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Related Concept Videos

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Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a higher temperature. When the...
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Related Experiment Video

Updated: Feb 16, 2026

Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
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A new method to quantify surface urban heat island intensity.

Huidong Li1, Yuyu Zhou2, Xiaoma Li2

  • 1Institute of Meteorology, Freie Universität Berlin, Berlin, Germany.

The Science of the Total Environment
|December 19, 2017
PubMed
Summary

This study introduces a new method to quantify the urban heat island (UHI) effect using land surface temperature and impervious surfaces. The approach improves accuracy by considering neighborhood data, offering a reliable way to assess heat risk.

Keywords:
Footprint of remote sensing observationImpervious surface areaKernel density estimationLand surface temperatureSurface urban heat island

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Area of Science:

  • Environmental Science
  • Remote Sensing
  • Urban Climatology

Background:

  • Quantifying the urban heat island (UHI) effect is crucial for evaluating heat risk.
  • Traditional UHI intensity (UHII) measurements are limited by station or grid selection and urban/rural divisions.
  • A novel approach is needed to overcome these limitations for more reliable SUHII quantification.

Purpose of the Study:

  • To propose and validate a new method for quantifying surface urban heat island intensity (SUHII).
  • To establish a relationship between MODIS land surface temperature (LST) and impervious surface area (ISA).
  • To overcome the limitations of traditional UHII measurement methods.

Main Methods:

  • Regionalizing impervious surface area (ISA) using Kernel Density Estimation (KDE) to incorporate neighborhood pixel information.
  • Analyzing the relationship between MODIS land surface temperature (LST) and the KDE-regionalized ISA (ISAKDE).
  • Defining SUHII as the slope of the linear function fitting the LST-ISAKDE relationship.

Main Results:

  • A strong positive correlation was found between LST and ISAKDE.
  • Linear functions accurately fitted the LST-ISAKDE relationship on annual and daily scales for Berlin.
  • Calculated SUHII values were higher in summer and during the day compared to winter and night.

Conclusions:

  • The proposed method provides a reliable quantification of SUHII by overcoming traditional limitations.
  • The KDE method effectively improves the LST-ISA relationship by considering spatial context.
  • Validation with finer resolution Landsat data confirmed the reliability of the new SUHII quantification approach.