33 Annals of Valahia University of Targoviste. Geographical Series (2018), 18(1): 33-40 DOI: 10.2478/avutgs-2018-0004 ISSN (Print): 2393-1485, ISSN (Online): 2393-1493 © Copyright by Department of Geography. Valahia University of Targoviste INVESTIGANTING CORRELATION LST AND VEGETATION INDICES USING LANDSAT IMAGES FOR THE WARMEST MONTH: A CASE STUDY OF IASI COUNTY Paul MACAROF 1 , Stefan GROZA 1 , Florian STATESCU 2 1 “Gheorghe Asachi” Technical University of Iasi, Faculty of Hydrotechnical Engineering, Geodes y and Environmental Engineering, Câmpului Str, Iasi, Romania 2 “Gheorghe Asachi” Technical University of Iasi, Faculty of Hydrotechnical Engineering, Geodesy and Environmental Engineering, Câmpului Str, Iasi, Romania Email: macarofpaul@yahoo.com Abstract In this paper is investigating correlation between land surface temperature and vegetation indices (Normalized Difference Vegetation Index - NDVI, Enhanced Vegetation Index 2 - EVI2 and Modified Soil Adjusted Vegetation Index - MSAVI) using Landsat images for august, the warmest month, for study area. Iaşi county is considered as study area in this research. Study Area is geographically situated on latitude 46°48'N to 47°35'N and longitude 26°29'E to 28°07'E. Land surface temperature (LST) can be used to define the temperature distribution at local, regional and global scale. First use of LST was in climate change models. Also LST is use to define the problems associated with the environment. A Vegetation Indices (VI) is a spectral transformation what suppose spatial-temporal intercomparisons of terrestrial photosynthetic dynamics and canopy structural variations. Landsat5 TM, Landsat7 ETM+ and Landsat8 OLI, all data were used in this study for modeling. Landsat images was taken for august 1994, 2006 and 2016. Preprocessing of Landsat 5/7/8 data stage represent that process that prepare images for subsequent analysis that attempts to compensate/correct for systematic errors. It was observed that the "mean" parameter for LST increased from 1994 to 2016 at approximately 5°C. Analyzing the data from VI, it can be assumed that the built-up area increased for the Iasi county, while the area occupied by dense vegetation has decreased. Many researches indicated that between LST and VI is a linear relationship. It is noted that the R 2 values for the LST-VI correlations decrease from 1994 (i.g.R 2 = 0.72 for LST-NDVI) in 2016 (i.g.R 2 = 0.23 for LST-NDVI). In conclusion, these correlation can be used to study vegetation health, drought damage, and areas where Urban Heat Island can occur. Keywords: Land surface temperature, Landsat, vegetation indices 1. INTODUCTION Local, regional and global change continues in the Earth’s climate since the industrial era starts. Some of the changes happens due to anthropogenic activities and natural phenomena such as: uncontrolled use of groundwater, land cover and land use change (LC-LU), greenhouse gas, rising water demands, deforestation, irrigation activities and urbanization etc. (Penny, Kealhofer, 2005). Since the seventies of the twentieth century, satellite-derived (like Landsat-5/7/8) surface temperature data have been utilized for regional and local climate analysis of different scale (Carlson et al. 1977; Zhu et al., 2016; Demirkesen et al., 2017). Nowadays land surface temperature (LST), according to Orhan, can be used to define the temperature distribution at local, regional and global scale. Also LST is use to define the problems associated with the environment. Using remote sensing (RS) data to determine LST value, is useful