简介：Theproductionofwood-basedpanelwaspresentedfirstlyinthispaper.SomefeaturesofChina’swood-basedpanelindustrywerereviewed,includingproductionbases,rawmaterialsandmainmarketsofwood-basedpanel.Inaddition,thetradeflowofwood-basedpanelwasdescribedintheend.

简介：Light-weightcompositepanelsweremanufacturedusingkenafcoreparticlesascorematerialandkenafbastfiber-wovensheetsastopandbottomsurfaces.Methylenediphenyldiisocyanate(MDI)resinwasusedastheadhesivewiththeresincontentof4%forcoreparticlesand50g/m2forbastfiber-wovensheets.Thetargetboarddensitiesweresetat0.35,0.45and0.55g/cm3.ThecompositepanelswereevaluatedwithJapaneseIndustrialStandardforParticleboards(JISA5908-2003).Theresultsshowthatthecompositepanelhashighmodulusofruptureandinternalbondingstrength.Thepropertiesof0.45g/cm3densitycompositepanelare:MOR20.4MPa,MOE1.94MPa,IB0.36MPa,WA142%,TS21%.Kenafisagoodrawmaterialformakinglight-weightcompositepanels.

简介：Inthispaper,thephysicalandmechanicalpropertiesoflaminatedbamboolamberwerestudiedbytestingmoisturecontent,delaminationratio,horizontalshearstrength,MOEandMORofthestructure-usematerial,inthesametime,thesesubjectsoffinger-jointweretestedtoo.Theresultsshowedthat,thehorizontalshearstrength,MOR,MOEoflaminatedbambooweresuperiortotheordinarystructure-usetimberinarchitecture,suchasPinus.Theperformanceofagingtestwasnotextraordinary,althoughthephysicalandmechanicalpropertiesoflaminatedbamboolamberdecreasedafteragingtest,thesepropertieswerebeyondPinusyet.

简介：Themanufacturetechnologiesoftwokindsofbamboolaminatedpanelandtheirphysical-mechanicalpropertieshavebeenstudiedinthepaper.ThespeciesofbambooaretheD.yunnanicusHsuehetD.Z.LiinYunnanProvinceandP.heterocyclavar.pubescensOhwiinZhejiangProvince.Thedataareofferedinordertoprovideprooftoproducearchitecturalpanelbybamboomaterials.Theresultsshowasfollows:Laminatedbamboopanelcanbeproducedbythereconstructiontechnology,andthemechanicalprope...

简介：ThefeasibilityofERSSARTandemdataformappingforestandnon-forestcoverinChinawasevaluatedoverZengchengCountyintheSouthChina.Anaccuracyof75%hasbeenachieved.Then,theMACFERST(MappingChinaForestwithERSSARTandemdata)projectstartedbytheMinistryofScienceandTechnology(MOST)ofChinaandtheEuropeanSpaceAgency(ESA)in1999.Thegenerationofalarge-scaleforestmaprequiressolvingproblemssuchasthegeoreferencingandmosaickingofverylongimagestripscov...

简介：ThepurposeofthispaperistostudytheRSdatawebservicesandrelatedsubjectsofdatastorageanddatamanagement.Basedonananalysisofthepresentsituationanddevelopmenttrendofstorageandmanagementofrasterdataandwebservicetechnology,amanagementandservicesystemarchitectureforRemoteSensingrasterdatabasedonwebservicetechnologieswasdeveloped,theimplementationmethodologiesofthekeytechnologyofthesystemwereexploredandaprototypeofthesystemwasillustrated.

