Daily Monitoring of Vegetation Conditions and Evapotranspiration at Field Scale by

Fusing Multi-satellite Images

Feng Gao and Martha Anderson

USDA-Agricultural Research Service Hydrology and Remote Sensing Laboratory Beltsville, MD 20705 feng.gao@ars.usda.gov

USDA is an equal opportunity provider and employer

MultiTemp 2017, June 27-29, 2017, Bruges, Belgium

May 6, 2016 May 11, 2016

May 27, 2016 June 11, 2016

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Landsat 30m on 5/29/2016 MODIS 250m on 5/29/2016

frequent but coarse fine but infrequent

Sentinel-2A 10m on 6/26/2016

Landsat 30m on 8/17/2016

MODIS 250m on 6/10/2016 MODIS 250m on 6/26/2016

MODIS 250m on 7/23/2016 MODIS 250m on 8/17/2016

Combine Multi-sensor Data - High Temporal and Spatial Resolution Datacubes

Multi-sensor VI for Daily Monitoring of Vegetation Conditions

org. Landsat and S2

Harmonization

Data Fusion

Phenology Program Yield/Biomass

Variability

SR /VI Datacubes

Anomaly Analysis

Phenology Crop Growth

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(i) Red

(j) NIR

(a) 4/18, ASTER (b) 4/26, AWiFS (c) 6/5, ASTER (d) 6/13, TM

(e) 7/7, AWiFS (f ) 7/23, ETM+ (g) 7/31, TM (h) 8/24, AWiFS

Multi-sensor Data Harmonization

Reference (MODIS NBAR)

Landsat 5/29/2016 MODIS 5/29/2016

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Spatial and Temporal Adaptive Reflectance Fusion Model

STA

RFM

(3

0 m

)

STARFM

MO

DIS

La

ndsa

t

6/4/01 (155) 7/4/01 (185)

Reconstructed images

Observed

pairs

5/24/01 (144) 7/11/01 (192)

https://www.ars.usda.gov/research/software/download/?softwareid=432 (Gao et al., TRGS 2006)

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Central Iowa (a rain-fed agricultural area) V

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MODIS NDVI (250m)

Jun 6 (157) Jul 4 (185) Aug 9 (221)

Sep 5 (248) Oct 1 (274) CDL (2011)

0.0 0.5 1.0 Yellow: corn; Green: soybeans

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Jun 6 (157) Jul 4 (185) Aug 9 (221)

Sep 5 (248) Oct 1 (274) CDL (2011)

0.0 0.5 1.0 NDVI from fused data (30m) Yellow: corn; Green: soybeans

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5

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Smoothed and Gap-filled Daily NDVI (30m), Apr. 1 – Nov. 1, 2011

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2001 2006 2011 2014

Apr

May

Ju

n

Greenup

CD

L

Gao etc. (2017). Mapping crop progress at field scales using Landsat and MODIS imagery. Remote Sensing of Environment. 188:9-25.

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Oct

N

ov

Dorm

ancy

Apr May Jun

Remote Sensing Phenology to

Crop Growth Stages

Gre

enup

dat

e R

elat

ions

hip

from

pre

viou

s ye

ars

Backcast Emerged Date (2014) VI a

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Yield Variability at Field Scale (corn, central Iowa, 2010)

0.7 0.8 0.9 1.0 max_NDVI

60 100 140 180 220 (Bu/Acre)

Monroe

Marshall

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Central Plains Experimental Range (CPER) V

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Gap-filled and smoothed daily NDVI(30m) using original Landsat and the fused Landsat-MODIS data Central Plains Experimental Range (CPER) LTAR site, 2013

Data Sources: Landsat -8 125, 157,173, 221,237,269, 365 MODIS Daily (250m) 16-day BRDF Approach: -STARFM -Modified SG filtering

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1.0

Precipitation (May 15-Oct 1)

NDVI (August 1)

ANHP (g/m2)

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_ND

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ANHP: Aboveground Net Herbaceous Production

ANHP (g/m2)

LM_N

DV

I

… based on land surface temperature MULTI-SCALE SATELLITE ET RETRIEVAL

EVAPOTRANSPIRATION = EVAPORATION (non-beneficial use) + TRANSPIRATION (beneficial use)

