Ismail, Mohd Hasmadi and Jusoff, Kamaruzaman (2006) Estimating Forest Area using Remote Sensing and Regression Estimator. In: Proceedings of the 2nd WSEAS International Conference on Remote Sensing , December 16-18, 2006, Tenerife, Canary Islands, Spain.
Full text not available from this repository.
Area estimates using remotely sensed data is an important subject that has been investigated around the world during the last decade. It plays an important role in the production of vegetation statistic when area frame sample design is used using regression estimator. This technique is used widely in estimation of crop area and yield. This work is carried out utilizing the same method but tested for the tropical forest in Malaysia. The estimates have been conducted using direct expansion from sample survey and regression estimator approaches. The latter result using regression of ground data and satellite data seem more reliable when training pixels are chosen at random subset of the area sampling frame. The regression analyses showed all the land cover class had a very high correlation (r2 = 0.86 to 0.89). This method is not only practical with accurate estimation for this task but also does not haveany additional time and cost implications.
|Item Type:||Conference or Workshop Item (Paper)|
|Keyword:||Forest, estimation, remote sensing, regression|
|Faculty or Institute:||Faculty of Forestry|
|Deposited By:||Norhazura Hamzah|
|Deposited On:||10 Aug 2010 06:17|
|Last Modified:||10 Aug 2010 06:23|
Repository Staff Only: Edit item detail
Document Download Statistics
This item has been downloaded for since 10 Aug 2010 06:17.