Chen, Youqi

He, Y

Lacoste, H.

Li, C.

Li, Z.L.

Lin, W.

Liu, Q.H.

Ma, Y.

Menenti, M.

Ouwehand, L.

Sobrino, J.A.

Su, Zhongbo

van der Velde, R.

van Helvoirt, M.D.

Verhoef, W.

Wan, L.

Wang, Lichun

Wen, J.

Xin, Shan

English

Su, Z.

Chen, Y.

Sobrino, J.

Wang, L.

He, Y.

Velde, R., van der

Helvoirt, M., van

Shan, X.

Wageningen Yield 

  
DROUGHT MONITORING AND PREDICTION OVER CHINA 
 
Z. (Bob) Su1, Y. Chen2, M. Menenti3, J. Sobrino4, Z.-L. Li5, W. Verhoef6, L. Wang7, Y. Ma8 , L. Wan9, Y. He10, 
Q.H. Liu11, C. Li12, J. WEN13, R. van der Velde1, M. van Helvoirt1, W. Lin1, X. Shan1 
 
1 International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands, email: 
b_su@itc.nl 
2 Institute of Natural Resources & Regional planning, Chinese Academy of Agricultural Sciences, Beijing, P. R. China, 
email: chenyqi@mail.caas.net.cn; chyqi@yahoo.com 
3 CNR - ISTITUTO PER I SISTEMI AGRICOLI E FORESTALI  DEL MEDITERRANEO - ISAFoM, Ercolano (NA), 
Italy, email: m.menenti@ispaim.na.cnr.it 
4 Global Change Unit, Universitat de Valencia, Burjassot, Spain, email: sobrino@uv.es 
5 GRTR/LSIIT, Illkirch, France, email: Zhao-Liang.Li@mail-grtr.u-strasbg.fr 
6 National Aerospace Laboratory (NLR) & International Institute for Geo-Information Science and Earth 
Observation (ITC), Enschede, The Netherlands, email: verhoef@itc.nl 
7 Remote Sensing Application Center, Ministry of Agriculture, P.R. China, email: wanglm@mail.caas.net.cn 
8 Institute of Tibetan Plateau Research (ITP/CAS), Beijing/Lhasa, P.R. China , email : ymma@itpcas.ac.cn 
9 China University of Geoscience (Beijing), Beijing 100083, P.R.China,email: wanly@cugb.edu.cn 
10 China National Meteorological Center, Beijing, P.R. China, email: yanbohe@cma.gov.cn 
11 Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, P. R. China, email: qhliu@irsa.ac.cn 
12 Chinese Academy of optical-electronics, China, email: Cxli21@ne.rsgs.ac.cn 
13 Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences , Lanzhou 
730000, Gansu P.R.China, email: jwen@lzb.ac.cn 
 
