Imagen de Portada

Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2013-2014)

Fuente: Zenodo

Guardado en:

Detalles Bibliográficos
Autor principal:	Cheng, Minghan
Formato:	Recurso digital
Publicado:	Zenodo 2024
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Approximate Bayesian inference for high-resolution spatial disaggregation using alternative data sources
por: Pakrashi, Anis, et al.
Publicado: (2024)

China global Land Surface Air Temperature, version 2.0
por: Li, Qingxiang, et al.
Publicado: (2020)

Reconstruction of Antarctic Near-Surface Air Temperatures NCL programs
por: Bromwich, David, et al.
Publicado: (2025)

Beamsplitter-free, high bit-rate, quantum random number generator based on temporal and spatial correlations of heralded single-photons
por: Nai, Ayan Kumar, et al.
Publicado: (2024)

Advancing technologies for high-resolution spatial and temporal measurements of macroscopic stellarator flows
por: Wright, A. M., et al.
Publicado: (2024)

Controlling deposition and characterising dynamics of thin liquid films with high temporal and spatial resolution
por: Lay, G Le, et al.
Publicado: (2025)

Fast spatial simulation of extreme high-resolution radar precipitation data using INLA
por: Vandeskog, Silius M., et al.
Publicado: (2023)

A view of the evolution of a CME and the associated wave-trains at high spatial and temporal resolution
por: Russano, G., et al.
Publicado: (2026)

Unravelling the spatial and temporal variability of natural disturbances in European forests
por: Sofia Miguel, et al.
Publicado: (2026)

Correction to “Unravelling the spatial and temporal variability of natural disturbances in European forests”
Publicado: (2026)

Estimating multi-year 24/7 origin-destination demand using high-granular multi-source traffic data
por: Ma, Wei, et al.
Publicado: (2019)

Nonparametric intensity estimation of spatial point processes by random forests
por: Biscio, Christophe, et al.
Publicado: (2025)

Theory-independent randomness generation from spatial symmetries
por: Jones, Caroline L., et al.
Publicado: (2022)

The source of metals in the high-redshift lyman_forest
por: Sebastian Lopez
Publicado: (2006)

VibrantVS: A high-resolution multi-task transformer for forest canopy height estimation
por: Chang, Tony, et al.
Publicado: (2024)

China Merged Surface Temperature
por: Li, Qingxiang
Publicado: (2019)

Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high‐spatial resolution
por: Joan Rué‐Queralt, et al.
Publicado: (2024)

The impact of the spatial resolution of wind data on multi-decadal wind power forecasts in Germany
por: Morelli, Sofia
Publicado: (2024)

Yield forecasting based on short time series with high spatial resolution data
por: Pokal, Sayli, et al.
Publicado: (2024)

Scalable ultrafast random bit generation using wideband chaos-based entropy sources
por: Tseng, Chin-Hao, et al.
Publicado: (2025)

An assessment of urban park accessibility using multi‐source data in Hefei, China: A social equity perspective
por: Zhao Yang, et al.
Publicado: (2024)

Multi-spatial Multi-temporal Air Quality Forecasting with Integrated Monitoring and Reanalysis Data
por: Hu, Yuxiao, et al.
Publicado: (2023)

SPyCer: Semi-Supervised Physics-Guided Contextual Attention for Near-Surface Air Temperature Estimation from Satellite Imagery
por: Bouaziz, Sofiane, et al.
Publicado: (2026)

Process signature-driven high spatio-temporal resolution alignment of multimodal data
por: Hanchate, Abhishek, et al.
Publicado: (2024)

Assessment of Broiler Surface Temperature Variation When Exposed to Different Air Temperatures
por: GR Nascimento
Publicado: (2011)

Higher spatial resolution and sensitivity in whole brain functional MRI at 7T using 3D EPI accelerated with variable density CAIPI sampling and temporal random walk
por: Suhyung Park, et al.
Publicado: (2025)

Using quantile mapping and random forest for bias‐correction of high‐resolution reanalysis precipitation data and CMIP6 climate projections over Iran
por: Maryam Raeesi, et al.
Publicado: (2024)

High-dimensional modeling of spatial and spatio-temporal conditional extremes using INLA and Gaussian Markov random fields
por: Simpson, Emma S., et al.
Publicado: (2020)

Multi-label classification for multi-temporal, multi-spatial coral reef condition monitoring using vision foundation model with adapter learning
por: Shao, Xinlei, et al.
Publicado: (2025)

Monitoring changes of forest canopy density in a temperature forest using high-resolution aerial digital photography
por: José López García
Publicado: (2016)

A spatial random forest algorithm for population-level epidemiological risk assessment
por: Lee, Duncan, et al.
Publicado: (2026)

NGC 1097 at high spatial resolution in the mid-infrared
por: A. O. Petric
Publicado: (2007)

GPS in the georectification of high spatial resolution satellite images
por: Hermógenes D. Suárez A.
Publicado: (2005)

Coral reef habitat maps derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis
por: Roelfsema, Christiaan M, et al.
Publicado: (2013)

Habitat map of Kubulau, Fiji derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis
por: Roelfsema, Christiaan M, et al.
Publicado: (2013)

Habitat map of Kadavu, Fiji derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis
por: Roelfsema, Christiaan M, et al.
Publicado: (2013)

Spatial and temporal distribution of stratospheric turbulence from global high-resolution radiosonde data
por: Ko, Han-Chang, et al.
Publicado: (2026)

Stability for a multi-frequency inverse random source problem
por: Wang, Tianjiao, et al.
Publicado: (2024)

Quantum-proof multi-source randomness extractors in the Markov model
por: Arnon, Rotem, et al.
Publicado: (2015)

Monitoring long‐term vegetation dynamics over the Yangtze River Basin, China, using multi‐temporal remote sensing data
por: Jing Fu, et al.
Publicado: (2024)