Filling Gaps of Monthly Terra/MODIS Daytime Land Surface Temperature Using Discrete Cosine Transform Method
暂无分享,去创建一个
Hou Jiang | Jun Qin | Ling Yao | Ning Lu | Hengzi Liu | N. Lu | L. Yao | Hou Jiang | Jun Qin | Hengzi Liu
[1] Peter Craven,et al. Smoothing noisy data with spline functions , 1978 .
[2] A. Tatem,et al. Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data , 2008, PloS one.
[3] Gautam Bisht,et al. Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains , 2006 .
[4] Nathaniel A. Brunsell,et al. How can we use MODIS land surface temperature to validate long‐term urban model simulations? , 2014 .
[5] Yang Zhang,et al. Reconstruction of MODIS Land Surface Temperature Products Based on Multi-Temporal Information , 2018, Remote. Sens..
[6] Xiaolu Li,et al. An Effective Similar-Pixel Reconstruction of the High-Frequency Cloud-Covered Areas of Southwest China , 2019, Remote. Sens..
[7] Jeff Dozier,et al. A generalized split-window algorithm for retrieving land-surface temperature from space , 1996, IEEE Trans. Geosci. Remote. Sens..
[8] Damien Garcia,et al. Robust smoothing of gridded data in one and higher dimensions with missing values , 2010, Comput. Stat. Data Anal..
[9] Yuyu Zhou,et al. Creating a seamless 1 km resolution daily land surface temperature dataset for urban and surrounding areas in the conterminous United States , 2018 .
[10] Bo Hu,et al. Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data , 2017, Comput. Geosci..
[11] Yi Liu,et al. A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations , 2012, Environ. Model. Softw..
[12] F. Gao,et al. Generating daily land surface temperature at Landsat resolution by fusing Landsat and MODIS data , 2014 .
[13] Liangpei Zhang,et al. Reconstructing MODIS LST Based on Multitemporal Classification and Robust Regression , 2015, IEEE Geoscience and Remote Sensing Letters.
[14] Da Li,et al. jag simple retrieval method of land surface temperature from AMSR-E passive icrowave data — A case study over Southern China during the strong snow isaster of 2008 , 2010 .
[15] I. D. Feis,et al. Kalman filter physical retrieval of surface emissivity and temperature from geostationary infrared radiances , 2013 .
[16] N. Ahmed,et al. Discrete Cosine Transform , 1996 .
[17] Douglas W. Nychka,et al. Statistical significance of trends and trend differences in layer-average atmospheric temperature time series , 2000 .
[18] Linna Chai,et al. Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method , 2016, Remote. Sens..
[19] Peter M. Atkinson,et al. An effective approach for gap-filling continental scale remotely sensed time-series , 2014, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.
[20] P. Atkinson,et al. Deriving DSMs from LiDAR data with kriging , 2002 .
[21] Wade T. Crow,et al. Assessment of the impact of spatial heterogeneity on microwave satellite soil moisture periodic error. , 2018, Remote sensing of environment.
[22] J. Arnó,et al. Review. Precision Viticulture. Research topics, challenges and opportunities in site-specific vineyard management , 2009 .
[23] Damien Garcia,et al. A fast all-in-one method for automated post-processing of PIV data , 2011, Experiments in fluids.
[24] Yousuke Noumi,et al. Discrepancy Between ASTER- and MODIS- Derived Land Surface Temperatures: Terrain Effects , 2009, Sensors.
[25] I. D. Feis,et al. Convergence for the regularized inversion of Fourier series , 1997 .
[26] Markus Neteler,et al. Estimating Daily Land Surface Temperatures in Mountainous Environments by Reconstructed MODIS LST Data , 2010, Remote. Sens..
[27] Rekha Vig,et al. Speech Compression using Multi-Resolution Hybrid Wavelet using DCT and Walsh Transforms , 2018 .
[28] Hao Zhang,et al. Gap-Filling of MODIS Time Series Land Surface Temperature (LST) Products Using Singular Spectrum Analysis (SSA) , 2018, Atmosphere.
[29] Zhao-Liang Li,et al. A framework for the retrieval of all-weather land surface temperature at a high spatial resolution from polar-orbiting thermal infrared and passive microwave data , 2017 .
[30] Z. Wan. New refinements and validation of the MODIS Land-Surface Temperature/Emissivity products , 2008 .
[31] Edzer Pebesma,et al. Spatio‐temporal interpolation of daily temperatures for global land areas at 1 km resolution , 2014 .
[32] Markus Metz,et al. A New Fully Gap-Free Time Series of Land Surface Temperature from MODIS LST Data , 2017, Remote. Sens..
[33] Gang Yang,et al. An Integrated Method for Reconstructing Daily MODIS Land Surface Temperature Data , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[34] B. Santer,et al. Uncertainties in observationally based estimates of temperature change in the free atmosphere , 1999 .
[35] Sibo Duan,et al. Spatiotemporal Reconstruction of Land Surface Temperature Derived From FengYun Geostationary Satellite Data , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[36] P. Sellers,et al. The First ISLSCP Field Experiment (FIFE) , 1988 .
[37] Ji Zhou,et al. A Method Based on Temporal Component Decomposition for Estimating 1-km All-Weather Land Surface Temperature by Merging Satellite Thermal Infrared and Passive Microwave Observations , 2019, IEEE Transactions on Geoscience and Remote Sensing.
[38] Gautam Bisht,et al. Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days , 2005 .
[39] William L. Crosson,et al. A daily merged MODIS Aqua–Terra land surface temperature data set for the conterminous United States , 2012 .
[40] Shuo Xu,et al. Reconstructing All-Weather Land Surface Temperature Using the Bayesian Maximum Entropy Method Over the Tibetan Plateau and Heihe River Basin , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[41] Gang Yang,et al. Recovering Quantitative Remote Sensing Products Contaminated by Thick Clouds and Shadows Using Multitemporal Dictionary Learning , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[42] Smoothing data with correlated noise via Fourier transform , 2000 .
[43] Sukadev Meher,et al. A Hybrid Image Compression Scheme Using DCT and Fractal Image Compression , 2013, Int. Arab J. Inf. Technol..
[44] Gang Yang,et al. Missing Information Reconstruction of Remote Sensing Data: A Technical Review , 2015, IEEE Geoscience and Remote Sensing Magazine.
[45] H. Mannstein,et al. Surface Energy Budget, Surface Temperature and Thermal Inertia , 1987 .
[46] Yongming Xu,et al. Reconstruction of the land surface temperature time series using harmonic analysis , 2013, Comput. Geosci..
[47] Seokhyeon Kim,et al. Building a Flood-Warning Framework for Ungauged Locations Using Low Resolution, Open-Access Remotely Sensed Surface Soil Moisture, Precipitation, Soil, and Topographic Information , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[48] Seokhyeon Kim,et al. Using 3D robust smoothing to fill land surface temperature gaps at the continental scale , 2019, Int. J. Appl. Earth Obs. Geoinformation.
[49] Markus Metz,et al. Surface Temperatures at the Continental Scale: Tracking Changes with Remote Sensing at Unprecedented Detail , 2014, Remote. Sens..
[50] D. Lamb,et al. Characterising and mapping vineyard canopy using high-spatial-resolution aerial multispectral images , 2003 .
[51] G. Heuvelink,et al. Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images , 2013, Theoretical and Applied Climatology.