ABSTRACT 
The objective of the Dragon Drought monitoring and 
prediction project was to develop the understanding 
for an operational system for nation wide drought 
monitoring and drought impact assessment for 
application in agriculture and hydrology in China 
using ESA and other relevant satellite data as major 
data source in combination with other data source (e.g. 
meteorological and drought statistics, etc.). In detail 
the project generated: (1) scientifically based drought 
monitoring methodologies and experimental datasets, 
(2) improved understanding of land surface processes 
over heterogeneous terrain, (3) algorithms for 
estimation of land surface parameters and heat fluxes 
over China, (4) evaporation and real time drought 
monitoring and prediction maps, and (5) training of 
students and young scientists for the use of advanced 
earth observation satellite data in applications related 
to drought monitoring and prediction. 
1. INTRODUCTION 
The conflict between supply and demand of water 
resources constitutes the biggest problem for food 
security of a huge population in China. The 
distribution of water resources in China is strongly 
heterogeneous both in time and space. For instance, to 
the north of the Yangtze river, the population is 46.5% 
of the total, with 43% farm land, but the available 
water resources is only 9.8% of the national total. In 
the mid north, the population is 11.8% with 13.7% 
farm land, the amount of water resources is only 1.8% 
of the national total. Due to the shortage of water 
_____________________________________________________ 
Proc. Dragon 1 Programme Final Results 2004–2007, Beijing, P.R. China 
21– 25 April 2008 (ESA SP-655, April 2008) 
 resources and its inhomogeneous distribution in space 
and time, large scale droughts occur frequently in 
China, with a big drought disaster every two years. 
Since 1949, average annual areas affected by drought 
disaster amounts 303 million mu (or 20.2 million 
hectares) and accounts 59.3% of areas of 
weather/climate induced disasters according the 
Ministry of Water resources. In 1959, 1960, 1961, 
1978, and 2000, the areas affected by droughts are all 
above 33.3 million hectares and the annual average 
loss of grains due to drought amounts above 10 billion 
kilogram. Around 20 provinces are affected annually. 
Consequently, drought has become a key factor 
constraining China’s economic development. In the 
21st century, the Chinese population will reach 1.6 
billion, food security will be a major issue which 
demands a proper solution of drought problem. 
Since 1970’s, some progresses have been made in 
drought quantification and research. However, the 
methods employed are mostly based on data collected 
on local meteorological variables and can not quantify 
real time, large scale actual drought process – i.e. its 
starting and ending time and its actual extent and 
severity. It has also often happened that a drought is 
not recognized while it is in fact already underway of 
its development. As a result of this inability, no 
adequate measure can be deployed to effectively fight 
any big drought disaster often causing great hunger 
and social instability. The “Agriculture Action Plan for 
China’s Agenda 21” issued by the Ministry of 
Agriculture in 1998 called for China’s sustainable 
agricultural development, with the following specific 
needs: (1) collection and assessment of information on 
crops; (2) survey and monitoring of agricultural and 
ecological resources; (3) assessment of the influence 
of severe natural disasters to agriculture and (4) 
development of precision agriculture. The current 
project directly contributes to the needs as formulated 
above and beyond. The objective of this project was to 
develop an operational system for nation wide drought 
monitoring and drought impact assessment for 
application in agriculture and hydrology. In the 
following sections, we will first describe the 
methodologies developed, followed by data and field 
experiments as contributions to this project, the results 
obtained so far and a outlook into the future. 
2. METHODOLOGIES 
In the development of methodologies for drought 
monitoring and prediction, emphasis was given to the 
understanding of the underlying physical processes 
and the necessary data and information for the 
quantification of the severity and extent of droughts as 
a physical phenomenon. We started with a simple 
question as indicated in Fig. 1, namely what is the 
difference of the two ecosystems? 
 
  
 
Figure 1. Two contrasting ecosystems in the Heihe River Basin in Northwest China 
  
Obviously the availability of water was the cause to the 
life and dead states of the two ecosystems. In order to 
answer precisely the above question, it was necessary 
to quantify the available water content in the rooting 
zone. As such scientifically based drought monitoring 
methodologies were proposed as a quantitative 
measure of the drought situation and two approaches 
were identified. Fig. 2 presents a sketch of the above 
strategy. 
 
 
Figure 2. Strategy for drought monitoring and prediction 
 
Approach 1: Surface Energy Balance. This approach 
starts with the derivation of relative evaporation and 
relates it to relative soil moisture in the root zone from 
land surface energy balance. After which a quantitative 
drought severity index (DSI) is defined for large scale 
drought monitoring [1,2]. The advantage of such an 
approach is the direct quantification of the water 
availability to the vegetation and comparison in space 
and time are made available. 
Approach 2: Soil Moisture Retrieval. This approach 
starts with the direct determination of surface soil 
determine surface soil moisture using active 
microwave observations [3,4,5]. Subsequently this 
information needs to be assimilated into a land surface 
hydrological model to derive root zone soil moisture. 
This is because that microwave observation does not 
provide the necessary information for the whole 
rooting zone but rather the surface or near surface 
information. The advantage of this approach is that it 
is not influenced by cloud cover. 
To validate the methodologies large scale field 
experiments were conducted as described in the 
following.  
 
