[1] 王效科, 冯宗炜.中国森林生态系统中植物固定大气碳的潜力[J].生态学杂志, 2000, 19(4):72-74.

WANG Xiaoke, FENG Zongwei. The potential to sequester atmospheric carbon through forest ecosystems in China[J]. Chin J Ecol, 2000, 19(4):72-74.
[2] 胡会峰, 刘国华.中国天然林保护工程的固碳能力估算[J].生态学报, 2006, 26(1):291-296.

HU Huifeng, LIU Guohua. Carbon sequestration of China's National Natural Forest Protection Project[J]. Acta Ecol Sin, 26(1):291-296.
[3] 胡会峰, 刘国华.森林管理在全球CO2减排中的作用[J].应用生态学报, 2006, 17(4):709-714.

HU Huifeng, LIU Guohua. Roles of forest management in global carbon dioxide mitigation[J]. Chin J Appl Ecol, 2006, 17(4):709-714.
[4] 汤旭光, 刘殿伟, 王宗明, 等.森林地上生物量遥感估算研究进展[J].生态学杂志, 2012, 31(5):1311-1318.

TANG Xuguang, LIU Dianwei, WANG Zongming, et al. Estimation of forest aboveground biomass based on remote sensing data:a review[J]. Chin J Ecol, 2012, 31(5):1311-1318.
[5] TOMPPO E. Satellite imagery-based national inventory of Finland[J]. Int Arch Photogramm Remote Sensing, 1991, 28(7/1):419-424.
[6] MCROBERTS R E. Estimating forest attribute parameters for small areas using nearest neighbors techniques[J]. For Ecol Manage, 2012, 272(3):3-12.
[7] MCROBERTS R E, NÆSSET E, GOBAKKEN T. Optimizing the k-Nearest Neighbors technique for estimating forest aboveground biomass using airborne laser scanning data[J]. Remote Sensing Environ, 2015, 163:13-22.
[8] MURA M, MCROBERTS R E, CHIRICI G, et al. Statistical inference for forest structural diversity indices using airborne laser scanning data and the k-Nearest Neighbors technique[J]. Remote Sensing Environ, 2016, 186:678-686.
[9] MCROBERTS R E, DOMKE G M, CHEN Q, et al. Using genetic algorithms to optimize k-Nearest Neighbors configurations for use with airborne laser scanning data[J]. Remote Sensing Environ, 2016, 184:387-395.
[10] MCROBERTS R E, CHEN Q, WALTERS B F. Multivariate inference for forest inventories using auxiliary airborne laser scanning data[J]. For Ecol Manage, 2017, 401:295-303.
[11] KATILA M, TOMPPO E. Stratification by ancillary data in multisource forest inventories employing k-nearest neighbor estimation[J]. Can J For Res, 2002, 32(9):1548-1561.
[12] TOMPPO E, HALME M. Using coarse scale forest variables as ancillary information and weighting of variables in k-NN estimation:a genetic algorithm approach[J]. Remote Sensing Environ, 2004, 92(1):1-20.
[13] TOMPPO E, GAGLIANO C, NATALE F D, et al. Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery[J]. Remote Sensing Environ, 2009, 113(3):500-517.
[14] 陈尔学, 李增元, 武红敢, 等.基于k-NN和Landsat数据的小面积统计单元森林蓄积量估测方法[J].林业科学研究, 2008, 21(6):745-750.

CHEN Erxue, LI Zengyuan, WU Honggan, et al. Forest volume estimation method for small areas based on k-NN and Landsat data[J]. For Res, 2008, 21(6):745-750.
[15] 郭颖.森林地上生物量的非参数遥感估测方法优化[D].北京: 中国林业科学研究院, 2011.

GUO Ying. Optimum Non-Parametric Method for Forest Aboveground Biomass Estimation based on Remote Sensing Data[D]. Beijing: Chinese Academy of Forestry, 2011.
[16] 胥辉, 张会儒.林木生物量模型研究[M].昆明:云南科技出版社, 2002.
[17] CHIRICI G, MURA M, MCINEMEY D, et al. A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data[J]. Remote Sensing Environ, 2016, 176(2):282-294.
[18] 谢福明, 舒清态, 字李, 等.基于k-NN非参数模型的高山松生物量遥感估测研究[J].江西农业大学学报, 2018, 40(4):743-750.

XIE Fuming, SHU Qingtai, ZI Li, et al. Remote sensing estimation of Pinus densata aboveground biomass based on k-NN nonparametric model[J]. Acta Agric Univ Jiangxi, 2018, 40(4):743-750.
[19] BEAUDOIN A, BERNIER P Y, GUINDON L, et al. Mapping attributes of Canada's forests at moderate resolution through k-NN and MODIS imagery[J]. Can J For Res, 2014, 44(5):521-532.
[20] MCROBERTS R E. Estimating forest attribute parameters for small areas using nearest neighbors techniques[J]. For Ecol Manage, 2012, 272(3):3-12.