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Vegetation Temperature Condition Index (VTCI) and Its Application for Low Streamflow Regional Regression Model Satoshi Hirabayashi Outline ESPM271 Project Outline Introduction Objectives Methods Data & Processing Results

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Vegetation Temperature Condition Index (VTCI) and Its Application for Low Streamflow Regional Regression Model Satoshi Hirabayashi

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SUNY-ESF SUNY-ESF 11/15/2005

ESPM271 Project

Outline Introduction Objectives Methods Data & Processing Results Conclusions

Outline

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ESPM271 Project

Outline

Outline

Introduction Objectives Methods Data & Processing Results Conclusions

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Research Theme

Introduction

Low streamflow prediction in ungauged watersheds

  • Regional regression model

⋅ ⋅ ⋅ =

γ β

α

2 1 10 , 7

X X Q

Q7,10 : 7-day, 10-year low streamflow statistics Xi : Watershed characteristics α, β, γ: model parameter to be estimated

Remotely sensed data

  • To derive a good indicator of the soil dryness

Groundwater discharge (Base flow)

  • Major source of the streamflow in low flow periods

Time Discharge Base flow Surface flow Flood Low flow

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Soil Dryness Indicator

Introduction Vegetation Temperature Condition Index (VTCI) Temperature-Vegetation Dryness Index (TVDI)

  • Calculated from Normalized Difference Vegetation Index (NDVI) and

Land Surface Temperature (LST)

  • NOAA-AVHRR, MODIS images
  • Good correlation with rainfall events and soil moisture
  • Applicable to a various geographical scales, from regional (~10,000 km2)

to semi-continental (whole China divided into three parts)

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ESPM271 Project Outline

Introduction Objectives Methods Data & Processing Results Conclusions

Outline

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Objectives

Objectives

  • 1. Explore and get familiar with MODIS data & VTCI
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  • 1. Explore and get familiar with MODIS data & VTCI

Objectives

  • 2. Develop an integrated VTCI calculation procedure

Objectives

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  • 1. Explore and get familiar with MODIS data & VTCI

Objectives

  • 3. Apply VTCI in low streamflow modeling

Objectives

  • 2. Develop an integrated VTCI calculation procedure
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ESPM271 Project Outline

Introduction Objectives Methods Data & Processing Results Conclusions

Outline

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NDVI-LST Space

Methods bare soil partial cover full cover Dry Edge LST

No Transpiration

Wet Edge NDVI

Max Transpiration

No

Evaporation Max

Evaporation

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VTCI Calculation

Methods LSTmax LSTmin NDVI LST NDVIi LST(NDVIi) LSTmax(NDVIi) LSTmin(NDVIi)

) ( ) ( ) ( ) (

min max max

NDVIi LST NDVIi LST NDVIi LST NDVIi LST VTCI − − = NDVIi b a NDVIi LST bNDVIi a NDVIi LST ' ' ) ( ) (

min max

+ = + =

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Introduction Objectives Methods Data & Processing Results Conclusions

Outline

Outline

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Study Area

Data & Manipulation

TN, KY, NC 31 watersheds for USGS gauging sites

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Drought Monitor

Data & Manipulation

Low flow condition in Oct, Nov, Dec of 2005

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MODIS/Terra Vegetation Indices 16-Day L3 Global 1km SIN Grid (MOD13A2)

5 periods in 2005

Oct.16 – Oct.31 Nov.1 – Nov.16 Nov.17 - Dec.2

  • Dec. 3 – Dec.18

Dec.19 - Jan.3

NDVI (Oct.16 – Oct.31)

NDVI band Quality band

  • 16-bit field indicating quality of each NDVI pixel

View angle band

  • Average view zenith angle for each NDVI pixel

Data & Manipulation

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10 periods in 2005

Oct.16 – Oct.23 Nov.1 – Nov.8 Nov.17 - Nov.24

  • Dec. 3 – Dec.10

Dec.19 – Dec.26 Oct.24 – Oct.31 Nov.9 – Nov.16 Nov.25 - Dec.2 Dec.11 – Dec.18 Dec.27 - Jan.3