3. FIELD EXPERIMENTS 
 Various field campaigns were organized, including 
campaigns for algorithms development and validation 
(SPARC2004, SEN2FELX2005, CAMP/Tibet, 
LOPEX2005) and other dedicated comprehensive field 
experiments were conduced in the summer 2006 
(EAGLE2006, Tibetan soil moisture experiment 2006, 
field expedition to the Heihe river basin in 2006) [6-8].  
Various ESA and third party mission earth observation 
data were acquired and investigated including MERIS, 
AATSR and ASAR data over different sites in Europe 
and China and some data processing were reported 
elsewhere [7-10]. An overview of the experimental 
sites in China is given in Fig. 3, while Fig. 4 presents 
the setup of the comprehensive EAGLE2006 campaign 
for algorithm validation. Fig. 5 shows some soil 
moisture sensors installed on the Tibetan plateau. 
 
 
Figure 3. An overview of the experimental sites in Chinain the Dragon drought project 
 
 
  
Figure 4. Overview of the EAGLE2006 experimental sites in the Netherlands – Cabauw, Loobos and Speulderbos 
towers. 
 
  
  
Figure 5. Soil moisture sensors installed at the BJ-Site in Naqu on the Tibetan plateau 
 3. RESUTLS 
The achieved results include (1) improved 
understanding of land surface processes over 
heterogeneous terrain, (2) algorithms for estimation 
of land surface parameters and heat fluxes over 
China, (3) evaporation and real time drought 
monitoring and prediction maps, and (4) training of 
students and young scientists for the use of advanced 
earth observation satellite data in applications 
related to drought monitoring and prediction. In 
particular, the following specific results were 
obtained. 
1. A new campaign data set was collected during 
EAGLE2006 where multi-sensor satellite data 
(MERIS, AATSR, ASAR, ASTER, MODIS, 
CHRIS/PROBA, SEVIRI) have been collected [6]. 
2. Data over several test sites in China have been 
continuously acquired and analyzed [7, 8]. 
3. Preliminary data assimilation using a mesoscale 
atmospheric data has started and is ongoing [8]. 
4. A case study was conducted to estimate 
evapotranspiration for the entire Heihe River basin 
using MODIS data was completed [9, 10]. 
5. An operational land data assimilation system for 
drought monitoring and prediction is under construction 
that will be capable to assimilate land surface states, 
surface energy balance fluxes and land surface soil 
moisture. Some simulation examples over China are 
shown in Figs. 6-7.   
6. Several visits took place to China by ITC scientists for 
field experiments and data analysis. Two MSc students 
were trained using Dragon datasets and methodologies. 
ITC has accepted three Chinese Dragon participants as 
a sandwich PhD candidates (Xin Tian, Yijian Zeng, & 
Lei Zhong). 
 
 
Figure 6. Simulation examples for land surface temperature over China 
  
 
Figure 7. Simulation examples for land surface soil moisture over China 
 
4. OUTLOOK 
The progress and achievements in this project has been 
very substantial and should be continued in Dragon II. 
In particular, the scientific results should be further 
utilized and deployed in operational processing chain, 
training of technical personnel, reporting. A web based 
information drought monitoring system, Operational 
data processing, validation of data products, 
consultation with end users could now be established 
and should be used in operation. Future collaboration 
should be extended to other major Chinese partners in 
the field of Earth Observation and Water Cycle 
research and applications. 
5. REFERENCES 
1. Su, Z. (2002) The Surface Energy Balance System 
(SEBS) for estimation of turbulent heat fluxes, 
Hydrology and Earth System Sciences, 6(1), 85-99. 
 
