- Title
- Identifying tree health using sentinel-2 images: a case study on Tortrix viridana L. infected oak trees in Western Iran
- Creator
- Haghighian, Farshad; Yousefi, Saleh; Keesstra, Saskia
- Relation
- Geocarto International Vol. 37, Issue 1, p. 304-314
- Publisher Link
- http://dx.doi.org/10.1080/10106049.2020.1716397
- Publisher
- Taylor & Francis
- Resource Type
- journal article
- Date
- 2020
- Description
- Forest land has a vital role in our planet ecosystem health. Forest areas are under natural and human pressure worldwide. Pests may have irreparable damages to vegetation cover; Tortrix viridana is one of the most important pests in the western forests of Iran and is mainly hosted by oak trees. In this study the performance of Sentinel-2 images to detect infected oaks by T. viridana in the Zagros forest habitat was considered. Vegetation indices (VIs) were extracted from affected and non-affected areas by T. viridana. The indices indices included normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), infrared percentage vegetation index (IPVI) and inverted red-edge chlorophyll index (IRECI) which were extracted from Sentinel-2 satellite images. The results of the present study show that VIs in affected and non-affected areas of the study site have significant differences at 99% of confidence level. In addition, the Spearman’s correlation coefficients between the VIs values in the affected and non-affected were 0.213, 0.213, 0.168 and 0.121 for IPVI, NDVI, IRECI and SAVI, respectively. This shows that Sentinel-2 images can be used to detect pests in forest areas.
- Subject
- Chaharmahal and Bakhtiari; remote sensing; NDVI; SAVI; IPVI; IRECI
- Identifier
- http://hdl.handle.net/1959.13/1432135
- Identifier
- uon:39020
- Identifier
- ISSN:1010-6049
- Language
- eng
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