Exploring New Remote Sensing Datafor Characterization of Tropical
Phenology
Tomoaki Miura
Professor, Dept. Natural Resources and Environmental Management,
University of Hawaii at Manoa
Visiting Principal Scientist, Japan Agency for Marine-Earth Science andTechnology (JAMSTEC)

Introduction• Remote sensing applications in tropical Asia
• Land use/land cover change analysis (deforestation etc.) with Landsat (30m, every 16-day)• Land use characterization with synthetic aperture radar (SAR, all weather capability)• Ecosystem productivity and vegetation-climate interactions with MODIS (500m, 1-2 days)• Biodiversity and ecosystem dynamics studies with remote sensing• Frequent and persistent cloud cover making it difficult to observe the surface• Moderate-low spatial resolution data nearly impossible to observe vegetation at species level
New Remote Sensing Data 1:

New Remote Sensing Data 2:

Third-Generation
Geostationary Satellites

Commercial Satellites

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New-generation
GeostationaryImagers• Larger number of“narrow” spectralbands• Higher spatial
resolution (1-2km)• Higher temporal
resolution (~10 min)

Sample Images: 2016-05-01
Himawari-8 AHI

S-NPP VIIRSDiurnal wildfire dynamics, Montana, USBy early afternoon, fires create local circulations and break out.

(Nemani et al., 2019)
New opportunities for land monitoringInternational Constellation ofThird-Generation Geostationary Satellites

Source: World Meteorological Organization website(http://www.wmo.int/pages/prog/sat/globalplanning_en.php)

International constellation
1-2km coverage for large portions of the Earthat 5-15 minute interval

GOES-17(USA)

GOES-16
(USA)

MTG-I
(EU)

FY-4(China)

GK-2A(Korea)Himawari(Japan)(Source: Nemani et al., 2019)

Himawari-8 Ground Coverage

https://sciblogs.co.nz/out-of-space/2019/01/16/satellite-orbits-geostationary/

NDVI

Himawari-8 NDVI image
for the month of July 2016

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Himawari-8

NDVI
TemporalProfiles forTakayama(TKY)

VIIRS(Miura et al., Scientific Reports, 2019)

10000

Himawari

TOA NDVI (x10,000)

TOA NDVI (x10,000)

10000
8000
6000
4000
2000

8000
6000
4000
2000

02016.000 2016.060 2016.120 2016.180 2016.240 2016.300 2016.360

02016.000 2016.060 2016.120 2016.180 2016.240 2016.300 2016.360

Year.DOY

Year.DOY
10000

TOA NDVI (x10,000)

10000

TOA NDVI (x10,000)

VIIRS

8000
6000
4000
2000
08000
60004000
20000

2016.1202016.140

2016.160

Year.DOY

Himawari - out of 43 days of green-up period:• 12 days with confirmed cloud-free observations

2016.1202016.140

2016.160

Year.DOYVIIRS - out of 43 days of green-up period:• 6 days with confirmed cloud-free observations(Miura et al., Scientific Reports, 2019)

Himawari-8 Images of Borneo: 31-May-2019
10 min resolution image

With Shin Nagai@JAMSTEC and Kazuhito Ichii@CEReS - Chiba University

Daily composite imageNDVI at Lambir Hills: Himawari-8 vs. MODIS
Himawari

MODIS

With Shin Nagai@JAMSTEC and Kazuhito Ichii@CEReS - Chiba University

NDVI at Lambir Hills: Himawari-8 vs. MODIS
Himawari (16-day composite)

MODIS (quality-assured)With Shin Nagai@JAMSTEC and Kazuhito Ichii@CEReS - Chiba University

Himawari-8 NDVI Comparison with In Situ
Cloud Cover Measurements at Lambir Hills
Year 2015
Very Sunny (3)Sunny (2)Cloudy (1)2015-358 at 16:15

2015-358 at 13:15

2015-358 at 09:15

With Shin Nagai@JAMSTEC and Kazuhito Ichii@CEReS - Chiba University

Himawari-8 NDVI Comparison with In Situ
Cloud Cover Measurements at Lambir Hills
Year 2015
PEN 15-min resolution

Himawari 10-min resolution

With Shin Nagai@JAMSTEC and Kazuhito Ichii@CEReS - Chiba University

Very Sunny (3); Sunny (2); Cloudy (1); Missing Obs. (0)3210

Himawari-8 NDVI Comparison with In Situ
Cloud Cover Measurements at Lambir Hills
Year 2015
PEN 15-min resolution

In Situ Cloud

NDVI

Himawari 10-min resolution*Darker Green = More Cloudy(Black = Missing Data)

With Shin Nagai@JAMSTEC and Kazuhito Ichii@CEReS - Chiba University

3210

Commercial Satellite Remote Sensing• Characterized by very highspatial resolution imagery(50 cm – 4 m)
• Available since the year
1999, but at very low
temporal frequencies

Mapping Trees in the Puu Waawaa Tropical Dry Forest in Hawaii(Martinez-Morales, Miura, & Idol, 2008, For. Ecol. Manag.)

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Commercial Satellite Remote Sensing• Characterized by very highspatial resolution imagery(50 cm – 4 m)
• Available since the year
1999, but at very low
temporal frequencies

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WorldView-2 50-cm Natural Color – Central City, Pennsylvania; October 1, 2012
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Commercial Satellite Remote Sensing• Recently, high resolution commercial remote sensing
data have become available at higher temporalfrequencies
PlanetDove (10 cm by 10 cm by 30 cm)• Spatial Resolution: 3-5 m(Source: https://www.planet.com/company/approach/)https://storage.googleapis.com/planet-ditl/day-in-the-life/index.html
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(Kääb et al., 2019, Hydrol. Earth Syst. Sci., https://doi.org/10.5194/hess-23-4233-2019)

Summary• Third-generation geostationary satellites• New data source for improved monitoring of tropical phenology andecosystem productivity• High resolution commercial satellites• Suitable data source for augmenting and/or spatially-extending field-based
species-level observations of tropical phenology

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