中国生物多样性核心监测指标遥感产品体系构建与思考

doi:10.17520/biods.2022530

生物多样性 ›› 2022, Vol. 30 ›› Issue (10): 22530. DOI: 10.17520/biods.2022530

中国生物多样性核心监测指标遥感产品体系构建与思考

任淯¹^,², 陶胜利², 胡天宇³^,⁴, 杨海涛¹, 关宏灿¹^,², 苏艳军³^,⁴, 程凯¹^,², 陈梦玺¹, 万华伟⁵, 郭庆华¹^,²^,^*()

1.北京大学地球与空间科学学院遥感与地理信息研究所, 北京 100871
2.北京大学城市与环境学院生态研究中心, 北京 100871
3.中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
4.中国科学院大学, 北京 100049
5.生态环境部卫星环境应用中心, 北京 100094

收稿日期:2022-09-15 接受日期:2022-11-07 出版日期:2022-10-20 发布日期:2022-11-11
通讯作者: 郭庆华
作者简介:* E-mail: guo.qinghua@pku.edu.cn
基金资助:
国家自然科学基金(31971575);中国科学院战略性科技先导专项(A类)(XDA19050401);国家重点研发计划(2021YFB3901102)

The outlook and system construction for monitoring Essential Biodiversity Variables based on remote sensing: The case of China

Yu Ren¹^,², Shengli Tao², Tianyu Hu³^,⁴, Haitao Yang¹, Hongcan Guan¹^,², Yanjun Su³^,⁴, Kai Cheng¹^,², Mengxi Chen¹, Huawei Wan⁵, Qinghua Guo¹^,²^,^*()

1. Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871
2. Institute of Ecology, College of Urban and Environmental Sciences, Peking University, Beijing 100871
3. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
4. University of Chinese Academy of Sciences, Beijing 100049
5. Satellite Environmental Application Center of Ministry of Ecology and Environment, Beijing 100094

Received:2022-09-15 Accepted:2022-11-07 Online:2022-10-20 Published:2022-11-11
Contact: Qinghua Guo

摘要/Abstract

摘要：

生物多样性的稳定维持关乎人类生存发展与地球健康。生物多样性核心监测指标(Essential Biodiversity Variables, EBVs)旨在结合地面调查与遥感技术, 为大尺度、长时间序列的生物多样性监测提供新的解决方案。然而, 目前学界仍然缺乏一套国家尺度标准化EBVs遥感监测产品数据集, 以进行生物多样性评估。本研究旨在对中国生物多样性核心监测指标遥感产品进行体系构建与思考, 首先综述了目前EBVs的遥感研究概况, 并根据EBVs研究文献的数量进行调研分析; 同时, 本文在已有遥感生物多样性产品优先标准的基础上, 添加了“可重复性”的新标准, 并据此构建了中国EBVs遥感产品体系与监测数据集的指标清单, 最终对中国EBVs遥感研究存在的问题进行思考与讨论。本研究可为中国的生物多样性遥感监测提供科学依据, 有望为中国生物多样性政策的制定提供支撑。

关键词: 生物多样性核心监测指标(Essential Biodiversity Variables, EBVs), 遥感, 生物多样性, 物种种群, 物种性状, 群落组成, 生态系统功能, 生态系统结构

Abstract

Background: Maintaining biodiversity is crucial to human beings. In recent years, the concept of Essential Biodiversity Variables (EBVs) has provided new insights into large-scale and long-time biodiversity monitoring. Looking at EBVs from a national monitoring perspective, some EBVs are anticipated to correspond with remote sensing-derived variables since remote sensing is the potential methodology able to offer globally qualified data with a high spatial and temporal resolution. However, the academic community still lacks consensual remote sensing variables that can correspond with EBVs solidly.
Aims: This study aims to (1) review the current researches of remote sensing on EBVs; (2) propose a new criterion called “repeatability” on the basis of the current four remote sensing biodiversity product prioritization criteria; (3) construct a list of remote sensing products for EBVs in China based on these criteria.
Problems & Prospects: First of all, there is a lack of systematic research on EBVs in China. Second, the potential of domestic satellites is not exploited enough. Third, some EBVs remote sensing products are not yet “repeatable”. In the future, there is a need to promote cooperation among scientists in the fields of ecology, remote sensing, and aerospace to further promote scientific research on the combination of EBVs and remote sensing.