2. Su, Z., Yacob, A., He, Y., Boogaard, H.,  Wen, J., 
Gao, B., Roerink,G., & van Diepen, K. (2003) 
Assessing Relative soil moisture with remote 
sensing data: theory and experimental validation, 
Physics and Chemistry of the Earth, 28(1-3), 
89-101.  
3. Wen, J., & Su, Z. (2003) A Method for Estimating 
Relative Soil Moisture with ESA Wind 
Scatterometer Data, Geophysical Research Letters, 
30 (7), 1397, doi:10.1029/ 2002GL016557. 
4. Wen, J., Su, Z. & Y. Ma (2003) Determination of 
Land Surface Temperature and Soil Moisture from 
TRMM/TMI Remote Sensing Data, Journal of 
Geophysical Research,  108(D2), 
10.1029/2002JD002176. 
5. Wen, J. & Su, Z. (2004) An analytical algorithm for 
the determination of vegetation Leaf Area Index 
from TRMM/TMI data, International Journal of 
Remote Sensing, 25(6), 1223–1234. 
 6. Su, Z., Timmermans, W.J., Dost, D.,  Bianchi, R., 
Gómez, J.A., House, A. Hajnsek, I., Menenti, M., 
Magliulo, V. , Esposito, M., Haarbrink, R., Bosveld, 
F., Rothe, R., Baltink, H.K., Vekerdy, Z. , Sobrino, 
J.A.,  van der Tol, C., Timmermans, J., van Laake, 
P., Salama, S., van der Kwast, H., Claassen, K., 
Stolk, A., Jia, L., Moors, E., Hartogensis, O. & 
Gillespie A., (2007) EAGLE 2006 – Multi-purpose, 
multi-angle and multi-sensor in-situ and airborne 
campaigns over grassland and forest, ESA 
AGRISAR & EAGLE Workshop Proceedings, 
ESTEC, 15-16 October 2007. 
7. Van der Velde, R., Rientjes, T.H.M., Ma, Y., Zhao, 
Z. & Su, Z. (2007). Characterization of the temporal 
and spatial variability of soil moisture through multi 
- temporal Analysis of ASAR Observations. In: 
Proc. of MultiTemp 2007: 4th International 
workshop on the analysis of multi-temporal remote 
sensing images, 18-20 July, 2007, Leuven, Belgium. 
(Eds. G.J.M. De Lannoy et al.). Leuven/Ghent: 
Katholieke Universiteit Leuven/Universiteit Ghent. 
8. van der Velde, R. van Helvoirt, M., van Aken, H. & 
Su, Z. (2007) On the use of satellite observations for 
drought monitoring and forecasting, ESA’s 
Publications Division as Special Publication SP-655, 
Proceedings of the Dragon Programme final results. 
9. Lin, W., van de Velde, R. & Su, Z., (2007) Satellite 
based regional-scale evapotranspiration in the 
Heibei plaing, Northeastern China, ESA’s 
Publications Division as Special Publication 
SP-655, Proceedings of the Dragon Programme 
final results. 
10. Shan, X., van de Velde, R., Wen, J., He, Y. & Su, 
Z., (2007), Regional Evapotranspiration over the 
Arid Inland Heihe River Basin in Northwest China, 
ESA’s Publications Division as Special Publication 
SP-655, Proceedings of the Dragon Programme 
final results. 


A Method for Estimating Relative Soil Moisture with

An analytical algorithm for the determination of vegetation Leaf Area Index from TRMM/TMI data,

Assessing Relative soil moisture with remote sensing data: theory and experimental validation,

Characterization of the temporal and spatial variability of soil moisture through multi - temporal Analysis of ASAR Observations. In:

Determination of Land Surface Temperature and Soil Moisture from TRMM/TMI Remote Sensing Data,

Multi-purpose, multi-angle and multi-sensor in-situ and airborne campaigns over grassland and forest,

On the use of satellite observations for drought monitoring and forecasting,

Regional Evapotranspiration over the Arid Inland Heihe River Basin

Satellite based regional-scale evapotranspiration in the Heibei plaing,

The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes,

Drought monitoring and prediction over China

Name not available

The objective of the Dragon Drought monitoring and prediction project was to develop the understanding for an operational system for nation wide drought monitoring and drought impact assessment for application in agriculture and hydrology in China using ESA and other relevant satellite data as major data source in combination with other data source (e.g. meteorological and drought statistics, etc.). In detail the project generated: (1) scientifically based drought monitoring methodologies and experimental datasets, (2) improved understanding of land surface processes over heterogeneous terrain, (3) algorithms for estimation of land surface parameters and heat fluxes over China, (4) evaporation and real time drought monitoring and prediction maps, and (5) training of students and young scientists for the use of advanced earth observation satellite data in applications related to drought monitoring and prediction.<br/

Su, Z. (Bob)

Li, Z.-L.

van Helvoirt, M.

Xin, S.

