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US Remote Sensing Capabilities. Chris Justice and John Townshend. NASA’s Earth Observing System & Related Satellites. Next Generation Missions. Relevance to Land of US assets. In fact relatively small number of assets directly relevant to land MODIS VIIRS Landsat

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us remote sensing capabilities

US Remote Sensing Capabilities

Chris Justice and John Townshend

relevance to land of us assets
Relevance to Land of US assets
  • In fact relatively small number of assets directly relevant to land
  • MODIS
  • VIIRS
  • Landsat
  • Also we need a “VCL” type instrument for the vertical dimension in vegetation
    • Just possibly may be revived.
  • Plus we need regular very high resolution data for scaling and validation which potentially could be provided by US commercial satellites
slide5

VIIRS EDR Priorities & Performance

Imagery (with four

ARRs

)

IA

Sea Surface Temp

Aerosol Optical Thickness

Aerosol Particle Size

Suspended Matter

Cloud Cover/Layers

Cloud Effective Particle Size

Cloud Optical Thickness

Cloud Top Height

Cloud Top Pressure

Cloud Top Temperature

IIA

Albedo

Land Surface Temperature

Vegetation Index

Snow Cover/Depth

Surface Type (ST)l

Fresh Water Ice(Sea Ice ARR)

Visible/IR Imager Radiometer Suite

Ice Surface Temperature

Ocean Color/Chlorophyll

Sea Ice Characterization

Active Fires (ST ARR)

IIB

Precipitable

Water

Cloud Base Height

IIIB

Net Heat Flux

Soil Moisture

avhrr viirs transition schedule

M

N

16

C2

N’

10-Year Mission Life

for NPOESS

EOS-Aqua

AVHRR-VIIRS Transition Schedule

CY

99

00

01

02

03

04

05

06

07

08

09

10

11

12

13

14

15

16

17

18

NPOESS

C1

VIIRS

0930 - 1030

AVHRR

METOP-AVHRR

1030

EOS-Terra

NPP

1330

VIIRS

AVHRR

Local Equatorial Crossing Time

S/C

Deliveries

S/C delivery interval driven by 15 month IAT schedule

6

Last Modified: Dec 1, 2001

landsat data
Landsat data
  • Landsat class data with the Landsat 7 acquisition strategy (LTAP) has been highly successful in satisfying multiple user needs
    • GLCF has regular downloads of 25,000 + scenes per month.
  • But Landsat now has major problems.
landsat 7 has significant problems for change detection
Scan Line Corrector failure means that only the central 28 kms has no missing data.

In fact this still means that 78% of the data is collected.

But the 22% not collected is NOT the same 22% on each image and hence change detection is significantly compromised.

Landsat 7 has significant problems for change detection.
landsat 7 fixes
Landsat 7 fixes

1. Enhanced SLC-off Browse Image

  • The Landsat 7 browse image displayed on all data ordering interfaces has been modified to allow users to estimate the width of potential SLC-off scan gaps over their area of interest.

2. User-Selected Interpolation

  • Users will have the ability to select the number of pixels that are interpolated across the data gaps during Level 1G processing. This will allow potential production of a fully populated image when specified by the user.

3. SLC-off Data Available through NLAPS

  • Users will have the option to purchase National Landsat Archive Production System (NLAPS) processing if desired.

4. Gap-filled product - Phase 1 (SLC-off / SLC-on Merge)

  • An initial (Phase 1) gap-filled image product will be generated by replacing the missing data of an SLC-off scene with pixel values derived from a coregistered, histogram-matched SLC-on scene. product.

5. Gap-Filled Product - Phase 2 (SLC-off / SLC-off Merge)

  • A second (Phase 2) gap-filled image product will be generated from the merge of two or more SLC-off scenes to produce a single image product.

6. Inclusion of band-specific Gap Mask

can landsat be replaced with existing assets
Can Landsat be replaced with existing assets?
  • SPOT HRV and IRS can provide data with ground receiving capability.
  • Some efforts already to do this, though very slow response from the US.
  • Unclear if resultant products are truly interoperable, but probably acceptable.
  • But far from global coverage and the quality of acquisition strategy will be below that of Landsat.
availability of the historical record
Availability of the historical record
  • Almost complete global coverage for the early 90’s and 2000 available through NASA/Earthsat’s Geocover initiative
  • Available on-line through the GLCF and through TRFIC
  • Made available to countries (though UNEP and FAO)
  • Very valuable data set but with significant limitations.
    • Timing of acquisition varies substantially
    • Varying phenology hinders change detection
slide13

