Paving the Way towards an Armenian Data Cube

Shushanik Asmaryan, Vahagn Muradyan, Garegin Tepanosyan, Azatuhi Hovsepyan, Armen Saghatelyan, Hrachya Astsatryan, Hayk Grigoryan, Rita Abrahamyan, Yaniss Guigoz and Gregory Giuliani
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Shushanik Asmaryan: GIS and Remote Sensing Department, Center for Ecological-Noosphere Studies NAS RA, Yerevan 0025, Armenia
Vahagn Muradyan: GIS and Remote Sensing Department, Center for Ecological-Noosphere Studies NAS RA, Yerevan 0025, Armenia
Garegin Tepanosyan: GIS and Remote Sensing Department, Center for Ecological-Noosphere Studies NAS RA, Yerevan 0025, Armenia
Azatuhi Hovsepyan: GIS and Remote Sensing Department, Center for Ecological-Noosphere Studies NAS RA, Yerevan 0025, Armenia
Armen Saghatelyan: GIS and Remote Sensing Department, Center for Ecological-Noosphere Studies NAS RA, Yerevan 0025, Armenia
Hrachya Astsatryan: Institute of Informatics and Automation Problems NAS RA, Yerevan 0014, Armenia
Hayk Grigoryan: Institute of Informatics and Automation Problems NAS RA, Yerevan 0014, Armenia
Rita Abrahamyan: Institute of Informatics and Automation Problems NAS RA, Yerevan 0014, Armenia
Yaniss Guigoz: Institute for Environmental Sciences, University of Geneva, 1205 Geneva, Switzerland
Gregory Giuliani: Institute for Environmental Sciences, University of Geneva, 1205 Geneva, Switzerland

Data, 2019, vol. 4, issue 3, 1-10

Abstract: Environmental issues become an increasing global concern because of the continuous pressure on natural resources. Earth observations (EO), which include both satellite/UAV and in-situ data, can provide robust monitoring for various environmental concerns. The realization of the full information potential of EO data requires innovative tools to minimize the time and scientific knowledge needed to access, prepare and analyze a large volume of data. EO Data Cube (DC) is a new paradigm aiming to realize it. The article presents the Swiss-Armenian joint initiative on the deployment of an Armenian DC, which is anchored on the best practices of the Swiss model. The Armenian DC is a complete and up-to-date archive of EO data (e.g., Landsat 5, 7, 8, Sentinel-2) by benefiting from Switzerland’s expertise in implementing the Swiss DC. The use-case of confirm delineation of Lake Sevan using McFeeters band ratio algorithm is discussed. The validation shows that the results are sufficiently reliable. The transfer of the necessary knowledge from Switzerland to Armenia for developing and implementing the first version of an Armenian DC should be considered as a first step of a permanent collaboration for paving the way towards continuous remote environmental monitoring in Armenia.

Keywords: big earth data; sustainable development goals; swiss DC; Armenian DC; Landsat; sentinel; analysis ready data (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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