Key words: Essential Biodiversity Variables (EBVs), remote sensing, biodiversity, species populations, species traits, community composition, ecosystem functioning, ecosystem structure

任淯, 陶胜利, 胡天宇, 杨海涛, 关宏灿, 苏艳军, 程凯, 陈梦玺, 万华伟, 郭庆华 (2022) 中国生物多样性核心监测指标遥感产品体系构建与思考. 生物多样性, 30, 22530. DOI: 10.17520/biods.2022530.

Yu Ren, Shengli Tao, Tianyu Hu, Haitao Yang, Hongcan Guan, Yanjun Su, Kai Cheng, Mengxi Chen, Huawei Wan, Qinghua Guo (2022) The outlook and system construction for monitoring Essential Biodiversity Variables based on remote sensing: The case of China. Biodiversity Science, 30, 22530. DOI: 10.17520/biods.2022530.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2022530

https://www.biodiversity-science.net/CN/Y2022/V30/I10/22530

图/表 6

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序号 Number	优先原则 Prioritization criteria	描述 Description
1	关联性 Relevance	遥感生物多样性产品的使用目的与方法决定了关联性的强弱。主要关注以下方面与遥感生物多样性产品的相关性: (1)管理问题; (2)为CBD目标提供信息; (3)为SDGs提供信息; (4)为生物多样性和生态系统服务政府间科学政策平台(IPBES)的风险评估过程提供数据。It is known who wants the remote sensing biodiversity product, what they will do with it and how it will be used. The remote sensing biodiversity product is relevant: (1) for management questions; (2) to inform the CBD targets; (3) to inform the SDGs; and (4) to provide data for the IPBES risk assessment processes.
2	可行性 Feasibility	可行性这一标准考虑了遥感数据的可用性、获取数据的便利性、遥感在时空尺度的完整性以及数据整合与分析的便利性和经济性。This criterion considers the availability of remote sensing data, the ease of access to such data, the completeness of remote sensing in space and time and the ease and affordability of data integration and analysis.
3	准确性(遥感状态) Accuracy (remote sensing status)	准确性是指衡量某一遥感生物多样性产品观测准确性的标准, 该标准考虑了遥感数据以及获取精准遥感生物多样性产品技术的有效性。A measure of the current activity for the accurate observation of a given remote sensing biodiversity product. This criterion considers the effectiveness of remote sensing data and techniques to achieve an accurate and precise value of the remote sensing-enabled biodiversity product.
4	成熟度(遥感状态) Maturity (remote sensing status)	成熟度这项标准指的是目前遥感生物多样性产品是否成熟且其程度如何, 即有能力生产遥感生物多样性产品的组织/机构是否可以向资助机构提出产品生产建议, 以及该项任务完成的难度如何。Maturity refers to the maturity and status of the current remote sensing biodiversity products. Institutions/organizations with hopes to generate remote sensing biodiversity products can be identified and/or proposed to a funding body.
5	可重复性(新添加) Repeatability (new addition)	可重复性主要描述某一遥感生物多样性产品在未来预期能够按照一定时间分辨率获取的能力, 即评判能否按照预期规律性获取遥感生物多样性产品及该需求的难度。Repeatability mainly describes the ability of a certain remotely sensed biodiversity product to be expected to be accessible at a certain temporal resolution in the future, i.e., it judges whether the remotely sensed biodiversity product can be accessed with the expected regularity and the difficulty of that demand.

