欢迎访问林草资源研究

Forest and Grassland Resources Research >

2022 , Vol. 0 >Issue 3: 73 - 80

DOI: https://doi.org/10.13466/j.cnki.lyzygl.2022.03.012

Scientific Research

Temporal and Spatial Changes of Natural Forest Loss in Xishuangbanna and its Landscape Ecological Response Based on Landsat Data

  • Yan PENG ,
  • Zhengtao SHI ,
  • Li HE ,
  • Run SHEN ,
  • Rui XU ,
  • Yuehao CHEN
Expand
  • Faculty of Geography,Yunnan Normal University,Kunming 650500,China

Received date: 2022-03-28

  Revised date: 2022-04-21

  Online published: 2022-08-04

Fold

Abstract

This paper extracted natural forest in Xishuangbanna in 1990 and 2019 using random forest method based on Landsat images.Meanwhile,the spatial-temporal variation characteristics and the impact on landscape ecology of natural forest losses in Xishuangbanna were analysed.The results showed that: 1) The area of natural forest in Xishuangbanna showed a variation tendency of continuous decrease from 1990 to 2019,with a decrease area of 369,601hm2,which was mainly converted into economic forest and cultivated land.2)Human activities were the main driving forces of natural forests losses in Xishuangbanna.The rapid population growth and the development of the social economy have increased the demand for agricultural land,thus exacerbating the loss of natural forests,and the loss of natural forests in Mengla County was the most serious.3)The loss of natural forest in Xishuangbanna resulted in severe forest landscape fragmentation,as well as the deterioration of habitat quality and significant edge effect.From 1990 to 2019,the number of natural forest patches increased by 1 950,and the average patch area decreased by 1 996.55 hm2.The landscape shape index increased from 48.06 in 1990 to 82.79 in 2019.

Key words： natural forest loss; landsat data; transfer matrix; landscape ecological response; Xishuangbanna

Cite this article

Yan PENG , Zhengtao SHI , Li HE , Run SHEN , Rui XU , Yuehao CHEN . Temporal and Spatial Changes of Natural Forest Loss in Xishuangbanna and its Landscape Ecological Response Based on Landsat Data[J]. Forest and Grassland Resources Research, 2022 , 0(3) : 73 -80 . DOI: 10.13466/j.cnki.lyzygl.2022.03.012

