Indian Forum for Water Adroit

Prediction of High Spatial Resolution LST under Cloudy Conditions

Karthikeyan L

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  • Institute : Indian Institute of Science, Bangalore
  • Programming language : Matlab, R
A work by Shwetha who is a PhD student under Prof. D. Nagesh Kumar has been published recently in ISPRS Journal of Photogrammetry and Remote Sensing.

Article: Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN

Description: Land Surface Temperature (LST) with high spatio-temporal resolution is in demand for hydrology, climate change, ecology, urban climate and environmental studies, etc. Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe to obtain LST, but is incapable of providing this data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements captured by the microwave sensors such as Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 are capable of penetrating through clouds. The current study proposes a methodology by exploring this property to predict high spatio-temporal resolution LST under cloudy conditions during daytime and nighttime without employing in-situ LST measurements. To achieve this, Artificial Neural Networks (ANNs) based models are employed for different land cover classes, utilizing Microwave Polarization Difference Index (MPDI) at finer resolution with ancillary data. MPDI was derived using resampled (from 0.25 to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from AMSR-E and AMSR2 sensors. The proposed methodology is tested over Cauvery basin in India. Results indicated that the proposed methodology performed well for the considered land cover classes.

Citation:
Shwetha, H. R., & Kumar, D. N. (2016). Prediction of high spatio-temporal resolution land surface temperature under cloudy conditions using microwave vegetation index and ANN. ISPRS Journal of Photogrammetry and Remote Sensing, 117, 40-55. http://dx.doi.org/10.1016/j.isprsjprs.2016.03.011

Prof. Nagesh Kumar can be reached at dasikanagesh@gmail.com