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Philip Heilman and Guillermo Ponce
With help from the BLM, Forest Service
and Applied Geosolutions
Strengths
๏‚— Cover whole allotment and area around it
๏‚— Can go back in time (Landsat 5 to 1984)
๏‚— Can compare across allotments
๏‚— Can compare to potential (given site potential and
recent climate)
Weaknesses
๏‚— Broader, but shallow (no composition)
๏‚— Not directly comparable to field measurements
๏‚— Error โ€“ but in many cases improvable
๏‚— A โ€œBig Dataโ€ problem โ€“ takes skill and time
Side view of lidar point cloud of a mesquite tree
by Tyson Swetnam
Sensor Production Cover
Landsat (1984-) Maximum NDVI Value in the
Year
30 m Spatial Resolution
Annual 2000-2013
SATVI Derived Total
(Green + Senescent)
Foliar Cover
30 m Spatial Resolution
Pre and Post Monsoon
2008-2011
MODIS (2000-) Integrated Enhanced
Vegetation Index (iEVI)
250 m Spatial Resolution
Every 16 Days. 2000-2013
SATVI Derived Total
(Green + Senescent)
Foliar Cover
500 m Spatial Resolution
Every 8 Days, 2000-2013
Other Sensors?
Other Products? ? ?
MODIS (8 Day) % Cover
500m
100m
Ranking Allotments for Production - Landsat Max NDVI
Loamy Upland
(41-3) Reference
Area
Loamy Upland
(41-3) Mesquite-
Dominated
Eroded State
R = 0.65
Algorithm
Field Measurements Used to Develop SATVI to Cover Relationship
Cover:
โ€ข 5% measured
โ€ข10% Landsat
(ID: 123-0.022)
Cover:
โ€ข 17% measured
โ€ข22% Landsat
(ID: 54-0.094)
AZ NM
Johnny Creek
Bonita Creek
Strengths
๏‚— Cover whole allotment
๏‚— Can go back in time
๏‚— Can compare across allotments
๏‚— Can compare to potential (given site potential and
recent climate)
Weaknesses
๏‚— Broader, but shallower (no composition)
๏‚— Not directly comparable to field measurements
๏‚— Error โ€“ but in many cases improvable
๏‚— A โ€œBig Dataโ€ problem โ€“ takes skill and time
Sensor Production Cover
Landsat (1984-) Maximum NDVI Value in the
Year
30 m Spatial Resolution
Annual 2000-2013
SATVI Derived Total
(Green + Senescent)
Foliar Cover
30 m Spatial Resolution
Pre and Post Monsoon
2008-2011
MODIS (2000-) Integrated Enhanced
Vegetation Index (iEVI)
250 m Spatial Resolution
Every 16 Days. 2000-2013
SATVI Derived Total
(Green + Senescent)
Foliar Cover
500 m Spatial Resolution
Every 8 Days, 2000-2013
Other Sensors?
Other Products? ? ?
The road to wisdom? Well its plain
and simple to express:
Err
and err,
and err again,
but less
and less
and less. by Piet Hein
๏‚— Field data becoming more expensive to collect
๏‚— Harder to stay up to date with NEPA requirements
๏‚— Catalog of free (raw) imagery (Landsat 1984-;
MODIS 2000-; Google Earth Engine)
๏‚— EVI and maxNDVI datasets, Total Cover from SATVI
๏‚— Supporting technology is improving (GPS; GIS
datasets; Aerial Photography; Big Data technology)
Remote sensing is on the verge of being able to
complement, but not replace, field data
Toward operational remote sensing of public land

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Toward operational remote sensing of public land

  • 1. Philip Heilman and Guillermo Ponce With help from the BLM, Forest Service and Applied Geosolutions
  • 2.
  • 3.
  • 4. Strengths ๏‚— Cover whole allotment and area around it ๏‚— Can go back in time (Landsat 5 to 1984) ๏‚— Can compare across allotments ๏‚— Can compare to potential (given site potential and recent climate) Weaknesses ๏‚— Broader, but shallow (no composition) ๏‚— Not directly comparable to field measurements ๏‚— Error โ€“ but in many cases improvable ๏‚— A โ€œBig Dataโ€ problem โ€“ takes skill and time
  • 5.
  • 6.
  • 7. Side view of lidar point cloud of a mesquite tree by Tyson Swetnam
  • 8. Sensor Production Cover Landsat (1984-) Maximum NDVI Value in the Year 30 m Spatial Resolution Annual 2000-2013 SATVI Derived Total (Green + Senescent) Foliar Cover 30 m Spatial Resolution Pre and Post Monsoon 2008-2011 MODIS (2000-) Integrated Enhanced Vegetation Index (iEVI) 250 m Spatial Resolution Every 16 Days. 2000-2013 SATVI Derived Total (Green + Senescent) Foliar Cover 500 m Spatial Resolution Every 8 Days, 2000-2013 Other Sensors? Other Products? ? ?
  • 9. MODIS (8 Day) % Cover
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  • 27. Ranking Allotments for Production - Landsat Max NDVI
  • 28.
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  • 31. Loamy Upland (41-3) Reference Area Loamy Upland (41-3) Mesquite- Dominated Eroded State
  • 33. Algorithm Field Measurements Used to Develop SATVI to Cover Relationship Cover: โ€ข 5% measured โ€ข10% Landsat (ID: 123-0.022) Cover: โ€ข 17% measured โ€ข22% Landsat (ID: 54-0.094)
  • 35.
  • 36.
  • 37.
  • 38. Strengths ๏‚— Cover whole allotment ๏‚— Can go back in time ๏‚— Can compare across allotments ๏‚— Can compare to potential (given site potential and recent climate) Weaknesses ๏‚— Broader, but shallower (no composition) ๏‚— Not directly comparable to field measurements ๏‚— Error โ€“ but in many cases improvable ๏‚— A โ€œBig Dataโ€ problem โ€“ takes skill and time
  • 39. Sensor Production Cover Landsat (1984-) Maximum NDVI Value in the Year 30 m Spatial Resolution Annual 2000-2013 SATVI Derived Total (Green + Senescent) Foliar Cover 30 m Spatial Resolution Pre and Post Monsoon 2008-2011 MODIS (2000-) Integrated Enhanced Vegetation Index (iEVI) 250 m Spatial Resolution Every 16 Days. 2000-2013 SATVI Derived Total (Green + Senescent) Foliar Cover 500 m Spatial Resolution Every 8 Days, 2000-2013 Other Sensors? Other Products? ? ?
  • 40. The road to wisdom? Well its plain and simple to express: Err and err, and err again, but less and less and less. by Piet Hein
  • 41. ๏‚— Field data becoming more expensive to collect ๏‚— Harder to stay up to date with NEPA requirements ๏‚— Catalog of free (raw) imagery (Landsat 1984-; MODIS 2000-; Google Earth Engine) ๏‚— EVI and maxNDVI datasets, Total Cover from SATVI ๏‚— Supporting technology is improving (GPS; GIS datasets; Aerial Photography; Big Data technology) Remote sensing is on the verge of being able to complement, but not replace, field data