简介：Basedonsixthandseventhnationalforestryinventorydataofthesixprovinces,includingGuangdong,Jiangxi,Guizhou,Shaanxi,JilinandBeijing,thethreemethods(IPCC,continuousfunctionforbiomassexpansionfactorandweightedbiomassregressionmodel)wereselectedtoestimatewoodbiomassinthispaper.Theestimationofthethreemethodswerecomparedandanalyzedfromcalculatingprocess,methodcharacters,repeatabilityandverifiabilitytostabilityofgrowthrateofbiomassbetweentwoperiods.TheresultsshowedthetotalbiomassestimatedbyIPCCmethodwithvariableBEF2waslarge,thetotalbiomassestimatedbyIPCCmethodwithconstantBEF2wassmallandthetotalbiomassesestimatedbycontinuousfunctionforbiomassexpansionfactorandweightedbiomassregressionmodelweremiddle.Thebiomassexpansionfactorderivedfromweightedregressionmodelwasmoststableinthedifferentprovinces.Basedontheseventhnationalforestryinventorydata,thebiomassexpansionfactorsofvariouskindsoftreespeciesderivedfromIPCCandtheweightedregressionmodelweremorestablethanthebiomassexpansionfactorsderivedfromcontinuousfunctionmethod.Thegrowthrateofbiomassbetweentwoperiodswasthesameregularpatternasthebiomassexpansionfactors.

简介：Climateisadominantenvironmentalfactorinbuildingecosystemstructureanddrivingbioticdynamicswithtopographicdependenceonspatialdistribution.Thispaperdemonstratestheapplicationofinterpolationtechniquetodescribespatialclimatedistribution.Adigitalelevationmodel(DEM)inresolutionof0.01degreeoflatitudeandlongitudehasbeendevelopedbecausetheincorporationofspatialdependenceontopographyiscrucialtoaccuracyofinterpolation.Climatedatafromsparseanddiscr...

简介：目前，关于防风林的保护的效果的大多数研究根据森林带和网络的二规模。与关于全球环境变化的进一步的研究，然而，更多的注意对防风林的地区性的气候效果被给予。在现在的学习，我们由使用陆地表面温度(LST)在地区性的规模分析了防风林的温度效果从在在到在2008的10月的从三月的中国的吉林省的Yushu，Nongan，Dehui，和Fuyu的中等决定成像分光辐射函数(MODIS)的数据。结果证明防风林能作为与没有防风林地区相比增加保护的农田的土壤温度，与0.57的增长吗？

简介：Forestgrowthismainlycurrentlymonitoredusingin-situmeasurementsinnortheastofChina.Toeffectivelymonitorforestgrowthdisturbanceatlargescale,weattemptedtouseremotesensingtechnique,particularly,timeseriesMODISdatafrom2004to2006.Theannualtimeseriesof8-dayenhancedvegetationindex(EVI)datasetwasgeneratedandsmoothedusingaSavitzky-Golayfilter.TheEVItrajectoryduringgrowthseasonwassimulatedusingalogisticmodel.Fromthesimulatedtrajectory,theEVIareaofgrowthseasonandannualEVIentropywerecalculated.Thesetwofactorswerecombinedtomapthedisturbanceregionsofforestgrowth.Finally,thedisturbanceregionswereverifiedusingasetofrandomsamples.Theresultindicatesthatthedisturbancepointshavedistinctivelyhigherentropyandlowerpeak.SomeofthesepointsalsoshowabruptEVIdeclineduringthemidseasonofthepeakphasesordoublepeaks.Thisapproachisdemonstratedtobefeasiblefordisturbancemonitoringofforestgrowth.

简介：农业庄稼的大规模耕作为领域害虫管理要求疾病的即时察觉。Hyperspectral遥感数据通常高光谱分辨率，它能为在叶和华盖在绿植被检测疾病应力很有用铺平。在这研究，在实验室和领域的大米的hyperspectral反射被测量描绘光谱区域和wavebands，它对棕色的点由Bipolarisoryzae感染了的大米最敏感(HelminthosporiumoryzaeBreda。deHann)。叶反射与感染的叶表面的增加的百分比在450～500nm和630～680nm的范围增加了，并且在520～580nm的范围减少了，760～790nm，1550～1750nm，并且有感染的叶表面的增加的百分比的2080～2350nm分别地。敏感分析和衍生物技术被用来为棕色的点由B感染了的米饭的察觉选择敏感wavebands。oryzae。米饭叶反射的比率作为棕色的点的指示物被评估。R669/R746(在669nm的反射在746nm由反射划分了，下列比率可以被类比推出)，R702/R718，R692/R530，R692/R732，R535/R746，R521/R718，并且R569/R718作为棕色的点不管它是否在叶或华盖水平有增加了的米饭的发生显著地增加了。R702/R718，R692/R530，R692/R732是为估计米饭褐的疾病严厉的三比率在叶和华盖层次看到的最好。这结果不仅在在真实世界上为精确害虫管理描绘庄稼疾病证实hyperspectral遥感数据的能力，而且证明庄稼反射的比率是一个有用方法估计庄稼疾病严厉。