What is the quality of the data: analysis for southern Africa of the quality of FAO proposed 1 degree sample 10km squares

analysis of suitability of geocover images for 1990 for southern africa by glcf
Analysis of suitability of GeoCover images for 1990 for Southern Africa by GLCF
  • Total Number: 308
  • Fully acceptable 180
  • Restricted value due to cloud etc 89
  • Unacceptable 39
  • Hence historical record is less satisfactory than at first appears
what can we learn from these issues
What can we learn from these issues?
  • We do not have the final solution.
  • We need an operational fine resolution (20-50m) land observing system
    • one that is guaranteed in the long-term
    • POLO Polar Orbiting Land Observer
    • Possible platform - NPOESS Lite
  • Having the assets in orbit is not sufficient: an excellent acquisition strategy is vital
  • Avoid moving parts if at all possible.
enhancements to etm are needed
Enhancements to ETM+ are needed.
  • LDCM Science Team for Resource 21made the following recommendations
    • Add bands especially a Cirrus band (1380nm – Goetz, Gao et al)
    • Alter bandwidths (lessons learnt from MODIS)
      • 10nm reduction (to 680 nm) in upper bound of red band
      • Narrow and reposition NIR band to avoid water vapor,
      • Narrowing and repositioning of SWIR2 to the 1560nm to 1660 nm region to avoid water vapor attenuation.
      • Shift the SWIR3 to the 2100 nm to 2300 nm region to reduce water vapor absorption impact.
    • Improve the MTF (e.g., average 9x10m bands)
    • Improve frequency of acquisition (e.g. to 2 days).
slide17

Conciliating spatial and temporal resolutions: towards an operational concept for land environment: argues for more frequent observations at Landsat/SPOT resolutions

Landsat

SPOT 5

SPOT

ERS

Pléiades

MERIS

MODIS

VGT

POLDER

MSG

« Gap »

10-20 m spatial resolution

8-12 spectral bands2 days revisit

Full and operational observation of continents

Source: H. Jeanjean

recent developments
Recent developments
  • US has at last accepted that a Landsat class capability be regarded as an operational necessity.
  • Proposal in recent RFI is to place an ETM+ like instrument on NPOESS.
  • But this could be 2009 or later. Hence possibility of a major gap.
      • May be a earlier launch but resources may not be available.
      • International effort should be launched to use existing international assets to satisfy LTAP.
  • Frequency would drop to once every 17 days.
  • Suggested enhancements:
      • Significantly widen swath (2-3 times)
      • Additional low cost free-flyers (Surrey Satellite model?) with possibly simpler sensors to improve temporal resolution and as operational back-ups.
      • Need reflectance products not DNs.
      • Also orthorectified products.
extra slides
Extra slides
  • One on a new crop data set though coarse resolution
  • Two extra JAXA slides if you need them
global distribution of wheat

Global Data Set of 18 Major Crops

Global Distribution of Wheat

Derived by merging remotely-sensed global land cover data with crop census data.

Leff, B., N. Ramankutty, and J. Foley, Geographic distribution of major crops across the world, Global Biogeochemical Cycles, 18, GB1009, 2004.

Center for Sustainability and the Global Environment Nelson Institute for Environmental Studies University of Wisconsin-Madison

sea 1 2 cd set mainland south east asia dual season dry rainy mosaicking sar processing by nasda

GRFM/GBFM Data Sets

AFR-1 (3 CD set)

West & Central Africa and Madagascar

Dual-season (Low water/high water)

Mosaicking by JRC

SAR processing by NASDA

AM-1 (4 CD set)

South America/Amazon

Dual-season (Low water/high water)

Mosaicking by JPL

SAR processing by ASF & NASDA

SEA-1 (2 CD set)

Mainland South-East Asia

Dual-season (Dry/rainy)

Mosaicking & SAR processing by NASDA

NA-1 (DVD)

Boreal North America

Dual-season (Summer/winter)

Mosaicking by JPL

SAR processing by ASF

AM-3 (2 CD set)

Central America/Pantanal

Mosaicking by JPL

SAR processing by ASF & NASDA

slide22

New Data Sets in the pipeline

SEA-3

Insular South-East Asia

(Philippines, New Guinea)

Single season

Mosaicking & SAR processing by JAXA

Target:June 2004

AU-1

Australia

Single season

Mosaicking & SAR processing by JAXA

Target: JFY 2004

SEA-2

Insular South-East Asia

(Kalimantan, Java, Sumatra, Sulawesi)

Multi-annual (1994/1996/1998)

Mosaicking & SAR processing: JAXA

Target: April 2004

AFR-2

Southern Africa

Single season

Mosaicking by JPL

SAR processing by JAXA

China

Single season

Mosaicking & SAR processing by JAXA

Target: JFY 2004

India

Single season

Mosaicking & SAR processing by JAXA

Target: JFY 2004

AM-4

Southern South America

Single season

Mosaicking by JPL

SAR processing by JAXA