Comparison of Different Sampling Methods of Forest Land Area Based on 3S Technology—A Case Study of Longquan City

doi:10.13466/j.cnki.lyzygl.2018.03.013

FOREST RESOURCES WANAGEMENT ›› 2018, Vol. 0 ›› Issue (3): 71-74.doi: 10.13466/j.cnki.lyzygl.2018.03.013

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Comparison of Different Sampling Methods of Forest Land Area Based on 3S Technology—A Case Study of Longquan City

HUA Yizhi¹^,²(), GONG Xinye¹^,², HUANG Xingmin¹^,², WEN Xiaorong¹^,²(), LIN Guozhong¹^,²

1. Co-Innovation for Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing 210037,China
2. Forestry College of Nanjing Forestry University,Nanjing 210037,China

Received:2018-03-07 Revised:2018-04-23 Online:2018-06-28 Published:2020-09-20
Contact: WEN Xiaorong E-mail:245390335@qq.com;njw9872@163.com

Abstract

Abstract:

This article takes forest land area in Longquan City of Zhejiang Province as an example,and sets 0.5km×0.5km,1km×1km,1.5km×1.5km and 2km×2km as four kinds of sample frame.With the reliability of 95% and the sampling precision of 85%,simple random sampling,stratified sampling and spatial stratified sampling are conducted.The overall variability index of 1km×1km sampling frame was the smallest,and the sampling plots required was the least.The plots with 1km×1km sampling frame were randomly sampled,stratified sampled,spatial sampling stratified,and spatial sampling stratified has the highest sampling precision.Finally,the spatial resolution of 1km×1km is determined as the optimal solution.The results show that the spatial sampling is a method with low sampling cost,high precision and small relative error in the sampling of forest area.The results provide references for the future forest resources survey at the county level.

Key words: forest area, sampling technique, spatial sampling, Spatial autocorrelation, Longquan City

CLC Number:

S757

HUA Yizhi, GONG Xinye, HUANG Xingmin, WEN Xiaorong, LIN Guozhong. Comparison of Different Sampling Methods of Forest Land Area Based on 3S Technology—A Case Study of Longquan City[J]. FOREST RESOURCES WANAGEMENT, 2018, 0(3): 71-74.

Figures/Tables 7

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References 14

[1]	史京京, 雷渊才, 赵天忠. 森林资源抽样调查技术方法研究进展[J]. 林业科学研究, 2009,22(1):101-108.
[2]	温小荣, 彭世揆, 佘光辉, 等. 地理信息系统在我国林业上应用的进展[J]. 南京林业大学学报:自然科学版, 2005,29(2):73-78.
[3]	张加龙, 张玥. 林地面积空间抽样方法研究[J]. 山东林业科技, 2011,41(2):14-17.
[4]	张小伟, 佘光辉, 温小荣, 等. 空间分层抽样在森林覆盖面积监测中的应用[J]. 南京林业大学学报:自然科学版, 2012,36(3):81-84.
[5]	孙皓晗. 空间分层抽样在森林覆盖监测中的应用研究[D]. 南京:南京林业大学, 2013.
[6]	王海宾, 邓华锋, 程志楚, 等. 基于3S 的森林植被面积空间抽样方法[J]. 森林与环境学报, 2015,35(1):74-80.
[7]	谢进金. 基于遥感抽样技术的平南县森林蓄积量估测[D]. 长沙:中南林业科技大学, 2011.
[8]	Xinliang X U, Zhuang D, Zhang S. Field sampling design for land-use and land-cover changes based on 3S technology—taking heilongjiang province as an example[J]. Remote Sensing Technology & Application, 2002,17(3):135-139.
[9]	何彦然, 彭道黎, 李云霄, 等. 基于不同抽样方案的三峡库区林地面积遥感监测研究[J]. 中南林业科技大学学报, 2015,35(7):50-56.
[10]	姚淑霞, 张铜会. 随机抽样必要样本容量的确定方法及其应用[J]. 干旱区研究, 2012,29(3):547-552.
[11]	杜子芳. 抽样技术及其应用[M]. 北京: 清华大学出版社, 2005.
[12]	孙皓晗, 佘光辉, 温小荣, 等. 空间自相关分析及绿地覆盖率的分层抽样估计[J]. 中南林业科技大学学报, 2012,32(4):75-80.
[13]	温小荣, 蒋丽秀, 刘磊, 等. 江苏省森林生物量与生产力估算及空间分布格局分析[J]. 西北林学院学报, 2014,29(1):36-40.
[14]	Wang D, Zhou Q, Chen Z, et al. Spatial autocorrelation and its influencing factors of the sampling units in a spatial sampling scheme for crop acreage estimation[C]// International Conference on Agro-Geoinformatics. Virginia:IEEE, 2017:1-6.

抽样框大小/(km× km)	总体变异性指数	样本数量/个
0.5×0.5	0.3451	222
1×1	0.2910	149
1.5×1.5	0.3015	151
2×2	0.3417	173

抽样结果	简单随机抽样	基于林地面积比的分层抽样	基于行政区划的空间分层抽样
样本数量/个	106	100	87
抽样成本	100	94	82
总体均值估计	0.7620	0.8527	0.8867
总体均值标准差估计	0.0288	0.0283	0.0492
抽样相对误差估计/%	7.41	6.50	5.32
抽样精度估计/%	92.59	93.50	94.68
林地面积估计/km²	2494.79	2791.74	2903.06
与实际调查面积差值/km²	366.2	69.25	42.07

Comparison of Different Sampling Methods of Forest Land Area Based on 3S Technology—A Case Study of Longquan City

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