A Spatial Downscaling Method of Multi-factor Remote Sensing Land Surface Temperature Based on Random Forest

A random forest and surface temperature technology, applied to computer parts, instruments, complex mathematical operations, etc., can solve problems such as low precision and unsatisfactory applications, and achieve the effects of improving accuracy and efficiency, expanding depth and breadth, and high efficiency

Active Publication Date: 2021-11-26
HOHAI UNIV
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Problems solved by technology

Therefore, the traditional method has low accuracy for downscaling of large-scale areas with complex land cover types, which cannot meet the needs of applications.

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  • A Spatial Downscaling Method of Multi-factor Remote Sensing Land Surface Temperature Based on Random Forest
  • A Spatial Downscaling Method of Multi-factor Remote Sensing Land Surface Temperature Based on Random Forest
  • A Spatial Downscaling Method of Multi-factor Remote Sensing Land Surface Temperature Based on Random Forest

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Embodiment Construction

[0031] The technical solution of the present invention will be further explained below in conjunction with the accompanying drawings.

[0032] The invention proposes a random forest-based multi-factor remote sensing land surface temperature space downscaling method. Specifically include the following steps:

[0033] Step 1: Obtain remote sensing data and preprocessing. Obtain thermal infrared remote sensing images and multispectral remote sensing images within the study area, and perform preprocessing. The preprocessing used mainly includes image correction, resampling, cropping and other operations. Correct the multispectral and thermal infrared images of remote sensing images, resample the multispectral remote sensing images to the same resolution as the thermal infrared remote sensing images, and uniformly crop them to the same research area, and then perform temperature inversion on the thermal infrared remote sensing images Obtain the surface temperature of the study a...

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Abstract

The invention discloses a random forest-based multi-factor remote sensing land surface temperature space downscaling method. First, a variety of surface parameters that can characterize water bodies, vegetation, buildings, and bare soil are inverted according to the type of land cover, and the surface parameters that have a strong correlation with surface temperature are selected as scale factors through correlation analysis; for deserts, bare soil, etc. For the problem of inaccurate temperature estimation in high-temperature areas, the short-wave infrared band is introduced as a scale factor to improve the downscaling accuracy in high-temperature areas; for the imbalance of randomly selected data in random forests, different regression models are established under different land cover types Using the method of downscaling under different land cover types, high-resolution land surface temperature images are obtained. The present invention has good applicability in large areas or areas with complex surface coverage, and effectively improves the accuracy and efficiency of downscaling.

Description

technical field [0001] The invention belongs to the field of downscaling, and in particular relates to a multi-factor remote sensing surface temperature space downscaling method based on random forest. Background technique [0002] Land Surface Temperature (LST) is an important parameter to characterize surface energy, and an important factor to study and evaluate ecosystems and climate change. Accurate surface temperature products are of great significance for monitoring urban heat islands, ecological environment, agricultural drought, monitoring global climate, estimating soil moisture and other surface processes. The traditional way to obtain surface temperature is through the observation data of surface meteorological stations. The observation station data has high precision and time continuity, but the monitoring coverage area is limited, which is not suitable for large-scale temperature monitoring. At present, the main way to obtain the surface temperature is through ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/18G06K9/00
CPCG06F17/18G06V20/13
Inventor 杨英宝李小龙潘鑫曹晨朱琴黄璐
Owner HOHAI UNIV
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