Forest Area Remote Sensing Monitoring Using the Multi-Level Sampling Interpretation Approach

【Objective】 It is the urgent requirement for forestry that forest resources data and changing information are quickly and effectively acquired by using remote sensing.【Method】 This study built forest resource monitoring approach by combining three levels sampling of remote sensing imagery and field surveying. We chose Liaoning Province as study area to assess our method by using multi-source remote sensing data with high,medium and low spatial resolution from2013 to 2014.【Result】Firstly,we obtained the forest area estimating model by combining separately filed measured plots and high,middle and low resolution remote sensing data. The performance of these three forest area regress model were evaluated and showed high precision( R2= 0. 99,0. 91,0. 70,respectively). Secondly,we estimated the forest area( 590. 83 million hectares) and forest coverage( 40. 54%) of Liaoning Province,respectively. The value of forest coverage is similar to that determined by forest resources inventory( 40. 49%),which proved that the