Development and technical paper
15 Feb 2017
Development and technical paper
| 15 Feb 2017
Spatio-temporal approach to moving window block kriging of satellite data v1.0
Jovan M. Tadić et al.
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Cited
20 citations as recorded by crossref.
- Efficient multi-scale Gaussian process regression for massive remote sensing data with satGP v0.1.2 J. Susiluoto et al. 10.5194/gmd-13-3439-2020
- Locally stationary spatio-temporal interpolation of Argo profiling float data M. Kuusela & M. Stein 10.1098/rspa.2018.0400
- Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes W. Sun et al. 10.1029/2020AV000310
- Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation E. Varouchakis et al. 10.3390/s21093132
- Effects of Climate Change on Precipitation and the Maximum Daily Temperature (Tmax) at Two US Military Bases with Different Present-Day Climates J. Tadić & S. Biraud 10.3390/cli8020018
- Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method Z. He et al. 10.3390/rs12030576
- A Regional Spatiotemporal Downscaling Method for CO2 Columns X. Ma et al. 10.1109/TGRS.2021.3052215
- Data reduction for inverse modeling: an adaptive approach v1.0 X. Liu et al. 10.5194/gmd-14-4683-2021
- QuickSampling v1.0: a robust and simplified pixel-based multiple-point simulation approach M. Gravey & G. Mariethoz 10.5194/gmd-13-2611-2020
- A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks Y. Zhang et al. 10.5194/bg-15-5779-2018
- Drought impacts on photosynthesis, isoprene emission and atmospheric formaldehyde in a mid-latitude forest Y. Zheng et al. 10.1016/j.atmosenv.2017.08.017
- Identification of Bias in Satellite Measurements Using its Geospatial Properties J. Tadic & S. Biraud 10.1109/LGRS.2020.3015174
- Spatiotemporal geostatistical modeling of groundwater levels under a Bayesian framework using means of physical background E. Varouchakis et al. 10.1016/j.jhydrol.2019.05.055
- A physics-based approach to oversample multi-satellite, multispecies observations to a common grid K. Sun et al. 10.5194/amt-11-6679-2018
- Towards Hyper-Dimensional Variography Using the Product-Sum Covariance Model J. Tadić et al. 10.3390/atmos10030148
- Assessment of Groundwater Depletion and Implications for Management in the Denver Basin Aquifer System C. Ruybal et al. 10.1111/1752-1688.12755
- Greenhouse gas fluxes from Alaska's North Slope inferred from the Airborne Carbon Measurements campaign (ACME-V) J. Tadić et al. 10.1016/j.atmosenv.2021.118239
- Atmospheric CO 2 Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar‐Induced Chlorophyll Fluorescence Y. Shiga et al. 10.1002/2017GL076630
- Validation of Column-Averaged Dry-Air Mole Fraction of CO2 Retrieved from OCO-2 Using Ground-Based FTS Measurements Y. Bi et al. 10.1007/s13351-018-7118-6
- Evaluation of Groundwater Levels in the Arapahoe Aquifer Using Spatiotemporal Regression Kriging C. Ruybal et al. 10.1029/2018WR023437
20 citations as recorded by crossref.
- Efficient multi-scale Gaussian process regression for massive remote sensing data with satGP v0.1.2 J. Susiluoto et al. 10.5194/gmd-13-3439-2020
- Locally stationary spatio-temporal interpolation of Argo profiling float data M. Kuusela & M. Stein 10.1098/rspa.2018.0400
- Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes W. Sun et al. 10.1029/2020AV000310
- Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation E. Varouchakis et al. 10.3390/s21093132
- Effects of Climate Change on Precipitation and the Maximum Daily Temperature (Tmax) at Two US Military Bases with Different Present-Day Climates J. Tadić & S. Biraud 10.3390/cli8020018
- Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method Z. He et al. 10.3390/rs12030576
- A Regional Spatiotemporal Downscaling Method for CO2 Columns X. Ma et al. 10.1109/TGRS.2021.3052215
- Data reduction for inverse modeling: an adaptive approach v1.0 X. Liu et al. 10.5194/gmd-14-4683-2021
- QuickSampling v1.0: a robust and simplified pixel-based multiple-point simulation approach M. Gravey & G. Mariethoz 10.5194/gmd-13-2611-2020
- A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks Y. Zhang et al. 10.5194/bg-15-5779-2018
- Drought impacts on photosynthesis, isoprene emission and atmospheric formaldehyde in a mid-latitude forest Y. Zheng et al. 10.1016/j.atmosenv.2017.08.017
- Identification of Bias in Satellite Measurements Using its Geospatial Properties J. Tadic & S. Biraud 10.1109/LGRS.2020.3015174
- Spatiotemporal geostatistical modeling of groundwater levels under a Bayesian framework using means of physical background E. Varouchakis et al. 10.1016/j.jhydrol.2019.05.055
- A physics-based approach to oversample multi-satellite, multispecies observations to a common grid K. Sun et al. 10.5194/amt-11-6679-2018
- Towards Hyper-Dimensional Variography Using the Product-Sum Covariance Model J. Tadić et al. 10.3390/atmos10030148
- Assessment of Groundwater Depletion and Implications for Management in the Denver Basin Aquifer System C. Ruybal et al. 10.1111/1752-1688.12755
- Greenhouse gas fluxes from Alaska's North Slope inferred from the Airborne Carbon Measurements campaign (ACME-V) J. Tadić et al. 10.1016/j.atmosenv.2021.118239
- Atmospheric CO 2 Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar‐Induced Chlorophyll Fluorescence Y. Shiga et al. 10.1002/2017GL076630
- Validation of Column-Averaged Dry-Air Mole Fraction of CO2 Retrieved from OCO-2 Using Ground-Based FTS Measurements Y. Bi et al. 10.1007/s13351-018-7118-6
- Evaluation of Groundwater Levels in the Arapahoe Aquifer Using Spatiotemporal Regression Kriging C. Ruybal et al. 10.1029/2018WR023437
Latest update: 03 Jul 2022
Short summary
We developed a new method to create contiguous maps from sparse and/or noisy satellite observations. This approach could be used to produce retroactive or real-time estimates of environmental data observed by satellites which exhibit spatio-temporal autocorrelations. The method could be applied in a standalone mode or as part of a broader satellite data processing package. Maps produced in this way could then be incorporated into physical and biogeochemical models of the Earth system.
We developed a new method to create contiguous maps from sparse and/or noisy satellite...