Strategic Research Agenda for Utilisation of Earth Observation in Agriculture

Zadražil, František; Šafář, Václav; Kubickova, Hana; Horáková, Šárka; Mildorf, Tomáš

doi:10.3390/engproc2021009035

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Fusion of dense multi-sensor time-series data remains complicated, however, and often poses the problem of high-dimensional feature space. [89] 4. Discussion…”

Section: Sentinel-1 and Sentinel-2 Data Fusionmentioning

confidence: 99%

Comparison of EO4Agri Recommendations With In-Depth Literature Review

Zadražil¹,

Onckelet²,

Kubickova³

2021

Preprint

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Copernicus is Europe's space-based Earth monitoring asset, which consists of a complex set of systems that collect data from different sources: remote sensing satellites (RS) and in-situ sensors such as ground stations, airborne and marine sensors. This study was originally prepared for the needs of the Czech agricultural community, where we provided an in-depth analysis of articles related to Earth observation in precision agriculture. At a later stage, we extended this study by comparing the recommendations of the European EO4Agri project and scientific articles published in MDPI. We had two important objectives, one was to validate the results of the EO4Agri project and the other was to look for gaps in current research and community needs. To recognize the importance of using Sentinel 1 data, we also added a specific analysis of methods for data fusion of Sentinel 1 and Sentinel 2 data.

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“…Fusion of dense multi-sensor time-series data remains complicated, however, and often poses the problem of high-dimensional feature space. [89] 4. Discussion…”

Section: Sentinel-1 and Sentinel-2 Data Fusionmentioning

confidence: 99%

Comparison of EO4Agri Recommendations With In-Depth Literature Review

Zadražil¹,

Onckelet²,

Kubickova³

2021

Preprint

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“…and in different time periods. In this case, analysed satellite data from the Copernicus programme were used as a thematic layer for OLU, as suggested in (Charvát et al, 2021a). Our aim is to enhance OLU data available in an area of interest with information raised from calculation of vegetation indexes and classification of satellite images, in our case adding crop type information.…”

Section: Introductionmentioning

confidence: 99%

Combination of OpenLandUse Database and Sentinel Data for Agriculture Purposes

Hájek¹,

Kepka²,

Švenajs³

et al. 2022

GIS Ostrava 2022 Earth Observation for Smart City and Smart Region

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Creating an Earth's twin in sufficient detail and complex relations is a challenge for the future arising from strategies like DestinE or Green Deal. Enormous amount of geospatial data available these days leads to a necessity of a suitable data structure to provide understandable information to a general user. An OpenLandUse (OLU) database can serve as such a structure for integrating datasets of different themes, different spatial resolution, and different temporal validity. This paper shows an example of incorporating Earth observation data into the Open Land Use data model, to provide enhanced information about field blocks of a farm in Vyškov region in CZE with information about crop types planted in fields. The data for enhancing the OLU database were based on Sentinel-1 and Sentinel-2 images from 2020, analysed into the form of supervised classification of crop types and various indexes, especially Enhanced Vegetation Index (EVI) and Radar Vegetation Index for Sentinel-1 SAR data (RVI4S1).

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