Assessment of Vegetation Cover Using Normalized Difference Vegetation Index Based on Satellite Images: Case Study from Ajloun in Northern Jordan

In this study, the vegetation cover in the Ajloun forest reserve was assessed using moderate spatial resolution satellite images. It was possible to construct maps of the Normalized Difference Vegetation Index (NDVI) for the study area, during the period 2000–2018 using the special QGIS software. Statistical analysis of the minimum NDVI values indicated an increasing trend in the vegetative cover of the study area, where NDVI values were increased from 0.05 to 0.18 during the period 2000–2018. Using satellite images in assessing the vegetation cover is a robust method that saves time and efforts. The results allow conducting a predictive analysis of the dynamics of the state of forest ecosystems based on actual data and will be useful as a tool for decision-makers to make informed decisions for inventory, remote control of logging, assessment of the consequences of fires, forest pathological monitoring, and scientific research. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Авторы
Kurbatova A.I. 1 , Abu-Qdais H.2 , Grigorets E.A. 1 , Kozhevnikova P.V. 1
Сборник материалов конференции
Издательство
Springer Berlin Heidelberg
Язык
Английский
Страницы
1855-1861
Статус
Опубликовано
Год
2021
Организации
  • 1 Faculty of Ecology, Peoples’ Friendship University of Russia (RUDN University), 6, Miklukho-Maklaya Street, Moscow, 117198, Russian Federation
  • 2 Civil Engineering Department, Jordan University of Science & Technology, P.O. Box 3030, Irbid, 22110, Jordan
Ключевые слова
Ajloun; Forest ecosystems; NDVI; Northern jordan; Phytomass reserve; Satellite images
Дата создания
16.12.2021
Дата изменения
22.04.2022
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/76345/
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Другие записи

Kochetkov D., Birukou A., Ermolayeva A.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science and Business Media Deutschland GmbH. Том 12602 LNCS. 2021. С. 369-378