Results 91 to 100 of about 41,752 (176)

Estimation and Evaluation of 15 Minute, 40 Meter Surface Upward Longwave Radiation Downscaled from the Geostationary FY-4B AGRI

Remote Sensing
Surface upward longwave radiation (SULR) is one of the four components of surface net radiation. Geostationary satellites can provide high temporal but coarse spatial resolution SULR products.
Limeng Zheng, Biao Cao, Qiang Na, Boxiong Qin, Junhua Bai, Yongming Du, Hua Li, Zunjian Bian, Qing Xiao, Qinhuo Liu   +9 more
doaj   +1 more source

Spatial Downscaling of Sea Surface Temperature Using Diffusion Model

Remote Sensing
In recent years, advancements in high-resolution digital twin platforms or artificial intelligence marine forecasting have led to the increased requirements of high-resolution oceanic data. However, existing sea surface temperature (SST) products from observations often fail to meet researchers’ resolution requirements.
Shuo Wang, Xiaoyan Li, Xueming Zhu, Jiandong Li, Shaojing Guo   +4 more
openaire   +2 more sources

Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia [PDF]

, 2018
Precipitation is a key input variable for hydrological and climate studies. Rain gauges can provide reliable precipitation measurements at a point of observations.
Alharbi, R, Hsu, K, Sorooshian, S
core   +1 more source

A hierarchical downscaling scheme for generating fine-resolution leaf area index with multisource and multiscale observations via deep learning

International Journal of Applied Earth Observations and Geoinformation
Leaf area index (LAI) is one of key variables for depicting vegetation structures in land ecosystems. Land surface models necessitate uniform LAI inputs at varying spatial scales to ensure accurate outputs at multiscale levels, however, operational ...
Huaan Jin, Yuting Qiao, Tian Liu, Xinyao Xie, Hongliang Fang, Qingchun Guo, Wei Zhao   +6 more
doaj   +1 more source

Fusion of Surface Soil Moisture Data for Spatial Downscaling of Daily Satellite Precipitation Data

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Remote sensing satellites provide an effective solution for obtaining large-scale precipitation data. However, the spatial resolution of satellite-based precipitation products is often too coarse for hydrological applications at the regional scale.
Qunming Wang, Ping Ji, Peter M. Atkinson
doaj   +1 more source

Spatial Downscaling of Satellite-Based Soil Moisture Products Using Machine Learning Techniques: A Review

Remote Sensing
Soil moisture (SM) is a key variable driving hydrologic, climatic, and ecological processes. Although it is highly variable, both spatially and temporally, there is limited data availability to inform about SM conditions at adequate spatial and temporal ...
Indishe P. Senanayake, Kalani R. L. Pathira Arachchilage, In-Young Yeo, Mehdi Khaki, Shin-Chan Han, Peter G. Dahlhaus   +5 more
doaj   +1 more source

PhySoilNet: A deep learning downscaling model for microwave satellite soil moisture with physical rule constraint

International Journal of Applied Earth Observations and Geoinformation
Surface soil moisture (SM) plays an important role in water and energy cycles. Passive microwave remote sensing observation has become the main means of obtaining large-scale surface SM.
Zhenheng Xu, Hao Sun, JinHua Gao, Yunjia Wang, Dan Wu, Tian Zhang, Huanyu Xu   +6 more
doaj   +1 more source

Spatial downscaling of survey data: a new approach

This article presents some innovative and useful extensions to the spatial downscaling method proposed by Izaguirre in ‘Geographic disaggregation of household surveys. Modified estimators for correcting misclassification bias’, in 2025, Spatial Economic Analysis, 107–127.
openaire   +1 more source

Empirically Derived Suitability Maps to Downscale Aggregated Land Use Data [PDF]

Understanding mechanisms that drive present land use patterns is essential in order to derive appropriate models of land use change. When static analyses of land use drivers are performed, they rarely explicitly deal with spatial autocorrelation.
Mark Rounsevell, Nicolas Dendoncker, Patrick Bogaert   +2 more
core  

A Likelihood-Based Generative Approach for Spatially Consistent Precipitation Downscaling

Peer ...
openaire   +3 more sources