LEADER 01088nam0-22003011i-450 001 990004928840403321 005 20230522091952.0 035 $a000492884 035 $aFED01000492884 035 $a(Aleph)000492884FED01 100 $a19990604f1969----km-y0itay50------ba 101 0 $aspa 102 $aES 105 $af-------101yy 200 1 $aActas e los consejos y comisión federal de la región española$e(1870-1874)$fAsociacion Internacional de los Trabajadores$gtranscripción y estudio preliminar por Carlos Seco Serrano 210 $aBarcelon$cUniversidad de Barcelona$d1969 215 $av., tav.$d24 cm 327 0 $a1.: Consejos I-II-III$a2.: Comisión federal 702 1$aSeco Serrano,$bCarlos 710 02$aAsociacion internacional de los trabajadores$0423749 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004928840403321 952 $aPA 98 (1)$bFil. Mod. 17639$fFLFBC 952 $aPA 98 (2)$bFil. Mod. 17639$fFLBC 959 $aFLFBC 996 $aActas e los consejos y comisión federal de la región española$9523289 997 $aUNINA LEADER 01456aam 2200421I 450 001 9910710761503321 005 20160421112347.0 024 8 $aGOVPUB-C13-782ad858ca11bdf715abb83a4e55fcf2 035 $a(CKB)5470000002478691 035 $a(OCoLC)947049384 035 $a(EXLCZ)995470000002478691 100 $a20160421d2008 ua 0 101 0 $aeng 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aMINEX II $eperformance of fingerprint match-on-card algorithms phase II report /$fP. Grother; W. Salamon; C. Watson; M. Indovina; P. Flanagan 210 1$aGaithersburg, MD :$cU.S. Dept. of Commerce, National Institute of Standards and Technology,$d2008. 215 $a1 online resource 225 1 $aNISTIR ;$v7477 300 $a2008. 300 $aContributed record: Metadata reviewed, not verified. Some fields updated by batch processes. 300 $aTitle from PDF title page. 320 $aIncludes bibliographical references. 517 $aMINEX II 700 $aGrother$b Patrick J$01385097 701 $aFlanagan$b P$01393545 701 $aGrother$b Patrick J$01385097 701 $aIndovina$b M$g(Michael D.)$01388768 701 $aSalamon$b W$01393546 712 02$aNational Institute of Standards and Technology (U.S.) 801 0$bNBS 801 1$bNBS 801 2$bGPO 906 $aBOOK 912 $a9910710761503321 996 $aMINEX II$93449781 997 $aUNINA LEADER 05875nam 2201537z- 450 001 9910576873503321 005 20220621 035 $a(CKB)5720000000008440 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/84553 035 $a(oapen)doab84553 035 $a(EXLCZ)995720000000008440 100 $a20202206d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aLand Degradation Assessment with Earth Observation 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (368 p.) 311 08$a3-0365-4227-2 311 08$a3-0365-4228-0 330 $aThis 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. 606 $aResearch & information: general$2bicssc 610 $aAmu Darya delta (ADD) 610 $aarchetypes 610 $aarid and semi-arid areas 610 $aaridity index 610 $aAVHRR 610 $abfast 610 $aBFAST 610 $aBotswana 610 $abreakpoint analysis 610 $abreakpoints and timeseries analysis 610 $abrowning 610 $acentral Asia 610 $adeveloping countries 610 $adrivers 610 $adrought 610 $adrought adaptation 610 $adrought impacts 610 $adrought index 610 $adrought vulnerability 610 $aEarth observation 610 $aEast Africa 610 $aecosystem structural change 610 $aGaofen satellite 610 $aGEE 610 $ageographically weighted regression (GWR) 610 $aGoogle Earth Engine 610 $agreenhouse gas emissions 610 $agreening 610 $agully mapping 610 $ahigh temporal resolution 610 $airrigated systems 610 $aKenya 610 $aKobresia pygmaea community 610 $aKyrgyzstan 610 $aland cover 610 $aland degradation 610 $aland degradation neutrality 610 $aland productivity 610 $aland surface phenology 610 $aland use 610 $aland use-land cover 610 $aLandsat 610 $aLandsat time series analysis 610 $amachine learning 610 $aMann-Kendall 610 $aMann-Kendall 610 $amining development 610 $aMODIS 610 $amonitoring and reporting 610 $an/a 610 $aNDVI 610 $aNiger River basin 610 $aNigeria 610 $aNormalised Difference Vegetation Index (NDVI) 610 $apastures 610 $aprecipitation 610 $arandom forest 610 $aREDD+ 610 $areference levels 610 $aremote sensing 610 $aremote sensing index 610 $aRWEQ 610 $asalinity index 610 $asalinization 610 $asalinized land degradation index (SDI) 610 $asatellite imagery 610 $asatellite-based aridity index 610 $asavannah 610 $aSDG 610 $aself-organizing maps 610 $asemi-arid areas 610 $asemi-arid environment 610 $aSen's slope 610 $aSentinel-1 610 $aSentinel-2 610 $aSentinel-2 images 610 $ashrub encroachment 610 $aslangbos 610 $aSoil Adjusted Vegetation Index (SAVI) 610 $asoil organic carbon 610 $aSouth Africa 610 $aspatial distribution 610 $aspatial heterogeneity 610 $aspatial-temporal variation 610 $astandardized precipitation evapotranspiration index 610 $asupport vector machines 610 $asustainable land management programmes 610 $aSynthetic Aperture Radar (SAR) 610 $aTI-NDVI 610 $atime series 610 $atrend analysis 610 $aUganda 610 $aunmanned aerial vehicle 610 $aVegetation Condition Index (VCI) 610 $avegetation index 610 $avegetation resilience 610 $avegetation trends 610 $avegetation-precipitation relationship 610 $awind erosion modeling 610 $aXishuangbanna 615 7$aResearch & information: general 700 $aSymeonakis$b Elias$4edt$01291007 702 $aSymeonakis$b Elias$4oth 906 $aBOOK 912 $a9910576873503321 996 $aLand Degradation Assessment with Earth Observation$93021746 997 $aUNINA