Implications of atmospheric conditions for analysis of surface temperature variability derived from landscape-scale thermography

Albin Hammerle,Fred Meier,Michael Heinl,Georg Leitinger,Angelika Egger

doi:10.1007/s00484-016-1234-8

Albin Hammerle, Fred Meier + Show 3 more

Open Access

https://doi.org/10.1007/s00484-016-1234-8

Copy DOI

Abstract

Thermal infrared (TIR) cameras perfectly bridge the gap between (i) on-site measurements of land surface temperature (LST) providing high temporal resolution at the cost of low spatial coverage and (ii) remotely sensed data from satellites that provide high spatial coverage at relatively low spatio-temporal resolution. While LST data from satellite (LSTsat) and airborne platforms are routinely corrected for atmospheric effects, such corrections are barely applied for LST from ground-based TIR imagery (using TIR cameras; LSTcam). We show the consequences of neglecting atmospheric effects on LSTcam of different vegetated surfaces at landscape scale. We compare LST measured from different platforms, focusing on the comparison of LST data from on-site radiometry (LSTosr) and LSTcam using a commercially available TIR camera in the region of Bozen/Bolzano (Italy). Given a digital elevation model and measured vertical air temperature profiles, we developed a multiple linear regression model to correct LSTcam data for atmospheric influences. We could show the distinct effect of atmospheric conditions and related radiative processes along the measurement path on LSTcam, proving the necessity to correct LSTcam data on landscape scale, despite their relatively low measurement distances compared to remotely sensed data. Corrected LSTcam data revealed the dampening effect of the atmosphere, especially at high temperature differences between the atmosphere and the vegetated surface. Not correcting for these effects leads to erroneous LST estimates, in particular to an underestimation of the heterogeneity in LST, both in time and space. In the most pronounced case, we found a temperature range extension of almost 10 K.

Highlights

Land surface temperature (LST) is a key variable for numerous environmental functions
The basis of the study was the comparison of surface temperatures measured (i) continuously by infrared radiometers mounted above the canopy, (ii) frequently by a Thermal infrared (TIR) camera operated at an elevated position within the study region, and (iii) by satellite remote sensing
The highest air temperature was measured at the Alte Mendel Strasse site, a site located in close proximity to Bozen/Bolzano (Fig. 1, Table 2)

Summary

Introduction

Land surface temperature (LST) is a key variable for numerous environmental functions. LST has become a basic requirement for model validation or model constraining in surface energy and water budget modelling on various scales (Kalma et al 2008; Kustas and Anderson 2009; and references therein) It serves as a metric for soil moisture and vegetation condition in eco/hydrological modelling and environmental monitoring (Czajkowski et al 2000; Kustas and Anderson 2009) and has been used in the area of thermal anomalies and hightemperature events detection (Sobrino et al 2009; Teuling et al 2010). Remote sensing platforms provide data with global coverage They can routinely either provide LST at a coarse spatial resolution at relatively high overpass frequencies (e.g., Terra-MODIS, Aqua-MODIS, NOAA-AVHRR) or provide less frequent but moderate

Methods

Results

Discussion

Conclusion