{"id":426,"date":"2017-11-30T12:46:59","date_gmt":"2017-11-30T12:46:59","guid":{"rendered":"http:\/\/www.swissdatacube.org\/?page_id=426"},"modified":"2023-11-15T16:11:24","modified_gmt":"2023-11-15T16:11:24","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.swissdatacube.org\/index.php\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"
    \n
  1. Obuchowicz C., Poussin C., Giuliani G. (2023) Change in observed long-term greening across Switzerland \u2013 Evidence from a three decades NDVI time-series and its relationship with climate and land cover factors, Big Earth Data<\/strong> https:\/\/doi.org\/10.1080\/20964471.2023.2268322<\/a><\/li>\n
  2. Poussin C., Timoner P., Chatenoux B., Giuliani G., Peduzzi P. (2023) Improved Landsat-based snow cover mapping accuracy using a spatiotemporal NDSI and generalised linear mixed model, Science of Remote Sensing <\/strong>7:100078 https:\/\/doi.org\/10.1016\/j.srs.2023.100078<\/a><\/li>\n
  3. Cornut C., Ozainne S., Poussin C., Andenmatten R., Giuliani G. (2022) Identifying areas of archaeological potential in the Swiss Alps using satellite-derived time-series of snow cover estimates.\u00a0Remote Sensing Applications: Society and Environment\u00a0<\/strong>28:100838 https:\/\/doi.org\/10.1016\/j.rsase.2022.100838<\/a><\/li>\n
  4. Xu C., Du X., Fan X., Giuliani G., Wang W., Liu J., Wang T., Hu Z., Yan Z., Zhu J., Jiang T., Guo H. (2022) Cloud-based Storage and Computing for Remote Sensing Big Data: A Technical Review.\u00a0International Journal of Digital Earth\u00a0<\/strong>15(1):1417-1445 https:\/\/doi.org\/10.1080\/17538947.2022.2115567<\/a><\/li>\n
  5. Blanc, N., Cannata, M., Collombin, M., Ertz, O., Giuliani, G., & Ingensand, J. (2022). OGC API state of play \u2013 a practical testbed for the national spatial data infrastructure in Switzerland. The International Archives Of The Photogrammetry, Remote Sensing And Spatial Information Sciences<\/strong>, XLVIII-4\/W1-2022, 59-65 https:\/\/doi.org\/10.5194\/isprs-archives-XLVIII-4-W1-2022-59-2022<\/a><\/li>\n
  6. Sudmanns M., Augustin H., Killough B., Giuliani G., Tiede D., Leith A., Yuan F. (2022) Think global, cube local: An Earth Observation Data Cube’s contribution to the Digital Earth vision, Big Earth Data<\/strong> https:\/\/doi.org\/10.1080\/20964471.2022.2099236<\/a><\/li>\n
  7. Chatenoux B., Richard J.-P. Small D., Roeoesli C., Wingate V., Poussin C., Rodila D., Peduzzi P., Steinmeier C., Ginzler C., Psomas A., Schaepman M., Giuliani G. (2021) The Swiss Data Cube: Analysis Ready Data archive using Earth Observations of Switzerland,\u00a0Nature Scientific Data<\/strong>. 8:295 https:\/\/doi.org\/10.1038\/s41597-021-01076-6<\/a><\/li>\n
  8. Poussin C., Massot A., Ginzler C., Weber D., Chatenoux B., Lacroix P., Piller T., Nguyen L., Giuliani G. (2021) Drying conditions in Switzerland – Indication from a 35-year Landsat trend analysis of vegetation water content estimates to support SDGs,\u00a0Big Earth Data <\/strong>x(x):xx-xx https:\/\/doi.org\/10.1080\/20964471.2021.1974681<\/a><\/li>\n
  9. Thornton J.M., Palazzi E., Pepin N.C., Cristofanelli P., Essery R., Kotlarski S., Giuliani G., Guigoz Y., Kulonen A., Li X., Pritchard D., Fowler H.J., Randin C.F., Shahgedanova M., Steinbacher M., Zebisch M., Adler C. (2021) Towards a definition of Essential Mountain Climate Variables, OneEarth<\/strong> https:\/\/doi.org\/10.1016\/j.oneear.2021.05.005<\/a><\/li>\n
