基于多源空间数据与空地协同的植被覆盖度估算——以东亚干草草原为例

doi:10.13474/j.cnki.11-2246.2022.0007

测绘通报 ›› 2022, Vol. 0 ›› Issue (1): 39-43,55.doi: 10.13474/j.cnki.11-2246.2022.0007

基于多源空间数据与空地协同的植被覆盖度估算——以东亚干草草原为例

柳絮¹, 张宁¹, 徐晓天², 安超¹, 许士翔¹, 李程¹

1. 中国城市规划设计研究院, 北京 100044;
2. 北京市林业果树科学研究院, 北京 100097

收稿日期:2021-02-02 修回日期:2021-08-25 发布日期:2022-02-22
通讯作者: 张宁。E-mail:zhangning0496@163.com
作者简介:柳絮(1989-),男,博士,助理研究员,研究方向为地理信息综合。E-mail:liuxu_ch@pku.edu.cn
基金资助:
国家重点研发计划（2017YFB0503903）

Estimating fractional woody/herbaceous cover based on multiple spatial data and air-ground co-sampling: taking East Asian steppe as an example

LIU Xu¹, ZHANG Ning¹, XU Xiaotian², AN Chao¹, XU Shixiang¹, LI Cheng¹

1. China Academy of Urban Planning & Design, Beijing 100044, China;
2. Institute of Forestry and Pomology, Beijing 100097, China

Received:2021-02-02 Revised:2021-08-25 Published:2022-02-22

摘要/Abstract

摘要： 植被覆盖度是植物生长状态的综合体现，是研究全球变化与植被变化的重要指标。本文基于多源空间数据和地面数据的协同，估算了东亚干草草原木本和草本覆盖度。估算结果表明，多源数据和地面测量数据相融合的方法提高了估算精度；模型对木本覆盖度的估算更稳健；估算结果改善了对草原地区木本覆盖的低估。估算模型有效地反映了草原低矮分散的木本植物，为分析草原大尺度植被覆盖度的格局和动态提供了参考。

关键词: 植被覆盖度, 多源空间数据, 空地协同, 东亚干草草原

Abstract: Fractional vegetation cover is the comprehensive description of vegetation growth, which is a base index for researching the interaction between global change and vegetation patterns. In this paper, we propose an approach for estimating fractional woody and herbaceous cover using multiple spatial datasets and air-ground co-sampling in East Asian steppe. Here are main conclusions:the accuracy of the estimation can be improved within the approach. The results of model evaluation show that the model is more robust when estimating woody cover. This method can response to sparse woody plants and be used for understanding the patterns and dynamics of vegetation cover in large grasslands.

Key words: fractional vegetation cover, multiple spatial data, air-ground co-sampling, East Asian steppe

中图分类号:

P237

柳絮, 张宁, 徐晓天, 安超, 许士翔, 李程. 基于多源空间数据与空地协同的植被覆盖度估算——以东亚干草草原为例[J]. 测绘通报, 2022, 0(1): 39-43,55.

LIU Xu, ZHANG Ning, XU Xiaotian, AN Chao, XU Shixiang, LI Cheng. Estimating fractional woody/herbaceous cover based on multiple spatial data and air-ground co-sampling: taking East Asian steppe as an example[J]. Bulletin of Surveying and Mapping, 2022, 0(1): 39-43,55.

参考文献

[1] CHOPPING M, SU L H, RANGO A, et al. Remote sensing of woody shrub cover in desert grasslands using MISR with a geometric-optical canopy reflectance model[J]. Remote Sensing Environment, 2008, 112(1):19-34.
[2] EUSKIRCHEN E S, BENNETT A P, BREEN A L, et al. Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada[J]. Environment Research Letters, 2016, 11(10):105.
[3] YANG J, WEISBERG P J, BRISTOW N A. Landsat remote sensing approaches for monitoring long-term tree cover dynamics in semi-arid woodlands:comparison of vegetation indices and spectral mixture analysis[J]. Remote Sensing Environment, 2012, 119:62-71.
[4] GITELSON A A, KAUFMAN Y J, STARK R, et al. Novel algorithms for remote estimation of vegetation fraction[J]. Remote Sensing Environment, 2002, 80(1):76-87.
[5] GESSNER U, MACHWITZ M, CONRAD C, et al. Estimating the fractional cover of growth forms and bare surface in savannas. a multi-resolution approach based on regression tree ensembles[J]. Remote Sensing Environment, 2013, 129:90-102.
[6] D'ODORICO P, OKIN G S, BESTELMEYER B T. A synthetic review of feedbacks and drivers of shrub encroachment in arid grasslands[J]. Ecohydrology, 2012, 5(5):520-530.
[7] 沈谦,朱长明, 张新. GF-2支持下的干旱区稀疏植被区植被覆盖度估算[J]. 测绘通报, 2019(7):33-38.
[8] MEDINA E, CUEVAS E, MOLINA S, et al. Structural variability and species diversity of a dwarf Caribbean dry forest[J]. Caribbean Journal of Science, 2010, 46(2-3):203-215.
[9] HANSEN M C, TOWNSHEND J R G, DEFRIES R S, et al. Estimation of tree cover using MODIS data at global, continental and regional/local scales[J]. International Journal of Remote Sensing, 2005, 26(19):4359-4380.
[10] SANKARAN M, HANAN N P, SCHOLES R J, et al. Determinants of woody cover in African savannas[J]. Nature, 2005, 438(7069):846-849.
[11] 张良培, 沈焕锋. 遥感数据融合的进展与前瞻[J]. 遥感学报, 2016, 20(5):1050-1061.
[12] LIU X, LIU H Y, QIU S, et al. An improved estimation of regional fractional woody/herbaceous cover using combined satellite data and high-quality training samples[J]. Remote Sensing, 2017, 9(1):32.
[13] CLARK M L, AIDE T M, GRAU H R, et al. A scalable approach to mapping annual land cover at 250m using MODIS time series data:a case study in the Dry Chaco ecoregion of South America[J]. Remote Sensing Environment, 2010, 114(11):2816-2832.
[14] BASTIN J F, BERRAHMOUNI N, GRAINGER A, et al. The extent of forest in dryland biomes[J]. Science, 2017, 356(6338):635-638.
[15] CLARK M L, ROBERTS D A, EWEL J J, et al. Estima-tion of tropical rain forest aboveground biomass with small-footprint LiDAR and hyperspectral sensors[J]. Remote Sensing Environment, 2011, 115(11):2931-2942.

基于多源空间数据与空地协同的植被覆盖度估算——以东亚干草草原为例

Estimating fractional woody/herbaceous cover based on multiple spatial data and air-ground co-sampling: taking East Asian steppe as an example

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