• Scopus
  • Chinese Science Citation Database (CSCD)
  • A Guide to the Core Journal of China
  • CSTPCD
  • F5000 Frontrunner
  • RCCSE
Advanced search
WANG Xue-jun, MA Wei, HUANG Guo-sheng, CHEN Xin-yun, DANG Yong-feng.. Estimation of forest area by large plot interpretation and division based on remote sensing.[J]. Journal of Beijing Forestry University, 2015, 37(11): 1-9. DOI: 10.13332/j.1000-1522.20150083
Citation: WANG Xue-jun, MA Wei, HUANG Guo-sheng, CHEN Xin-yun, DANG Yong-feng.. Estimation of forest area by large plot interpretation and division based on remote sensing.[J]. Journal of Beijing Forestry University, 2015, 37(11): 1-9. DOI: 10.13332/j.1000-1522.20150083

Estimation of forest area by large plot interpretation and division based on remote sensing.

More Information
  • Received Date: March 19, 2015
  • Published Date: November 29, 2015
  • Based on “forestland spatial distribution” database, multisource remote sensing (RS) data from 2010 to 2013, continuous forest inventory data in 2010 and other forestry management materials, the area of forest and other different land types in Longjiang Forest Industry Group (LFIG, in Heilongjiang Province) was estimated by interpretation and division on RS large plots. Results showed that: 1) 231 large plots with 20 km interval were set in LFIG, and the 4 km×4 km quadrat was suitable for monitoring with variation coefficient of forest land area of 14.41%. 2) Interpretation accuracy of land type area increased with resolution ratio of RS image. Interpretation accuracy of all land types in RS large plots reached 90.68%, highest as 96.82% of that in forestry land. 3) There was no significant difference among forestry land area, which was monitored by large plots at different scales. Forestry land of LFIG monitored by 4 km×4 km large plots occurred in a higher proportion of 89.47% in land, as almost 9 million hectare, which included 8.7 million hectare forest land. 4) Beside enclosure, afforestation was the main practice for the rise in forestland area. Conversely, deforestation, forest harvesting and forestland requisition occupation all caused decline of forestland area. Forestland area presented a net decrease of 59.4 thousand hectare from 2010 to 2013, i.e., an average reduction of 14.8 thousand hectare every year in LFIG. In conclusion, the RS large plot method proposed in this research for dynamic monitoring forest resources is reliable and worthy of promotion to relevant fields.
  • [1]
    HU R Z, LIU H Q. Application of remote sensing technology for crop yield estimation in Europe and US [M]. Beijing: China Meteorological Press, 2002: 69-82.
    [1]
    CHARLES T. Sampling method for estimating change in forest resources [J]. Ecological Application, 1998, 8(2): 228-233.
    [2]
    ROGAN J, FRANKLIN J, Roberts D A. A comparison of methods for monitoring multi-temporal vegetation change using thematic mapper imagery [J]. Remote Sensing of Environment, 2002, 1: 143-156.
    [2]
    LIN C F. Estimating method for forest stock based on satellite image inversion [J]. Forestry Science Technology, 2000, 25(5): 15-17.
    [3]
    LI L F, WANG J F, LIU J Y. Optimization decision of spacial sampling in remote sensing survey [J]. Science in China Series D: Earth Sciences, 2004, 34(10): 975-982.
    [3]
    SAKARI T, ANSSI P. Performance of different spectral and textural aerial photograph features in multi-source forest inventory [J]. Remote Sensing of Environment, 2005, 94: 256-268.
    [4]
    RDER A, UDELHOVEN T, HILL J, et al. Trend analysis of landsat-TM and -ETM+ imagery to monitor grazing impact in a rangeland ecosystem in Northern Greece [J]. Remote Sensing of Environment, 2008, 112: 2863-2875.
    [4]
    SUN Y J. Monitoring and assessment of resources and environment [M]. Beijing: Higher Education Press, 2007: 142.
    [5]
    FRASER R H, OLTHOF I, POULIOT D. Monitoring land cover change and ecological integrity in Canadas National Parks [J]. Remote Sensing of Environment, 2009, 113: 1397-1409.
    [5]
    ZENG W S, CHENG Z C, XIA C Z. A new scheme for coordinating continuous forest inventory withforest management inventory [J].Central South Forest Inventory and Planning,2012, 31(3):1-4.
    [6]
    LI Z X, CAO N X, WANG W Q, et al. Forest resources inventory by multiple order, non-equal probability sampling based on remote sensing technique [J]. Journal of Beijing Forestry College, 1985, 7(2):70-75.
    [6]
    CHHIKARE R S, Houston A G, LUNDGREN J C. Corp acreage estimation using a landsat-based estimator as an auxiliary variable [J]. IEEE Transactions on Geoscience and Remote Sensing, 1985, 24(l): 158-172.
    [7]
    MACDONALD R B, HALL F G. Global crop forecasting[J]. Science, 1980, 208(4445): 670-679.
    [7]
    ZHANG L G, WANG N W. Using stratified sampling technique in torest management survey based on TM image [J]. Anhui Forestry Science Technology, 2000(2): 1-3.
    [8]
    LUO X X. Theoretical and applied research on related sampling techniques of comprehensive forest resource monitoring [D]. Beijing: Beijing Forestry University, 2010.
    [8]
    胡如忠, 刘海启. 遥感技术应用与欧美农作物估产[M]. 北京: 气象出版社, 2002: 69-82.
    [9]
    林春芳. 卫星像片估测森林蓄积量的方法初探[J]. 林业科技, 2000, 25(5): 15-17.
    [9]
    WANG X J. Annual forest resources dynamic monitoring research based on multi-data source in the case of Anshan city[D]. Beijing: Beijing Forestry University, 2013.
    [10]
    李连发, 王劲峰, 刘纪远. 国土遥感调查的空间抽样优化决策[J]. 中国科学D辑:地球科学, 2004, 34(10): 975-982.
    [10]
    State Forestry Administration. Helping the integrated monitoring of forest resources for Anhui Province in 2014 [R]. Beijing: State Forestry Administration, 2014 (2014-05-28)[2015-11-01]. http:www.forestry.gov.cnportalhdys 1517content-680149.html.
    [11]
    MUUKKONEN P, HEISKANEN J. Biomass estimation over a large area based on standwise forest inventory data and ASTER and MODIS satellite data: a possibility to verify carbon inventories [J]. Remote Sensing of Environment, 2007, 107: 617-624.
    [11]
    ZHANG D X, CHEN H L, JI H W, et al. National grating data production methods of land Use [J]. Land and Resources Informatization, 2014(2): 32-39.
    [12]
    SMITH W B. Forest inventory and analysis: a national inventory and monitoring program [J]. Environmental Pollution, 2002, 116: 233-242.
    [13]
    GILLIS M D, OMULE A Y, BRIERIEY T. Monitoring Canada forests: the national forest inventory [J]. The Forestry Chronicle, 2005, 81(2): 214-221.
    [14]
    孙玉军.资源环境监测与评价[M].北京:高等教育出版社,2007: 142.
    [15]
    曾伟生,程志楚,夏朝宗.一种衔接森林资源一类清查和二类调查的新方案[J].中南林业调查规划,2012,31(3):1-4.
    [16]
    李芝喜,曹宁湘,王维勤,等.利用遥感多阶不等概抽样清查森林资源[J].北京林学院学报,1985,7(2):70-75.
    [17]
    章礼拐,汪乃武.利用TM图像进行二类调查中的分层抽样技术[J].安徽林业科技, 2000(2):1-3.
    [18]
    罗仙仙.森林资源综合监测相关抽样技术理论与应用研究[D]. 北京: 北京林业大学, 2010.
    [19]
    王雪军. 基于多源数据源的森林资源年度动态监测研究[D]. 北京:北京林业大学, 2013.
    [20]
    国家林业局. 我院助力安徽省开展2014年度森林资源一体化监测[R].北京:国家林业局,2014(2014-05-28)[2015-11-01]. http:www.forestry.gov.cnportalhdys 1517content-680149.html.
    [21]
    张定祥,陈宏磊,季宏伟,等. 全国土地利用格网数据生产技术方法探讨[J].国土资源信息化, 2014(2): 32-39.
    [22]
    TEERASIT K, MANOJ K A, PRAMOD K V. Super-resolution land cover mapping using a markov random field based approach [J]. Remote Sensing of Environment, 2005, 96: 302-314.
  • Cited by