序号 Number	优先原则 Prioritization criteria	描述 Description
1	关联性 Relevance	遥感生物多样性产品的使用目的与方法决定了关联性的强弱。主要关注以下方面与遥感生物多样性产品的相关性: (1)管理问题; (2)为CBD目标提供信息; (3)为SDGs提供信息; (4)为生物多样性和生态系统服务政府间科学政策平台(IPBES)的风险评估过程提供数据。It is known who wants the remote sensing biodiversity product, what they will do with it and how it will be used. The remote sensing biodiversity product is relevant: (1) for management questions; (2) to inform the CBD targets; (3) to inform the SDGs; and (4) to provide data for the IPBES risk assessment processes.
2	可行性 Feasibility	可行性这一标准考虑了遥感数据的可用性、获取数据的便利性、遥感在时空尺度的完整性以及数据整合与分析的便利性和经济性。This criterion considers the availability of remote sensing data, the ease of access to such data, the completeness of remote sensing in space and time and the ease and affordability of data integration and analysis.
3	准确性(遥感状态) Accuracy (remote sensing status)	准确性是指衡量某一遥感生物多样性产品观测准确性的标准, 该标准考虑了遥感数据以及获取精准遥感生物多样性产品技术的有效性。A measure of the current activity for the accurate observation of a given remote sensing biodiversity product. This criterion considers the effectiveness of remote sensing data and techniques to achieve an accurate and precise value of the remote sensing-enabled biodiversity product.
4	成熟度(遥感状态) Maturity (remote sensing status)	成熟度这项标准指的是目前遥感生物多样性产品是否成熟且其程度如何, 即有能力生产遥感生物多样性产品的组织/机构是否可以向资助机构提出产品生产建议, 以及该项任务完成的难度如何。Maturity refers to the maturity and status of the current remote sensing biodiversity products. Institutions/organizations with hopes to generate remote sensing biodiversity products can be identified and/or proposed to a funding body.
5	可重复性(新添加) Repeatability (new addition)	可重复性主要描述某一遥感生物多样性产品在未来预期能够按照一定时间分辨率获取的能力, 即评判能否按照预期规律性获取遥感生物多样性产品及该需求的难度。Repeatability mainly describes the ability of a certain remotely sensed biodiversity product to be expected to be accessible at a certain temporal resolution in the future, i.e., it judges whether the remotely sensed biodiversity product can be accessed with the expected regularity and the difficulty of that demand.

