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Wyszukujesz frazę "Sentinel 2 satellite" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Spatial and Temporal Variability of Moisture Condition in Soil-Plant Environment using Spectral Data and Gis Tools
Autorzy:
Grzywna, H.
Dąbek, P. B.
Olszewska, B.
Powiązania:
https://bibliotekanauki.pl/articles/123280.pdf
Data publikacji:
2018
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
drought
soil moisture
NDVI
Sentinel-2
satellite data
remote sensing
Opis:
The studies on agricultural droughts require long-term atmospheric, hydrological and meteorological data. On the other hand, today, the possibilities of using spectral data in environmental studies are indicated. The development of remote sensing techniques, increasing the spectral and spatial resolution of data allows using remote sensing data in the study of water content in the environment. The paper presents the results of the analysis of moisture content of soil-plant environment in the lowland areas of river valley using the spectral data from Sentinel-2. The analyses were conducted between February and November 2016. The spectral data were used to calculate the Normalize Differential Vegetation Index (NDVI) which provided the information about the moisture content of the soil-plant environment. The analyses were performed only on grasslands, on 22 objects located in the research area in the Oder river valley between Malczyce and Brzeg Dolny, Poland. The NDVI values were correlated with the hydrological and meteorological parameters. The analyses showed spatial and temporal variability of the moisture conditions in the soil-plant environment showed by the NDVI variability and existence some relationships between the climatic and spectral indices characterizing the moisture content in the environment.
Źródło:
Journal of Ecological Engineering; 2018, 19, 6; 56-64
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Processing of satellite data in the cloud
Autorzy:
Proficz, J.
Drypczewski, K.
Powiązania:
https://bibliotekanauki.pl/articles/1940555.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska
Tematy:
Apache Spark
satellite data
Sentinel-2
ESA
big data
cloud
OpenStack
dane satelitarne
duże zbiory danych
chmura
Opis:
The dynamic development of digital technologies, especially those dedicated to devices generating large data streams, such as all kinds of measurement equipment (temperature and humidity sensors, cameras, radio-telescopes and satellites – Internet of Things) enables more in-depth analysis of the surrounding reality, including better understanding of various natural phenomenon, starting from atomic level reactions, through macroscopic processes (e.g. meteorology) to observation of the Earth and the outer space. On the other hand such a large quantitative improvement requires a great number of processing and storage resources, resulting in the recent rapid development of Big Data technologies. Since 2015, the European Space Agency (ESA) has been providing a great amount of data gathered by exploratory equipment: a collection of Sentinel satellites – which perform Earth observation using various measurement techniques. For example Sentinel-2 provides a stream of digital photos, including images of the Baltic Sea and the whole territory of Poland. This data is used in an experimental installation of a Big Data processing system based on the open source software at the Academic Computer Center in Gdansk. The center has one of the most powerful supercomputers in Poland – the Tryton computing cluster, consisting of 1600 nodes interconnected by a fast Infiniband network (56 Gbps) and over 6 PB of storage. Some of these nodes are used as a computational cloud supervised by an OpenStack platform, where the Sentinel-2 data is processed. A subsystem of the automatic, perpetual data download to object storage (based on Swift) is deployed, the required software libraries for the image processing are configured and the Apache Spark cluster has been set up. The above system enables gathering and analysis of the recorded satellite images and the associated metadata, benefiting from the parallel computation mechanisms. This paper describes the above solution including its technical aspects.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2017, 21, 4; 365-377
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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