简介：Informationaboutthespatialdistributionofsoilattributesisindispensableformanylandresourcemanagementapplications;however,theabilityofsoilmapstosupplysuchinformationformodernmodelingtoolsisquestionable.Theobjectivesofthisstudyweretoinvestigatethepossibilityofpredictingsoildepthusingsometerrainattributesderivedfromdigitalelevationmodels(DEMs)withgeographicinformationsystems(GIS)andtosuggestanapproachtopredictothersoilattributes.Soildepthwasdeterminedat652fieldobservationsovertheAl-MuwaqqarWatershed(70km2)inJordan.Terrainattributesderivedfrom30-mresolutionDEMswereutilizedtopredictsoildepth.Theresultsindicatedthattheuseofmultiplelinearregressionmodelswithinsmallwatershedsubdivisionsenabledthepredictionofsoildepthwithadifferenceof50cmfor77%ofthefieldobservations.Thespatialdistributionofthepredictedsoildepthwasvisuallycoincidedandhadgoodcorrelationswiththespatialdistributionoftheclassesamalgamatingthreeterrainattributes,slopesteepness,slopeshape,andcompoundtopographicindex.Thesesuggestedthatthemodelingofsoil-landscaperelationshipswithinsmallwatershedsubdivisionsusingthethreeterrainattributeswasapromisingapproachtopredictothersoilattributes.

简介：Keerqin沙土地位于在向东北平凡、内部的蒙古之间的过渡地面(42°41′-45°15′N，118°35′-123°30′E)在东北Chinaand，它被沙漠化严重影响。根据地球表面的配置和生态环境，植被，赤裸的砂土的职业比率和土壤质地的范围被使用地调查数据作为评估索引选择。Keerqin沙的沙漠化的评估索引系统被使用遥感数据建立，并且赤裸的砂土的职业比率被混合光谱模型获得。这个索引系统被域调查数据验证，结果显示它对Keerqin的thedesertification评估合适。

简介：MODIS(中等决定成像分光辐射函数)是在地(曙光女神AM)和水(曙光女神下午)上的一台关键仪器卫星。线性光谱混合模型为陆地封面的亚象素分类被用于MOIDS数据。在中国的浙江省的Shaoxing县被选择是学习地点，早米饭作为学习庄稼被选择。从MODIS象素使用的陆地封面的导出的比例线性光谱混合模型与从在一样的天获得的TM数据导出的无指导的分类相比，它暗示MODIS数据能为米饭耕作被用作卫星数据来源区域评价，可能米饭生长在地区性的规模上监视并且产量预报。

简介：作为由地面生产的数据的数量，为根渗透雷达(GPR)大，传播和数据的存储消费大资源。减轻这个问题，我们这里用混乱粒子群建议一个根成像算法最佳(CPSO)压缩了根据根空间的稀少基于GPR数据察觉到。雷达数据以稀少的方式被分解，观察，测量并且代表，因此根图象能与有限数据被重建。第一，雷达信号测量和稀少的表示被实现，并且解决方案空格被小浪基础和高斯随机矩阵建立；第二，匹配的功能被看作健康功能，并且最好的健康价值被一个PSO算法发现；然后，混乱搜索被用来获得全球最佳的操作员；最后，根图象被最佳的操作符重建。分别地，从美国GSSIGPR的A扫描数据，B扫描数据，和复杂数据在试验性的测试被使用。为B扫描数据，计算时间被减少60?%和PSNR被改进5.539?dB；为实际的根数据成像，重建PSNR是26.300?dB，和全部的计算时间仅仅是67.210?s。CPSO-OMP算法克服本地最佳套住的问题并且包括地在重建期间提高精确。

