01158nam0-22003371i-450-99000747327040332120041213102620.088-14-05181-X000747327FED01000747327(Aleph)000747327FED0100074732720030814d--------km-y0itay50------baita<<La >>distribuzione dei carburanti per autotrazione in Sardegnaricerche di geografia applicata all'assetto economico e viario della regioneGiuseppe Scanu, Gian Marco Ugolini. -MilanoGiuffrè1995217 p. + 1 c. ripieg.25 cmMonografi della Società Geografica ItalianaIn duplice copia.SARDEGNA - TRASPORTISARDEGNA - ECONOMIAScanu,Giuseppe<1950- >231843Ugolini,Gian MarcoITUNINARICAUNIMARCBK990007473270403321A-IT 0319I.G.1477ILFGEA-IT 0319BISI.G.s.i.ILFGEILFGEDistribuzione dei carburanti per autotrazione in Sardegna674622UNINA04708nam 2201081z- 450 991055742790332120210501(CKB)5400000000043445(oapen)https://directory.doabooks.org/handle/20.500.12854/68491(oapen)doab68491(EXLCZ)99540000000004344520202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAssessment of Renewable Energy Resources with Remote SensingBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (244 p.)3-0365-0480-X 3-0365-0481-8 The book "Assessment of Renewable Energy Resources with Remote Sensing" focuses on disseminating scientific knowledge and technological developments for the assessment and forecasting of renewable energy resources using remote sensing techniques. The eleven papers inside the book provide an overview of remote sensing applications on hydro, solar, wind and geothermal energy resources and their major goal is to provide state of art knowledge to contribute with the renewable energy resource deployment, especially in regions where energy demand is rapidly expanding. Renewable energy resources have an intrinsic relationship with local environmental features and the regional climate. Even small and fast environment and/or climate changes can cause significant variability in power generation at different time and space scales. Methodologies based on remote sensing are the primary source of information for the development of numerical models that aim to support the planning and operation of an electric system with a substantial contribution of intermittent energy sources. In addition, reliable data and knowledge on renewable energy resource assessment are fundamental to ensure sustainable expansion considering environmental, financial and energetic security.Research & information: generalbicsscartificial neural networksBaltic areaclimatecloudcloud coveragecloud detectioncoastal wind measurementscoastlinecomputational design methodconvectionCSP plantsdata processingdigitized image processingelectrical resistivity tomographyextreme value analysisfeature engineeringfeature importanceforecastinggeophysical prospectinggeothermal energyGES-CAL softwareglobal radiationgraphical user interface softwareHazaki Oceanographical Research Stationhydropower reservoirimage processinglake breeze influencelight gradient boosting machinemachine learningmachine learning techniquesmetaheuristicmultistep-ahead predictionparameter extractionpassive design strategyphotovoltaic power plantplan position indicatorpoint cloud datapotential well field locationremote sensingremote sensing data acquisitionrenewable energy resource assessment and forecastingsatellitescanning LiDARscatterometershading envelopessky camerasmart islandsolar energysolar energy resourcesolar irradiance enhancementsolar irradiance estimationsolar irradiance forecastingsolar photovoltaicsolar radiation forecastingstatistical analysissurface solar radiationtime domain electromagnetic methodtotal sky imageryvelocity volume processingvoxel-design approachwhale optimization algorithmwind speedResearch & information: generalMartins Fernando Ramosedt1297532Martins Fernando RamosothBOOK9910557427903321Assessment of Renewable Energy Resources with Remote Sensing3024506UNINA03982nam 22006975 450 991025410430332120251106222634.03-662-47946-X10.1007/978-3-662-47946-9(CKB)3710000000486737(EBL)4178917(SSID)ssj0001584493(PQKBManifestationID)16265111(PQKBTitleCode)TC0001584493(PQKBWorkID)14865680(PQKB)11646506(DE-He213)978-3-662-47946-9(MiAaPQ)EBC4178917(PPN)190524502(EXLCZ)99371000000048673720151005d2016 u| 0engur|n|---|||||txtccrPetrolipalynology /by Dexin Jiang, Eleanora I. Robbins, Yongdong Wang, Huiqiu Yang1st ed. 2016.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2016.1 online resource (275 p.)Springer Geology,2197-9545Description based upon print version of record.3-662-47945-1 Includes bibliographical references at the end of each chapters.Introduction -- Geological Background -- Fossil Spores and Pollen in Crude Oils -- Petroleum Sporo-pollen Assemblages and Judgment of Petroleum Source Rocks -- Spore/Pollen Fossil Coloration and Petroleum Source Rock Quality -- Palynological Evidence for Organic Petroleum Origin Theory -- Environment for Formation of Petroleum Source Rocks -- Mechanisms of Petroleum Migration -- Geochronic and Geographic distribution of Nonmarine Petroleum Source Rocks.                        .This book addresses the principles and methods for determining petroleum source rocks based on fossil spores and pollen. Studying petroliferous basins in China, we discovered that there are often as many as three different sources of the microfossils: the source rocks, the rocks along the pathway, and the reservoir rocks. Therefore, fossil spores, pollen and algae from inland and coastal shelf petroliferous basins are analyzed and illustrated to show this complex process. Furthermore, the organic origin theory of oil is proven and environmental characteristics for hydrocarbon source-rock formation are discussed. Along with the geochronical and geographic distribution of non-marine petroleum source rocks in China, the mechanisms of petroleum migration following the pathways to the reservoirs are investigated. It will be a valuable reference work as well as a textbook for a wider research areas ranging from stratigraphy, palynology, palaeontology and petroleum geology.Springer Geology,2197-9545PaleontologyGeology, EconomicFossil fuelsPaleontologyhttps://scigraph.springernature.com/ontologies/product-market-codes/G39000Economic Geologyhttps://scigraph.springernature.com/ontologies/product-market-codes/G17010Fossil Fuels (incl. Carbon Capture)https://scigraph.springernature.com/ontologies/product-market-codes/114000Paleontology.Geology, Economic.Fossil fuels.Paleontology.Economic Geology.Fossil Fuels (incl. Carbon Capture).561.13Jiang Dexinauthttp://id.loc.gov/vocabulary/relators/aut1059015Robbins Eleanora I(Eleanora Iberall),1942-authttp://id.loc.gov/vocabulary/relators/autWang Yongdongauthttp://id.loc.gov/vocabulary/relators/autYang Huiqiuauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910254104303321Petrolipalynology2503711UNINA