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.

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.

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.

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.

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.

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.

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.

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.

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.

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.