Agriculture drought with remote sensing
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Agricultural Drought Monitoring with Agricultural Drought Monitoring with Remote SensingRemote Sensing
Dr Yan NanaInstitute of Remote Sensing Applications (IRSA)
Chinese Academy of Sciences (CAS)
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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-
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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
……
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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
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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)
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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
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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)
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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
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NDWI dataset
Cloud removal
May,2003
NDWI (Normalized Difference Water Index)
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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
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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
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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
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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
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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
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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
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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
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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;
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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
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Soil Moisture Ground Measurement Points
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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
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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
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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
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Pre-processingDroughtIndexDroughtGrade Statistics
DroughtWatchUpgrading: AVHRR to MODIS MODIS to MERSI
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Operational Products
Percent of different drought grads different provinces of China (April, 2006)
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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
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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
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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
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Scale issues
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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
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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
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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
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Thanks for Attention !