Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Grigor Ayvazyan"'
Publikováno v:
Applied Sciences, Vol 14, Iss 22, p 10205 (2024)
Remote sensing (RS) is a compulsory component in studying and monitoring ecosystems suffering from the disruption of natural balance, productivity, and degradation. The current study attempted to assess the feasibility of multisource RS for assessing
Externí odkaz:
https://doaj.org/article/7846c873f1ba4752a5f175ae7cc9fc8d
Autor:
Garegin Tepanosyan, Shushanik Asmaryan, Vahagn Muradyan, Rima Avetisyan, Azatuhi Hovsepyan, Anahit Khlghatyan, Grigor Ayvazyan, Fabio Dell’Acqua
Publikováno v:
Remote Sensing, Vol 15, Iss 11, p 2795 (2023)
Machine learning (ML) was used to assess and predict urban air temperature (Tair) considering the complexity of the terrain features in Yerevan (Armenia). The estimation was performed based on the Partial Least-Squares Regression (PLSR) model with a
Externí odkaz:
https://doaj.org/article/3f93a5cfa6b34b4f8e965966dccff056
Publikováno v:
Geosciences, Vol 12, Iss 11, p 412 (2022)
This paper presents a comprehensive analysis of links between satellite-measured vegetation vigor and climate variables in Armenian mountain grassland ecosystems in the years 1984–2018. NDVI is derived from MODIS and LANDSAT data, temperature and p
Externí odkaz:
https://doaj.org/article/ceef68d1b63d4505b691c99b9006b2be
Autor:
Garegin Tepanosyan, Vahagn Muradyan, Azatuhi Hovsepyan, Grigor Ayvazyan, Rima Avetisyan, Shushanik Asmaryan
Publikováno v:
Global NEST International Conference on Environmental Science & Technology.
As is known, chlorophyll is an important biophysical parameter used to monitor the overall physiological status of plants. The aim of this research was to study the potential of UAV multispectral images for estimating the contents of leaf chlorophyll
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c068b2cb8ebab2079b07151fb0c2488c
https://doi.org/10.30955/gnc2021.00131
https://doi.org/10.30955/gnc2021.00131
Publikováno v:
Geosciences; Volume 12; Issue 11; Pages: 412
This paper presents a comprehensive analysis of links between satellite-measured vegetation vigor and climate variables in Armenian mountain grassland ecosystems in years 1984–2018. NDVI is derived from MODIS and Landsat data, temperature and preci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7437158f3b4d22b6f1e6d976cd26679f
