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Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China
2017
Journal of Applied Remote Sensing
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The performance was also assessed using the G DOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. ...
The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data, and active/passive microwave remotely sensed Essential Climate ...
Methods of Downscaling
Independent explanatory variables for soil moisture Studies have showed that the main factors affecting soil moisture are climate, terrain, and land surface and soil characteristics ...
doi:10.1117/1.jrs.11.045003
fatcat:2mhtjufd45duvnx5mf45wqz3y4
Spatial Downscaling of Land Surface Temperature Based on a Multi-Factor Geographically Weighted Machine Learning Model
2021
Remote Sensing
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Land surface temperature (LST) is a critical parameter of surface energy fluxes and has become the focus of numerous studies. ...
To address this issue, we propose a multi-factor geographically weighted machine learning (MFGWML) algorithm. ...
Meanwhile, we thank associate professor Mengmeng Wang (China University of Geosciences) for his insightful suggestions.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13061186
fatcat:mqfzpslrb5bvbi4g4usu3isxwm
Downscaling of ASTER Thermal Images Based on Geographically Weighted Regression Kriging
2018
Remote Sensing
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The lower spatial resolution of thermal infrared (TIR) satellite images and derived land surface temperature (LST) is one of the biggest challenges in mapping temperature at a detailed map scale. ...
Vegetation Index (NDVI), according to the geographically weighted regression (GWRK) and area-to-point kriging of regressed residuals. ...
Y.L. supported with insights on image downscaling, also helping on the suggestion of improvements in the first efforts of O.J.R.P. on downscaling satellite images. ...
doi:10.3390/rs10040633
fatcat:htrzr7ydgje7tez4fd4o2nj4pu
Downscaling Aster Land Surface Temperature over Urban Areas with Machine Learning-Based Area-To-Point Regression Kriging
2020
Remote Sensing
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Land surface temperature (LST) is a vital physical parameter of earth surface system. Estimating high-resolution LST precisely is essential to understand heat change processes in urban environments. ...
NDVI is a poor indicator for impervious surfaces and water bodies; the RFATPK captured LST difference over different land coverage patterns and produced the spatial details of downscaled LST on heterogeneous ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs12071082
fatcat:vv3fz22b3vdrzp3a37adk4hmkm
Spatial Downscaling of Land Surface Temperature over Heterogeneous Regions Using Random Forest Regression Considering Spatial Features
2021
Remote Sensing
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Land surface temperature (LST) is one of the crucial parameters in the physical processes of the Earth. ...
weighted regression, and random forest downscaling method. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13183645
fatcat:hfa6hihkzbdmjjq467m5ndobse
Climate projections and downscaling techniques: a discussion for impact studies in urban systems
2017
International Journal of Urban Sciences
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Thirdly, special attention is given to previous works focused on the utilization of downscaled ensembles of climate simulations in urban agglomerations. ...
In the context of the planet currently undergoing a process of greenhouse warming, and simultaneously predominantly urban based ever continuing population growth, our agglomerations became vulnerable to ...
One of the most complex approaches for downscaling urban climate data involving land use modelling is the work of Solecki and Oliveri (2004) . ...
doi:10.1080/12265934.2017.1409132
fatcat:umfejopwonggbgq23p43xbfwr4
Spatially Continuous and High-resolution Land Surface Temperature: A Review of Reconstruction and Spatiotemporal Fusion Techniques
[article]
2019
arXiv
pre-print
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(PMW)-based and Surface Energy Balance (SEB)-based methods) and three kinds of spatiotemporal fusion methods (weighted function-based, unmixing-based and hybrid methods). ...
Remotely sensed, spatially continuous and high spatiotemporal resolution (hereafter referred to as high resolution) land surface temperature (LST) is a key parameter for studying the thermal environment ...
Recently, Fu et al. proposed another physical model-based method for retrieving urban land
surface temperatures under cloudy conditions (Fu et al. 2019). ...
arXiv:1909.09316v1
fatcat:vuh27iundzcofko7httat6kocm
Fine-Resolution Precipitation Mapping in a Mountainous Watershed: Geostatistical Downscaling of TRMM Products Based on Environmental Variables
2018
Remote Sensing
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According to the comparison of different regression models and residual interpolation methods, a geographically-weighted regression kriging (GWRK) method was accepted to conduct the downscaling of TRMM ...
