Fuzzy clustering for the within-season estimation of cotton phenology.

Crop phenology is crucial information for crop yield estimation and agricultural management. Traditionally, phenology has been observed from the ground; however Earth observation, weather and soil data have been used to capture the physiological growth of crops. In this work, we propose a new approach for the within-season phenology estimation for cotton at the field level. For this, we exploit a variety of Earth observation vegetation indices (derived from Sentinel-2) and numerical simulations of atmospheric and soil parameters. Our method is unsupervised to address the ever-present problem of sparse and scarce ground truth data that makes most supervised alternatives impractical in real-world scenarios. We applied fuzzy c-means clustering to identify the principal phenological stages of cotton and then used the cluster membership weights to further predict the transitional phases between adjacent stages. In order to evaluate our models, we collected 1,285 crop growth ground observations in Orchomenos, Greece. We introduced a new collection protocol, assigning up to two phenology labels that represent the primary and secondary growth stage in the field and thus indicate when stages are transitioning. Our model was tested against a baseline model that allowed to isolate the random agreement and evaluate its true competence. The results showed that our model considerably outperforms the baseline one, which is promising considering the unsupervised nature of the approach. The limitations and the relevant future work are thoroughly discussed. The ground observations are formatted in an ready-to-use dataset and will be available at https://github.com/Agri-Hub/cotton-phenology-dataset upon publication.

Monitoring of land surface subsidence using persistent scatterer interferometry techniques and ground truth data in arid and semi-arid regions, the case of Remah, UAE.

The United Arab Emirates (UAE) is located in an arid desert climate with very limited water resources and scarce rainfall. Along with the fast development of the country, the water demand for agriculture, industrial, and domestic purposes increased and led to diminishing groundwater resources. In this study, we explore the land surface deformations due to groundwater overexploitation in the agricultural area of Remah by analyzing Sentinel-1 data between 2015 and 2019 with the novel Parallelized-Persistent Scatterer Interferometry (P-PSI) technique. The detected land surface deformations have been correlated to the recorded groundwater levels at nearby water wells. This study detected land surface deformations in a form of an extensive subsidence bowl (with 28.5 km in diameter) with a maximum subsidence rate of 40 mm/year and a standard deviation within the bowl of less than 2 mm/year. The detected subsidence was associated with a 12 m drop in the water table level within the study area. The Persistent Scatterers with the highest deformations rate were spatially correlated with the depression cone of the groundwater level. These findings provide useful insights in understanding the groundwater regime of the area and have an important role in assessing regional hazards and driving mitigation measures towards managing uncontrolled groundwater overexploitation for sustainable management of groundwater resources.

Multi-Temporal InSAR Analysis for Monitoring Ground Deformation in Amorgos Island, Greece.

Radar Interferometry is a widely used method for estimating ground deformation, as it provides precision to a few millimeters to centimeters, and at the same time, a wide spatial coverage of the study area. On July 9, 1956, one of the strongest earthquakes of the 20th century in the area of the South Aegean, occurred in Amorgos, with a magnitude of Mw = 7.7. The objective of this research is to map ground deformation in Amorgos island, using InSAR techniques. We conducted a multi-temporal analysis of all available data from 2003 to 2019 by exploiting historical ENVISAT SAR imagery, as well as the dense archive of Sentinel-1 SLC imagery. Persistent Scatterer Interferometry (PS) and Small Baseline Subset (SBAS) methods were implemented. Results of both data-sets indicate a small-scale deformation on the island. A multi-track analysis was implemented on Sentinel-1 data to decompose the line of sight velocities to vertical and horizontal. The central south coast is experiencing horizontal movement, while uplift of a maximum value of 5 mm/y is observed in the southeastern coast. The combination of the good spatial coverage achievable via InSAR, with GPS measurements, is suggested an important tool for the seamless monitoring of Amorgos island towards tectonic hazard estimation.

National scale operational mapping of burnt areas as a tool for the better understanding of contemporary wildfire patterns and regimes.

This paper presents the results of an operational nationwide burnt area mapping service realized over Greece for the years 2007-2011, through the implementation of the so-called BSM_NOA dedicated method developed at the National Observatory of Athens for post-fire recovery management. The method exploits multispectral satellite imagery, such as Landsat-TM, SPOT, FORMOSAT-2, WorldView and IKONOS. The analysis of fire size distribution reveals that a high number of fire events evolve to large and extremely large wildfires under favorable wildfire conditions, confirming the reported trend of an increasing fire-severity in recent years. Furthermore, under such conditions wildfires affect to a higher degree areas at high altitudes, threatening the existence of ecologically significant ecosystems. Finally, recent socioeconomic changes and land abandonment has resulted in the encroachment of former agricultural areas of limited productivity by shrubs and trees, resulting both in increased fuel availability and continuity, and subsequently increased burnability.