Remote Sensing Information Needs
for the North Slope Science Initiative
N.H. French and R.A. Shuchman, Altarum Institute
January 2004
Introduction
The environment and ecosystem of the North Slope of Alaska has been undergoing
change since the 1960’s. Some of this change has resulted from affordable motorized
boats, terrain vehicles and snow machines being available to the local indigenous
Alaskan people. Other changes in the environment and ecosystem may be the result of oil
and gas exploration and production, while some impacts are most likely the result of
global climate change. Sorting out changes in the environment of the North Slope that are
the result of anthropogenic activities versus naturally occurring environmental changes is
a difficult task. Remote sensing, with its ability to synoptically map the region, can play
an important role in clarifying the sources of change.
Managing the North Slope requires characterization (inventory), monitoring changes, and
potentially remediation of the environment. Remote sensing is one way of collecting
inventory data of a region in a consistent format. Remote sensing also provides consistent
information over time to serve a monitoring role. Remote sensing data can be used as is,
in the form of images, as products derived from the images, such as land cover type or
feature maps, . The data is most often housed in a geographic information system (GIS), a
tool for organizing, visualizing and analyzing spatial data sets from various sources. A
GIS-based decision support system (DSS) can be employed to use this information for
quantifying the impacts of land use on the environment and ecosystem, and to create
useful information in decision-making for the North Slope management teams.
A set of fundamental layers typically make up an environmental GIS. These layers
include topography, hydrology, infrastructure, meteorology and climate, land cover/land
use, soil type, vegetation type (flora), local fauna, demographics and socioeconomics.
Remote sensing systems can provide some of the critical information needed to create the
GIS layers necessary for a useful DSS.
This paper suggests such a role for remote sensing. Recommendations are made in
respect to the use of civil, commercial, and National Technical Means (NTM) remote
sensing data. First, a review of how remote sensing has been used to study the North
Slope is presented. Next is a summary of remote sensing data sets available as well as
products that have been and could be derived from these data. Finally, recommendations
and strategies for using remote sensing to fill the gaps in the data needed to create an
effective DSS for management of the North Slope.
Background
Within the academic research community, the largest share of research has been funded
under National Science Foundation (NSF) research programs. The main program for
land-based science is the LAII Program – Land-Atmosphere-Ice Interactions, funded by
NSF through the Office of Polar Programs Arctic System Science Program (ARCSS).
Some notes on LAII:
 Started in 1993 with the Flux Study
 Worked on research questions in the Kuparuk River Basin in initial initiative
(Flux Study)
 Continued in 1998 with ATLAS – Kuparuk Basin-based models were
extrapolated to a transect across the North Slope and to Seward Penninsula
 Includes ITEX/NATEX – North American Tundra Experiment
 Includes CALM – Circumpolar Active Layer Monitoring Program
Additional work has been conducted under the NSF’s Long Term Ecological Research
program (LTER). The University of Alaska runs a research station funded largely by
LTER near Toolik Lake in the northern foothills of the Brooks Range, that has been the
site of many research projects and serves as a base of research for Arctic land issues
(http://www.uaf.edu/toolik/).
The US Army Corps of Engineers Cold Regions Research & Engineering Lab (CRREL)
has also conducted many studies of northern Alaska.
The remote sensing work done under NSF, CRREL and other programs includes:
 Landsat – A 50 meter resolution MSS mosaic of the North Slope was done by the
USGS EROS Data Center from imagery of 1977 to 1979. A small mosaic (4
scenes) from Landsat TM of the region around Prudhoe Bay and the northern area
of ANWAR for 1987 is also available at 30 meter resolution. Landsat images of
the Kuparuk River Basin are also available.
 Land cover & vegetation map – A complete, validated map of the north slope was
completed under ARCSS (Muller et al. 1999, Walker 1999, Walker et al. 2002).
The method used Landsat & AVHRR. Layers include:
o land cover (circa 1978)– 100 m pixel
o vegetation complex map – 1:4M
o plant functional types – 1:4M
o horizontal structure – 1:4M
o biomass density – 1:4M
o primary production – 1:4M
 Lake Ice mapping/monitoring – A technique has been developed to monitor lake
ice, including determination of lake depth and freezing to the bottom. This has not
been done for the North Slope as a region, only for select locations for single
winter seasons (Weeks et al. 1977, Weeks et al. 1978, Weeks et al. 1981, Morris
et al. 1995, Jeffries et al. 1996, Duguay and Lafleur 2003).
