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[null,"1.","Record Nr.",null,"UNINA9910452956603321"]
[null,null,"Autore",null,"Delsing Lars-Olof <1959->"]
[null,null,"Titolo",null,"Håller språket ihop Norden? [[electronic resource] ] : en forskningsrapport om ungdomars förståelse av danska, svenska och norska / / Lars-Olof Delsing & Katarina Lundin Åkersson"]
[null,null,"Pubbl/distr/stampa",null,"Köpenhamn, : Nordiska ministerrådet, 2005"]
[null,null,"Descrizione fisica",null,"1 online resource (212 p.)"]
[null,null,"Collana",null,"TemaNord (København), , 0908-6692 ; ; 2005:573"]
[null,null,"Disciplina",null,"401.9"]
[null,null,"Soggetti",null,"Språkkontakter - Sverige - Danmark - Norge"]
[{"$nulls":4},"Språkförståelse - Sverige - Danmark - Norge"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Swedish"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,"Nota di contenuto",null,"\"\"7.8 Avslutande kommentar\"\""]
[null,"2.","Record Nr.",null,"UNINA9910765758803321"]
[null,null,"Autore",null,"Kumar Lalit"]
[null,null,"Titolo",null,"Google Earth Engine Applications / / Lalit Kumar, Onisimo Mutanga"]
[null,null,"Pubbl/distr/stampa",null,"Basel, Switzerland : , : MDPI, , 2019"]
[null,null,"ISBN",null,"9783038978855"]
[{"$nulls":4},"303897885X"]
[null,null,"Descrizione fisica",null,"1 online resource (420 pages)"]
[null,null,"Disciplina",null,"910.285"]
[null,null,"Soggetti",null,"Google Earth"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"About the Special Issue Editors . ix -- Onisimo Mutanga and Lalit Kumar Google Earth Engine Applications Reprinted from: Remote Sens. 2019, 11, 591, doi:10.3390/rs11050591 . 1 -- Lalit Kumar and Onisimo Mutanga Google Earth Engine Applications Since Inception: Usage, Trends, and Potential Reprinted from: Remote Sens. 2018, 10, 1509, doi:10.3390/rs10101509 . 5 -- Manuel Campos-Taberner,Alvaro ´ Moreno-Mart´ınez, Francisco Javier Garc´ıa-Haro, Gustau Camps-Valls, Nathaniel P. Robinson, Jens Kattge, and Steven W. Running Global Estimation of Biophysical Variables from Google Earth Engine Platform Reprinted from: Remote Sens. 2018, 10, 1167, doi:10.3390/rs10081167 . 20 -- Ate Poortinga, Nicholas Clinton, David Saah1, Peter Cutter, Farrukh Chishtie, Kel N.Markert, Eric R. Anderson, Austin Troy, Mark Fenn, Lan Huong Tran, Brian Bean,Quyen Nguyen, Biplov Bhandari, Gary Johnson and Peeranan Towashiraporn An Operational Before-After-Control-Impact (BACI) Designed Platform for Vegetation Monitoring at Planetary Scale Reprinted from: Remote Sens. 2018, 10, 760, doi:10.3390/rs10050760 . 37 -- Yu Hsin Tsai, Douglas Stow, Hsiang Ling Chen, Rebecca Lewison, Li An and Lei Shi Mapping Vegetation and Land Use Types in Fanjingshan National Nature Reserve Using Google Earth Engine Reprinted from: Remote Sens. 2018, 10, 927, doi:10.3390/rs10060927 . 50 -- Nathaniel P. Robinson, Brady W. Allred, Matthew O. Jones, Alvaro Moreno, John S. Kimball, David E. Naugle, Tyler A. Erickson and Andrew D. Richardson A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States Reprinted from: Remote Sens. 2017, 9, 863, doi:10.3390/rs9080863 . 64 -- Ran Goldblatt, Alexis Rivera "]
[{"$nulls":4},"Ballesteros and Jennifer Burney High Spatial Resolution Visual Band Imagery Outperforms Medium Resolution Spectral Imagery for Ecosystem Assessment in the Semi-Arid Brazilian Sertao˜ Reprinted from: Remote Sens. 2017, 9, 1336, doi:10.3390/rs9121336  78 -- Leandro Parente and Laerte Ferreira Assessing the Spatial and Occupation Dynamics of the Brazilian Pasturelands Based on the Automated Classification of MODIS Images from 2000 to 2016 Reprinted from: Remote Sens. 2018, 10, 606, doi:10.3390/rs10040606 . 104 -- Dimosthenis Traganos, Bharat Aggarwal, Dimitris Poursanidis, Konstantinos Topouzelis, Nektarios Chrysoulakis and Peter Reinartz Towards Global-Scale Seagrass Mapping and Monitoring Using Sentinel-2 on Google Earth Engine: The Case Study of the Aegean and Ionian Seas Reprinted from: Remote Sens. 2018, 10, 1227, doi:10.3390/rs10081227 . 