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Regional and Global Eco-Hydrological Parameter Products Synergizing Multi-source Remote Sensing Data

Qinhuo Liu(liuqh@radi.ac.cn)

State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,

Chinese Academy of Sciences

2016-10-26Beijing

Global Conference “more than a decade enhancing water and sustainable development for arid regions”

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1. Objectives

2. Multi-source data Synergized Quantitative remote sensing production system(MuSyQ)

3. Eco-Hydrological Key Parameter Products

4. Conclusion and Expectations

Contents

Distributed Hydrological Model ：DHSVM（Wigmosta et al., 1994）、SWAT（Arnold and Fohrer, 2005）and GEOtop（Rigon et al., 2006）；

Underground Water model: MODFLOW（Harbaugh et al., 2000）；

Dynamic vegetation model and Vegetation Growth model: LPJ-DGVM（Sitch et al., 2003）、BIOME-BGC（Thornton and Running, 2002） and WOFOST（Vandiepen et al., 1989）；

Land surface process model: SiB2（Sellers et al., 1996）、CoLM（Dai et al., 2003）and CLM 3.0/4.0（Oleson et al., 2010）。

Li, Xin et. al., BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2013

What kind of parameters are needed for Eco-hydrological models??

驱动生态水文过程模型需要哪些参量？

variables／parameters applications Chinese satellite International satellite

降雨(Precipitation) 流域水循环；驱动变量 FY-3 TRMM, GPM

蒸散发(ET) 流域水循环；生态耗水；水分利用效

率（生态水文耦合）

FY-3成像光谱仪、HJ-1 ASTER, MODIS, MERIS, AATSR

地表径流(Flow) 流域水循环；分布式水文模型 OSTM/Jason-2 Radar Altimeter, ENVISAT Radar Altimeter-2, TerraSAR-X, SWOT

地下水(Ground Water) 流域水循环；地表－地下水相互作用 GOCE, GRACE, GRACE-II土壤水分(Soil Moisture)流域水循环；冻土水文 FY-3微波辐射计 SMAP, SMOS, ALOS PALSAR, Envisat

ASAR, BIOMASS积雪(Snow) 流域水循环；积雪水文 FY-3微波辐射计 CoReH2O, SCLP植被类型(Vegetaion) 分布式水文模型和生态模型所需参数 HJ-1, CBERS Proba CHRIS, HYSPIRI, 其他高光谱卫

星

土地利用(Land Use) 分布式水文模型和生态模型所需参数；

人类活动影响评价

HJ-1, CBERS TM, SPOT, MODIS, 其他多光谱卫星

植 被 结 构 (VegetationStructure)

水文模型和生态模型所需参数；灌溉

管理

HJ-1, CBERS Proba CHRIS, HYSPIRI, 其他高光谱卫

星

植被覆盖度(VC) 水文模型和生态模型所需参数 HJ-1, CBERS TM, SPOT, MODIS, 其他多光谱卫星

叶面积指数(LAI) 水文模型和生态模型所需参数；生态

系统动态

HJ-1, CBERS TM, SPOT, Proba CHRIS, MODIS, 其他

多光谱卫星

植被物候(Phenology) 生态模型所需参数

经初级生产力(NPP) 生态系统动态；水分利用效率（生态

水文耦合）

HJ-1 DESDynI, BIOMASS, 其他高光谱卫星，

其他激光雷达卫星

地形 分布式水文模型和生态模型所需参数 ALOS PRISM, ASTER等立体像对数据

驱动生态水文过程模型需要哪些参量？

variables／parameters applications Chinese satellite International satellite

地表反照率(Albedo) 地表能量平衡模型，生态水文模型；

驱动变量

FY-3成像光谱仪、HJ-1 ASTER, MODIS, MERIS, AATSR

地表温度(LST) 生态水文模型，地表能量平衡模型；

同化变量

FY-3成像光谱仪、HJ-1 ASTER, MODIS, MERIS, AATSR

地 表 发 射 率(Emissivity)

生态水文模型，地表能量平衡模型；

驱动变量

FY-3成像光谱仪、HJ-1 ASTER, MODIS, MERIS, AATSR

太 阳 辐 射 (SolarRadiation)

生态水文模型，地表能量平衡模型；

驱动变量

FY-2\FY-3 成像光谱仪

MSG, MODIS,

光合有效辐射(PAR) 生态水文模型，地表能量平衡模型；驱动参量

FY-2\FY-3成像光谱仪 MSG, MODIS

AVHRR (for C3 LAI）MODIS (for C4 LAI） VEGATATION

take LAI as an example

目前全球部分LAI产品主要特征

Are the Global Remote Sensing Product satisfy model requirement?

