Agricultural Drought Monitoring with Agricultural Drought Monitoring with Remote SensingRemote Sensing

Dr Yan NanaInstitute of Remote Sensing Applications (IRSA)

Chinese Academy of Sciences (CAS)

Introduction

Drought is the most serious disaster damaging crop

Establish drought monitoring system at Ministry of water resources

The system consists of three components– Meteorological Model (6 indices)

(1996-– Hydrological model (2 indices)

(2005-– Remote sensing (4 indices) (2005-

Methods

VisibleVisible and Near infraredThermal infraredMicrowave

Albedo Vegetation Index Surface temperature Backscatter coefficient

Indices– Visible and Near Infrared ： NDVI, VCI, BMVCI– Shortwave Infrared ： NDWI– Thermal Infrared: CWSI ， TCI ， DSI– Visible 、 Near Infrared and Thermal

Infrared ： Ts/NDVI ， TVDI ， VTCI– Microwave remote sensing: soil moisture

……

DroughtWatch System

Remote sensing data :AVHRR/MODISIndices: VCI\TCI\NDWI \VHI

Preprocessing– Geometric correction– Atmosphere correction– BRDF correction

Surface parameters calculation– Cloud removal, NDVI, surface

temperature, Albedo

NDVIj: NDVI of date j ； NDVImax: the maximum NDVI of all dataset ; NDVImin :the minimum NDVI of all dataset ;

%100II

I

mm

m

inax

inj

j NDVNDV

NDVNDVIVCI

The maximum and minimum NDVI calculation May,2003

VCI (Vegetation Condition Index)

Daily NDVI dataset (1991-2004)

Cloud removal

Crop NDVI range

The maximum and minimum NDVI dataset

Cloud channel

growth seasonNDVI (0.15~0.8)

NDVImax and NDVImin

Tmax and Tmin

TCI, Early May 2003

Tsj surface temperature of date j ； Tmax the maximum temperature of all dataset ; Tmin the minimum temperature of all dataset ;

TCI (Temperature Condition Index)

Tmax and Tmin

Cloud ID

The range of T0 based on the drought district

DEM

Ts Dataset(1991-2005)

Cloud removl

T thresh

Tmax and Tmin dataset

DEM correction

NDWI dataset

Cloud removal

May,2003

NDWI (Normalized Difference Water Index)

VHI= aVCI+bTCI –VHI: considering vegetation condition and the surface

temperature change simultaneously;

–a,b are the weight coefficient of indices.

a=R2vci/( R2

vci+ R2tci) ;b=R2tci/( R2

vci+ R2tci)

R2vci : R2 between VCI and relative soil moisture

VHI

Soil Water Holding Capacity

0-10cm田间持水量图 10-20cm田间持水量图

Station Map and soil type map 178 stations

Study area: Shanxi Data

Soil moisture data: 2002-

2005, seventy stations

Indices: 2002 -2005,

seventy stationsShanxi

The relation between VCI, TCI and relative soil moisture: relative soil moisturerelative soil moisture ＝＝ soil water content/field capacitysoil water content/field capacity

