Crawley using r to evaluate street stress on park use
Caldwell community sustainability and land use policy
1. Community Sustainability and
Land Use Policy Development
through Remote Sensing and
GIS Based Land Cover Mapping
Presented by:
Jason Caldwell
Vice President of Business Development and Sales
Date: September 24th, 2014
3. Sanborn – Leader Since 1866 Sanborn MapsTM
• Extensive mapping & GIS collection with over
12,000 municipalities nationwide
• Digital Photogrammetric Mapping since 1979
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4. Company Overview
• Sanborn is an industry leader in terms of acquisition
resources and data processing throughput, assets included:
– Aircraft (12)
– UltraCam Eagle Digital (3)
– UltraCamD (2)
– Integraph Z/I (4)
– 5-way oblique system (4)
– Airborne GPS systems (7)
– Inertial Navigation Systems (6)
– Trimble GPS survey equipment
– IT Infrastructure (over a Petabyte of storage)
– Over 1,200 distributive processing CPUs
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Decision
Support
Visualization
Systems
Software Applications
Value Added Services
(Base Map Analysis)
Data and Map Production
Comprehensive Solutions
• Decision Support Systems
– Wildfire Management
– Forestry and Ecosystem Management
– Emergency Response
• Visualization Systems
– 2D
– 3D
– Prism 4D, Common Operating Picture
• Software Applications
– GIS Software Development
(Enterprise/Desktop/Web)
– Portals and Distribution Tools
• Value-Added Services
– Land use and land cover analyses
– Change detection
– Other imagery analysis services
• Mapping & Remote-Sensed Services
– LiDAR, Digital Orthoimagery,
Photogrammetric, Topographical Maps
12. What is Community Sustainability?
“Sustainable development is development that meets the needs of
the present without compromising the ability of future generation
to meet their own needs.”
Land Use Planning Should support sustainability
Brundtland Commission of the UN 3/20/87
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Land Cover vs. Land Use
• Land cover
– The physical state of the landscape
– i.e. water, bare soil, grass, impervious surface
• Land use
– How the land is used
– High density residential, golf course, pasture
• All communities understand land use
• A few but increasing number of communities understand
land cover
• Land cover is a complementary dataset to land use
• Most communities with a digital parcel base have the
land use attribute as part of their database, the rarely
know the land cover on that parcel.
14. Land Cover Mapping
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• Understanding current landcover and how
it is being used, along with an accurate
means of monitoring change over time, is
vital to anyone responsible for land use
management.
• Measuring current conditions and how
they are changing can be easily achieved
through land cover mapping, a process
that quantifies current land resources into
a series of thematic categories
Vegetation Mapping
Landcover Mapping
15. Land Use
– Policy can be supported
based on land cover
– Need to work through
decision rules about when
one land use changes to
another
– Made easier if digital
parcel map available
– Similar but not the same
as hand delineated land
use maps
16. How Can GIS and Remote Sensing based Land Cover
Mapping Help Our Communities Be Sustainable?
By Supporting Land Use Policy for:
– Water Shed Delineation/Environmental protection, Water
quality protection
– Green Infrastructure
– Habitat Analysis and Management
– Impervious surfaces
– Irrigated vs. non-irrigated
– Wildfire Risk
– Wetlands Mapping
– Agricultural production
– Forest production
– Recreation
18. What is Multi-Spectral Imagery?
• Imagery acquired with a sensor
that is also sensitive to
electromagnetic energy outside of
the visible light spectrum – usually
near-infrared.
• Can be displayed in a variety of
band combinations to emphasize
desired features.
• Shows reflected energy (from
sunlight), not emitted energy.
Graphic courtesy
Lumenistics.com
19. Why is Multi-Spectral Imagery Useful?
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• Many physical objects reflect infrared energy much
differently than visible light.
• This makes new forms of analysis possible, and others much
more efficient, particularly when it comes to process
automation.
• Infrared energy is very sensitive to the chlorophyll in
vegetation, so imagery can be used for a variety of unique
applications involving vegetation.
Credit Jolyn Keck, Utah State
University
Credit Jolyn Keck, Utah State
University
20. Vegetation Classification
Unique spectral signatures in the NIR band allow differentiation of invasive
species, different types of beneficial plants
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Credit North Credit D. Lichaa El- Dakota State University
Khoury, AUB
21. Imagery Inputs for Various Scales
Low Resolution
National/State level
mapping
Medium Resolution
NOAA, State/Regional
Mapping, Multi-county
regions
High Resolution
Land cover, canopy,
green infrastructure,
land use & impervious
Sensor/Resolution
Classification
TM/ETM 30 m pixel
$
SPOT/DG/IRS 5m
$$
Airborne camera 1 m
$$$
Low Resolution Medium Resolution High Resolution
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Imagery Collection Parameters
• Need to make sure imagery is suitable for land
cover mapping which will relate to season
– Impervious maps best produced from leaf off imagery
– Wetland maps best produced from spring green up imagery
– Forest type maps are best produced from early senescent fall
imagery
– Agricultural type maps are best produced using growing season
imagery
23. General Land Cover Maps
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Impervious Level 1 Level 2 Level 3
Impervious Impervious Impervious Paved Surfaces
Building
Other Impervious
Pervious Woody Deciduous Upland
Lowland
Coniferous Upland
Lowland
Shrub Upland
Lowland
Non woody Vegetation Grassland Urban Grassland
Emergent Wetland
Other grassland
Cropland Cropland
Water Lake Lake
River River
Pond Pond
Barren Natural Natural
Man Made Man made
24. Impervious vs. Pervious Surface
• Impervious surfaces generate runoff that can create
costly problems for both residents living in a community
and the surrounding environment.