(Garrigues et al., 2008)

( Garrigues, 2008)

Global Remote Sensing LAI product’s accuracy and consistence are not good enough for global ecological and environmental monitoring

It maybe helpful synergize multi-source remote sensing data for global ecosystem and environmental monitoring

Multi-source remote sensing data from different sensors provide a chance to improve the temporal and spatial

resolution of existing hydrological products.

Earth Observations Ability atAsia Oceania Region

China FY，ZY，HY，HJ，CHEOS-GF series satellites Jilin Constellation, TripleSat Constellation

Japan Advanced Land Observing Satellite (ALOS), JERS-1, ADEOS, ALOS,

PALSAR, PRISM Greenhouse Gases Observing Satellite (GOSAT) Global Precipitation Mission (GPM) ADEOS-II Follow-on Mission (GCOM) Himawari-8 and -9

Korea Kompsat-3

India IRS Resource sat INSAT – 1,2, 3 series MeghaTropiques

Other observations in AO Region

Earth Observations Ability of China

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1. Objectives

2. Multi-source data Synergized Quantitative remote sensing production system(MuSyQ)

3. Eco-Hydrological Key Parameter Products

4. Conclusion and Expectations

Contents

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Global ecological and Hydrological monitoring based on Virtue Constellation Satellite

1：Establishing robust system for standardized pre-processing

of multi-data and timely generation of base remote

sensing products

2: Generation of comprehensive global remote sensing products for domain-

specific applications

3:Formation integrated service protocols and operational

generation system for QRS products

First stage (96.12 MY): 2012-2014 Second stage(37.12MY): 2013-2015

Quantitative Remote Sensing Generation and Serving System

Base QRS products support

Thematic QRS data support

Standardized RS data support

Standardized generation and comprehensive applications of satellite-airborne-ground synergetic quantitative remote sensing (QRS) products

The National High Technology Research and Development Program of China (No. 2012AA12A304)

4. Generation of Synergized land remote sensing

production

3.Establishment of surface prior knowledge database and assimilation of remote sensing

products

7.Supply situation of maize, rice, wheat and soybean

10.Ecological

environment factors

9.Large terrestrial

surface water areas

8.Vital mineral

and energy resources

1.Synergetic Earth Observation by satellite-

airborne-ground networking

2.Comprehensive Calibration and Validation of Multi-sensor

5.Standarized validation of remote sensing products

11.Integreted services platform for quantitative remote sensing applications

6.Forest biomass

and carbon sink

Monitoring and Estimation

Virtue Constellation Satellite

数据类型 卫星/传感器 数据类型 卫星/传感器

静止卫星数据

Geostationary Satellites

(波段：可见光—热红外；

分辨率：公里至10公里)

FY-2D 中高分辨率

极轨卫星数据

Orbit Satellites with higher resolution

(波段：可见光、近红外、中红外、

热红外；分辨率：十米级)

Landsat/TM

MTSAT HJ-1/CCD/IRS/HIS

MSG CEBRS02B

GOES-E ZY-3

GOES-W GF-1

低分辨率

极轨卫星数据

Orbit Satellites with lower resolution

(波段：可见光—热红外；

分辨率：百米到1公里)

FY-3A/VIRR

其他数据

Other satellites

GRACE卫星重力数据

FY-3A/MERSI ICESAT

MODIS SSMIS

Vegetation FY3B-微波辐射计数据

NOAA/AVHRR-16,17,18,19

SSMI

MeTOP/AVHRR TERRA/SAR或者COSMO/SKYMED

ENISAT/MERIS 辅助数据

Ancillary data

气象台站数据(Meteorological station)

SPOT/VEGETATION气象再分析数据（NCEP）

NPP/VIIRS 数字高程数据等(DEM)15

•Raw multi-source remote sensing data

•Normalized multi-source remote sensing data

•Common Quantitative remote sensing product

•Thematic Quantitative remote sensing product

•Ecological and environmental evaluation Application

Architecture of Quantitative remote sensing

QRS Products for global ecological and Hydrological monitoring

编号

QRS products Resolution Chinese satellite data

Other satellite data

1 VI、LAI、VC、Cha、Phenology、Fpar

30m-1k m

HJ, GY,CBERS, FY

TM, MODIS, MISR, MERIS, VEGETATION, POLDER, MSG

2 AOD、Albedo、LST、LSE 30m-1km HJ, FY, CBERS

TM, MODIS, ASTER, AATSR,

MSG, GMS, GOES

3 DSR、DLR、PAR、NR 300m-1k m HJ, FY MODIS、MTSAT、

GOES、MSG

4 SM、SD、SC、Precipitation 1km-25 km FY

SMOS, SMAP, AMSR-E, TRMM、AMSR、AMSU-B、

GEO-VIRS

5 Roughness、Sensible Flux、LatentFlux、ET、NPP 300m-1km HJ, FY

AVHRR, MODIS , AATSR, MSG,

MTSAT、GOES

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Challenge Issues in the System Development

Satellite virtual constellation

Retrieval algorithm

Normalization process

High efficiency

Automatic Prod-uctionsystem

In order to exploit the ability and feasibility to improve the

accuracy, spatial/temporal resolution, continuous and/or

consistency of existing hydrological products, the

Multi-source data Synergized Quantitative remote sensing production system(MuSyQ)

has been developed.

