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

doi:10.17520/biods.2018052

Abstract

Abstract:

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

Ainong Li, Gaofei Yin, Zhengjian Zhang, Jianbo Tan, Xi Nan, Keping Ma, Qinghua Guo. Space-air-field integrated biodiversity monitoring based on experimental station[J]. Biodiv Sci, 2018, 26(8): 819-827.

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URL: https://www.biodiversity-science.net/EN/10.17520/biods.2018052

https://www.biodiversity-science.net/EN/Y2018/V26/I8/819

Figures/Tables 2

References 63

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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
天基遥感 Space-based	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	冠层、物种信息 Canopy and species information	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
地基遥感 Ground-based	红外相机 Infrared camera 视频监控 Video monitoring 声景监控 Soundscape	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	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	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

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
天基遥感 Space-based	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	冠层、物种信息 Canopy and species information	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
地基遥感 Ground-based	红外相机 Infrared camera 视频监控 Video monitoring 声景监控 Soundscape	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	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	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