University of Twente Research Information

  DROUGHT MONITORING AND PREDICTION OVER CHINA  Z. (Bob) Su1, Y. Chen2, M. Menenti3, J. Sobrino4, Z.-L. Li5, W. Verhoef6, L. Wang7, Y. Ma8 , L. Wan9, Y. He10, Q.H. Liu11, C. Li12, J. WEN13, R. van der Velde1, M. van Helvoirt1, W. Lin1, X. Shan1  1 International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands, email: b_su@itc.nl 2 Institute of Natural Resources & Regional planning, Chinese Academy of Agricultural Sciences, Beijing, P. R. China, email: chenyqi@mail.caas.net.cn; chyqi@yahoo.com 3 CNR - ISTITUTO PER I SISTEMI AGRICOLI E FORESTALI  DEL MEDITERRANEO - ISAFoM, Ercolano (NA), Italy, email: m.menenti@ispaim.na.cnr.it 4 Global Change Unit, Universitat de Valencia, Burjassot, Spain, email: sobrino@uv.es 5 GRTR/LSIIT, Illkirch, France, email: Zhao-Liang.Li@mail-grtr.u-strasbg.fr 6 National Aerospace Laboratory (NLR) & International Institute for Geo-Information Science and Earth Observation (ITC), Enschede, The Netherlands, email: verhoef@itc.nl 7 Remote Sensing Application Center, Ministry of Agriculture, P.R. China, email: wanglm@mail.caas.net.cn 8 Institute of Tibetan Plateau Research (ITP/CAS), Beijing/Lhasa, P.R. China , email : ymma@itpcas.ac.cn 9 China University of Geoscience (Beijing), Beijing 100083, P.R.China,email: wanly@cugb.edu.cn 10 China National Meteorological Center, Beijing, P.R. China, email: yanbohe@cma.gov.cn 11 Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, P. R. China, email: qhliu@irsa.ac.cn 12 Chinese Academy of optical-electronics, China, email: Cxli21@ne.rsgs.ac.cn 13 Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences , Lanzhou 730000, Gansu P.R.China, email: jwen@lzb.ac.cn  ABSTRACT The objective of the Dragon Drought monitoring and prediction project was to develop the understanding for an operational system for nation wide drought monitoring and drought impact assessment for application in agriculture and hydrology in China using ESA and other relevant satellite data as major data source in combination with other data source (e.g. meteorological and drought statistics, etc.). In detail the project generated: (1) scientifically based drought monitoring methodologies and experimental datasets, (2) improved understanding of land surface processes over heterogeneous terrain, (3) algorithms for estimation of land surface parameters and heat fluxes over China, (4) evaporation and real time drought monitoring and prediction maps, and (5) training of students and young scientists for the use of advanced earth observation satellite data in applications related to drought monitoring and prediction. 1. INTRODUCTION The conflict between supply and demand of water resources constitutes the biggest problem for food security of a huge population in China. The distribution of water resources in China is strongly heterogeneous both in time and space. For instance, to the north of the Yangtze river, the population is 46.5% of the total, with 43% farm land, but the available water resources is only 9.8% of the national total. In the mid north, the population is 11.8% with 13.7% farm land, the amount of water resources is only 1.8% of the national total. Due to the shortage of water _____________________________________________________ Proc. Dragon 1 Programme Final Results 2004–2007, Beijing, P.R. China 21– 25 April 2008 (ESA SP-655, April 2008)  resources and its inhomogeneous distribution in space and time, large scale droughts occur frequently in China, with a big drought disaster every two years. Since 1949, average annual areas affected by drought disaster amounts 303 million mu (or 20.2 million hectares) and accounts 59.3% of areas of weather/climate induced disasters according the Ministry of Water resources. In 1959, 1960, 1961, 1978, and 2000, the areas affected by droughts are all above 33.3 million hectares and the annual average loss of grains due to drought amounts above 10 billion kilogram. Around 20 provinces are affected annually. Consequently, drought has become a key factor constraining China’s economic development. In the 21st century, the Chinese population will reach 1.6 billion, food security will be a major issue which demands a proper solution of drought problem. Since 1970’s, some progresses have been made in drought quantification and research. However, the methods employed are mostly based on data collected on local meteorological variables and can not quantify real time, large scale actual drought process – i.e. its starting and ending time and its actual extent and severity. It has also often happened that a drought is not recognized while it is in fact already underway of its development. As a result of this inability, no