118 -- Jacky Lee, Jeffrey A. Cardille and Michael T. Coe BULC-U: Sharpening Resolution and Improving Accuracy of Land-Use/Land-Cover Classifications in Google Earth Engine Reprinted from: Remote Sens. 2018, 10, 1455, doi:10.3390/rs10091455 . 132 -- Roberta Ravanelli, Andrea Nascetti, Raffaella Valeria Cirigliano, Clarissa Di Rico, Giovanni Leuzzi, Paolo Monti and Mattia Crespi Monitoring the Impact of Land Cover Change on Surface Urban Heat Island through Google Earth Engine: Proposal of a Global Methodology, First Applications and Problems Reprinted from: Remote Sens. 2018, 10, 1488, doi:10.3390/rs10091488 . 153 -- Mingzhu He, John S. Kimball, Marco P. Maneta, Bruce D. Maxwell, Alvaro Moreno, Santiago Beguer´ıa and Xiaocui Wu Regional Crop Gross Primary Productivity and Yield Estimation Using Fused Landsat-MODIS Data Reprinted from: Remote Sens. 2018, 10, 372, doi:10.3390/rs10030372 . 174 -- Masoud Mahdianpari, Bahram Salehi, Fariba Mohammadimanesh, Saeid Homayouni and Eric Gill The First Wetland Inventory Map of Newfoundland at a Spatial Resolution of 10 m Using Sentinel-1 and Sentinel-2 Data on the Google Earth Engine Cloud Computing Platform Reprinted from: Remote Sens. 2019, 11, 43, doi:10.3390/rs11010043  195 -- Rosa Aguilar, Raul Zurita-Milla, Emma Izquierdo-Verdiguier and Rolf A. de By A Cloud-Based Multi-Temporal Ensemble Classifier to Map Smallholder Farming Systems Reprinted from: Remote Sens. 2018, 10, 729, doi:10.3390/rs10050729 . 222 -- Jun Xiong, Prasad S. Thenkabail, James C. Tilton, Murali K. Gumma, Pardhasaradhi Teluguntla, Adam Oliphant, Russell G. Congalton, Kamini Yadav and Noel Gorelick Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine Reprinted from: Remote Sens. 2016, .9, 1065, doi:10.3390/rs9101065  240 -- Eric A. Sproles, Ryan L. Crumley, Anne W. Nolin, Eugene Mar and Juan Ignacio Lopez Moreno SnowCloudHydro-A New Framework for Forecasting Streamflow in Snowy, Data-Scarce Regions Reprinted from: Remote Sens. 2018, 10, 1276, doi:10.3390/rs10081276 . 267 -- Cheng-Chien Liu, Ming-Chang Shieh, Ming-Syun Ke and Kung-Hwa Wang Flood Prevention and Emergency Response System Powered by Google Earth Engine Reprinted from: Remote Sens. 2018, 10, 1283, doi:10.3390/rs10081283 . 282 -- Nazmus Sazib, Iliana Mladenova and John Bolten Leveraging the Google Earth Engine for Drought Assessment Using Global Soil Moisture Data Reprinted from: Remote Sens. 2018, 10, 1265, doi:10.3390/rs10081265 . 302 -- Gonzalo Mateo-Garc´ıa, Luis Gomez-Chova, ´ Julia Amoros-L ´ opez, ´ Jordi Munoz-Mar´ı, ˜ Gustau Camps-Valls Multitemporal Cloud Masking in the Google Earth Engine Reprinted from: Remote Sens. 2018, 10, 1079, doi:10.3390/rs10071079 . 325 -- Kel N. Markert, Calla M. Schmidt, Robert E. Griffin, Africa I. Flores, Ate Poortinga, David S. Saah, Rebekke E. "]
[{"$nulls":4},"Muench, Nicholas E. Clinton, Farrukh Chishtie, Kritsana Kityuttachai, Paradis Someth, Eric R. Anderson, Aekkapol Aekakkararungroj and David J. Ganz Historical and Operational Monitoring of Surface Sediments in the Lower Mekong Basin Using Landsat and Google Earth Engine Cloud Computing Reprinted from: Remote Sens. 2018, 10, 909, doi:10.3390/rs10060909 . 343 -- Felipe de Lucia Lobo, Pedro Walfir M. Souza-Filho, Evlyn M´arcia Le ˜ao de Moraes Novo, Felipe Menino Carlos and Claudio Clemente Faria Barbosa Mapping Mining Areas in the Brazilian Amazon Using MSI/Sentinel-2 Imagery (2017) Reprinted from: Remote Sens. 2018, 10, 1178, doi:10.3390/rs10081178 . 362 -- Dimosthenis Traganos, Dimitris Poursanidis, Bharat Aggarwal, Nektarios Chrysoulakis and Peter Reinartz Estimating Satellite-Derived Bathymetry (SDB) with the Google Earth Engine and Sentinel-2 Reprinted from: Remote Sens. 2018, 10, 859, doi:10.3390/rs10060859 . 376 -- Sean A. Parks, Lisa M. Holsinger, Morgan A. Voss, Rachel A. Loehman and Nathaniel P. Robinson Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential Reprinted from: Remote Sens. 2018, 10, 879, doi:10.3390/rs10060879 . 394."]
[null,null,null,"Sommario/riassunto","In a rapidly changing world, there is an ever-increasing need to monitor the Earth's resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth's surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales."]