Multiple Linear Regression for Generation of Gap-Free LST Maps in Parts of Eastern Antarctica
D.L Sai Teja1, S. Surya Teja2, Mehanaz Fathima J3, Rajashree Vinod Bothale4, D.S Chandra5
1D.L Sai Teja, Department of Geo Informatics Civil Engineering, KL Deemed to be University, Vijayawada (Andhra Pradesh), India.
2S. Surya Teja, Department of Geo Informatics Civil Engineering, KL Deemed to be University, Vijayawada (Andhra Pradesh), India.
3Mehanaz Fathima J, Aerial Services, Digital Mapping, National Remote Sensing Centre, ISRO, Hyderabad (Telangana), India.
4Rajashree Vinod Bothale, Aerial Services, Digital Mapping & Outreach Area, National Remote Sensing Centre, ISRO, Hyderabad (Telangana), India.
5D. Satish Chandra, Department of Civil Engineering, KL Deemed to be University, Vijayawada (Andhra Pradesh), India.
Manuscript received on 04 May 2019 | Revised Manuscript received on 16 May 2019 | Manuscript Published on 28 May 2019 | PP: 780-784 | Volume-7 Issue-6C2 April 2019 | Retrieval Number: F11440476C219/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Remote sensing methods have large potential in Antarctica atmospheric studies due to remoteness and sparseness of weather station. Land surface temperature (LST) is the skin temperature of the surface and it is used for wide variety of applications. MODIS aboard Aqua and Terra satellites are widely used to acquire LST products because of their high temporal resolution and with smaller LST errors when compared to other sensors. The data has large gaps in LST calculations due to its sensitivity to the particles present in the atmosphere. Multiple linear regression is used to generate missing pixels in MODIS data which uses parameters like elevation, latitude & longitude. Temperature reduces as we go away from shoreline in Antarctica; distance from the coast is also used as one parameter in the analysis. The results are compared with the output generated using spatial interpolation technique. This methodology shows better results for calculating missing pixels in homogeneous areas with snow and ice cover.
Keywords: Land Surface Temperature, MODIS, Aqua, Terra, Antarctica, Multiple Linear Regression Analysis.
Scope of the Article: Structural Reliability Analysis