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  • Author: Stefan Groza x
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Investiganting Correlation LST and Vegetation Indices Using Landsat Images for the Warmest Month: A Case Study of Iasi County

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 R2 values for the LST-VI correlations decrease from 1994 (i.g.R2= 0.72 for LST-NDVI) in 2016 (i.g.R2= 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.

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Sperm sexing technology - new directions in medicine
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Canine Amniotic Membrane Derived Mesenchymal Stem Cells- Potential Sources for Regenerative Medicine

Abstract

Canine mesenchymal stem cells (MSCs) can be defined with self renew potential and specific differentiation capacity. Amiotic membrane represent an important source of MSCs, which can be harvested by minimally invasive methods. The aim of our study was to evaluate the growth characteristics of canine amniotic membrane derived mesenchymal stem cells. The placenta samples were collected after cesarean section from healthy mixed breed dogs. MSCs isolation was performed using enzymatic method. Isolated cells were cultured in propagation medium: Dulbecco’s Modified Eagle’s Medium/F12 (DMEM/F12, Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco) and 1% antibiotic-antimycotic (Sigma-Aldrich). The medium was changed after 4 days. The cell doubling number, cell proliferation capacity, cell doubling time, daily duplication rate and clonogenic efficacy were evaluated. Our study demonstrate the self renew potential of canine amniotic membrane derived mesenchymal stem cells, and can represent a potential source of stem cells for canine regenerative medicine.

Open access