遥感产品 Remote sensing product				数据名称 Data name		卫星平台 Satellite platform		获取时间 Acquire time		时间分辨率 Time resolution		空间分辨率/比例尺 Spatial resolution /Scale		可重复性 Repeata- bility	下载链接 Download link
生态系统功能 Ecosystem functioning
叶面积指数 LAI				MCD15A3H v006		MODIS		2000-present		4 d		500 m		1	https://lpdaac.usgs.gov/products/mcd15a3hv006/
				CGLS-LAI300		Sentinel-3/ PROBA-V		2014-present		10 d		300 m			https://land.copernicus.eu/global/products/lai
				GLASS-LAI		AVHRR		1981-2018		8 d		0.05°		1	http://www.glass.umd.edu/
光合有效辐射分量 FAPAR				MCD15A3H v061		MODIS		2002-present		8 d		500 m			https://lpdaac.usgs.gov/products/mcd15a2hv061/
				CGLS-FAPAR300		Sentinel-3/ PROBA-V		2014-present		10 d		300 m			https://land.copernicus.eu/global/products/fapar
				GLASS-FAPAR		AVHRR		1981-2018		8 d		0.05°			http://www.glass.umd.edu/
蒸散 ET				MOD16A2 v006		MODIS		2001-present		8 d		500 m		1	https://lpdaac.usgs.gov/products/mod16a2v006/
蒸散 ET				GLASS-ET		MODIS		2000-2018		8 d		1 km, 0.05°		1	http://www.glass.umd.edu/Download.html
净初级生产力 NPP				MOD17A3Hv006		MODIS		2001-present		Yearly		500 m			https://lpdaac.usgs.gov/products/mod17a3hv006/
总初级生产力 GPP				MOD17A2HGF v061		MODIS		2000-present		8 d		1 km		1	https://lpdaac.usgs.gov/products/mod17a2hgfv061/
				NIRv-GPP		AVHRR		1982-2018		Monthly		0.05°			https://doi.org/10.12199/nesdc.ecodb.2016YFA0600200.02.002
				GLASS-GPP		MODIS		2000-2020 2000-2020		8 d		500 m, 0.05°			http://www.glass.umd.edu/
叶绿素荧光 SIF				OCO2_L2_Lite_SIF 10r		OCO-2		2014-2022		16 d		2.25 km		1	https://disc.gsfc.nasa.gov/datasets?keywords=OCO2%20SIF&page=1
				OCO2_L2_Lite_SIF 11r		OCO-2		2019-2022		16 d		2.25 km			https://disc.gsfc.nasa.gov/datasets?keywords=OCO2%20SIF&page=1
				OCO3_L2_Lite_SIF 10r		ISS OCO-3		2019-2022		16 d		2.25 km			https://disc.gsfc.nasa.gov/datasets?keywords=OCO2%20SIF&page=1
				Tansat-SIF		TanSat		2017-2019		Daily		2 km			http://www.geodata.cn/data/datadetails.html?dataguid=3695497&docId=10126
叶绿素含量 Chlorophyll content				Chl_leaf		ENVISAT- MERIS		2011		7 d		300 m		2	https://doi.org/10.1016/j.rse.2019.111479
物候 Phenology				MCD12Q2 v006		MODIS		2001-2019		Yearly		500 m		1.5	https://lpdaac.usgs.gov/products/mcd12q2v006/
叶片性状 Leaf traits	叶片磷含量 LPC 比叶面积 LA 叶片干物质含量 LDMC			Global trait maps		2015		-		-		1 km, 3 km		2.5	https://www.try-db.org/TryWeb/Data.php#59
生物量 Biomass			China forest Aboveground Biomass (AGB) map			ICESat/ GLAS, MODIS		2004		-		1 km		2	http://www.3decology.org/dataset-software/
生物量 Biomass			Global Aboveground Biomass (AGB) Map (version: V02)			MODIS/ GLAS		2005		-		1 km			http://www.glass.umd.edu/
遥感产品 Remote sensing product				数据名称 Data name		卫星平台 Satellite platform		获取时间 Acquire time		时间分辨率 Time resolution		空间分辨率/比例尺 Spatial resolution /Scale	可重复性 Repeata- bility		下载链接 Download link
生态系统结构 Ecosystem structure
植被连续覆盖/全球森林覆盖变化 VCF/GFCC		Global 2010 Tree Cover (30 m)			Landsat		2010		-		30 m		2		https://glad.umd.edu/dataset/global-2010-tree-cover-30-m
土地覆盖 LC		MCD12Q1 v006			MODIS		2001-2020		Yearly		500 m		1.5		https://lpdaac.usgs.gov/products/mcd12q1v006/
		GlobeLand30			Landsat		2000, 2010, 2020		-		30 m				http://www.globallandcover.com/
		FROM_GLC30			Landsat		2010, 2015, 2017		-		30 m				http://data.ess.tsinghua.edu.cn/
		GLC_FCS30			Landsat		1985-2020		Every 5 years		30 m				https://data.casearth.cn/thematic/glc_fcs30?lang=zh_CN
火烧迹地 BA		MCD64A1 v006			MODIS		2000-present		Monthly		500 m		1.5		https://lpdaac.usgs.gov/products/mcd64a1v006/
火烧迹地 BA		Burnt Area 300m			Sentinel-3/OLCI, SLSTR, PROBA-V		2014-2020		10 d/monthly		300 m				https://land.copernicus.eu/global/products/ba
植被覆盖度 FCover		FCover			Sentinel-3/OLCI, PROBA-V		2014-present		10 d		300m		1.5		https://land.copernicus.eu/global/products/fcover
植被覆盖度 FCover		Fractional Vegetation Coverage (FCover) (version: V40)			MODIS		2000-2018		8 d		500 m				http://www.glass.umd.edu/
冰面范围 IE		MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 6			MODIS		2000-present		5 mins		1 km		1		https://nsidc.org/data/mod29/versions/6#anchor-1
冰面范围 IE		SMOS L3 Sea Ice Thickness			SMOS		2010-present		Daily		12.5 km				https://earth.esa.int/eogateway/catalog/smos-l3-sea-ice-thickness
栖息地异质性 Habitat heterogeneity		Global Habitat Heterogeneity			MODIS		2005		-		1 km, 5 km, 25 km		2		http://www.earthenv.org/texture
森林冠层高度 Forest canopy height		Forest tree height map of China			GEDI, ICESAT2		2019		-		30 m		2.5		http://www.3decology.org/dataset-software/
植被类型 Vegetation type		An updated Vegetation Map of China (1:1000,000)			Landsat		2018		-		1:1,000,000		2.5		http://www.3decology.org/dataset-software/

