
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
  <dc:rights>All rights reserved</dc:rights>
  <dc:creator id="https://orcid.org/0000-0003-1715-1748">Jaramaz, Darko</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-6666-0875">Mrvić, Vesna</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-5848-1551">Pivić, Radmila</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-3865-6529">Tošić, Sonja</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-8308-4582">Sikirić, Biljana</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-5176-9827">Stanojković-Sebić, Aleksandra</dc:creator>
  <dc:creator id="https://orcid.org/0000-0001-5217-3972">Maksimović, Jelena</dc:creator>
  <dc:identifier>https://unilib.phaidrabg.rs/o:1184</dc:identifier>
  <dc:date>2021</dc:date>
  <dc:subject xml:lang="eng"> remote sensing, vegetation indices, NDVI, ARVI, Sentinel-2</dc:subject>
  <dc:title xml:lang="eng">Comparison of NDVI and ARVI vegetation indices: case study in the City of Belgrade, Serbia</dc:title>
  <dc:type>info:eu-repo/semantics/conferenceProceedings</dc:type>
  <dc:language>eng</dc:language>
  <dc:description xml:lang="eng">Abstract: Global climate changes affects plant growth, in the same perspective, rapid and accurate  vegetation mapping has gradually become of key importance for monitoring and assessing  environmental conditions. Remote sensing includes analysis and interpretation of Earth&apos;s  surface digital images, that can be obtained from the airspace and aerospace, as well as  from the terrain surface. In the last few decades, the possibility of obtaining spatially  oriented information by applying remote sensing has drastically increased. Remote  detection enables the analysis of plant cover without physical contact with the examined  objects and can be applied to large-scale areas. Vegetation indices obtained from the  satellite images are simple and efficient algorithms for quantitative and qualitative  assessments of vegetation cover, as well as monitoring of plants condition. NDVI  (Normalized Difference Vegetation Index) is an indicator of vegetation distribution on a  given area, that measures the amount of vegetation through differences between spectral  reflections. ARVI (Atmospherically Resistant Vegetation Index) is a vegetation index  whose values are prone to changes under the influence of atmospheric factors (rain, fog,  smoke, dust, air pollution, etc), and represents corrected NDVI index for the effects of  atmospheric scattering in the red reflection spectrum, using measurements in blue  wavelengths. Previous researches have determined that in areas with high atmospheric  pollution the ARVI index provides better results than the NDVI index. The European  Space Agency (ESA) in 2015 has launched a Sentinel-2 mission as part of the Copernicus  program, the mission consists of two satellites: A (launched on June 23, 2015) and B  (launched on March 7, 2017), which are both equipped with multispectral sensors  resolutions from 10 to 60 m that obtaining 13 bands. The data from the Sentinel-2 mission  in the non-vegetation and vegetation period were used in this study, for the determination  of the NDVI and ARVI indices suitability in urban and rural areas. The study area was the  City of Belgrade, the capital of the Republic of Serbia which has a moderate continental  climate, that covers 322.268 ha, and includes 10 urban and 7 suburban municipalities. The  result obtained with this research displays differences in values between NDVI and ARVI  indexes, and their comparison.</dc:description>
  <dc:description xml:lang="srp">Sažetak</dc:description>
  <dc:description xml:lang="srp">Identifikator monografske publikacije: ISBN 978-86-912877-4-0
</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:format>402022 bytes</dc:format>
  <dc:source>Book of Abstracts of 3rd International and 15th National Congress of Serbian Society of Soil Science “SOILS FOR FUTURE UNDER GLOBAL CHALLENGES”, Soko Banja</dc:source>
</oai_dc:dc>