Water use accounting

Irrigation efficiency

Crop stress and yield prediction

Crop water productivity (crop per drop)

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1.0

4/1 5/1 5/31 6/30 7/30 8/29 9/28 10/28

ND

VI

Date

planted emerged silked dough dented mature harvestedStress (ET/PET)

[ ]∑ ××= HIETTLUEfPARPARYield iii *),,( maxεPeak

Dormancy

Clear Landsat

Landsat/ MODIS fusion

Remote sensing stages Phenological

stages

timeseries fit

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DATA FUSION: daily ET at field scale

Pola

r (L

ands

at)

Airb

orne

(U

SU a

ircra

ft)

Watershed

(60m)

Field scale (30m

)

SURFACE TEMPERATURE EVAPOTRANSPIRATION

GEO

(G

OES

Imag

er) Regional

(5km)

GEO

(G

OES

Sou

nder

) Continental (10km

)

Tem

pera

ture

(C)

Pola

r (M

ODI

S) Basin

(1km)

Latent Heat (Wm

-2) G

EO

(ISCC

P) G

lobal (25km

)

1 July 2002 – 10:30AM LST

corn soy

Hourly

Daily

1 LS – 16 day 2 LS – 8 day

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GOES/MODIS/Landsat FUSION

GO

ES

(A

LEXI

) M

OD

IS

(Dis

ALEX

I) LA

ND

SA

T

(Dis

ALEX

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DOY 328 329 330 331 332 333 334 335 336

Landsat 5 Landsat 7

Spatial Temporal Adaptive Reflectance Fusion Model (STARFM)

Daily Evapotranspiration – Orlando, FL, 2002

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Daily

ET (

mm

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)

Day of Year

SMEX02 (Iowa) Soil Moisture Experiment 2002 Ames, Iowa Rainfed corn and soybean

4 km

SMEX02

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Daily

ET (

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Day of Year

Rainfed soybean – SMEX02 (Iowa)

Reference ET Observed ET Landsat retrievals Landsat-only

RAIN

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ET (

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Day of Year

Rainfed soybean – SMEX02 (Iowa)

Reference ET Observed ET Landsat retrievals Landsat-only Landsat-MODIS fusion

RAIN

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Cum

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ET (m

m)

Day of Year

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Reference ET Observed ET Landsat retrievals Landsat-only Landsat-MODIS fusion

Daily

ET (

mm

per

day

)

RAIN

Rainfed soybean – SMEX02 (Iowa) V

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Gallo Vineyards, Lodi CA

GRAPEX (Grape Remote sensing Atmospheric Profiling & Evapotranspiration eXperiment), 2013-2017

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Landsat-7 and 8 (p44r33 and p43r33)

0 1 2 3 4

1/1 4/1 7/1 10/1 12/31

Landsat LAI VI a

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Landsat (30m)

Cumulative ET Cumulative LAI Max LAI

2013 Yield V

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Gallo Vineyards, Lodi CA

2015 Cumulative ET (mm) Cumulative ET (mm) 2016

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NOAA – NESDIS – STAR GOES Evapotranspiration and Drought Product System (GET-D)

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NOAA – NESDIS – STAR GOES Evapotranspiration and Drought Product System (GET-D)

Landsat (30m) GOES (4km)

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ET (m

m/d

ay)

Day of year

Choptank (2014)

Rainfall (m

m/day)

ALEXI ET (4km) Observed ET Landsat retrieval Landsat-MODIS fusion Precipitation

4km

Sun, L., Anderson, M. C., Gao, F., Hain, C., Alfieri, J. G., Sharifi, A., McCarty, G. W., Yang, Y., Yang, Y., Kustas, W. P. and McKee, L. (2017), Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach. Water Resour. Res.. doi:10.1002/2017WR020700. V

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Daily VI and ET Datacubes Improved monitoring of vegetation conditions Improved accounting of current water use and crop

water productivity (crop per drop) Monitoring changes in vegetation phenology and

water use with changing climate, land-use and human activities

Improved hydrologic monitoring (flood, drought, runoff) to better cope with extremes

Improved crop growth stages and stress detection for yield estimation

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