遥感产品 Remote sensing product				数据名称 Data name		卫星平台 Satellite platform		获取时间 Acquire time		时间分辨率 Time resolution		空间分辨率/比例尺 Spatial resolution /Scale		可重复性 Repeata- bility	下载链接 Download link
生态系统功能 Ecosystem functioning
叶面积指数 LAI				MCD15A3H v006		MODIS		2000-present		4 d		500 m		1	https://lpdaac.usgs.gov/products/mcd15a3hv006/
				CGLS-LAI300		Sentinel-3/ PROBA-V		2014-present		10 d		300 m			https://land.copernicus.eu/global/products/lai
				GLASS-LAI		AVHRR		1981-2018		8 d		0.05°		1	http://www.glass.umd.edu/
光合有效辐射分量 FAPAR				MCD15A3H v061		MODIS		2002-present		8 d		500 m			https://lpdaac.usgs.gov/products/mcd15a2hv061/
				CGLS-FAPAR300		Sentinel-3/ PROBA-V		2014-present		10 d		300 m			https://land.copernicus.eu/global/products/fapar
				GLASS-FAPAR		AVHRR		1981-2018		8 d		0.05°			http://www.glass.umd.edu/
蒸散 ET				MOD16A2 v006		MODIS		2001-present		8 d		500 m		1	https://lpdaac.usgs.gov/products/mod16a2v006/
蒸散 ET				GLASS-ET		MODIS		2000-2018		8 d		1 km, 0.05°		1	http://www.glass.umd.edu/Download.html
净初级生产力 NPP				MOD17A3Hv006		MODIS		2001-present		Yearly		500 m			https://lpdaac.usgs.gov/products/mod17a3hv006/
总初级生产力 GPP				MOD17A2HGF v061		MODIS		2000-present		8 d		1 km		1	https://lpdaac.usgs.gov/products/mod17a2hgfv061/
				NIRv-GPP		AVHRR		1982-2018		Monthly		0.05°			https://doi.org/10.12199/nesdc.ecodb.2016YFA0600200.02.002
				GLASS-GPP		MODIS		2000-2020 2000-2020		8 d		500 m, 0.05°			http://www.glass.umd.edu/
叶绿素荧光 SIF				OCO2_L2_Lite_SIF 10r		OCO-2		2014-2022		16 d		2.25 km		1	https://disc.gsfc.nasa.gov/datasets?keywords=OCO2%20SIF&page=1
				OCO2_L2_Lite_SIF 11r		OCO-2		2019-2022		16 d		2.25 km			https://disc.gsfc.nasa.gov/datasets?keywords=OCO2%20SIF&page=1
				OCO3_L2_Lite_SIF 10r		ISS OCO-3		2019-2022		16 d		2.25 km			https://disc.gsfc.nasa.gov/datasets?keywords=OCO2%20SIF&page=1
				Tansat-SIF		TanSat		2017-2019		Daily		2 km			http://www.geodata.cn/data/datadetails.html?dataguid=3695497&docId=10126
叶绿素含量 Chlorophyll content				Chl_leaf		ENVISAT- MERIS		2011		7 d		300 m		2	https://doi.org/10.1016/j.rse.2019.111479
物候 Phenology				MCD12Q2 v006		MODIS		2001-2019		Yearly		500 m		1.5	https://lpdaac.usgs.gov/products/mcd12q2v006/
叶片性状 Leaf traits	叶片磷含量 LPC 比叶面积 LA 叶片干物质含量 LDMC			Global trait maps		2015		-		-		1 km, 3 km		2.5	https://www.try-db.org/TryWeb/Data.php#59