Soil Moisture inversion

Soil Moisture

Daily TCI and Soil MoistureTCI - 10CM相关性 y = 0. 059x + 12. 712

R2 = 0. 5865

05

1015202530

0 50 100 150 200

TCI - 20CM相关性 y = 0. 0737x + 12. 832R2 = 0. 4832

05

1015202530

0 50 100 150 200

TCI - 10CM旬 相关性 y = 0. 0432x + 12. 853

R2 = 0. 513

05

1015202530

0 50 100 150 200 250

TCI - 20CM旬 相关性 y = 0. 0451x + 14. 193

R2 = 0. 3483

05

1015202530

0 50 100 150 200 250

10 days TCI and soil Moisture

Soil Moisture

VCI - 10CM相关性 y = 0. 0457x + 12. 693R2 = 0. 4536

05

1015202530

0 50 100 150 200

VCI - 20CM相关性 y = 0. 0513x + 13. 556R2 = 0. 2694

05

1015202530

0 50 100 150 200

VCI - 10CM旬 相关性 y = 0. 0573x + 12. 859R2 = 0. 5072

05

1015202530

0 50 100 150 200

VCI - 20CM旬 相关性 y = 0. 0336x + 15. 656R2 = 0. 1598

05

1015202530

0 50 100 150 200

Daily VCI and Soil Moisture

10 days VCI and soil Moisture

Soil Moisture

VHI - 10cm太谷实验区天 湿度相关性分析y = 0. 2439x + 50. 678

R2 = 0. 60

0

20

40

60

80

100

120

0 50 100 150 200

TCI

湿度

VHI - 20cm太谷实验区天 湿度相关性分析y = 0. 2594x + 49. 101

R2 = 0. 42

0

20

40

60

80

100

120

0 50 100 150 200

TCI

湿度

VHI - 10cm太谷实验区旬 湿度相关性分析y = 0. 2406x + 50. 084

R2 = 0. 56

0

20

40

60

80

100

120

0 50 100 150 200

TCI

湿度

VHI - 20cm太谷实验区旬 湿度相关性分析y = 0. 1863x + 55. 461

R2 = 0. 29

0

20

40

60

80

100

120

0 50 100 150 200

TCI

湿度

Daily VHI and Soil Moisture

10 days VHI and soil moisture

VHI= a TCI + b VCI

Soil Moisture

ndwi - 10CM相关性 y = - 0. 0382x + 19. 5

R2 = 0. 2137

05

101520

2530

0 50 100 150 200

ndwi - 20CM相关性 y = - 0. 0498x + 21. 441

R2 = 0. 1667

05

1015202530

0 50 100 150 200

Daily NDWI and Soil Moisture

Comparison results

The relation between indices and soil moisture VHI > TCI >VCI>NDWI R2 between VCI and soil moisture at 10cm and 20cm respectively is 0.45,0.26 R2 between TCI and soil moisture at 10cm and 20cm respectively is 0.58 ， 0.48 ； R2 between VHI and soil moisture at 10cm and 20cm respectively is 0.6 ， 0.42;R2 between NDWI and soil moisture at 10cm and 20cm respectively is 0.21 ， 0.16;

Region Suitability

Drought zone

geomorpho+Soil

Cluster

Climate

Cluster

Overlay

全国旱情区划基本单元制作流程图

Soil Moisture Ground Measurement Points

DroughtIndex Suitability

不同旱情区划单元指数适应性表 : T 表示 TCI ， V 表示 VCI ， H 表示 VHI ， \ 后的指数为次最佳指数

Validation of drought monitoring resultsValidation area: Taigu,Shanxi

Data required:

– Indices,2003~2005, day and ten-days– Day soil moisture, 2003-2005, two depth of 10CM and 20CM– Ten-days soil moisture,2003-2005

5km

Sample allocation Observation point

100m

40m

40m

10m

10m

40m 40m10m 10m

Depth TCI_R2 VCI_R2 NDWI_R2 VHI_R2

10cm Soil moisture0.93 0.66 0.08 0.97

20cm Soil moisture0.91 0.60 0.15 0.92

Validation of drought monitoring results

　

Pre-processingDroughtIndexDroughtGrade Statistics

DroughtWatchUpgrading: AVHRR to MODIS MODIS to MERSI

Operational Products

Percent of different drought grads different provinces of China (April, 2006)

Because consecutive days without rain and snow reached more than 80 days in the north plain, the area percentage of wheat drought between January 20 and February 16 were 49.5%, 36.9% and 30.5%, respectively.

Since Feb 16, the drought area had a large decrease because of precipitation and irrigation in large area of the north plain

Drought monitoring in North Plain In early spring, 2009

January 21-31 February 1st-10

February 11-16 February17-22

In august, drought area expanded rapidly in the north-west of Liaoning and the west of Jilin, and mostly are minor drought

The drought area percentage are 20.9 ％ and 15.2 in Liaoning and Jilin respectively

Drought monitoring in Dongbei from July to August,2009

On-going research

Incorporate HJ data, CCD to increase resolution for better monitoring

Microwave data for soil moisture

Develop new indices: combination of optical and microwave data

Scale issues

Soil moisture inversion based on active microwave radiometer

Soil moisture in Yucheng based on Radarsat2 , August 28,2008

)())sec(2exp()))sec(2exp(1(cos0svvV dMcbMbMMa ＝

Water Cloud Model

Mv is vegetation watercontent ， Ms is soil water content ， θ is incidence angle, a,b,c,d are coefficients

Fast drought monitoring in region scaleDrought monitoring in local scale

HJ-1 （CCD, IRS)

Vegetation IndexSurface Temperature

Max/Min VIMax/Min Ts

AVHRR/MODIS/FY3(vi sible,near-

infrared,thermal red)

Drought moinitoring in region scale(1km)

Drought moinitoring in local scale

(30m-100m)

Vegetation IndexSurface Temperature

Soil moisture data

cal ibrationval idation

Serial data set

Drought Indices(VCI/TCI/EF)

ETWatch

Drought model

Conclusion

RS is only way to monitor Drought Need ground data to calibrate the model High Resolution for disaster reduction Soil Moisture is not a good indicator for all

crop season, new indicator should be found

Thanks for Attention ！