简介：WemappedtheforestcoverofKhadimnagarNationalPark(KNP)ofSylhetForestDivisionandestimatedforestchangeoveraperiodof22years(1988-2010)usingLandsatTMimagesandotherGISdata.SupervisedclassificationandNormalizedDifferenceVegetationIndex(NDVI)imageclassificationapproacheswereappliedtotheimagestoproducethreecoverclasses,viz.denseforest,mediumdenseforest,andbareland.Thechangemapwasproducedbydifferencingclassifiedimageriesof1988and2010asbeforeimageandafterimage,respectively,inERDASIMAGINE.Errormatrixandkappastatisticswereusedtoassesstheaccuracyoftheproducedmaps.Overallmapaccuraciesresultingfromsupervisedclassificationof1988and2010imagerieswere84.6%(Kappa0.75)and87.5%(Kappa0.80),respectively.Forestcoverstatisticsresultingfromsupervisedclassificationshowedthatdenseforestandbarelanddeclinedfrom526ha(67%)to417ha(59%)and105ha(13%)to8ha(1%),respectively,whereasmediumdenseforestincreasedfrom155ha(20%)to317ha(40%).ForestcoverchangestatisticsderivedfromNDVIclassificationshowedthatdenseforestdeclinedfrom525ha(67%)to421ha(54%)whilemediumdenseforestincreasedfrom253ha(32%)to356ha(45%).BothsupervisedandNDVIclassificationapproachesshowedsimilartrendsofforestchange,i.e.decreaseofdenseforestandincreaseofmediumdenseforest,whichindicatesdenseforesthasbeenconvertedtomediumdenseforest.Areaofbarelandwasunchanged.Illicitfelling,encroachment,andsettlementnearforestscausedthedenseforestdeclinewhileshortandlongrotationplantationsraisedinvariousyearscausedtheincreaseinareaofmediumdenseforest.ProtectivemeasuresshouldbeundertakentocheckfurtherdegradationofforestatKNP.

简介：Usingthemulti-temporalLandsatdataandsurveydataofnationalresources,theauthorsstudiedthedynamicsofcultivatedlandandlandcoverchangesoftypicalecologicalregionsinChina.TheresultsofinvestigationshowedthatthewholedistributionofthecultivatedlandshiftedtoNortheastandNorthwestChina,andasaresult,theecologicalqualityofcultivatedlanddroppeddown.TheseacoastandcultivatedlandintheareaofYellowRiverMouthexpandedbyanincreasingrateof0.73km?a-1,withadepositingrateof2.1km?a-1.ThedesertificationareaofthedynamicofHorqinSandyLandincreasedfrom60.02%ofthetotallandareain1970sto64.82%in1980sbutdecreasedto54.90%inearly1990s.AstothechangeofNorthTibetlakes,thewaterareaoftheNamuLakedecreasedby38.58km2fromyear1970to1988,withadecreasingrateof2.14km2?a-1.

简介：Background:Overthelastdecades,manyforestsimulatorshavebeendevelopedfortheforestsofindividualEuropeancountries.Theunderlyinggrowthmodelsareusuallybasedonnationaldatasetsofvaryingsize,obtainedfromNationalForestInventoriesorfromlong-termresearchplots.Manyofthesemodelsincludecountry-andlocation-specificpredictors,suchassitequalityindicesthatmayaggregateclimate,soilpropertiesandtopographyeffects.Consequently,itisnotsensibletocomparesuchmodelsamongcountries,anditisoftenimpossibletoapplymodelsoutsidetheregionorcountrytheyweredevelopedfor.However,thereisaclearneedformoregenericallyapplicablebutstilllocallyaccurateandclimatesensitivesimulatorsattheEuropeanscale,whichrequiresthedevelopmentofmodelsthatareapplicableacrosstheEuropeancontinent.ThepurposeofthisstudyistodeveloptreediameterincrementmodelsthatareapplicableattheEuropeanscale,butstilllocallyaccurate.Wecompiledandusedadatasetofdiameterincrementobservationsofover2.3milliontreesfrom10NationalForestInventoriesinEuropeandasetof99potentialexplanatoryvariablescoveringforeststructure,weather,climate,soilandnutrientdeposition.Results:Diameterincrementmodelsarepresentedfor20species/speciesgroups.Selectionofexplanatoryvariableswasdoneusingacombinationofforwardandbackwardselectionmethods.Theexplainedvariancerangedfrom10%to53%dependingonthespecies.Variablesrelatedtoforeststructure(basalareaofthestandandrelativesizeofthetree)contributedmosttotheexplainedvariance,butenvironmentalvariableswereimportanttoaccountforspatialpatterns.Thetypeofenvironmentalvariablesincludeddifferedgreatlyamongspecies.Conclusions:ThepresenteddiameterincrementmodelsarethefirstoftheirkindthatareapplicableattheEuropeanscale.Thisisanimportantsteptowardsthedevelopmentofanewgenerationofforestdevelopmentsimulatorsthatcan

