vegetation temperature condition index (vtci) and its...

Vegetation Temperature Condition Index (VTCI) and Its Application for

Low Streamflow Regional Regression Model

Satoshi Hirabayashi

SUNY-ESFSUNY-ESF11/15/2005

ESPM271 Project

Outline

Introduction

Objectives

Methods

Data & Processing

Results

Conclusions

Outline


ESPM271 Project

Outline

Outline

Introduction

Objectives

Methods

Data & Processing

Results

Conclusions


ESPM271 Project

Research Theme

Introduction

Low streamflow prediction in ungauged watersheds- Regional regression model

⋅⋅⋅= γβα 2110,7 XXQQ7,10 : 7-day, 10-year low streamflow statisticsXi : Watershed characteristicsα, 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

TimeD

isch

arge

Base flow

Surface flow

Flood

Low flow


ESPM271 Project

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)


ESPM271 ProjectOutline

Introduction

Objectives

Methods

Data & Processing

Results

Conclusions

Outline


ESPM271 Project

Objectives

Objectives

1. Explore and get familiar with MODIS data & VTCI


ESPM271 Project


Objectives

2. Develop an integrated VTCI calculation procedure

Objectives


ESPM271 Project


Objectives

3. Apply VTCI in low streamflow modeling

Objectives




Introduction

Objectives

Methods

Data & Processing

Results

Conclusions

Outline


ESPM271 Project

NDVI-LST Space

Methods

bare soil

partial cover

full cover

Dry Edge

LST

No Transpiration

Wet Edge

NDVI

Max Transpiration

No Evaporation

MaxEvaporation


ESPM271 Project

VTCI Calculation

Methods

LSTmax

LSTmin

NDVI

LST

NDVIi

LST(NDVIi)

LSTmax(NDVIi)

LSTmin(NDVIi)

)()()()(

minmax

max

NDVIiLSTNDVIiLSTNDVIiLSTNDVIiLSTVTCI

−−

=NDVIibaNDVIiLST

bNDVIiaNDVIiLST'')(

)(

min

max

+=+=


ESPM271 Project

Introduction

Objectives

Methods

Data & Processing

Results

Conclusions

Outline

Outline


ESPM271 Project

Study Area

Data & Manipulation

TN, KY, NC

31 watersheds for USGS gauging sites


ESPM271 Project

Drought Monitor

Data & Manipulation

Low flow condition in Oct, Nov, Dec of 2005


ESPM271 Project

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


ESPM271 Project

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


ESPM271 Project

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

ArcGISmacro

R

Data & Manipulation



Introduction

Objectives

Methods

Data & Processing

Results

Conclusions

Outline


ESPM271 Project

NDVI-LST Plot & VTCI

Results

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

LST

NDVI

VTCI

NDVI-LST plot


ESPM271 Project


Results

VTCI

NDVI-LST plot

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

NDVI-LST plot

VTCI


ESPM271 Project


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


ESPM271 Project


Results

Eastern part (360 * 260 km2)



Dec.19 – Jan. 3

VTCI


ESPM271 Project


Results

Western part (250 * 260 km2)



Dec.19 – Jan. 3

VTCI


ESPM271 Project

Low Streamflow Regional Regression Model

Results

Merged VTCI result with other watershed characteristics database

Stepwise regression

%7.77

59.432

96.287.388.006.410,7

=−

−=

RAdj

VTCIRDLDABFIQ

%5.76

9.262

72.039.286.018.410,7

=

−= −

R

OMRDLDABFIQ

- With VTCI

- Without VTCI



Introduction

Objectives

Methods

Data & Processing

Results

Conclusions

Outline


ESPM271 ProjectConclusions

Conclusions

Objective


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


ESPM271 ProjectConclusions

Conclusions

Objective


3. Apply VTCI in low streamflow modeling

VTCI calculation procedure with MODIS ReprojectionTool (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


ESPM271 Project

ReferencesAndersen, 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.


ESPM271 Project

Outline

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