An integrated service-based solution addressing the modernised common agriculture policy regulations and environmental perspectives

Karagiannopoulou, Aikaterini; Tsiakos, Chrysovalantis; Tsimiklis, Georgios; Tsertou, Athanasia; Amditis, Angelos; Milčinski, Grega; Vesel, Nejc; Protić, Dragutin; Kilibarda, Milan; Tsakiridis, Nikolaos L.; Chondronasios, Apostolos

doi:10.1117/12.2576171

Cited by 2 publications

(2 citation statements)

References 61 publications

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“…The relative ease of managing data storage and programmatic data transfer between software systems is another important enabling technology, which underpins the proliferation of sensor networks for precision agriculture, e.g. Karagiannopoulou et al 2020.…”

Section: Cloud Platforms and Apismentioning

confidence: 99%

Remote Sensing Data to Support Integrated Decision Making in Cultural and Natural Heritage Management. Impasses and opportunities for collaboration in agricultural areas

Opitz¹,

Baldwin²,

Smedt³

et al. 2023

Internet Archaeol.

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Remote and near surface sensing data are widely used in archaeology and heritage management for feature discovery, change detection and monitoring, as an input to predictive modelling, and in the planning process. While global and regional datasets are widely used for some purposes, data are regularly acquired specifically for archaeological projects because of the very high spatial resolution required for feature detection and assessments of archaeological significance and the need for data on subsurface features. The sensing data collected for archaeology cover limited areas and only a few types of sensors, known to produce data efficiently, are regularly employed. Precision agriculture is beginning to produce large quantities of varied sensing data across extensive landscape areas. This situation creates an opportunity to adapt and reuse precision agricultural data for archaeology and heritage work, extending covering and enhancing our understanding of archaeology in contemporary agricultural landscapes. Equally, there is potential for coordinated data collection, collecting data once for multiple applications, and to add value through analyses which bring together perspectives from multiple related domains to model long-term processes in anthropogenic soil systems. This article provides a high-level overview of policy and technological developments which create the potential for sensing data reuse, coordinated data collection, and collaborative analyses across archaeological, agricultural, and agri-environmental applications while underscoring the structural barriers which, at present, constrain this potential. It highlights examples where the development of interoperable data and workflows can promote tighter integration of archaeology and cultural heritage management with sustainable agricultural land management and support integrated decision making.

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Section: Cloud Platforms and Apismentioning

confidence: 99%

Remote Sensing Data to Support Integrated Decision Making in Cultural and Natural Heritage Management. Impasses and opportunities for collaboration in agricultural areas

Opitz¹,

Baldwin²,

Smedt³

et al. 2023

Internet Archaeol.

View full text Add to dashboard Cite

show abstract

“…Data from synthetic aperture radar (SAR) systems can operate during all-weather conditions, and, while exploring agronomical issues, they can be used to analyze the moisture and geometrical conditions of crops [33][34][35]. In particular, dual-polarimetric SAR acquisitions from Copernicus Sentinel-1 mission (S1) provide unique opportunities to disseminate operational monitoring for several application communities [36,37]. Dual-pol acquisition mode has a larger swath and a lower data volume compared with full-pol acquisitions, thus improving data collection and processing for operational activities [38,39].…”

Section: Introductionmentioning

confidence: 99%

Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

Petris

Sarvia

Gullino³

et al. 2021

Remote Sensing

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Climate change increases extreme whether events such as floods, hailstorms, or storms, which can affect agriculture, causing damages and economic loss within the agro-food sector. Optical remote sensing data have been successfully used in damage detections. Cloud conditions limit their potential, especially while monitoring floods or storms that are usually related to cloudy situations. Conversely, data from the Polarimetric Synthetic Aperture Radar (PolSAR) are operational in all-weather conditions and are sensitive to the geometrical properties of crops. Apple orchards play a key role in the Italian agriculture sector, presenting a cultivation system that is very sensitive to high-wind events. In this work, the H-α-A polarimetric decomposition technique was adopted to map damaged apple orchards with reference to a stormy event that had occurred in the study area (NW Italy) on 12 August 2020. The results showed that damaged orchards have higher H (entropy) and α (alpha angle) values compared with undamaged ones taken as reference (Mann–Whitney one-tailed test U = 14,514, p < 0.001; U = 16604, p < 0.001 for H and α, respectively). By contrast, A (anisotropy) values were significantly lower for damaged orchards (Mann–Whitney one-tailed test U = 8616, p < 0.001). Based on this evidence, the authors generated a map of potentially storm-damaged orchards, assigning a probability value to each of them. This map is intended to support local funding restoration policies by insurance companies and local administrations.

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An integrated service-based solution addressing the modernised common agriculture policy regulations and environmental perspectives

Cited by 2 publications

References 61 publications

Remote Sensing Data to Support Integrated Decision Making in Cultural and Natural Heritage Management. Impasses and opportunities for collaboration in agricultural areas

Remote Sensing Data to Support Integrated Decision Making in Cultural and Natural Heritage Management. Impasses and opportunities for collaboration in agricultural areas

Sentinel-1 Polarimetry to Map Apple Orchard Damage after a Storm

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