简介：Forestsareamongthemostimportantcarbonsinksonearth.However,theircomplexstructureandvastareasprecludeaccurateestimationofforestcarbonstocks.Datasetsfromforestmonitoringusingadvancedsatelliteimageryarenowusedininternationalpolicyagreements.DatasetsenabletrackingofemissionsofCO2intotheatmospherecausedbydeforestationandothertypesofland-usechanges.TheaimofthisstudyistodeterminethecapabilityofSPOT-HRGSatellitedatatoestimateabovegroundcarbonstockinadistrictofDarabkolaresearchandtrainingforest,Iran.Preprocessingtoeliminateorreducegeometricerrorandatmosphericerrorwereperformedontheimages.Usingclustersampling,165sampleplotsweretaken.Of165plots,81wereinnaturalhabitats,and84wereinforestplantations.Followingthecollectionofgrounddata,biomassandcarbonstockswerequantifiedforthesampleplotsonaperhectarebasis.Nonparametricregressionmodelssuchassupportvectorregressionwereusedformodelingpurposeswithdifferentkernelsincludinglinear,sigmoid,polynomial,andradialbasisfunction.Theresultsshowedthatathird-degreepolynomialwasthebestmodelfortheentirestudiedareashavinganrootmeansquareerror,biasandaccuracy,respectively,of38.41,5.31,and62.2;42.77,16.58,and57.3%forthebestpolynomialfornaturalforest;and44.71,2.31,and64.3%forafforestation.Overall,theseresultsindicatethatSPOTHRGsatellitedataandsupportvectormachinesareusefulforestimatingabovegroundcarbonstock.

简介：Background:Remotesensing-basedmappingofforestEcosystemService(ES)indicatorshasbecomeincreasinglypopular.TheresultingmapsmayenabletospatiallyassesstheprovisioningpotentialofESsandprioritizethelanduseinsubsequentdecisionanalyses.However,themappingisoftenbasedonreadilyavailabledata,suchaslandcovermapsandotherpubliclyavailabledatabases,andignoringtherelateduncertainties.Methods:Thisstudytestedthepotentialtoimprovetherobustnessofthedecisionsbymeansoflocalmodelfittinganduncertaintyanalysis.Thequalityofforestlanduseprioritizationwasevaluatedundertwodifferentdecisionsupportmodels:eitherusingthedevelopedmodelsdeterministicallyorincorporationwiththeuncertaintiesofthemodels.Results:PredictionmodelsbasedonAirborneLaserScanning(ALS)dataexplainedthevariationinproxiesofthesuitabilityofforestplotsformaintainingbiodiversity,producingtimber,storingcarbon,orprovidingrecreationaluses(berrypickingandvisualamenity)withRMSEsof15%–30%,dependingontheES.TheRMSEsoftheALS-basedpredictionswere47%–97%ofthosederivedfromforestresourcemapswithasimilarresolution.Duetoapplyingasimilarfieldcalibrationsteponbothofthedatasources,thedifferencecanbeattributedtothebetterabilityofALStoexplainthevariationintheESproxies.Conclusions:Despitethedifferentaccuracies,proxyvaluespredictedbyboththedatasourcescouldbeusedforapixel-basedprioritizationoflanduseataresolutionof250m~2,i.e.,inaconsiderablymoredetailedscalethanrequiredbycurrentoperationalforestmanagement.TheuncertaintyanalysisindicatedthatmapsoftheESprovisioningpotentialshouldbepreparedseparatelybasedonexpectedandextremeoutcomesoftheESproxymodelstofullydescribetheproductionpossibilitiesofthelandscapeundertheuncertaintiesinthemodels.