Linking remote sensing and ecological vegetation communities: A multivariate approach
2008
Malik, R.N. (Quaid-i-Azam Univ., Islamabad (Pakistan). Dept. of Plant Sciences) | Husain, S.Z. (Fatima Jinnah Women Univ., Rawalpindi (Pakistan). Environmental Sciences Dept.)
In spite of few attempts for mapping land-cover types in Pakistan, remotely sensed data has not been used widely; and its potential is not being explored for providing information on mapping vegetation cover in general and ecological communities in particular. The present study was undertaken in the Lohibehr scrub forest in the Foothills of Himalaya, northeast of Pakistan. The objective of the study was of find out the relationship between remote sensing data and vegetation communities of ecological importance using multivariate techniques such as Two Way Indicator Species Analysis (TWINSPAN), Principal Component Analysis (PCA) and Correspondence Canonical Analysis (CCA). Floristic data were compiled for vegetation types and Digital number (DN) values were extracted from SPOT XS image for visible and near infrared bands (NIR).
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