Skip to main content

Forest cover mapping in Central Spain with IRS-WIFS images and multi-extent textual-contextual measures

Buy Article:

$60.90 plus tax (Refund Policy)

Abstract:

An area of 95 200 km2 in central Spain was mapped using IRS-WiFS data to test the potential use of this imagery for regional cover type mapping. In addition to the original WiFS red and NIR spectral bands, textural-contextual images were computed as means and variances of the NDVI and the NIR and red bands over windows of different sizes (3×3 to 50×50 pixels) and included in the analysis. An iterative classification of the imagery was performed using a maximum likelihood classifier with feature selection by spectral separability indices. Results obtained in this study show that IRS-WiFS is a valuable source of information for forest cover mapping at regional scales. Semi-natural areas (comprising forests, shrubs and grasslands) and forests were classified with 93% and 83% mean accuracy, respectively. The classification accuracy of most cover types increased when textural-contextual information computed over large windows (larger than those reported in the literature) were used for classification in combination with spectral data.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160110069917

Publication date: February 20, 2002

More about this publication?

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Partial Open Access Content
Partial Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more