References

[1] 刘世荣, 马姜明, 缪宁. 中国天然林保护生态恢复与可持续经营的理论与技术[J]. 生态学报, 2015, 35(1):212-218.
[2] 刘世荣, 庞勇, 张会儒, 等. 中国天然林资源保护工程综合评价指标体系与评估方法[J]. 生态学报, 2021, 41(13):5067-5079.
[3] Hansen M C, Wang L, Song X P, et al. The fate of tropical forest fragments[J]. Science Advances, 2020, 6(11):eaax8574.
[4] Terefe B, Kim D G. Shifting cultivation maintains but its conversion to mono-cropping decreases soil carbon and nitrogen stocks compared to natural forest in Western Ethiopia[J]. Plant and Soil, 2020, 453(1):105-117.
[5] Yekwayo I, Pryke J S, Roets F, et al. Surrounding vegetation matters for arthropods of small,natural patches of indigenous forest[J]. Insect Conservation and Diversity, 2016, 9(3):224-235.
[6] Clark M L, Roberts D A, Ewel J J, et al. Estimation of tropical rain forest aboveground biomass with small-footprint lidar and hyperspectral sensors[J]. Remote Sensing of Environment, 2011, 115(11):2931-2942.
[7] Lin C, Thomson G, Popescu S C. An IPCC-compliant technique for forest carbon stock assessment using airborne LiDAR-derived tree metrics and competition index[J]. Remote Sensing, 2016, 8(6): 528.
[8] Ferreira M P, Wagner F H, Aragão L E O C, et al. Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis[J]. ISPRS journal of photogrammetry and remote sensing, 2019, 149:119-131.
[9] 周梅, 李春干, 代华兵. 基于RGB-NDVI图像的桉树人工林区森林覆盖变化年度监测[J]. 南京林业大学学报:自然科学版, 2017, 41(05):65-71.
[10] Gyamfi-Ampadu E, Gebreslasie M. Two Decades Progress on The Application of Remote Sensing for Monitoring Tropical and Sub-Tropical Natural Forests:A Review[J]. Forests, 2021, 12(6):739.
[11] MacDicken K G. Global forest resources assessment 2015:What,why and how?[J]. Forest Ecology and Management, 2015, 352:3-8.
[12] Gyamfi-Ampadu E, Gebreslasie M, Mendoza-Ponce A. Mapping natural forest cover using satellite imagery of Nkandla forest reserve,KwaZulu-Natal,South Africa[J]. Remote Sensing Applications:Society and Environment, 2020, 18:100302.
[13] Cao H, Liu J, Fu C, et al. Urban expansion and its impact on the land use pattern in Xishuangbanna since the reform and opening up of China[J]. Remote Sensing, 2017, 9(2):137.
[14] Xiao C, Li P, Feng Z, et al. Mapping rubber plantations in Xishuangbanna,southwest China based on the re-normalization of two Landsat-based vegetation-moisture indices and meteorological data[J]. Geocarto International, 2021, 36(17):1923-1937.
[15] 杨珏婕, 刘世梁, 赵清贺, 等. 基于网络K函数的西双版纳人工林空间格局及动态[J]. 生态学报, 2011, 31(22):6734-6742.
[16] 李红梅, 马友鑫, 郭宗峰, 等. 基于RS和GIS的西双版纳土地覆被动态变化[J]. 山地学报, 2007(3):280-289.
[17] 周岩, 刘世梁, 谢苗苗, 等. 人类活动干扰下区域植被动态变化--以西双版纳为例[J]. 生态学报, 2021, 41(2):565-574.
[18] 廖谌婳, 李鹏, 封志明, 等. 西双版纳橡胶林面积遥感监测和时空变化[J]. 农业工程学报, 2014, 30(22):170-180.
[19] 刘怡媛, 肖池伟, 李鹏, 等. 基于CR_(NBR)物候算法的西双版纳橡胶成林提取及时空变化研究[J]. 地球信息科学学报, 2019, 21(3):467-474.
[20] 沈润. 西双版纳景观破碎化演变与生态安全格局构建[D]. 昆明: 云南师范大学, 2021.
[21] 刘晓娜, 封志明, 姜鲁光, 等. 西双版纳土地利用/土地覆被变化时空格局分析[J]. 资源科学, 2014, 36(2):233-244.
[22] 朱华, 王洪, 李保贵, 等. 西双版纳森林植被研究[J]. 植物科学学报, 2015, 33(5):641-726.
[23] 宋艳红. 西双版纳橡胶林土壤质量变化特征研究[D]. 昆明: 云南师范大学, 2019.
[24] 彭海英, 史正涛, 童绍玉. 西双版纳地区雾的气候学特征及其影响因素[J]. 地理研究, 2020, 39(8):1907-1919.
[25] 李治, 杨晓梅, 孟樊, 等. 物候特征辅助下的随机森林宏观尺度土地覆盖分类方法研究[J]. 遥感信息, 2013, 28(6):48-55.
[26] Pal M. Random forest classifier for remote sensing classification[J]. International Journal of Remote Sensing, 2005, 26(1):217-222.
[27] 梁继, 王建, 王建华. 基于光谱角分类器遥感影像的自动分类和精度分析研究[J]. 遥感技术与应用, 2002(6):299-303.
[28] 朱筠, 孙九林, 秦奋, 等. 2015年中国1:10万土地覆被数据河南地区精度评价[J]. 中国土地科学, 2019, 33(3):59-67.
[29] Deng X, Liu Q, Deng Y, et al. An improved method to construct basic probability assignment based on the confusion matrix for classification problem[J]. Information Sciences, 2016, 340:250-261.
[30] 任杰, 姜纪沂, 赵振宏, 等. 1980-2015年伊犁盆地土地利用/覆被变化及驱动力研究[J]. 科学技术与工程, 2020, 20(21):8480-8488.
[31] 吴琳娜, 杨胜天, 刘晓燕, 等. 1976年以来北洛河流域土地利用变化对人类活动程度的响应[J]. 地理学报, 2014, 69(1):54-63.
[32] 毛鸿欣, 贾科利, 高曦文, 等. 1980-2018年银川平原土地利用变化时空格局分析[J]. 科学技术与工程, 2020, 20(20):8008-8018.
[33] Guan D, Gao W, Watari K, et al. Land use change of Kitakyushu based on landscape ecology and Markov model[J]. Journal of Geographical Sciences, 2008, 18(4):455-468.
[34] 侯秀英, 黄菲, 赵青, 等. 福建省森林丧失的时空格局演化及其驱动力机制[J]. 山地学报, 2020, 38(6):829-840.
[35] 陈鹏, 潘晓玲. 干旱区内陆流域区域景观生态风险分析--以阜康三工河流域为例[J]. 生态学杂志, 2003(4):116-120.
[36] 刘春霞, 李月臣, 罗茜. 重庆市都市区土地利用/覆盖变化的生态响应研究[J]. 水土保持研究, 2011, 18(1):111-115.
[37] GB/T 21010-2017,土地利用现状分类[S].
[38] Ahrends A, Hollingsworth P M, Ziegler A D, et al. Current trends of rubber plantation expansion may threaten biodiversity and livelihoods[J]. Global Environmental Change, 2015, 34:48-58.
[39] 张卓亚. 西双版纳生态系统格局演变与生态价值响应[D]. 昆明: 昆明理工大学, 2020.
[40] 欧朝蓉. 元谋干热河谷地区生态安全评价研究[D]. 北京: 北京林业大学, 2017.
[41] 华能澜沧江水电有限公司. 华能景洪水电厂日发电超过3000万kW·h[J]. 水力发电, 2009, 35(9):4.
[42] 国家统计局. 云南统计年鉴[M]. 北京: 中国统计出版社, 2019.
[43] 曾辉. 景观生态学[M]. 北京: 高等教育出版社, 2017.
[44] 何承刚, 冯彦, 杨燕平. 西双版纳林地景观演变过程及其驱动力分析[J]. 云南地理环境研究, 2008(5):12-17.
Options
Outlines

/

〈 〉