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Estimating forest area using remote sensing and regression estimator

Ismail, Mohd Hasmadi and Jusoff, Kamaruzaman (2006) Estimating forest area using remote sensing and regression estimator. In: 2nd WSEAS International Conference on Remote Sensing, 16-18 Dec. 2006, Tenerife, Canary Islands, Spain. pp. 88-94.

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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
ID Code:7645
Deposited By: Norhazura Hamzah
Deposited On:10 Aug 2010 14:17
Last Modified:09 Jan 2015 11:32

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