Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–˛ Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-3181 Book chapters 2016 Dalezios N., Spyropoulos N., Eslamian S The remote sensing in drought quantification and assessment. AI & Machine Learning Irrigation Systems No abstract available 633945
publications-3182 Conference proceedings 2016 Psomiadis E., Dercas N., Dalezios N. and Spyropoulos N. The role of spatial and spectral resolution on the effectiveness of satellite-based vegetation indices SPIE Remote Sensing International Congress, Conference of Remote Sensing for Agriculture, Ecosystems, and Hydrology (RS101), Edinburgh AI & Machine Learning Knowledge Graphs No abstract available 633945
publications-3183 Conference proceedings 2016 A.Cseko, I.Fernandez,E.Hartai KINDRA Project- End user requirements Groundwater and Society. 43rd International Congress of International Association of Geologists, Montpellier (France) AI & Machine Learning Knowledge Graphs No abstract available 642047
publications-3184 Conference proceedings 2016 M.Petitta, B. Bodo, M.Caschetto, C. Colombani, V. Correia, A. Cseko,M. Di Cairano, I. Fernandez, C.GarcĂ­a Alibrand, E. Hartai, K. Hinsby, T. Madarasz, V.Mikita, M.Garcia Padilla, P.Szucs, P.van der Keur KINDRA Project: classification and inventory of groundwater research and knowledge in Europe 35th International Geological Congress. Cape Town AI & Machine Learning Uncategorized No abstract available 642047
publications-3185 Conference proceedings 2016 Mikita Viktória Hidrogeológiai kutatások új szemléletű rendszerzése Természeti erőforrásaink az észak-magyarországi térségben : a Magyarhoni Földtani Társulat Földtudományi Vándorgyűlése és Kiállítása, Sárospatak, 2016 Data Management & Analytics Uncategorized No abstract available 642047
publications-3186 Conference proceedings 2016 M.Petitta, P.Van Der Keur, K.Hinsby, I.Fernandez KINDRA Project- relevance for implementation of EU Water Directives Groundwater and Society. 43rd International Congress of International Association of Geologists, Montpellier (France) VR & AR Uncategorized No abstract available 642047
publications-3187 Conference proceedings 2016 Marco Petitta, Balazs Bodo, Maria Chiara Caschetto, Victor Correia, Adrienn Cseko, Maria Di Cairano, Isabel Fernandez, Eva Hartai, Klaus Hinsby, Clint Marcelo García Alibrand, Tamás Madarász, Victoria Mikita, Mercedes Garcia Padilla, Peter Szucs, Peter Van Der Keur The KINDRA project: a knowledge inventory for hydrogeology research Rendiconti on-line della Società Geologica Italiana 10.3301/ROL.2016.63 Data Management & Analytics Uncategorized No abstract available 642047
publications-3188 Conference proceedings 2017 M.Petitta, A.Cseko, I.Fernandez, C.GarcĂ­a Alibrandi, E.Hartai, K.Hinsby, V. Mikita, M. Garcia Padilla, P.Szucs, P.Van Der Keur Making groundwater visible: a contribution for classifying hydrogeological research and knowledge by KINDRA H2020 project Flowpath 2017, National Congress of Italian Chapter of IAH, Cagliari (Italy) 10.13125/flowpath2017/2832 AI & Machine Learning Uncategorized No abstract available 642047
publications-3189 Conference proceedings 2015 M.Petitta, B.Bodo, M.Caschetto, V.Correia, A.Cseko, I.Fernandez, E.Hartai, K.Hinsby, T. Madarasz, M.Garcia Padilla, P.Szucs The KINDRA H2020 Project: a knowledge inventory for hydrogeology research Geophysical Research Abstracts Data Management & Analytics Irrigation Systems No abstract available 642047
publications-3190 Non-peer reviewed articles 2017 Evelyn Uuemaa Põllumajandus ohustab Uus-Meremaa loodust/Agriculture is damaging New Zealand's nature Eesti Loodus AI & Machine Learning Knowledge Graphs No abstract available 660391