LST (Oct.16 – Oct.23)

LST band

MODIS/Terra Land Surface Temperature 8-Day L3 Global 1km SIN Grid (MOD11A2)

Quality band

  • 16-bit field indicating quality of each LST pixel

View angle band

  • Average view zenith angle for each LST pixel

Data & Manipulation

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VTCI calculation

  • NDVI-LST plot
  • Dry/wet edges
  • NDVI/quality/angle process
  • LST/quality/angle process
  • LST compositing
  • NDVI-LST extraction

Data Manipulation Process Flow

  • Mosaicing
  • Reprojection
  • Clipping

MRT ArcGIS macro R Data & Manipulation

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ESPM271 Project Outline

Introduction Objectives Methods Data & Processing Results Conclusions

Outline

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NDVI-LST Plot & VTCI

Results

Whole area (610 * 260 km2) in Oct.16 - Oct.31

LST NDVI VTCI NDVI-LST plot

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NDVI-LST Plot & VTCI

Results VTCI NDVI-LST plot

Eastern part (360 * 260 km2) Western part (250 * 260 km2)

NDVI-LST plot VTCI

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NDVI-LST Plot & VTCI

Results VTCI

Whole area (610 * 260 km2)

Oct.16 – Oct.31 Nov.1 – Nov.16 Nov.17 – Dec.2 Dec.3 – Dec.18 Dec.19 – Jan. 3

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NDVI-LST Plot & VTCI

Results

Eastern part (360 * 260 km2)

Oct.16 – Oct.31 Nov.1 – Nov.16 Nov.17 – Dec.2 Dec.3 – Dec.18 Dec.19 – Jan. 3 VTCI

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NDVI-LST Plot & VTCI

Results

Western part (250 * 260 km2)

Oct.16 – Oct.31 Nov.1 – Nov.16 Nov.17 – Dec.2 Dec.3 – Dec.18 Dec.19 – Jan. 3 VTCI

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Low Streamflow Regional Regression Model

Results

Merged VTCI result with other watershed characteristics

database

Stepwise regression

% 7 . 77 5 9 . 43

2 96 . 2 87 . 3 88 . 06 . 4 10 , 7

= − − = R Adj VTCI RDL DA BFI Q % 5 . 76 9 . 26

2 72 . 39 . 2 86 . 18 . 4 10 , 7

= − =

−

R OM RDL DA BFI Q

  • With VTCI
  • Without VTCI
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ESPM271 Project Outline

Introduction Objectives Methods Data & Processing Results Conclusions

Outline

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ESPM271 Project Conclusions

Conclusions

Objective

  • 1. Explore and get familiar with MODIS data & VTCI

MODIS L3 NDVI & LST, quality, view angle data VTCI indicates soil dryness NDVI-LST plot not always a triangle

In the future…

Topographic influences Geographical scales

Conclusion

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Conclusions

Objective

  • 2. Develop an integrated VTCI calculation procedure
  • 3. Apply VTCI in low streamflow modeling

VTCI calculation procedure with MODIS Reprojection

Tool (MRT), ArcGIS macro codes and R

One VTCI data entered in the model

Conclusion

In the future…

Further study on NDVI may lead to model improvement

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References

Andersen, J., I. Sandholt, K. H. Jensen, J. C. Refsgaard and H. Gupta, (2002), Perspetives in using a remotely sensed dryness index in distributed hydrological models at the river-basin scale, Hydrological Processes, 16 (2002), 2973 - 2987. Sandholt, I., K. Rasmussen and J. Andersen, (2002), A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status, Remote Sensing of Environment, 79 (2002), 213 – 224. Wan, Z., P. Wang and X. Li, (2004), Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains, USA, Journal of Remote Sensing, 25(1), 61 – 72. Wang, P., X., Li, J., Gong and C. Song, (2001), Vegetation temperature condition index and its application for drought monitoring, IEEE, 2001. Wang, C., S., Qi, Z., Niu and J. Wang, (2004), Evaluating soil moisture status in China using the temperature-vegetation dryness index (TVDI), Journal of Remote Sensing, 30(5), 671 – 679.

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Outline

END