Radiation Budget Parameter：PAR、Net radiation、LST、

Albedo…

Vegetation Parameter:VI、LAI VC NPP Biomass

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1. Objectives

2. Multi-source data Synergized Quantitative remote sensing production system(MuSyQ)

3. Eco-Hydrological Key Parameter Products3.1 Eco-Hydrological Products for Heihe River Basin

3.2 Eco-Hydrological Products for China-ASEAN

3.3 Global Eco-Hydrological Products

4. Conclusion and Expectations

Contents

HiWATER 21

Vegetation Product产品名称 空间分辨率 时间分辨率

Land Use/Vegetation 250m（30m） 1个月

VI（NDVI） 1km 5天

Vegetation Coverage 1km 5天

Vegetation Phenology 1km 1年

FPAR 1km 5天

NPP 1km 5天

3.1 Eco-Hydrological Products for Heihe River Basin

HiWATER 22

3.1 Eco-Hydrological Products for Heihe River Basin

产品集名称 时间范围 大小(MB) 下载次数 浏览次数

黑河流域1km/5天光合有效辐射吸收比例(FPAR)数据集

2013-2014 22.2 0 314

黑河流域1km/5天合成叶面积指数（LAI）数据集 2011-2014 30.12 0 893黑河流域1km/5天合成植被覆盖度（FVC）数据集 2011-2014 33.7 0 908黑河流域1km/5天合成植被指数（NDVI/EVI）数据集

2011-2014 65.1 0 763黑河流域250m/1km月合成植被覆盖度（FVC）数据集

2011-2014 63.58 15 1119黑河流域30m/月合成光合有效辐射吸收比例（FAPAR）数据集

2011-2014 5611.52 0 353

黑河流域30m/月合成叶面积指数（LAI）数据集 2011-2014 5939.2 0 390黑河流域30m/月合成植被覆盖度（FVC）数据集 2011-2014 4571.36 0 965黑河流域30m/月合成植被指数（NDVI/EVI）数据集

2011-2014 11622.4 0 1077

黑河流域净初级生产力（NPP）数据集 2011-2014 4.16 11 885黑河流域土地利用覆被(Land USE)数据集 2011-2015 255 161 6245黑河流域植被物候(Phenology)数据集 2012-2015 68.7 18 958

HiWATER

黑河流域月度土地覆盖图

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HiWATER

黑河流域产品——FPAR

生产了黑河流域直射FPAR，散射FPAR，总FPAR

China-ASEAN has become a new engine for world economy. ASEAN mainly includes the Indo-China Peninsula and Malay Archipelago in

the southeast of Asia.

The increasingly acceleratedurbanization, rapid growth ofpopulation and socio-economicdevelopment could cause a seriesof ecological environmentalproblems.

There is hence an urgent need tomonitor the ecologicalenvironment and to cooperate inrespect of environmentalprotection in China-ASEAN.

3.2 Eco-Hydrological Key Parameter Products for China-ASEAN

Fig. 1 Distribution of PAR in China-ASEAN in 2013

The maximum value of PAR in theregion is 3,500 MJ/m2, which islocated on the south slope ofTibetan Plateau with relativelylow latitude and high altitude;and the minimum value is 2,400MJ/m2, which is located inHeilongjiang, the northeast ofChina, with a relatively highlatitude and a low altitude.

As the ASEAN countries are inthe region with low latitude,their annual PARs are close andare generally 3,000 MJ/m2.

Fig. 2 Distribution of annual light-temperature potential productivity in China-ASEAN in 2013

The lowest annual light-temperaturepotential productivity in China-ASEANis on the Tibetan Plateau and thehighest is on Indo-China Peninsula.

It can be above 225 t/hm2 (hm2: hectare)in some areas of Myanmar, Thailand andCambodia on the Indo-China Peninsula,the highest value of the region; theannual light-temperature potentialproductivity at the boundary of thenorthwest part of the Tibetan Plateauand Xinjiang is below 25 t/hm2, thelowest value in the region.

The annual light-temperature potentialproductivity in eastern China presentsthe trend of gradual increase fromnorth to south, and the highest valuecan be up to 50t/hm2.

