نوع المادة: تقرير

الموضوعات

Robotics.

Quality control.

Engineering.

Reliability.

Electrical engineering.

Machinery and Machine Elements.

Image processing.

Mechatronics.

Industrial safety.

Machinery.

Electrical Engineering.

Control engineering.

Engineering.

Quality Control, Reliability, Safety and Risk.

Control, Robotics, Mechatronics.

Image Processing and Computer Vision.

التصنيف:

العلوم التطبيقية

الهندسة

الفيزياء التطبيقية

المصادر: Springer Protocols

اللغة: الإنجليزية

التاريخ: 2012

ردمك: 9781849961691

eReference.

online resource.

ملف خارجي

نوع المادة: كتاب

الموضوعات

Business enterprises, Corunna., Michigan

World War, 1939-1945.

Stables.

Michigan, Streets, Flint.

Freemasonry.

1946-1960., Politics and government

World War, 1914-1918.

Michigan, Post offices, Flint.

Business enterprises.

Parades and processions.

Michigan, Post office buildings, Flint

Sports.

Flint, Streets, Michigan

Children.

Machine shops.

Military art and science.

Soldiers, American.

Interiors.

المصادر: University of Michigan

اللغة: الإنجليزية

3 linear ft. and 5 v. (outsize).

ملف خارجي

نوع المادة: كتاب

الموضوعات

evapotranspiration; Northeast China; MS–PT algorithm; spatial-temporal variations; controlling factors; potential evapotranspiration; vegetation remote sensing; reflectance model; spectra; leaf; copper; PROSPECT; leaf area density; terrestrial LiDAR; tree canopy; vertical structure; voxel; spatial representativeness; heterogeneity; validation; land-surface temperature products (LSTs); observations; HiWATER; remote sensing; spatiotemporal representative; cost-efficient, sampling design; heterogeneity; validation; FY-3C/MERSI; GLASS; Land surface temperature; Land surface emissivity; GPP; SIF; MuSyQ-GPP algorithm; BEPS; vegetation phenology; Tibetan Plateau; MODIS; NDVI; start of growing season (SOS); end of growing season (EOS); GLASS LAI time series; forest disturbance; disturbance index; latent heat; machine learning algorithms; plant functional type; high-resolution freeze/thaw; AMSR2; MODIS; LAI; ZY-3 MUX; GF-1 WFV; HJ-1 CCD; maize; PROSPECT-5B+SAILH (PROSAIL) model; spatial heterogeneity; variability; evapotranspiration; land surface variables; probability density function; HiWATER; spectral; albedometer; interference filter; photoelectric detector; validation; land surface albedo; multi-scale validation; rugged terrain; MRT-based model; MCD43A3 C6; precipitation; statistics methods; China; Tibetan Plateau; South China’s; drought; SPI; TMI data; crop-growing regions; downward shortwave radiation; machine learning; gradient boosting regression tree; AVHRR; CMA; BRDF; aerosol; MODIS; sunphotometer; arid/semiarid; solar-induced chlorophyll fluorescence; fluorescence quantum efficiency in dark-adapted conditions (FQE); SCOPE; Fraunhofer Line Discrimination (FLD); gross primary productivity (GPP); longwave upwelling radiation (LWUP); Visible Infrared Imaging Radiometer Suite (VIIRS); surface radiation budget; hybrid method; remote sensing; leaf age; leaf spectral properties; leaf area index; Cunninghamia; Chinese fir; canopy reflectance; NIR; EVI2; geometric optical radiative transfer (GORT) model; land surface albedo; snow-free albedo; rugged terrain; topographic effects; black-sky albedo (BSA); GPP; NPP; MODIS; validation; phenology; RADARSAT-2; rice; Synthetic Aperture Radar (SAR); decision tree; forest canopy height; aboveground biomass; ICESat GLAS; Landsat; random forest model; anisotropic reflectance; BRDF; rugged terrain; solo slope; composite slope; surface solar irradiance; geostationary satellite; polar orbiting satellite; LUT method; SURFRAD; downward shortwave radiation; daily average value; Antarctica; sinusoidal method; cloud fraction; interpolation; boreal forest; GPP; spatiotemporal distribution and variation; meteorological factors; phenological parameters; multisource data fusion; aerosol retrieval; urban scale; vegetation dust-retention; multiple ecological factors; geographical detector model; snow cover; passive microwave; FY-3C/MWRI; algorithmic assessment; China; land surface temperature; satellite observations; flux measurements; latitudinal pattern; land cover change; fractional vegetation cover (FVC); multi-data set; northern China; spatio-temporal; inter-annual variation; uncertainty; standard error of the mean; downscaling; GPP; spatial heterogeneity; remote sensing; subpixel information; LiDAR; point cloud; leaf; gap fraction; 3D reconstruction; biodiversity; remote sensing; species richness; metric comparison; metric integration; leaf area index; MODIS products; Landsat; high resolution; homogeneous and pure pixel filter; pixel unmixing; vertical vegetation stratification; gross primary production (GPP); light use efficiency; dense forest; MODIS; VPM; temperature profiles; humidity profiles; n/a; geometric-optical model; thermal radiation directionality; quantitative remote sensing inversion; scale effects; comprehensive field experiment

