Landsat ET

Mapping

Applications over

Forested

Landscapes Martha C. Anderson, Feng Gao, Yun Yang, Liang Sun

USDA-Agricultural Research Service

Hydrology and Remote Sensing Laboratory

Beltsville, MD

Bruce Cook

NASA - GSFC

Randy Wynne, Val Thomas, Cameron Houser

Virginia Tech

Pro

jec

t o

ve

rvie

w

TOOLS

Multi-sensor data fusion

STARFM

DMS

ALEXI

Thermal image sharpening

Multi-scale ET modeling

ASSETS

GEO

MODIS

Landsat

Lsat-like

Hourly 5km/5km

Daily 250m/1km

16 day 30m/100m

~20-60m/ --

SW/TIR

APPLICATIONS (daily/30 m)

Crop phenology metrics

Crop water use (Evapotranspiration)

Crop stress (drought early warning)

Landsat Science Team, July 2015

DATA FUSION: daily ET at

field scale

Po

lar

(Lan

dsa

t)

Air

bo

rne

(U

SU a

ircr

aft)

Wate

rshe

d

(60

m)

Field

scale

(30

m)

SURFACE TEMPERATURE EVAPOTRANSPIRATION

GEO

(G

OES

Imag

er) R

egio

nal

(5km

) G

EO

(GO

ES S

ou

nd

er) C

on

tine

ntal

(10

km)

Tem

per

atu

re (C

)

Po

lar

(MO

DIS

) Basin

(1

km)

Latent H

eat (W

m-2)

GEO

(I

SCC

P)

Glo

bal

(25

km)

1 July 2002 – 10:30AM LST

corn soy

Hourly

Daily

1 LS – 16 day

2 LS – 8 day

GOES/MODIS/Landsat FUSION

GO

ES

(AL

EX

I)

MO

DIS

(Dis

AL

EX

I)

LA

ND

SA

T

(Dis

AL

EX

I)

DOY 328 329 330 331 332 333 334 335 336

Landsat 5 Landsat 7

(Gao et al, 2006)

Spatial Temporal Adaptive Reflectance Fusion Model

(STARFM)

Daily Evapotranspiration – Orlando, FL, 2002

Loblolly Pine Plantation, NC

Landsat 8 - 2013 Eff

ec

t o

f fo

rest

ma

na

ge

me

nt

Yang, Y., et al. (2015). Daily Landsat-scale evapotranspiration estimation over a

managed pine plantation in North Carolina, USA using multi-satellite data fusion.

Remote Sens. Environ., in preparation

NC2

NC3

Landsat Science Team, July 2015

ALE

XI/

Dis

ALE

XI

GOES MODIS/Landsat LST:

MODIS MODIS/Landsat LAI:

Landcover, fc HEIGHT: hc = hcmin*(1-fc) +hcmax*fc)

Landsat Science Team, July 2015

Ga

p-f

illin

g w

ith

STA

RFM

Landsat Science Team, July 2015

mm/day

5.5

5.3

5.1

4.9

4.7

4.5

4.3

4.1

3.9

3.7

3.5

3.3

3.1

2.9

2.7

2.5

MODIS ET 96

STARFM ET 96

MODIS ET 104

Landsat ET 104

STARFM Landsat ET 96

Gapfilled

Landsat ET 96

Flu

x e

va

lua

tio

n o

n L

an

dsa

t d

ate

s

Ov

erp

ass

Tim

e

Da

ytim

e

NC2 (20yr) NC3 (clearcut)

Landsat Science Team, July 2015

Eff

ec

t o

f fo

rest

ma

na

ge

me

nt

NC2: Loblolly Pine (2013)

Landsat Science Team, July 2015

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

Eff

ec

t o

f fo

rest

ma

na

ge

me

nt

NC3: Clearcut Pine (2013)

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

Landsat Science Team, July 2015

Eff

ec

t o

f fo

rest

ma

na

ge

me

nt

Landsat Science Team, July 2015

Wa

ter

use

va

ria

bili

ty w

ith

sta

nd

ag

e

Pine Plantation Stand Age

Landsat Science Team, July 2015

Wa

ter

use

va

ria

bili

ty w

ith

lan

d u

se

Landsat overpasses

Landsat Science Team, July 2015

7-D

ay A

ver

age

ET

(m

m)

Cu

mu

lati

ve

ET

(m

m)

Day of Year

Day of Year

NA

SA

G-L

iHT

airb

orn

e s

yst

em

Goddard’s LiDAR, Hyperspectral and Thermal

Airborne Imaging System

Collaborator B. Cook

Landsat Science Team, July 2015

Landsat Science Team, July 2015

NA

SA

G-L

iHT

airb

orn

e s

yst

em

Landsat Science Team, July 2015

GLiHT TSEB Difference

Canopy height over Parker Tract NC2

NC3

Landsat Science Team, July 2015

LST Canopy

Height Fraction

Cover LAI N

ASA

G-L

iHT

airb

orn

e s

yst

em

Other G-LiHT inputs to TSEB

NC2

NC3

Co

nc

lusi

on

s

USDA is an equal opportunity provider and employer.

For further investigation:

Study differences in water balances among different

land cover types (natural/managed forests, crops).

How has ET and runoff (P - ET) in the region changed

over time?

How does forest age affect ET and water yield? How

might this kind of information impact management

of water yield through forest cutting?

Can we use Landsat ET to validate

watershed/regional hydrological models?

hrsl.arsusda.gov/drought

Landsat Science Team, July 2015

Afr

ica

n M

on

soo

n P

roje

ct

(MJ m-2 d-1)

African Monsoon Multidisciplinary Analysis (CNRM, CESBIO)

BENIN

NIGER

MALI Flux towers

Landsat Science Team, July 2015

MSG (3km)

MSG (3km)

MODIS (1km)

MODIS (1km) L7 (30m) L7 (30m)

L7 (30m)

Bellefoungou Forest

BENIN, AFRICA mm/day