adequate measure can be deployed to effectively fight any big drought disaster often causing great hunger and social instability. The “Agriculture Action Plan for China’s Agenda 21” issued by the Ministry of Agriculture in 1998 called for China’s sustainable agricultural development, with the following specific needs: (1) collection and assessment of information on crops; (2) survey and monitoring of agricultural and ecological resources; (3) assessment of the influence of severe natural disasters to agriculture and (4) development of precision agriculture. The current project directly contributes to the needs as formulated above and beyond. The objective of this project was to develop an operational system for nation wide drought monitoring and drought impact assessment for application in agriculture and hydrology. In the following sections, we will first describe the methodologies developed, followed by data and field experiments as contributions to this project, the results obtained so far and a outlook into the future. 2. METHODOLOGIES In the development of methodologies for drought monitoring and prediction, emphasis was given to the understanding of the underlying physical processes and the necessary data and information for the quantification of the severity and extent of droughts as a physical phenomenon. We started with a simple question as indicated in Fig. 1, namely what is the difference of the two ecosystems?     Figure 1. Two contrasting ecosystems in the Heihe River Basin in Northwest China   Obviously the availability of water was the cause to the life and dead states of the two ecosystems. In order to answer precisely the above question, it was necessary to quantify the available water content in the rooting zone. As such scientifically based drought monitoring methodologies were proposed as a quantitative measure of the drought situation and two approaches were identified. Fig. 2 presents a sketch of the above strategy.   Figure 2. Strategy for drought monitoring and prediction  Approach 1: Surface Energy Balance. This approach starts with the derivation of relative evaporation and relates it to relative soil moisture in the root zone from land surface energy balance. After which a quantitative drought severity index (DSI) is defined for large scale drought monitoring [1,2]. The advantage of such an approach is the direct quantification of the water availability to the vegetation and comparison in space and time are made available. Approach 2: Soil Moisture Retrieval. This approach starts with the direct determination of surface soil determine surface soil moisture using active microwave observations [3,4,5]. Subsequently this information needs to be assimilated into a land surface hydrological model to derive root zone soil moisture. This is because that microwave observation does not provide the necessary information for the whole rooting zone but rather the surface or near surface information. The advantage of this approach is that it is not influenced by cloud cover. To validate the methodologies large scale field experiments were conducted as described in the following.   3. FIELD EXPERIMENTS  Various field campaigns were organized, including campaigns for algorithms development and validation (SPARC2004, SEN2FELX2005, CAMP/Tibet, LOPEX2005) and other dedicated comprehensive field experiments were conduced in the summer 2006 (EAGLE2006, Tibetan soil moisture experiment 2006, field expedition to the Heihe river basin in 2006) [6-8].  Various ESA and third party mission earth observation data were acquired and investigated including MERIS, AATSR and ASAR data over different sites in Europe and China and some data processing were reported elsewhere [7-10]. An overview of the experimental sites in China is given in Fig. 3, while Fig. 4 presents the setup of the comprehensive EAGLE2006 campaign for algorithm validation. Fig. 5 shows some soil moisture sensors installed on the Tibetan plateau.   Figure 3. An overview of the experimental sites in Chinain the Dragon drought project     Figure 4. Overview of the EAGLE2006 experimental sites in the Netherlands – Cabauw, Loobos and Speulderbos towers.      Figure 5. Soil moisture sensors installed at the BJ-Site in Naqu on the Tibetan plateau  3. RESUTLS The achieved results include (1) improved understanding of land surface processes over heterogeneous terrain, (2) algorithms for estimation of land surface parameters and heat fluxes over China, (3) evaporation and real time drought monitoring and prediction maps, and (4) training of students and young scientists for the use of advanced earth observation satellite data in applications related to drought monitoring and prediction. In particular, the following specific results were obtained. 