Skip to main content
padlock icon - secure page this page is secure

Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset

Buy Article:

$60.00 + tax (Refund Policy)

The paper describes a remote sensing change detection approach used to assess change on a section of the Kafue Flats floodplain wetland system in southern Zambia, which is under the pressures of reduced regional rainfall and damming and water abstraction by man. Four images from September 1984 (Landsat MSS), 1988 (Landsat MSS), 1991 (Landsat TM) and 1994 (Landsat TM) were used. Being near-anniversary images, the change detection error introduced by mere seasonal differences was minimized. Following atmospheric correction of the reference (1994) image, the images were radiometrically normalized and geometrically registered to a common map projection. Each image was separately classified into categories of open water, dense green vegetation, sparse green vegetation, very sparse green vegetation, dry and burnt land. Similar, supervised maximum likelihood classification procedures were employed on all images. The classified images produced were analysed for change in each land-cover category by overlaying them in a Geographic Information System (GIS) framework. The results indicated spatial reduction in area of dense green vegetation in upstream sections of the wetland. Inter-image changes in this land-cover class could be explained by the variations in the timing of regulated flood events on the Kafue Flats. The methodology employed appears to be applicable to monitoring southern Africa's inland wetland systems.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: June 15, 2000

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
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