 Hydrology – from the standard USGS base mapping. Rivers, lakes and wetlands
on the North Slope are mapped at the 1:250,000 scale for the entire region, and at
1:63,360 in limited areas. The data was updated in some areas in the mid-1980’s.
The accuracy and precision of the data is not known.

Snow cover – Remote sensing techniques for mapping snow cover are based on
passive microwave and multi-spectral image algorithms. The two MODIS sensors
collect daily data that is used for mapping snow cover. 8-day composite maps of
snow cover should be available for the North Slope from 2000 to the present.
Historic maps of snow cover may be available from collections of passive
microwave sensors.
NSSI Baseline Information Needs
The following table lists the information needed for an effective GIS-based DSS:
Spatial data layer
Desired spatial
accuracy
Temporal sampling
period
Status
Topography (DEM)
Submeter height 10m
horiz res
1 time
30 -60m resolution avail.
(see below)
Land cover/land use
(vegetation, bare
ground, water,
manmade)
Vegetation type
30m pixels
1 time for region
5 to 10 years for limited
areas
20m pixels
10-15 years
Fauna (animal
population)
1 km
Variable by species
50 m available for region
from 1978
30 m avail for limited
areas
100 m Available for
region
20 m avail for limited
areas
Variable information
Soil type
1 km
1 time
Permafrost
Thaw depth/active
layer
1 km
1 km
5 years
5 years
Surface Hydrology
(lakes, ponds, rivers,
streams, wetlands)
10m pixels
1 time
Coarse scale, circa 1980
maps avail from USGS
1:250,000. Not fully
validated.
Lake depth
Watershed boundaries
Water quality
Snow cover
1m
1:2M
1 km
5 years
1 time
5 years
Bi-weekly in winter
Avail for small areas
Avail.
Unknown
MODIS product avail
beginning 2000.
Meteorology (air
temperature &
pressure, air quality,
cloud cover, etc.)
Air Quality
Climate
Jurisdiction boundaries
Infrastructure (roads,
trails, utility lines,
pipelines, drill pads,
etc.)
Demographics census
tracts
Socioeconomics
1 km
4 hrs
Interpolated data avail
from various sources.
1 km
1 km
10m pixels
5 years
1 time
1 time
5 years
Avail for Barrow
Avail?
Avail.
Incomplete
Census tracts
10 years
Avail
1 km
10 years
Avail
STATSGO. Not
validated.
1970
Searching for data
(CALM)
Available remote sensing data and products
Landsat –16-17 scenes required for full coverage of North Slope (see figure).
 Landsat MSS from mid 1970’s to 1980 – limited available – mosaic is better
 Landsat TM from early 1980’s to 1990’s – limited coverage
 Landsat 7 (ETM+) 1999 to 2003 – very good coverage, but sensor problems
beginning in 2003 continue at present.
 Landsat MSS Mosaic Circa 1978 – Covers entire North Slope, three spectral
bands (green, red, near-ir); 50 m pixel spacing. 2 scenes from 1987.
 Landsat TM – 4-scene mosaic of Prudhoe Bay and east. 30 m resolution
 Landsat ETM+ images of portion of NPRA-northwest – 2 adjacent scenes from
2002
AVHRR – one or two scenes required for full coverage. Composite data more useful than
raw images.
 AVHRR composite images – bi-monthly composites of Alaska for summers 1990
to 1992. 1 km resolution. May be available for 1993/4.
 AVHRR imagery – available at least 2X per day from 1981 to present – difficult
to use “raw” data (see composite images above)
Synthetic Aperture Radar – many data collections from each sensor
 ERS-1/2 SAR – 300+ scenes needed for full NS coverage 1991 to present.
 JERS SAR – 300+ scenes needed for full NS coverage 1994 To 1998
 Radarsat standard beam – 300+ scenes needed for full coverage
 Radarsat ScanSAR – 4 to 6 scenes needed to cover NS 1995 to present
TERRA/AQUA sensors:
 MODIS – multi-spectral system – data collected on 2 satellites – at least one
morning and one afternoon collection each day. 250m to 1km resolution. Many
data products being created (see below).
 MISR & ASTER – multi-spectral sensors with small coverage per scene (smaller
than Landsat). Targeted collections can be requested as a NASA investigator.
Remote sensing products:
 Vegetation index (NDVI) – AVHRR-derived; 15-day composite; 8-km resolution;
global product for 1982 to 2000 available.
 Vegetation index (NDVI/EVI) – MODIS-derived 16-day composite; 250 or 500
m resolution; global product for 2000 to present.