  10. Giuliani G., Cazeaux H. \u00a0Burgi P.-Y., Poussin C., Richard J.-P., Chatenoux B. (2021) SwissEnvEO: a FAIR national environmental data repository for Earth Observation Open Science,\u00a0CODATA Data Science Journal <\/strong>20(1):22 https:\/\/datascience.codata.org\/articles\/10.5334\/dsj-2021-022\/<\/a><\/li>\n
  11. Barras A.G., Braunisch V., Arlettaz R. (2021) Predictive models of distribution and abundance of a threatened mountain species show that impacts of climate change overrule those of land use change. Divers Distrib. \u00a0https:\/\/doi.org\/10.1111\/ddi.13247<\/a><\/li>\n
  12. Astsatryan H., Grigoryan H., Poghosyan A., Abrahamyan R., Asmaryan S., Muradyan V., Tepanosyan G., Guigoz Y., Giuliani G. (2021) Air temperature forecasting using artificial neural network for Ararat valley, Earth Science Informatics<\/strong> 14:711-722\u00a0https:\/\/link.springer.com\/article\/10.1007\/s12145-021-00583-9<\/a><\/li>\n
  13. Giuliani G., Egger E., Italiano J., Poussin C., Richard J.-P., Chatenoux B. (2020) Essential Variables for environmental monitoring: What are the possible contributions of Earth Observation Data Cubes, Data<\/strong> 5:100\u00a0https:\/\/www.mdpi.com\/2306-5729\/5\/4\/100<\/a><\/li>\n
  14. Giuliani G., Mazzetti P., Santoro M., Nativi S., Van Bemmelen J., Colangeli G., Lehmann A. (2020) Knowledge generation using satellite Earth Observations to support Sustainable Development Goals (SDG): a use case on Land Degradation, I<\/strong>nternational Journal of Applied Earth Observation and Geoinformation\u00a0<\/strong>88:10206 https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0303243419311869<\/a><\/li>\n
  15. Giuliani G., Chatenoux B., Benvenuti A., Lacroix P., Santoro M., Mazzetti P. (2020) Monitoring Land Degradation at national level using satellite Earth Observation time-series data to support SDG15 – Exploring the potential of Data Cube,\u00a0Big Earth Data\u00a0<\/strong>X(X):XX https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/20964471.2020.1711633<\/a><\/li>\n
  16. Giuliani G., Chatenoux B., Piller T., Moser F., Lacroix P.,\u00a0Data Cube on Demand (DCoD): Generating Earth Observation Data Cube anywhere (2020)\u00a0International Journal of Applied Earth Observation and Geoinformation <\/strong>87:102035 https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0303243419310372<\/a><\/li>\n
  17. Giuliani G., Camara G., Killough B., Minchin S. (2019) Earth Observation Open Science: Enhancing reproducible science using Data Cubes,\u00a0Data <\/strong>4(4):14 https:\/\/www.mdpi.com\/2306-5729\/4\/4\/147<\/a><\/li>\n
  18. Dhu T., Giuliani G.,\u00a0Juarez J., Kavadda A.,\u00a0Killough B., Merodio P., Minchin S., Ramage S. (2019) \u00a0National Open Data Cubes and Their Contribution to Country-Level Development Policies and Practices,\u00a0Data\u00a0<\/strong>4(4): 144 https:\/\/www.mdpi.com\/2306-5729\/4\/4\/144<\/a><\/li>\n
  19. Poussin C., Guigoz Y., Palazzi E., Terzago S., Chatenoux B., Giuliani G. (2019) Snow Cover Evolution in the Gran Paradiso National Park, Italian Alps, Using the Earth Observation Data Cube. Data<\/strong> 4(4):138 https:\/\/www.mdpi.com\/2306-5729\/4\/4\/138<\/a><\/li>\n
  20. Asmaryan S., Muradyan, V., Tepanosyan G., Hovsepyan A., Saghatelyan A., Astsatryan H., Grigoryan H., Abrahamyan R., Guigoz G., Giuliani G. (2019) Paving the way towards an Armenian Data Cube. Data<\/strong> 4(3):117 https:\/\/www.mdpi.com\/2306-5729\/4\/3\/117<\/a><\/li>\n