生物量 Biomass			China forest Aboveground Biomass (AGB) map			ICESat/ GLAS, MODIS		2004		-		1 km		2	http://www.3decology.org/dataset-software/
生物量 Biomass			Global Aboveground Biomass (AGB) Map (version: V02)			MODIS/ GLAS		2005		-		1 km			http://www.glass.umd.edu/
遥感产品 Remote sensing product				数据名称 Data name		卫星平台 Satellite platform		获取时间 Acquire time		时间分辨率 Time resolution		空间分辨率/比例尺 Spatial resolution /Scale	可重复性 Repeata- bility		下载链接 Download link
生态系统结构 Ecosystem structure
植被连续覆盖/全球森林覆盖变化 VCF/GFCC		Global 2010 Tree Cover (30 m)			Landsat		2010		-		30 m		2		https://glad.umd.edu/dataset/global-2010-tree-cover-30-m
土地覆盖 LC		MCD12Q1 v006			MODIS		2001-2020		Yearly		500 m		1.5		https://lpdaac.usgs.gov/products/mcd12q1v006/
		GlobeLand30			Landsat		2000, 2010, 2020		-		30 m				http://www.globallandcover.com/
		FROM_GLC30			Landsat		2010, 2015, 2017		-		30 m				http://data.ess.tsinghua.edu.cn/
		GLC_FCS30			Landsat		1985-2020		Every 5 years		30 m				https://data.casearth.cn/thematic/glc_fcs30?lang=zh_CN
火烧迹地 BA		MCD64A1 v006			MODIS		2000-present		Monthly		500 m		1.5		https://lpdaac.usgs.gov/products/mcd64a1v006/
火烧迹地 BA		Burnt Area 300m			Sentinel-3/OLCI, SLSTR, PROBA-V		2014-2020		10 d/monthly		300 m				https://land.copernicus.eu/global/products/ba
植被覆盖度 FCover		FCover			Sentinel-3/OLCI, PROBA-V		2014-present		10 d		300m		1.5		https://land.copernicus.eu/global/products/fcover
植被覆盖度 FCover		Fractional Vegetation Coverage (FCover) (version: V40)			MODIS		2000-2018		8 d		500 m				http://www.glass.umd.edu/
冰面范围 IE		MODIS/Terra Sea Ice Extent 5-Min L2 Swath 1km, Version 6			MODIS		2000-present		5 mins		1 km		1		https://nsidc.org/data/mod29/versions/6#anchor-1
冰面范围 IE		SMOS L3 Sea Ice Thickness			SMOS		2010-present		Daily		12.5 km				https://earth.esa.int/eogateway/catalog/smos-l3-sea-ice-thickness
栖息地异质性 Habitat heterogeneity		Global Habitat Heterogeneity			MODIS		2005		-		1 km, 5 km, 25 km		2		http://www.earthenv.org/texture
森林冠层高度 Forest canopy height		Forest tree height map of China			GEDI, ICESAT2		2019		-		30 m		2.5		http://www.3decology.org/dataset-software/
植被类型 Vegetation type		An updated Vegetation Map of China (1:1000,000)			Landsat		2018		-		1:1,000,000		2.5		http://www.3decology.org/dataset-software/

