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Evaluation of the NDVI in plant community composition mapping: a case study of Tersakan Valley, Amasya County, Turkey
Date
2009-01-01
Author
DOĞAN, Hakan Mete
Celep, Ferhat
Karaer, Fergan
Metadata
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Mapping the composition of plant community types requires reliable spatial data obtained from field surveys and satellite-derived indices. The normalized difference vegetation index (NDVI) is the simplest and most frequently used index in plant applications. If relationships between the NDVI and plant cover abundance are determined, this information can be used in the mapping process. In this study, we investigated these possible connections for mapping the plant community composition of Tersakan Valley in Turkey. We collected georeferenced cover-abundance (Braun-Blanquet, BB) data from 1077 quadrats in the field, and derived an NDVI raster map from a Landsat Enhanced Thematic Mapper Plus (ETM+) image. Then we classified this NDVI map by using various methods and class numbers. Using bivariate correlation analysis, we explored the relationships between 26 classified NDVI maps and BB, and chose the classified NDVI map with the strongest correlation. We further examined this relationship by using scatter plots, histograms and paired samples t-tests. According to the results, the NDVI (equal-interval 15) classes between 4 and 8 corresponded with the BB classes between 1 and 5, respectively. Using this relationship, the spatial distribution of 43 different plant community compositions were determined in geographic information systems (GIS). The results indicate that the NDVI has the potential to map plant community composition reliably.
Subject Keywords
General Earth and Planetary Sciences
URI
https://hdl.handle.net/11511/66431
Journal
INTERNATIONAL JOURNAL OF REMOTE SENSING
DOI
https://doi.org/10.1080/01431160902918381
Collections
Department of Biology, Article
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BibTeX
H. M. DOĞAN, F. Celep, and F. Karaer, “Evaluation of the NDVI in plant community composition mapping: a case study of Tersakan Valley, Amasya County, Turkey,”
INTERNATIONAL JOURNAL OF REMOTE SENSING
, pp. 3769–3798, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66431.