00905nam0-2200313---450-99000970833040332120130404100849.0000970833FED01000970833(Aleph)000970833FED0100097083320130404d1968----km-y0itay50------baengNL--------001yyStatistical methods in the social sciencesD.D.Bugg, M.A.Henderson, K.Holden, P.J.LundAmsterdamNorth-Holland1968xi, 315 p.22 cmBuggD.D.519589HendersonM.A.519590HoldenK.121860LundP.J.519591ITUNINARICAUNIMARCBK990009708330403321ISVE C1/133029DECTSDECTSStatistical methods in the social sciences844181UNINA01626nam 2200361 450 991047679830332120230512015747.0(CKB)5470000000566563(NjHacI)995470000000566563(EXLCZ)99547000000056656320230512d2003 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierClassical Economics and Modern Theory /Heinz D. Kurz, Neri Salvadori[Place of publication not identified] :Taylor & Francis,2003.1 online resource1-134-20222-9 1. Classical Theory and its Interpretations -- 2. Growth Theory and the Classical Tradition -- 3. Criticism of Neoclassical Theory.In this thought-provoking book, well known economists Kurz and Salvadori cover original findings and new vistas on old problems. They cover: alternative interpretations of classical economists new growth theory the relationship between Sraffian theory and Von Neumann the treatment of capital in neoclassical long-period theory. Incorporating cutting-edge research and new work, this book will be of great interest to those working in the field of the history of economic thought.Economic historyEconomic history.330.9Kurz Heinz D.122063Salvadori NeriNjHacINjHaclBOOK9910476798303321Classical Economics and Modern Theory3363069UNINA05875nam 2201537z- 450 991057687350332120220621(CKB)5720000000008440(oapen)https://directory.doabooks.org/handle/20.500.12854/84553(oapen)doab84553(EXLCZ)99572000000000844020202206d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierLand Degradation Assessment with Earth ObservationBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (368 p.)3-0365-4227-2 3-0365-4228-0 This Special Issue (SI) on "Land Degradation Assessment with Earth Observation" comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps-some of which have been identified in this SI-and produce highly accurate and relevant land-degradation assessment and monitoring tools.Research & information: generalbicsscAmu Darya delta (ADD)archetypesarid and semi-arid areasaridity indexAVHRRbfastBFASTBotswanabreakpoint analysisbreakpoints and timeseries analysisbrowningcentral Asiadeveloping countriesdriversdroughtdrought adaptationdrought impactsdrought indexdrought vulnerabilityEarth observationEast Africaecosystem structural changeGaofen satelliteGEEgeographically weighted regression (GWR)Google Earth Enginegreenhouse gas emissionsgreeninggully mappinghigh temporal resolutionirrigated systemsKenyaKobresia pygmaea communityKyrgyzstanland coverland degradationland degradation neutralityland productivityland surface phenologyland useland use-land coverLandsatLandsat time series analysismachine learningMann-KendallMann-Kendallmining developmentMODISmonitoring and reportingn/aNDVINiger River basinNigeriaNormalised Difference Vegetation Index (NDVI)pasturesprecipitationrandom forestREDD+reference levelsremote sensingremote sensing indexRWEQsalinity indexsalinizationsalinized land degradation index (SDI)satellite imagerysatellite-based aridity indexsavannahSDGself-organizing mapssemi-arid areassemi-arid environmentSen's slopeSentinel-1Sentinel-2Sentinel-2 imagesshrub encroachmentslangbosSoil Adjusted Vegetation Index (SAVI)soil organic carbonSouth Africaspatial distributionspatial heterogeneityspatial-temporal variationstandardized precipitation evapotranspiration indexsupport vector machinessustainable land management programmesSynthetic Aperture Radar (SAR)TI-NDVItime seriestrend analysisUgandaunmanned aerial vehicleVegetation Condition Index (VCI)vegetation indexvegetation resiliencevegetation trendsvegetation-precipitation relationshipwind erosion modelingXishuangbannaResearch & information: generalSymeonakis Eliasedt1291007Symeonakis EliasothBOOK9910576873503321Land Degradation Assessment with Earth Observation3021746UNINA