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Forest and Grassland Resources Research >

2020 , Vol. 0 >Issue 6: 54 - 60

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2020.06.009

Scientific Research

Research on Rubber Plantation Identification and Suitable Areas Based on Multi-source Remote Sensing Data

  • Yongquan JIANG ,
  • Zhengtao SHI ,
  • Shupeng GAO
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  • Department of Geography,Yunnan Normal University,Kunming 650500,China

Received date: 2020-09-30

  Revised date: 2020-10-26

  Online published: 2021-01-26

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Abstract

Taking Ruili City,Dehong Prefecture,Yunnan Province as the study area,this paper analyzes the spatial distribution characteristics of the rubber forest and its suitable planting areas.Sentinel-2 multi-spectral remote sensing images and MOD13Q1 were used as data sources to identify the rubber forest with the method of supporting vector machine classification.The results show that 1) the identification ability of the combined Sentinel-2 and MOD13Q1 NDVI data for rubber forest was significantly better than using only one kind of Sentinel-2 multi-spectral image or MOD13Q1-NDVI time series data,which achieved high precision identification of rubber forest.The overall identification accuracy is 91.41% and the Kappa coefficient is 0.76.2) By the end of 2019,the rubber planting area in Ruili was 7693.83 hm2,with the elevation range of the main planting area being 682-900 m,accounting for 83.61% of the total planting area;the slope of the main planting area was 5-15°,accounting for 84.61% of the total planting area.3) At present,6,433.11 hm2 of rubber was planted in the suitable areas in Ruili while 1,260.72 hm2 of rubber was not,accounting for 83.61% and 16.39%,respectively.

Key words： multi-source remote sensing data; rubber plantation identification; spatial distribution characteristics; suitable planting areas; Ruili City

Cite this article

Yongquan JIANG , Zhengtao SHI , Shupeng GAO . Research on Rubber Plantation Identification and Suitable Areas Based on Multi-source Remote Sensing Data[J]. Forest and Grassland Resources Research, 2020 , 0(6) : 54 -60 . DOI: 10.13466/j.cnki.lyzygl.2020.06.009

References

[1] 杜香玉. 从战略资源到生态系统遭受破坏——对20世纪以来橡胶引种的认知与反思[J]. 原生态民族文化学刊, 2020,12(1):10-20.
[2] 何康, 黄宗道. 热带北缘橡胶树栽培[M]. 广州: 广东科技出版社, 1987.
[3] 付如作. 瑞丽市橡胶产业发展现状及对策研究[J]. 农业与技术, 2017,37(5):145-147.
[4] Li H, Aide T M, Ma Y, et al. Demand for rubber is causing the loss of high diversity rain forest in SW China[M]// Plant Conservation and Biodiversity.Dordrecht:Springer, 2006: 157-171.
[5] 陈汇林, 陈小敏, 陈珍丽, 等. 基于MODIS遥感数据提取海南橡胶信息初步研究[J]. 热带作物学报, 2010,31(7):1181-1185.
[6] Senf C, Pflugmacher D, Van der Linden S, et al. Mapping rubber plantations and natural forests in Xishuangbanna(Southwest China) using multi-spectral phenological metrics from MODIS time series[J]. Remote Sensing, 2013,5(6):2795-2812.
[7] 高书鹏, 史正涛, 刘晓龙, 等. 基于高时空分辨率可见光遥感数据的热带山地橡胶林识别[J]. 遥感技术与应用, 2018,33(6):1122-1131.
[8] Chen Bangqian, Li Xiangping, Xiao Xiangming, et al. Mapping tropical forests and deciduous rubber plantations in Hainan Island,China by integrating PALSAR 25-m and multi-temporal Landsat images[J]. International journal of applied earth observation and geoinformation, 2016,50:117-130.
[9] Kou Weili, Xiao Xiangming, Dong Jinwei, et al. Mapping deciduous rubber plantation areas and stand ages with PALSAR and Landsat images[J]. Remote Sensing, 2015,7(1):1048-1073.
[10] Pohl C Van Genderen J L. Review article multisensor image fusion in remote sensing:concepts,methods and applications[J]. International journal of remote sensing, 1998,19(5):823-854.
[11] 黄艳, 廖玲. 云研77-2和77-4橡胶树新品种区域性栽培试验初报[J]. 中国热带农业, 2009(2):38-40.
[12] 江爱良. 云南南部、西南部生态气候和橡胶树的引种[J]. 中国农业气象, 1995(5):26-31.
[13] 吴俊. 云南橡胶树气候生态适应性分析[J]. 现代农业科技, 2011(19):308-309.
[14] 德宏州农垦分局. 德宏垦区1982/83年冬期橡胶树寒害调查报告[J]. 云南热作科技, 1984(2):4-8.
[15] 付如作. 瑞丽市橡胶产业发展现状及对策研究[J]. 农业与技术, 2017,37(5):145-147.
[16] 祁栋灵, 王秀全, 左雪冬. 宣贯橡胶树栽培和割胶技术规程提升植胶业科技水平[J]. 热带农业科学, 2008,28(5):50-54.
[17] 康靖. 浅论瑞丽市热带天然林停伐后的保护问题[J]. 农村实用技术, 2020(5):123-124.
[18] 董丽芳, 杨军, 杨涛, 等. 瑞丽市橡胶产业发展现状及对策[J]. 云南农业, 2018(8):42-45.
[19] 陈柳嫱, 刘杰, 杨雯雯. 森林培育对瑞丽市生态环境建设的影响[J]. 绿色科技, 2019(8):128-129.
[20] 尹啟令, 李仕娇, 雷荣华, 等. 瑞丽地区橡胶幼林套种百香果初探[J]. 热带农业科技, 2019,42(4):29-31.
[21] Main-Knorn M, Pflug B, Louis J, et al. Calibration and validation plan for the L2A processor and products of the Sentinel-2 mission[C]// Proceedings of International Symposium on Remote Sensing of Environment.36th International Symposium on Remote Sensing of Environment(ISRSE), 2015.
[22] Emde C, Buras-Schnell R, Kylling A, et al. The libRadtran software package for radiative transfer calculations(version 2.0.1)[J]. Geoscientific Model Development, 2016,9(5):1647-1672.
[23] 罗媛, 谢堂民, 龙显静, 等. 基于红光和近红外反射光谱特征参数反演草地地上生物量[J]. 草原与草坪, 2015,35(5):65-69.
[24] Tucker C J. Red and photographic infrared linear combinations for monitoring vegetation[J]. Remote sensing of Environment, 1979,8(2):127-150.
[25] Haralick R M, Shanmugam K, Dinstein I H. Textural features for image classification[J]. IEEE Trans.SMC, 1973(6):610-621.
[26] 陈强, 田杰, 黄海宁, 等. 基于统计和纹理特征的SAS图像SVM分割研究[J]. 仪器仪表学报, 2013,34(6):214-221.
[27] SL 190-2007,土壤侵蚀分类分级标准[S].
[28] NY/T221-2016,橡胶树栽培技术规程[S].
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