Land Surface Temperature

A QGIS 3 plugin — Author: Milton Isaya — License: GNU GPL v2+
https://github.com/miltonisaya/landSurfaceTemperature

Overview

This plugin provides a complete, step-by-step workflow for deriving Land Surface Temperature (LST) from satellite thermal infrared imagery using 16 algorithms in the QGIS Processing toolbox. It supports Landsat 5 TM, Landsat 7 ETM+, Landsat 8 TIRS, and ASTER sensors.

Input imagery can be obtained free of charge from USGS EarthExplorer or NASA Earthdata.

Applications

Urban heat island analysis
Drought and vegetation stress monitoring
Agricultural water management
Wildfire burn severity assessment
Climate and land use change studies

Workflow

Compute NDVI from red and near-infrared bands
Convert thermal band digital numbers to spectral radiance
Convert radiance to at-sensor brightness temperature using K1/K2 calibration constants
Estimate land surface emissivity (LSE) using NDVI-based classification
Retrieve land surface temperature using one of six LST algorithms

Supported Sensors

Sensor	Thermal Band(s)
Landsat 5 TM	Band 6
Landsat 7 ETM+	Band 6 (high gain / low gain)
Landsat 8 TIRS	Bands 10 and 11
ASTER	TIR bands 10–14 / VNIR bands 1–3

Algorithms

Vegetation Indices

Algorithm	Description
Landsat NDVI	NDVI from separate Landsat red and NIR band rasters
ASTER NDVI	NDVI from ASTER VNIR multi-band raster (bands 2 and 3)

Radiance

Algorithm	Description
TM Radiance (L5)	Landsat 5 TM thermal band DN to spectral radiance using MTL metadata
ETM+ Radiance (L7)	Landsat 7 ETM+ thermal band DN to spectral radiance (high/low gain)
TIRS Radiance (L8)	Landsat 8 TIRS bands 10/11 DN to spectral radiance with optional calibration offset
ASTER Radiance	ASTER TIR bands 10–14 DN to spectral radiance using unit conversion coefficients

Brightness Temperature

Algorithm	Description
Brightness Temperature	Converts spectral radiance to at-sensor brightness temperature using K1/K2 calibration constants: BT = K2 / ln(K1/L + 1)

Land Surface Emissivity

Algorithm	Description
Zhang LSE	NDVI-threshold classification method (Zhang et al.)
NDVI Threshold LSE	NDVI threshold with proportion of vegetation (Pv) and cavity effect correction
ASTER LSE	ASTER band-specific LSE using NDVI-derived Pv and MODIS emissivity library coefficients

Land Surface Temperature

Algorithm	Description
Planck Equation LST	Emissivity-corrected Planck inversion for all sensors
Mono-Window Algorithm	Qin et al. (2001) — requires atmospheric transmittance and near-surface air temperature
Single Channel Algorithm	Jimenez-Munoz & Sobrino (2003) — requires atmospheric water vapor content
Radiative Transfer Equation	Full atmospheric correction using upwelling and downwelling radiance
ASTER Single Channel	ASTER bands 13/14 LST using MODTRAN4 atmospheric database parameters
ASTER Split-Window	Combines ASTER bands 13 and 14 brightness temperature and emissivity

Temperature output available in Kelvin, Celsius, or Fahrenheit.

Installation

Download or clone this repository.

Copy the entire folder into your QGIS 3 Python plugin directory:

Linux/macOS: ~/.local/share/QGIS/QGIS3/profiles/default/python/plugins/
Windows:     %APPDATA%\QGIS\QGIS3\profiles\default\python\plugins\

Start QGIS and enable the plugin via Plugins > Manage and Install Plugins.
The algorithms will appear in Processing > Toolbox under Land Surface Temperature.

Compiling Resources (optional)

If you modify icons or resources.qrc, recompile with:

pyrcc5 -o resources.py resources.qrc

Requirements

QGIS ≥ 3.0
Python ≥ 3.6
GDAL/OGR (included with QGIS)
NumPy (included with QGIS)

License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 2 of the License, or (at your option) any later version.