Studies On Mass Appraisal Of Chinese Fir Forestland In County Area

In 21st century,with the further development of market economy and forestry system reform,people have gradually realized the forestland value,forestland circulation and transfer have become more frequently.Though forest farmers have owned the management right of mountain forest from the forest right reform,aslo have lost the advantage of forestry scale management.Forest farmers took family as unit,the management was scattered and small scale,if we must evaluate a large number of individual sublots,the present appraisal methods of forestland assets still not adapted to the demands of the development.So,in this paper,intruduced the mass appraisal method into forestland asset appraisal,took county as unit,builded the mass appraisal database of forestland asset,and determined the the mass appraisal model of forestland asset,which could reduce the appraisal cost,improve the appraisal rate,accelerate the appraisal speed,and meet the new social demand of the forestland assets appraisal.Meanwhile,the intruduce of mass appraisal method not only expanded the practical depth and width in forestland assets appraisal,but aslo accelerated the management process of forestland resources assets,protected the value of forestland assets.In this paper,firstly discussed the influence factors on forestland value,finally determined the site quality,stand quality(including stand volume,mean diameter at breast high,mean height),economic quality,forest market price,and rate of return on investment as the build model factors of the mass appraisal model of forestland asset.Based on the collection data of forest resources survey in Shunchang County of Nanping City,and the related technical and economic index,then used the method of forestland evaluation value,calculated the forestland asset value of Chinese Fir sublots that meet the requirement,then bulided the mass appraisal database of forestland asset with these data in Shunchang County.Using the mass appraisal database of forestland asset,builded the mass appraisal model of Chinese Fir forestland resource assets in Shunchang County,respectively calibrated the models with the multiple linear regression technology and BP neural network technology,finally determined the models,and tested the model precision with testing samples.The testing results showed that the multiple linear regression and BP neural network both could more accuratly evalute the Chinese Fir forestland resource assets of county area,the precision could meet the qualification,and in contrast,the model precision which using BP neural network was higher than using the multiple linear regression.In addition,on the base of analyzing the mass appraisal of forestland assets value at static state,analyzed the influence factors on forestland value which constantly changed with the change of time,including the forest market price,production cost, cost of silviculture,rate of return on investment and so on,then used those factors as the build model factors,therefore builded the dynamics mass appraisal model of forestland assets,which could satisfy the realistic forestland assets appraisal.The innovations in this paper: through summarizing and analyzing forefathers research results,and according to practical situation,analyzed the factor of"forestland adopting state"which influenced the forestland value for the first time,have further perfected the influence factor system of forestland value. Besides that,through the study of mass appraisal methord and traditional asset appraisal methord of forestland resource,intruduced the mass appraisal method into asset appraisal of forestland resource for the first time,builded the appraisal models of forestland asset with the multiple linear regression principle and neural network principle,the results have further perfected the methord and theoretical system of forestland asset appraisal, accelerated the management process of forestland resources assets,aslo widen the application and research of mass appraisal technology in the forestry field.