Biodiversity Science ›› 2018, Vol. 26 ›› Issue (8): 819-827.doi: 10.17520/biods.2018052

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Space-air-field integrated biodiversity monitoring based on experimental station

Ainong Li1, *(), Gaofei Yin1, Zhengjian Zhang1, 2, Jianbo Tan1, 2, Xi Nan1, Keping Ma3, Qinghua Guo3   

  1. 1 Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041
    2 University of Chinese Academy of Sciences, Beijing 100049
    3 State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
  • Received:2018-02-11 Accepted:2018-06-24 Online:2018-09-27
  • Li Ainong E-mail:ainongli@imde.ac.cn
  • About author:# Co-first authors

Developing effective policies for biodiversity conservation and restoration policies requires spatially and temporally explicit data on distribution of species and habitats. Remote sensing provides an effective technical tool to meet this requirement. In recent years, the rapid development of integrated multi-platform, multi-scale, multi-mode remote sensing technology the implementation of integrated remote sensing observations across space-air-field provides novel opportunities for biodiversity monitoring. In this paper, we review the main methods of remote sensing that aids biodiversity monitoring and assess existing remote sensing observation experiments. We found that current methods of biodiversity monitoring using remotely-sensed data lacked the support of space-air-field integrated observations and the existing space-air-field integrated observations did not include biodiversity parameters. The Wanglang integrated observation and experiment station for mountain ecological remote sensing illustrates the potential to integrate experimental station-based and space-air-field integrated observations for biodiversity monitoring. Our review highlights that integrating direct observations with remote sensing can provide spatio-temporally explicit information on species and habitats and improve the informed monitoring of biodiversity.

Key words: biodiversity, space-air-field integrated observation, remote sensing, Wanglang

Table 1

Main methods of remote sensing for biodiversity monitoring"

方法
Method
传感器
Sensor
空间分辨率
Spatial resolution
光谱分辨
Spectral resolution
监测内容
Monitoring contents
参考文献
Reference
直接法 Direct approaches
天基遥感
Space-based
IKONOS
Quickbird
WorldView-2
吉林一号 Jilin-1
1-4 m
0.6-2.4 m
0.5 m, 2 m
0.72-2.88 m
4波段 4 bands
4波段 4 bands
8波段 8 bands
4波段 4 bands
冠层、物种信息
Canopy and
species information
Bejarano et al, 2010
Wulder et al, 2008
Petrou et al, 2014
ADS40
AHS-160
CASI
Lidar
0.2 m
2.4 m
1 m
4波段 4 bands
63波段 63 bands
288波段 288 bands
Forzieri et al, 2013
Delalieux et al, 2012
Belluco et al, 2006
Guo et al, 2016
地基遥感
Ground-based
红外相机 Infrared camera
视频监控 Video monitoring
声景监控 Soundscape
可见光、红外
Visible, infrared
可见光、红外
Visible and infrared
物种活动场景
The behavior of species
Xiao et al, 2014
Burton et al, 2015
Towsey et al, 2014
间接法 Indirect approaches
景观指数法
Landscape index
TM/ETM +
HJ
MODIS
EO-1 Hyperion
ASTER
Sentinel-2 MSI
SPOT
CBERS-04
30-120 m
30-100 m
250-1 km
30 m
15 m, 30 m, 90 m
10 m, 20 m, 60 m
1.5 m, 6 m, 1 km
5-80 m
7-9波段 7-9 bands
4波段 4 bands
36波段 36 bands
220波段 220 bands
14波段 14 bands
13波段 13 bands
4-6波段 4-6 bands
12波段 12 bands
土地分类
Land cover classification
Zhong et al, 2014
Wang et al, 2012
Fang et al, 2011
遥感指数法
Satellite index
多样性指数
Biodiversity index
Pu et al, 2010
Reiche et al, 2012
光谱变异性指数法
Spectral
heterogeneity index
光谱异质性指数
Spectral heterogeneity index
Herrmann et al, 2011
Guyon et al, 2011
模型模拟法
Model simulation
TRMM/TMI
FY-3C/VIRR
5-72 km
1 km
5波段 5 bands
10波段 10 bands
物种分布
Species distribution
Zainuddin et al, 2006

Fig. 1

The concepted design of biodiversity monitoring at Wanglang integrated observation and experiment station based on space-air-field integrated remote sensing observation"

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