المصادر: قاعدة بيانات الكتب المجانية

اللغة: الإنجليزية

التاريخ: 2019

ردمك: 9783038972709

ملف خارجي

نوع المادة: كتاب

الموضوعات

evapotranspiration; Northeast China; MS–PT algorithm; spatial-temporal variations; controlling factors; potential evapotranspiration; vegetation remote sensing; reflectance model; spectra; leaf; copper; PROSPECT; leaf area density; terrestrial LiDAR; tree canopy; vertical structure; voxel; spatial representativeness; heterogeneity; validation; land-surface temperature products (LSTs); observations; HiWATER; remote sensing; spatiotemporal representative; cost-efficient, sampling design; heterogeneity; validation; FY-3C/MERSI; GLASS; Land surface temperature; Land surface emissivity; GPP; SIF; MuSyQ-GPP algorithm; BEPS; vegetation phenology; Tibetan Plateau; MODIS; NDVI; start of growing season (SOS); end of growing season (EOS); GLASS LAI time series; forest disturbance; disturbance index; latent heat; machine learning algorithms; plant functional type; high-resolution freeze/thaw; AMSR2; MODIS; LAI; ZY-3 MUX; GF-1 WFV; HJ-1 CCD; maize; PROSPECT-5B+SAILH (PROSAIL) model; spatial heterogeneity; variability; evapotranspiration; land surface variables; probability density function; HiWATER; spectral; albedometer; interference filter; photoelectric detector; validation; land surface albedo; multi-scale validation; rugged terrain; MRT-based model; MCD43A3 C6; precipitation; statistics methods; China; Tibetan Plateau; South China’s; drought; SPI; TMI data; crop-growing regions; downward shortwave radiation; machine learning; gradient boosting regression tree; AVHRR; CMA; BRDF; aerosol; MODIS; sunphotometer; arid/semiarid; solar-induced chlorophyll fluorescence; fluorescence quantum efficiency in dark-adapted conditions (FQE); SCOPE; Fraunhofer Line Discrimination (FLD); gross primary productivity (GPP); longwave upwelling radiation (LWUP); Visible Infrared Imaging Radiometer Suite (VIIRS); surface radiation budget; hybrid method; remote sensing; leaf age; leaf spectral properties; leaf area index; Cunninghamia; Chinese fir; canopy reflectance; NIR; EVI2; geometric optical radiative transfer (GORT) model; land surface albedo; snow-free albedo; rugged terrain; topographic effects; black-sky albedo (BSA); GPP; NPP; MODIS; validation; phenology; RADARSAT-2; rice; Synthetic Aperture Radar (SAR); decision tree; forest canopy height; aboveground biomass; ICESat GLAS; Landsat; random forest model; anisotropic reflectance; BRDF; rugged terrain; solo slope; composite slope; surface solar irradiance; geostationary satellite; polar orbiting satellite; LUT method; SURFRAD; downward shortwave radiation; daily average value; Antarctica; sinusoidal method; cloud fraction; interpolation; boreal forest; GPP; spatiotemporal distribution and variation; meteorological factors; phenological parameters; multisource data fusion; aerosol retrieval; urban scale; vegetation dust-retention; multiple ecological factors; geographical detector model; snow cover; passive microwave; FY-3C/MWRI; algorithmic assessment; China; land surface temperature; satellite observations; flux measurements; latitudinal pattern; land cover change; fractional vegetation cover (FVC); multi-data set; northern China; spatio-temporal; inter-annual variation; uncertainty; standard error of the mean; downscaling; GPP; spatial heterogeneity; remote sensing; subpixel information; LiDAR; point cloud; leaf; gap fraction; 3D reconstruction; biodiversity; remote sensing; species richness; metric comparison; metric integration; leaf area index; MODIS products; Landsat; high resolution; homogeneous and pure pixel filter; pixel unmixing; vertical vegetation stratification; gross primary production (GPP); light use efficiency; dense forest; MODIS; VPM; temperature profiles; humidity profiles; n/a; geometric-optical model; thermal radiation directionality; quantitative remote sensing inversion; scale effects; comprehensive field experiment

المصادر: قاعدة بيانات الكتب المجانية

اللغة: الإنجليزية

التاريخ: 2019

ردمك: 9783038972761

ملف خارجي