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

Agenda • Sanborn Overview

• How do we define community sustainability

• What is Land Use, What is Land Cover

• How does GIS and Remote Sensing support land use policy, what are the applications

• What data source support land cover mapping

• Land Cover map types and applications – Basic land cover maps and applications

• Impervious, level 1, 2, 3

– Specific land cover maps

• Irrigated

• Green infrastructure

• Wild Fire

9/29/2014 ©2014, The Sanborn Map Company, Inc. 2

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Sanborn – Leader Since 1866 Sanborn MapsTM

• Extensive mapping & GIS collection with over 12,000 municipalities nationwide

• Digital Photogrammetric Mapping since 1979

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

Airborne LiDAR USGS QL1 SAMPLE

Orthoimagery

Oblique Imagery

Planimetrics

3D Data

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Ecological Systems Classification

Land Cover Mapping

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.

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

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

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

Landcover Classification

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Multi-Spectral imagery assists with the creation of thematic maps showing land cover.

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

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.

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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 Dakota State University Credit D. Lichaa El-Khoury, AUB

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

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General Land Cover Maps 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

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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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

Stormwater Needs

Assessment &

Rate Structure

Development

Ordinance for

New Rate

Structure

Public Info

Review &

Adjustment

Billing

&

Collection

Update

&

Maintenance

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

Land Cover • Level 3 Land Cover

– Use for ecological inventories – Use for wetland mapping – Use for stormwater and pollution modeling

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 Time

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Tree Effects on Runoff

Hydrograph

less treesmore trees

Decrease total runoff volume

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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

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

USDA Farm Service Agency Subsidy and Insurance Monitoring

NAIP Program is well-known example

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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

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

CITYgreen© inputs and models • The Air Pollution Removal program is based on research conducted by David Nowak,

Ph.D., of the USDA Forest Service. Dr. Nowak developed a methodology to assess the air pollution removal capacity of urban forests with respect to pollutants such as nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), carbon monoxide (CO), and particulate matter less than 10 microns (PM10). Pollution removal is reported on an annual basis in pounds and U.S. dollars. – F (g/cm2/sec) = Vd(cm/sec) x C (g/cm3)

– Nowak, D.J. and Crane, D.E. 2000. The Urban Forest Effects (UFORE) Model: quantifying urban forest structure and functions. In M. Hansen and T. Burk, eds. Proceedings: Integrated tools for natural resources inventories in the 21st century. IUFRO Conference, 16-20 August 1998, Boise, ID; General Technical Report NC-212, U.S. Department of Agriculture, Forest Service, North Central Research Station, St. Paul, MN. pp. 714-720.

• Carbon Storage and Sequestration

• Storage - Study area (acres) x Percent tree cover x Carbon Storage Multiplier = Carbon Storage Capacity

• Sequestration - Study area (acres) x Percent tree cover x Carbon Sequestration Multiplier = Carbon Sequestration Annual Rate – Nowak, David and Rowan A. Rowntree. “Quantifying the Role of Urban Forests in Removing

Atmospheric Carbon Dioxide.” Journal of Arboriculture, 17 (10): 269 (October 1, 1991).

Ann Arbor

Air Pollution

Rainfall

Soils

Landcover

Bottom Line

Land Structure + Ecological Analysis Model = Decision Support Material

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

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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

Surface Fuels

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Prevention and Risk Mitigation

Questions

Jason Caldwell

Vice President of Business Development and Sales

719-264-5547

jcaldwell@sanborn.com 9/29/2014 ©2014, The Sanborn Map Company, Inc. 42