Random forest downscaling

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August undefined, 2024

WebbAn object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). WebbA methodological framework for the application of downscaling methods, Random Forest Regression (RFR), Thermal sharpening (TsHARP), Pixel block intensity modulation (PBIM), has been proposed to estimate the surface temperature (LST) from MODIS 1000 m to …

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Webbusing random forest model. Since the 1970s, the region has entered a period of low rainfall, and the continuous drought has a ected the distribution and utilization of water resources. has jeep discontinued the cherokee

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Webb22 feb. 2024 · Downscaling satellite-based precipitation to fine scales is crucial for deepening our understanding of global hydrologic cycles and water-related issues. In this study, a novel approach that integrates precipitation zoning with random forest regression is proposed for the spatial downscaling of satellite-based precipitation. Webbweighting [30], random forest , [31]geographic differential analysis (GDA) [32], kriging with external drift (KED) [33], and cokriging (CK). A downscaling–merging (DM) scheme based on random forest and cokriging was adopted in this study. By merging the downscaled satellite precipitation with the gauge WebbCombing Random Forest and Least Square Support Vector Regression for Improving Extreme Rainfall Downscaling 郭振民分類: 期刊 / SCI(Sciences Citation Index) / has jean duhardin won best actor award

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Scilit Article - Spatial Downscaling of Forest Above-Ground …

WebbIn this study, a random forest (RF) -based downscaling approach was applied to downscale the FY3B L2 soil moisture data from 25 -km to 1 -km, synergistically using the optical … WebbThis study presents an evaluation of the random forest algorithm for downscaling MODIS LST, based on the relationship between land surface temperature and static and … boomer scoringWebbIn this study, an Adaptive random forest regression (ARFR) method was developed for LST downscaling at national scale. This study also provided a framework to shift from downscaling single-time image sets to extensive time-series of MOD11A1 LST images in an operational approach (i.e., a 19-years spatiotemporal LST trend analysis over Iran) … boomers corning

"Webb3 dec. 2024 · How can I downscale raster images using basic interpolation methods in Google Earth Engine? For example, I want to resample Landsat image from 30m to 10m, but I cannot find corresponding functions... " - Random forest downscaling

Random forest downscaling

Downscaling MODIS Land Surface Temperature Product Using an …

Webb11 apr. 2024 · In the past years, several studies have shown that ML models such as Long Short-Term Memory Models (LSTM) or Random Forests (RF) are suitable for predicting hydrological variables such as discharge or groundwater levels (Kratzert et al., 2024; Hauswirth et al., 2024; Koch et al., 2024), often even outperforming the conventional … Webb7 mars 2024 · Specifically, optimal predictor variable sets identified by random forest importance ranking, multiple stepwise regression, and Pearson VIF methods were first assessed based on their total explanatory power (R square), followed by reconfirmation of the optimal predictor variable set based on the non-stationarity impact of each variable’s …

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WebbDetails. Geographically Weighted Random Forest (GRF) is a spatial analysis method using a local version of the famous Machine Learning algorithm. It allows for the investigation of the existence of spatial non-stationarity, in the relationship between a dependent and a set of independent variables. WebbRemote sensing images of nighttime lights (NTL) were successfully used at global and regional scales for various applications, including studies on population, politics, economics, and environmental protection. The Suomi National Polar-orbiting Partnership with the Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data has the …

Webb6 apr. 2024 · This article presents a stepwise downscaling approach in that the random forest regression kriging technique is used to downscale census data to multi-resolution gridded population datasets. Using Nanjing, China, as the experimental case, population distribution maps were generated at 100 m, 500 m, and 1 km spatial resolution, and … WebbRandom forest is efficient for the estimation of SIF escape probability. • Only reflectance at red, red-edge and far-red bands are needed for SIF downscaling. • The method is effective for ground-based and airborne SIF measurements. • The relationship between SIF and APAR can be improved by SIF downscaling.

WebbKeywords: GPM; spatial downscaling; random forest; daily precipitation; cokriging; precipitation data merging 1. Introduction As an important part of the energy and material cycles, precipitation is of great signiﬁ-cance to hydrology, meteorology, and ecology [1–3]. The surface process is mostly affected WebbA passionate expert in the use of remote sensing for the societal benefit. My expertise includes the management of complex and international projects in research and development. I elaborate advanced strategies for the integration of earth observation data in state of the art algorithms to provide robust and qualified products that meet tenders …

WebbSeasonal predictability of daily rainfall statistics over Indramayu district, Indonesia

Webb8 juni 2024 · I was thinking to perform a random forest model for each variable, in which I could relate the CHELSA values with variables such as elevation, coordinates xy or aspect. If those models were good enough, I would use them to predict in those 500x500 m or 50x50 m grids, in which I have calculated the same topographic variables. has jeep quality improvedWebbPrincipal component analysis (PCA) is one of the extensively used approaches for reducing the dimensionality of the predictors. However, PCA reduces the efficiency of downscaling models when a nonlinear predictor-predictand relationship exists. To solve this issue, the approach was used to minimise the dimension of the predictor variables. boomers corning menuhttp://jmr.cmsjournal.net/article/doi/10.1007/s13351-021-0023-4 boomers couchWebbThe random forest (RF) algorithm was adopted to obtain its land surface temperature (LST) map with 30-m resolution by downscaling the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product; the remote sensing indices emphasizing different land cover types, LST calculated by the radiative transfer equation, and elevation were … has jean duhardin won best actorWebbDeveloped machine learning-based (Decision Trees, Random Forests, Support Vector Machines, Multi-Layer Perceptron) models for downscaling rainfall from large-scale hydro-climatological variables of NCEP (National Center for … has jeff bezos been to spaceWebb12 sep. 2024 · A spatial random forest downscaling LST method (SRFD) was proposed in this study. Abundant predictor variables—including land surface reflection data, remote … boomers coupon codeWebb3 nov. 2024 · This study proposes an easy-to-use downscaling-calibration method based on a spatial random forest with the incorporation of high-resolution variables. The … has jeff bridges had a stroke