 Snow cover – MODIS-derived; 8-day composite; 500 m resolution; global
product, composite used to eliminate clouds. Algorithm is well tested and robust.
Combination of MODIS snow cover product with passive microwave (AMSR on
AQUA) can yield snow-water equivalent.
 Active layer/thaw depth – Data from the CALM project – may not be RS-derived
Recommendations for filling some baseline information needs with remote sensing:
Infrastructure
Current status:
Metadata on the available infrastructure maps is incomplete, and it is likely that the
digital maps of pipelines and transmission lines are at a relatively coarse scale. We have
good maps of roads, as of 2002, from the TIGER files. It is unknown if the roads layer
has been adequately validated.
Strategy for improving data:
A 2-tiered approach for validating and up-dating existing infrastructure maps is
recommended. High resolution (IKONOS, Quickbird, NTM) and Landsat for new
development areas and Landsat, Aster, or MODIS for outlying areas where precision is
not as necessary and change has been minimal.
A historic time series of infrastructure would be of use for both resource management and
as a resource in homeland defense. This information could be obtained from Landsat or
other archived photos or images including NTM. This task could be limited to areas of
known infrastructure change (Prudhoe, the pipeline corridor, and recent development
areas).
Topography
Current status:
Current DEMs are available from the USGS National Elevation Dataset (NED)
(http://gisdata.usgs.gov/NED/default.asp) based on USGS DLGS. The data is a low
resolution source grided to a 2-arc-second resolution, which equals about 30 meters in
northern Alaska. The precision of the source data determined the NED data precision. In
northern Alaska, the data is not well resolved. Some areas of the North Slope have had
some additional data collections. Also, some NSF projects have acquired airborne
IFSARE data for specific areas.
Strategy for improving data:
It is recommended that 10 m elevation data be acquired for use in the NSSI for adequate
use in hydrologic modeling. This can be done using IFSARE or through standard
photogrammetric methods.
Hydrology
Current status:
The current maps are from standard USGS mapping procedures. Much of the NS has
been mapped at the coarser 1:250,000 scale. Some areas are mapped at the 1:63,360 scale
(inch to a mile). Map updates may not be recent.
Strategy for improving data:
A 2-tiered approach for validating and up-dating existing hydrological features is
recommended. High resolution (IKONOS or Quickbird) and Landsat for new
development areas and Landsat, Aster, or MODIS for outlying areas where precision is
not as necessary and change is less likely.
Land Cover Change
Current status:
A comprehensive, slope-wide mapping of land cover has been done once, in the late
1970’s using Landsat MSS.
Strategy for improving data:
Improvement in land cover change maps will require a new, up-to-date change analysis
with recent ETM+ or other appropriate Multi-spectral data. It is recommended that land
cover change be completed for areas of oil & gas development on a 5 to 10 year
increment.
Lake depth/freezing
Current status:
Lake depth and freezing has not been done for the North Slope, aside from a few studies
of individual lakes for algorithm development.
Strategy for improving data:
The recommendation is to use established SAR-based techniques to map and monitor ice
freezing at development sites and for the entire North Slope region. Lakes around
development areas and along roads and ice road trails can be mapped using ERS SAR.
Development of a slope-wide map of lakes could be done using broad-scale SAR
(Radarsat or EnviSAT).
Snow cover
Current status:
Snow cover maps may be available from 2000 to the present from NASA (MODIS Land
program). The status and validity of the product is unknown. Historic snow cover (pre2000) may be derived from passive microwave imagery (SSMI), but the accuracy would
be less than MODIS-derived maps.
Strategy for improving data:
It is recommended that MODIS products of snow cover be obtained to assess data
validity and utility. Improvements in snow cover information, including snow-water
equivalent, is possible using coincident passive microwave data.
Available passive microwave data and snow cover products should be obtained for a
review of past snow cover conditions. AVHRR-derived NDVI could also be used for
snow cover estimation.
Freeze/thaw
Current status:
Freeze/thaw maps derived from SAR may be available from NASA JPL. The status and
validity of the product is unknown.
Strategy for improving data:
It is recommended that SAR products of freeze/thaw be obtained to assess data validity
and utility.
Vegatation/greenness (NDVI)
Current status:
15-day composite NDVI products would be the desired product for April to September.
Many years of composite data are avail, and a product is currently being made using
MODIS. Approx 20 years of 8-km data are not difficult to obtain. 1 km resolution could
be compiled, but with some missing years.
Strategy for improving data:
It is recommended that appropriate data sets be obtained and conditioned for use in NSSI.
For missing years, raw AVHRR could be acquired and composted.
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