• Better information regarding current and projected
changes is increasingly important.
• Mitigating impacts of urbanization on water resources
requires location and extent of impervious surface
• Impervious surfaces is important for a variety of
applications including stormwater applications for fee
charges, stormwater runoff, infrastructure design, and
watershed health and modeling
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25. Storm Water Utility and Fee Management Using
Impervious Data
Cities can revamp their Storm Water Utility
Rate Structure using Google Imagery and
Sanborn’s Premium Impervious Data
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Stormwater Needs
Assessment &
Rate Structure
Development
Ordinance for
New Rate
Structure
Public Info
Review &
Adjustment
Billing
&
Collection
Update
&
Maintenance
26. Impervious area: 10,549 sq ft
Parcel area: 25,118 sq ft
Current Rate Structure: $22.75/quarter
User fee based on Impervious amount:
$58.72/quarter
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Land Cover
• Level 1 Land Cover
– Provide information on the cover for parcels
– Use for environmental assessments
– Use for stormwater planning
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Land Cover
• Level 2 land cover
– Use for tree canopy monitoring
– Use for development monitoring
– Use for land use planning
29. Land Cover
• Level 3 Land Cover
– Use for ecological inventories
– Use for wetland mapping
– Use for stormwater and pollution modeling
30. Why Map Vegetation?
• Vegetation makes a big difference
– Allows infiltration of water to soil
– Stores and evaporates water during a rain storm
(transpiration and interception)
– Filters air and water pollution
– Impacts microclimate (cooling houses in summer,
warming houses in winter)
– Enhances quality of life
– Supports urban wildlife
– Provides recreational opportunities
– Forestry resources
– Agricultural and forest health
– Agricultural crop damage and compliance
– Provides input for wildfire fuels modeling
Tree Effects on Runoff
Time
Runoff Volume
Hydrograph
Decrease total runoff volume
less trees
more trees
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Irrigated Lands Mapping
• In many states water use is an issue
– One large water consumer is for irrigation
– Monitoring and managing irrigation water is a required best
management practice for certain areas
32. Vegetation/Crop Health
Identification of water deficiency or surplus, nutrient deficiencies, diseases,
insect/weed infestation, pollutant damage, wind/hail/flood/fire damage,
yield estimation
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Imagery Credit
NASA
33. USDA Farm Service Agency
Subsidy and Insurance Monitoring
NAIP Program is well-known example
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34. Green vs. Grey Infrastructure
• Grey infrastructure are the hard surfaces that are built
• Green infrastructure are the soft surfaces that can offset the
impact of the hard surfaces
• Stormwater runoff relates to the amount of water not
infiltrating the ground after a rain event
– Impervious (grey infrastructure)
– Permeability of other land surfaces (green infrastructure)
• Non-point source pollution depends on the surfaces over
which the runoff runs
– Type of surface
– Pollution load of that surface
• Relates to land cover type and how it is used
35. Green Infrastructure
• Modeling software calculates the impact of trees and green space on
– Storm water
– Water pollution
– Atmospheric pollution
• Modeling presents results in terms of dollars based on research
into externality costs
– These are figures that many people can relate to: decision makers, the
general public
• A Green Infrastructure classification provides the base layer for this
program.
– The more detail present in the classification in terms of land cover,
overstory, and understory, the more accurate the classification will be
– The added detail enables the software to calculate more precise runoff
curve numbers
37. Land Structure + Ecological Analysis Model = Decision Support Material
Ann Arbor
Air Pollution
Rainfall
Soils
Landcover
Bottom Line
Ecosystem Analysis Model
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Wildfire Risk Assessment
• Over the past 2 decades the number of
acres burned by wildland fire has steadily
risen
– Past management practices, including a
concerted federal policy of suppression, has
unintentionally led to a steady accumulation of
dense fuels across the U.S.
– This fuels buildup has resulted in several years of
catastrophic wildfires that has cost lives and
significant damage to property and the
ecosystems in the Wildland Urban Interface
• 1990 to present
– Massive shift in available monetary resources in
response to catastrophic wildland fire seasons
40. Wildfire Fuels Mapping
• Advanced image classification techniques are used in
combination with field surveys to develop a fuel model
classification scheme
• Supports the 13 FBPS fuel models, or the newly
developed Scott/Burgen 40 fuel models CIR Imagery
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Surface Fuels