  21. Giuliani G., Maso J., Mazzetti P.,\u00a0Nativi S.,\u00a0Zabala A. (2019) \u00a0 Paving the way to increased interoperability of Earth Observations Data Cube.\u00a0Data 4(3):113 https:\/\/www.mdpi.com\/2306-5729\/4\/3\/113<\/a><\/li>\n
  22. Truckenbrodt J., Freemantle T., Williams C., Jones T., Small D., Dubois C., Thiel C., Rossi C., Syriou A., Giuliani G. (2019) Towards Sentinel-1 SAR Analysis Ready Data: A best practices assessment on preparing backscatter data for the cube. Data 4(3):93 https:\/\/www.mdpi.com\/2306-5729\/4\/3\/93<\/a><\/li>\n
  23. Salzano R., Salvatori R., Valt M., Giuliani G., Chatenoux B., Ioppi L. (2019) The contribution of terrestrial photography to the remote sensing of\u00a0snow cover, Geosciences 9(2):97\u00a0https:\/\/www.mdpi.com\/2076-3263\/9\/2\/97\/htm<\/a><\/li>\n
  24. Honeck E., Castello R., Chatenoux B., Richard J.-P., Lehmann A., Giuliani G. (2018)\u00a0From a Vegetation Index to a Sustainable Development Goal Indicator: Forest Trend Monitoring Using Three Decades of Earth Observations across Switzerland. International Journal of Geo-Information 7(12):455\u00a0https:\/\/www.mdpi.com\/2220-9964\/7\/12\/455<\/a><\/li>\n
  25. Frau L., Rizvi S., Chatenoux B., Richard J.-P., Giuliani G. (2018) Snow Observations from Space: An approach to map snow cover from three decades of Landsat imagery across Switzerland. In: IGARSS 2018 – IEEE International Geoscience and Remote Sensing Symposium. Valencia (Spain). p. 8672-8675\u00a0https:\/\/ieeexplore.ieee.org\/document\/8518394<\/a><\/li>\n
  26. Giuliani G., Chatenoux B., Honeck E., RichardJ.-P. (2018) Towards Sentinel 2 Analysis Ready Data: A Swiss Data Cube Perspective. In: IGARSS 2018 – IEEE International Geoscience and Remote Sensing Symposium. Valencia (Spain). p. 8668-8671\u00a0https:\/\/ieeexplore.ieee.org\/document\/8517954<\/a><\/li>\n
  27. Giuliani G., Chatenoux B., De Bono A., Rodila D., Richard J.-P., Allenbach K., Dao H., Peduzzi P. (2017) Building an Earth Observations Data Cube: lessons learned from the Swiss Data Cube (SDC) on generating Analysis Ready Data (ARD).\u00a0Big Earth Data\u00a01(1):1-18\u00a0http:\/\/www.tandfonline.com\/doi\/full\/10.1080\/20964471.2017.1398903<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Obuchowicz C., Poussin C., Giuliani G. (2023) Change in observed long-term greening across Switzerland \u2013 Evidence from a three decades NDVI time-series and its relationship with climate and land cover factors, Big Earth Data https:\/\/doi.org\/10.1080\/20964471.2023.2268322 Poussin C., Timoner P., Chatenoux B., Giuliani G., Peduzzi P. (2023) Improved Landsat-based snow cover mapping accuracy using a spatiotemporal … <\/p>\n

    Read more “Publications”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"pgc_meta":"","jetpack_post_was_ever_published":false,"footnotes":""},"class_list":["post-426","page","type-page","status-publish","hentry"],"pgc_meta":"","jetpack_shortlink":"https:\/\/wp.me\/P9mMCF-6S","jetpack-related-posts":[],"jetpack_sharing_enabled":true,"featured_media_urls":[],"_links":{"self":[{"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/pages\/426","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/comments?post=426"}],"version-history":[{"count":23,"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/pages\/426\/revisions"}],"predecessor-version":[{"id":5632,"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/pages\/426\/revisions\/5632"}],"wp:attachment":[{"href":"https:\/\/www.swissdatacube.org\/index.php\/wp-json\/wp\/v2\/media?parent=426"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}