Fig. 3 Spatial distribution of the evapotranspiration in China-ASEAN

Malaysia in China-ASEAN has the best overallwater conditions, followed by the Indo-ChinaPeninsula. China has the poorest water conditionswhich are extremely uneven in their spatialdistribution.

The area with a tropical rainforest climate inMalay Archipelago has a stable precipitationthroughout the year, while the precipitation inIndo-China Peninsula characterized with tropicalmonsoon climate and tropical savanna climate hasobvious differences in dry and rainy seasons, ofwhich the precipitation in the rainy seasonaccounts for about 70~80% of the annualprecipitation;

the evapotranspiration of each month in the ASEANcountries is above 40 mm and there is no obviousdifference in the dry and rainy seasons.Different climate areas in China arecharacterized with wet/warm and dry/cold seasonsand the precipitation and evapotranspirationreach their peak in June – August in summer.

Malaysia has a tropical rainforest climateand tropical rainforest ecosystem withprecipitation(3,022mm), evapotranspiration(947mm) and water surplus (2,075mm) higherthan those of the Indo-China Peninsula(2,107 mm, 793 mm, 1314 mm).

Under the influence of the temperatecontinental climate, the precipitation(720 mm), evapotranspiration (383 mm) andwater surplus (337 mm) of China are thelowest in the region.

The water deficit area in China-ASEANaccounts for 9% and mainly distributes inthe agricultural areas in north andnorthwest China, the Tibetan Plateau, etc.

Fig. 4 Spatial distribution of the water surplus in China-ASEAN

2013.

(a) (b)Fig. 7 (a) Runoff depth and (b) Rainfall Distribution in the Lantsang-Mekong River Basin from June 2013 to May 2014

Simulationperiod

Lancang Riverbasin (m3/s)

Stung Treng section (m3/s)

Proportion (%)

Whole Year 1525 13732 11.1RainySeason 2657 27088 9.8

DrySeason 748 4257 17.6

Table Proportion of the average daily flow of the Stung Treng section from the LancangRiver basin in rainy season, dry season and a whole year Runoff volumes at the four

main control sections,mainly concentrate in rainyseason from June to October：

Chiang Saen of Thailand; 73.4%,

Luang Prabang of Laos: 73.6%

Mukdahan of Thailand:81.3%

Stung Treng of Cambodia:81.4%

The annual total runoffvolume at the Stung Trengsection is 433 billion m3,which is close to anaverage year level.

3.3 Global Eco-Hydrological Key Parameter Products

共 个传感器MODIS-Terra/Aqua, FY3A/B-MERSI共4个传感器

1KM, 5 day

全球1km5天合成植被指数

全球1km5天合成植被指数动画

全球1km5天合成植被覆盖度和叶面积指数

2014年1km5天LAI动画

全球1km气溶胶光学厚度产品

1km地表发射率

宽波段发射率3-∞um示意图

1km地表温度与地表反照率产品

5km卫星地表温度

全球5km地表温度产品：2012年6月1日

日总下行短波辐射(2012-7-1)

0

480W/m2

DSR/PAR 产品

全球下行长波辐射（3小时，5km）

全球土壤水分产品（25km）

全球月度5km蒸散发产品

全球蒸散发产品1，7月均（5km）

Annual Report on Remote Sensing Monitoring of Globle Ecosystem and Environment(GEO ARC)“The China-ASEAN Ecological Environmental Conditions”, “The Belt and Road Ecological EnvironmentalConditions” were released public by Ministry of Science and Technology on 5 June, 2015 and 6 June,2016. ( www.nrscc.gov.cn)

Dataset and products will be shared based on “the national comprehensive earth observation datasharing platform ",

http://www.geodoi.ac.cn/WebCn/Default.aspx

http://124.16.184.151/dsp/home/index.jsp

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1. Objectives

2. Multi-source data Synergized Quantitative remote sensing production system(MuSyQ)

3. Eco-Hydrological Key Parameter Products

4. Conclusion and Expectations

Contents

(1) Demonstration applications show that the Multi-source SynergizedQuantitative Remote Sensing Production System (MuSyQ) has thecapabilities to integrate the Chinese, European, and other satelliteobservation to retrieve the global and regional scale land surfaceparameters.

(2) Large-scale monitoring and analysis based on the MuSyQ productscan been used for ecological and hydrological system evaluation andsimulation.

(3) Comprehensive assessment may be carried based on the ecologicalenvironmental and water resource conditions for global andregional scale.

Conclusions

(1) Synergizing accumulated earth observationdata(Geostationary and polar orbiting, USA,China, ESA and other sides) to generate theglobal long-term, consistent and accuratehydrological products

(2) Validate the remote sensing product of landsurface parameters at different scale

(3) Combine remote sensing observation with theland surface process model to support globalhydrological and ecological monitoring

Expectation

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Thank you very much for your attention!