1. A new campaign data set was collected during EAGLE2006 where multi-sensor satellite data (MERIS, AATSR, ASAR, ASTER, MODIS, CHRIS/PROBA, SEVIRI) have been collected [6]. 2. Data over several test sites in China have been continuously acquired and analyzed [7, 8]. 3. Preliminary data assimilation using a mesoscale atmospheric data has started and is ongoing [8]. 4. A case study was conducted to estimate evapotranspiration for the entire Heihe River basin using MODIS data was completed [9, 10]. 5. An operational land data assimilation system for drought monitoring and prediction is under construction that will be capable to assimilate land surface states, surface energy balance fluxes and land surface soil moisture. Some simulation examples over China are shown in Figs. 6-7.   6. Several visits took place to China by ITC scientists for field experiments and data analysis. Two MSc students were trained using Dragon datasets and methodologies. ITC has accepted three Chinese Dragon participants as a sandwich PhD candidates (Xin Tian, Yijian Zeng, & Lei Zhong).   Figure 6. Simulation examples for land surface temperature over China    Figure 7. Simulation examples for land surface soil moisture over China  4. OUTLOOK The progress and achievements in this project has been very substantial and should be continued in Dragon II. In particular, the scientific results should be further utilized and deployed in operational processing chain, training of technical personnel, reporting. A web based information drought monitoring system, Operational data processing, validation of data products, consultation with end users could now be established and should be used in operation. Future collaboration should be extended to other major Chinese partners in the field of Earth Observation and Water Cycle research and applications. 5. REFERENCES 1. Su, Z. (2002) The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes, Hydrology and Earth System Sciences, 6(1), 85-99.  2. Su, Z., Yacob, A., He, Y., Boogaard, H.,  Wen, J., Gao, B., Roerink,G., & van Diepen, K. (2003) Assessing Relative soil moisture with remote sensing data: theory and experimental validation, Physics and Chemistry of the Earth, 28(1-3), 89-101.  3. Wen, J., & Su, Z. (2003) A Method for Estimating Relative Soil Moisture with ESA Wind Scatterometer Data, Geophysical Research Letters, 30 (7), 1397, doi:10.1029/ 2002GL016557. 4. Wen, J., Su, Z. & Y. Ma (2003) Determination of Land Surface Temperature and Soil Moisture from TRMM/TMI Remote Sensing Data, Journal of Geophysical Research,  108(D2), 10.1029/2002JD002176. 5. Wen, J. & Su, Z. (2004) An analytical algorithm for the determination of vegetation Leaf Area Index from TRMM/TMI data, International Journal of Remote Sensing, 25(6), 1223–1234.  6. Su, Z., Timmermans, W.J., Dost, D.,  Bianchi, R., Gómez, J.A., House, A. Hajnsek, I., Menenti, M., Magliulo, V. , Esposito, M., Haarbrink, R., Bosveld, F., Rothe, R., Baltink, H.K., Vekerdy, Z. , Sobrino, J.A.,  van der Tol, C., Timmermans, J., van Laake, P., Salama, S., van der Kwast, H., Claassen, K., Stolk, A., Jia, L., Moors, E., Hartogensis, O. & Gillespie A., (2007) EAGLE 2006 – Multi-purpose, multi-angle and multi-sensor in-situ and airborne campaigns over grassland and forest, ESA AGRISAR & EAGLE Workshop Proceedings, ESTEC, 15-16 October 2007. 7. Van der Velde, R., Rientjes, T.H.M., Ma, Y., Zhao, Z. & Su, Z. (2007). Characterization of the temporal and spatial variability of soil moisture through multi - temporal Analysis of ASAR Observations. In: Proc. of MultiTemp 2007: 4th International workshop on the analysis of multi-temporal remote sensing images, 18-20 July, 2007, Leuven, Belgium. (Eds. G.J.M. De Lannoy et al.). Leuven/Ghent: Katholieke Universiteit Leuven/Universiteit Ghent. 8. van der Velde, R. van Helvoirt, M., van Aken, H. & Su, Z. (2007) On the use of satellite observations for drought monitoring and forecasting, ESA’s Publications Division as Special Publication SP-655, Proceedings of the Dragon Programme final results. 9. Lin, W., van de Velde, R. & Su, Z., (2007) Satellite based regional-scale evapotranspiration in the Heibei plaing, Northeastern China, ESA’s Publications Division as Special Publication SP-655, Proceedings of the Dragon Programme final results. 10. Shan, X., van de Velde, R., Wen, J., He, Y. & Su, Z., (2007), Regional Evapotranspiration over the Arid Inland Heihe River Basin in Northwest China, ESA’s Publications Division as Special Publication SP-655, Proceedings of the Dragon Programme final results. View publication stats

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