    Periodical cited type(13)

    1. 聂靖,陆驰,欧光龙,胥辉. 基于Landsat8 OLI遥感因子的思茅松地上生物量二阶抽样估测. 林业资源管理. 2022(06): 68-75 .
    2. 阳帆,白星雯. 森林资源监测地面固定样地优化研究. 林业资源管理. 2022(06): 76-81 .
    3. 王伟,杨净,高显连,曾伟生. 2020年全球森林资源评估遥感调查方法和思考. 林业资源管理. 2021(06): 1-5 .
    4. 曹飞,穆宝慧,徐丹,高乾,孙建欣,孙浩,孙中平. 遥感技术在环境变化监测中的应用进展. 环境与可持续发展. 2020(02): 96-99 .
    5. 辛成锋. 新一轮森林资源二类调查技术要点——以广东省茂名地区为例. 湖南林业科技. 2019(02): 72-76 .
    6. 马炜,张阳武,周天元,蒋亚芳. 基于空间抽样调查的宁夏全区和吴忠市湿地面积估测. 湿地科学. 2019(04): 384-390 .
    7. 刘谦,张煜星,王雪军,王少杰,杨英,I Nengah Suratijaya,Dewayany Sutrisno,Ita Carolita. 东南亚国家森林资源年度遥感监测设计——以印度尼西亚为例. 林业资源管理. 2018(03): 113-120 .
    8. 蒋仟,林辉,严恩萍,罗攀. 基于SPOT5遥感影像分类的抽样技术研究. 西南林业大学学报(自然科学). 2018(03): 145-150 .
    9. 陈宗铸,杨琦,雷金睿,陈小花,李苑菱. 基于激光雷达数据的热带森林冠高模型生成及平均树高估计. 中南林业科技大学学报. 2018(07): 1-7 .
    10. 张煜星,王雪军,黄国胜,党永峰,陈新云. 森林面积多阶遥感监测方法. 林业科学. 2017(07): 94-104 .
    11. 陆月报. 提高森林采伐调查设计精度和效率探讨. 农技服务. 2017(06): 93-94 .
    12. 葛宏立,孟源源. 森林面积不同抽样估计方法的无偏性及有效性分析与证明. 林业资源管理. 2016(04): 47-52 .
    13. 孟源源,葛宏立. 块状与带状森林的面积抽样估计计算机模拟. 林业资源管理. 2016(02): 49-55 .

    Other cited types(9)

Catalog

    Article views (2031) PDF downloads (62) Cited by(22)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return