卫星名称 Satellite name	发射日期 Launch time	轨道高度 Orbit height (km)	重访周期 Revisit capacity	幅宽 Swath width (km)	传感器类型 Sensor type	波段 Number of bands	空间分辨率 Spatial resolution (m)
高分系列 GF series
高分一号 GF-1	2013/4/26	645	4 d	60	全色/多光谱 PAN/MS	5	2/8
高分一号 GF-1	2013/4/26	645	2 d	800	宽视场多光谱 WFV-MS	4	16
高分二号 GF-2	2014/8/19	631	5 d	45	全色/多光谱 PAN/MS	5	0.8/3.2
高分三号 GF-3	2016/8/10	755	2 d	5-650	合成孔径雷达 SAR	1	1-500
高分四号 GF-4	2015/12/29	36,000	20 s	400	多光谱 MS	5	50
高分四号 GF-4	2015/12/29	36,000	20 s	400	中红外 MWIR	1	400
高分五号 GF-5	2018/5/9	705	5 d	60	高光谱 HS	330	30
高分五号 GF-5	2018/5/9	705	5 d	60	多光谱 MS	12	20/40
高分六号 GF-6	2018/6/2	645	4 d	90	全色/多光谱 PAN/MS	5	2/8
高分六号 GF-6	2018/6/2	645	2 d	800	宽视场多光谱 WFV MS	8	16
高分七号 GF-7	2019/11/3	505	5 d	20	双线阵相机 DLC	1	0.8/0.65
				20	多光谱 MS	4	3.2
				1.6	激光测高仪 LA	1	0.1
高分一号 02/03/04星 GF-1-02\03\04	2018/3/31	645	2 d	66	全色/多光谱 PAN/MS	5	2/8
资源系列 ZY series
资源一号01/02星 ZY-1-01/02	1999/10/14	778	3 d	113	CCD相机 CCD	5	20
			3 d	890	宽视场多光谱 WFV-MS	2	258
			26 d	119.5	红外多光谱 MS-IR	4	78/156
资源一号02B星 ZY-1-02B	2007/12/19	778	3 d	27	高分辨率相机 HD	1	2.36
				113	CCD相机 CCD	5	20
				890	宽视场多光谱 WFV-MS	2	258
资源一号02C星 ZY-1-02C	2011/12/22	780	3 d	54	高分辨率相机 HD	1	2.36
资源一号02C星 ZY-1-02C	2011/12/22	780	3 d	60	全色/多光谱 PAN/MS	4	5/10
资源一号04星 ZY-1-04	2014/12/7	778	3 d	60	全色/多光谱 PAN/MS	4	5/10
			26 d	120	红外多光谱 MS-IR	4	40/80
			26 d	120	多光谱 MS	4	20
			3 d	866	宽视场多光谱 WFV MS	4	73
资源一号02D星 ZY-1-02D	2019/12/12	778	3 d	115	全色/多光谱 PAN/MS	9	2.5/10
资源一号02D星 ZY-1-02D	2019/12/12	778	3 d	60	高光谱相机 HS	166	30
资源三号01星 ZY-3-01	2012/1/9	506	5 d	52	双线阵相机 DLC	1	3.5
资源三号01星 ZY-3-01	2012/1/9	506	5 d	52	全色/多光谱 PAN/MS	5	2.1/5.8
资源三号02星 ZY-3-02	2016/5/3	505	3-5 d	51	双线阵相机 DLC	1	2.5
资源三号02星 ZY-3-02	2016/5/3	505	3 d	51	全色/多光谱 PAN/MS	4	2.1/5.8
资源三号03星 ZY-3-03	2020/7/25	505	3-5 d	51	双线阵相机 DLC	1	2.5
			3 d	51	全色/多光谱 PAN/MS	4	2.1/5.8
			5 d	0.07	激光测高仪 LA	1	1
环境一号 HS-1
环境一号 A星 HS-1A	2008/9/6	649	4 d	360	CCD相机 CCD	4	30
环境一号 A星 HS-1A	2008/9/6	649	4 d	50	高光谱 HS	115	100
环境一号 B星 HS-1B	2008/9/6	649	4 d	360	CCD相机 CCD	4	30
环境一号 B星 HS-1B	2008/9/6	649	4 d	720	红外多光谱 MS-IR	4	150/300
环境一号 C星 HS-1C	2012/12/9	499	4 d	40/100	合成孔径雷达 SAR	1	5/25
实践九号 SJ-9
实践九号 A星 SJ-9A	2012/10/14	645	4 d	30	全色/多光谱 PAN/MS	5	2.5/10
实践九号 B星 SJ-9B	2012/10/14	645	8 d	18	红外相机 IR	1	73

中国生物多样性核心监测指标遥感产品体系构建与思考

The outlook and system construction for monitoring Essential Biodiversity Variables based on remote sensing: The case of China

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