Therefore, it is feasible to develop a spatial downscaling-calibration procedure for low-resolution satellite-based precipitation datasets based on NDVI and terrain factors in this area. ...
Acknowledgments: This work was funded by the National Key R & D Program of China (grant 2016YFA0601601) and Applied Basic Research Programs of Yunnan Province (grant 2017FB071). ...
doi:10.3390/rs10010119
fatcat:rtyhuk3uknbonouku2fesm4pky
Downscaling Switzerland Land Use/Land Cover Data Using Nearest Neighbors and an Expert System
2022
Land
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The spatial resolution of the resulting LU/LC map was improved by a factor of 16 to reach a resolution of 25 m, while the thematic resolution was increased from 29 (in the base map) to 62 land use categories ...
The method presented in this study is a generalizable approach that can be used to downscale different types of geographic information. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/land11050615
fatcat:ymcotqer2jgn5bgnepaxxgc6za
High-resolution air temperature mapping in urban areas: A review on different modelling techniques
2017
Thermal Science
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the major factors affecting air temperature in urban areas are introduced. ...
Based upon previous studies and developments, the interpolation, regression and coupled simulation techniques show potential for spatio-temporal modelling of air temperature in urban areas. ...
They thank Kristin Krone for her valuable help in the preparation of this paper in journal style format. They also thank Chris Engert and David Mottram for their valuable proof-readings of this paper. ...
doi:10.2298/tsci150922094t
fatcat:rcejiv6rtjdurf27eqwzosdu3q
Urban-Hazard Risk Analysis: Mapping of Heat-Related Risks in the Elderly in Major Italian Cities
2015
PLoS ONE
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night-time land surface temperatures (LST). ...
Short-term impacts of high temperatures on the elderly are well known. ...
b
LST: Land Surface Temperature.
c SD: Standard Deviation. ...
doi:10.1371/journal.pone.0127277
pmid:25985204
pmcid:PMC4436225
fatcat:xrpiw5wgbvb3zpr2xeo5rkqpx4
Estimating Subpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods to MODIS Data
2017
Remote Sensing
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Two temperature-sharpening methods, the disaggregation procedure for radiometric surface temperature (DisTrad) and the geographically-weighted regression (GWR)-based downscaling algorithm, were used to ...
obtain accurate subpixel land surface temperature (LST) within the Zhangye oasis in China, where the surface is heterogeneous. ...
In addition, we thank all of the scientists and engineers who took part in the HiWATER experiment. This
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs9080836
fatcat:htagbpaoqbfnrg7gw4ueya7yyu
Guidelines For Use Of Climate Scenarios Developed From Statistical Downscaling Methods
[article]
2004
Zenodo
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This is especially true for regions of complex topography, coastal or island locations, and in regions of highly heterogeneous land-cover. ...
This guidance documents reviews statistical methods of estimating point climate from coarse scale climate projections. ...
22/27
ACKNOWLEDGEMENTS The authors are extremely grateful to Elaine Barrow, Tim Carter, Bruce Hewitson and John Mitchell for their constructive remarks on earlier versions of the document. ...
doi:10.5281/zenodo.1438319
fatcat:onml7kdsezcypaeloxfgjdgtfi
Downscaling Land Surface Temperature from MODIS Dataset with Random Forest Approach over Alpine Vegetated Areas
2019
Remote Sensing
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Due to the topographical and land-cover complexity and to the sparse distribution of meteorological stations in the region, the remotely-sensed land surface temperature (LST) at regional scale is of major ...
vegetation content (EM1) and (iii) only pixels with 75% threshold of homogeneity for vegetated land-cover classes (EM2). ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs11111319
fatcat:64txde2wpbe6znhbx35djekqvi
The Impact of Climate Change on the Viticultural Suitability of Maipo Valley, Chile
2016
Professional Geographer
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The impact of climate change on viticultural suitability was modeled by overlaying downscaled Global Circulation Model temperature data for two emission scenarios. ...
Using a GIS analysis of topographic, soil, land use and climate data, a baseline assessment of viticultural suitability in the Maipo Valley was performed. ...
Acknowledgements The authors appreciate the contribution of David Poblete and Eduardo Bustos from the Centro de Cambio Global for their help with the downscaling process and trouble-shooting as well as ...
doi:10.1080/00330124.2015.1124788
fatcat:td3g2ydy6fc25oagzl6rhgza6u
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