagnostic indices able to capture low-productivity areas. We tested this procedure in two districts of Basilicata (Southern Italy): the Vulture-Melfese and the Metapontino, representing the core areas of regional agricultural specialization for vineyards and intensive fruit and vegetable crops, respectively.

 

How to cite: Coluzzi, R., Di Paola, F., Imbrenda, V., Lanfredi, M., Pace, L., Ricciardelli, E., Samela, C., and Tramutoli, V.: Development of algorithms based on the integration of meteorological data and remote sensing indices for the identification of low-productivity agricultural areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12958, https://doi.org/10.5194/egusphere-egu23-12958, 2023.

X4.162
|
EGU23-13430
|
ESSI4.2
The estimation of Crop Land Productivity based on satellite and biophysical modelled data
(withdrawn)
Oleksii Kryvobok
X4.163
|
EGU23-15419
|
ESSI4.2
|
ECS
Modeling water flow dynamics in an agricultural field in Cyprus using image spectral data
(withdrawn)
Ioannis Varvaris, Zampela Pittaki, Stelios Neophytides, Georgios Leventis, Marinos Eliades, Christiana Papoutsa, Marios Tzouvaras, Nikolaos Stathopoulos, Kyriacos Neocleous, Kyriacos Themistocleous, Silas Michaelides, Charalampos Kontoes, and Diofantos Hadjimitsis
X4.164
|
EGU23-15837
|
ESSI4.2
|
ECS
Georgios Leventis, Georgios Melillos, Athanasios Argyrioy, Ioannis Varvaris, Zampella Pittaki, Kyriacos Themistocleous, and Diofantos Hadjimitsis

The Eastern Mediterranean, Middle East, and North Africa (EMMENA) region encompasses three continents (Europe, Asia, and Africa). The region is not only strategically vital for political and military forces, but it is also archaeologically and culturally significant due to the large amount of cultural wealth, due to being an important crossroad in archaic times for various civilizations [1]. However, the cultural assets of the region are often susceptible to risks associated either to nature (like land deformation, earthquakes etc.) or to human activity (looting, war atrocities, etc.).

To protect cultural heritage in uncertain crisis scenarios, it is critical to recognize any risk situation early and support the decision-makers and cultural stakeholders with timely, accurate and relevant information, while raising at the same time public awareness on important issues that pertain to the cultural destruction, alteration and/or looting. Towards the end of responding properly in due time to any threats, ERATOSTHENES Centre of Excellence through its two departments; Big Earth Data Analytics and Cultural Heritage at the current work showcases its efforts in building and exploiting a cultural data cube based and building upon the open-source project called Open Data Cube [2]. Taking advantage of such endeavor, centre’s researchers are able to store, extract and analyse geospatial and satellite data, which due to their cube-shaped transformation can be accessed quickly thus providing a better understanding of any critical risk situations that might affect possible cultural assets. As the scale and pattern of occurrence fluctuate based on the type of disaster, as well as the extent of damage may vary from time to time depending on regional features, the timing of incident(s) and of the response, the proposed work encapsulates various forms of data acquired throughout an entire risk scenario (prior to the event, during the event and post to the event), to ensure the best possible assessment of any ongoing risk(s).

It becomes perceivable that damaged cultural assets cannot be restored to their former condition, hence is crucial to preserve them as much as possible and increase the resilience of cultural properties by reducing the harm brought on by disaster scenarios. Fostering on geospatial advances, the particular work aspires to become a common ground and valuable tool for efficient incident management within the EMMENA region starting from the field of Cultural Heritage and extending to others (i.e., marine security, agriculture, water resources management etc.).

 

Acknowledgements

The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.

 

References

[1] - Longuet, R.: Encyclopaedia of the History of Science, Technology, and Medicine in Non-Western Cultures. Springer, Netherlands, Dordrecht (2008)

[2] – Open Data Cube, open-source project, https://www.opendatacube.org/about. Last accessed on 8/01/2023.

How to cite: Leventis, G., Melillos, G., Argyrioy, A., Varvaris, I., Pittaki, Z., Themistocleous, K., and Hadjimitsis, D.: Exploring the benefits of building a data cube towards the efficient risk monitoring and assessment of cultural heritage assets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15837, https://doi.org/10.5194/egusphere-egu23-15837, 2023.

Posters virtual: Fri, 28 Apr, 10:45–12:30 | vHall ESSI/GI/NP

Chairpersons: Konstantinos Panagiotou, Rodanthi-Elisavet Mamouri
vEGN.5
|
EGU23-16909
|
ESSI4.2
|
ECS
|
Eleftheria Kalogirou, George Melillos, Diofantos Hadjimitsis, and Despoina Makri

The ability to measure sea surface temperature allows us to observe the global system and quantify ongoing weather and climate change. Several industries are particularly affected by increased SST the shipping industry, the offshore oil and gas industry, the fishing industry, etc. Knowledge of ocean wind behaviour will enable ship masters to choose routes that avoid heavy seas or high headwinds that may slow the ship's travel, increase fuel consumption, or possibly cause damage to vessels and loss of life. This paper aims to realise the Cyprus region's sea surface temperature and wind speed data. The comparison of results obtained using Sentinel Application Platform (SNAP) and ArcGIS Pro, shows that both tools can be used to realise Sea Surface Temperature and Ocean Wind Speed Data and give satisfactory results.

Keywords: Sea surface temperature, Ocean Wind Speed Data, Sentinel-3, SNAP, ArcGIS Pro.

How to cite: Kalogirou, E., Melillos, G., Hadjimitsis, D., and Makri, D.: Sea Surface Temperature and Ocean Wind Speed Data in the Cyprus region from Sentinel-3 using Sentinel Application Platform (SNAP) and Arc GIS Pro., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16909, https://doi.org/10.5194/egusphere-egu23-16909, 2023.