Natural Resources
GeoConnections
Data Needs Assessment for Integrated Landscape Management (ILM)
Decision-Making Processes
Decision Support for
ILM:
Analysis of Four Case
Studies
Executive Summary
March 31, 2010
Prepared by: Gail
Kucera
Evert
Kenk
Dave
Nicolson
Pierre
Lafond
Executive Summary
The
“quality of life” in
Background
ILM
is a holistic approach to planning and management that seeks to maintain the
well-being of communities while maintaining ecological integrity within the
context of “a place” at the community, landscape, watershed or regional level.
ILM uses a vision of desired future condition, defined in social, cultural,
economic and environmental terms that guide development across all sectors
giving expression and definition to “quality of life”.
These
various approaches to ILM develop out of the need to address progressively more
complex issues, commonly referred to as “wicked problems” such as persistent
socio-economic and environmental policy, planning and management issues, all
requiring a high level of collaboration among governments with other players.
They are often initiated in response to land use conflict and the perception of
crisis. Water quality contamination, depleted fisheries, or resource
developments can catalyze a range of jurisdictions, stakeholders and interests
to address the issue through an ad-hoc “place-based” governance initiative. ”Place”
is where the impacts of decisions are felt, and where best to address social,
cultural, environmental and economic problems and their interconnectedness. It
is where citizens in their urban and rural communities overlap with the
ecosystems they are part of.
While
no universal definition exists, ILM approaches contain a number of similarities
in how they assess current and future conditions and environmental responses to
natural and human induced changes. To be successful, they need
to address their need for geospatial data and their ability to turn that data
into information and knowledge to inform the development of policy, to in-turn
enable planning and management and ultimately support place-based decisions.
ILM
approaches have become more sophisticated through time as new science methods
and technologies have allowed the use of increasingly complex and disparate
datasets. Data limitations, including the integration of data from many sources
and different disciplines to inform the ILM process and create knowledge to
support place-based policy development, planning and decision making is one of
the biggest constraints to ILM. Discovering ways to integrate socio-economic
and environmental information across existing sectoral, jurisdictional and
disciplinary boundaries continues to be a challenge. This is exacerbated by a
lack of a common definition, or framework for ILM, which allows the integration
across different information and knowledge cultures, including natural
sciences, social sciences, cultures and economics.
Context and Approach
To
address the challenge, Environment Canada and GeoConnections have identified
the need to support a growing community of practice for ILM and have been
actively doing so since 2005. IMAGINE
To
support the ILM community of practice, Natural Resources Canada -
GeoConnections contracted Holonics to undertake a Data Needs Assessment for ILM
Decision Making Processes. As part of the GeoConnections national program to
enable decision-makers to use place-based information to benefit public health,
safety and security, the environment, and Aboriginal communities this project
has provided a number of recommendations for consideration by GeoConnections,
its federal partners and the ILM community of practice to further address ILM
data needs and its transformation into meaningful information in support of the
ILM decision-making process.
Four
sites sponsored by IMAGINE
|
IMAGINE |
||
|
Region of Interest |
Lead Organization |
Key Issues |
|
|
Bras d’Or
Institute for Ecosystem Research, |
Cumulative
impacts of human economic and recreational activities. |
|
|
|
Sustainable timber supply to maintain a healthy
local economy. |
|
Eastern |
Eastern |
To achieve
community well-being by maintaining economic stability via sustainable
development while safeguarding ecological integrity. |
|
Foothills Area ( |
Foothills Research Institute |
To relieve
conflicts between resource extraction activities and wildlife – minimizing
development “footprint”. |
Interviews
and questionnaires were used to capture site information on data needs and use
of information in the ILM decision-making process. Focus was on a range of
roles in the ILM process that include policy analysts, planners, resource
managers, decision-makers, information specialists and discipline experts.
Conversations with stakeholders were tailored to the individual or group and
revolved around these major points:
·
What
worked? What did not work?
·
What
are the limitations, issues and challenges?
·
Are
there good ideas for improvement?
ILM
is a complex process that brings together many players from diverse backgrounds
with different language, different knowledge and their own way of doing things.
Lacking a formal definition for ILM presented a problem for effectively
undertaking this project. In response, a conceptual Framework for ILM was developed.
The Framework captures the complexity of the ILM process and the role of
information and knowledge in enabling that process.
The
ILM Framework shows the components of ILM that comprise the overall ILM process
through drivers, expression, implementation and the use of instruments. The
people involved in the formal ILM process are supported by people who provide
information and knowledge to the ILM process. ILM success results from
purposeful steps and the collaborative actions of many people in a range of
roles to create legislation and build policy to drive plans that are
implemented on the ground via decisions. That series of events is enabled
through the use of data, commonly geospatial, to inform with knowledge each
stage in the process.
The
framework provides a picture that helps stakeholders understand how their roles
support the ILM process; as such, the framework provided focus and context to
capture and organize project results and to develop recommendations relevant to
the whole ILM community of practice, with a focus on GeoConnections and the
role of the federal government.
Roles
were useful to this study because they provide simple definitions of how
stakeholders handle and use their data. Differences in how organizations assign
roles to staff also offer useful insights. The roles defined here support three
very different areas that need to work together to effectively deliver ILM:
·
The
information domain, which deals with data and information through collection,
management, integration, and analysis.
·
The
knowledge domain, which builds on and uses information in the course of
scientific research, education, and training.
·
The
business domain, which applies information and knowledge to the business at
hand, and includes decision-makers, planners, policy analysts, and stakeholder
groups.
Results
For a
policy analyst or resource manager to make effective place-based decisions
requires that a diverse range of information and knowledge needs to be brought
to the process in a timely and integrated manner understandable by a wide range
of stakeholders. The required information and knowledge pertain to the diverse
needs of community given available natural capital, potentially conflicting
demands on resources, and the range of ecosystem services[1]
available. The body of stakeholders includes citizens who increasingly want to
be part of the way solutions are defined and decisions are made.
This
project revealed seven major classes of data in use, or identified as needed.
To produce this list, Holonics surveyed stakeholders who develop policy for
place-based planning and management and resource managers making decisions on
the ground. The key use to which the data is applied also was captured from the
interviews and questionnaires.
|
Data Classes for ILM |
||
|
Name |
Description |
Key Usage |
|
Base data (or Framework data) |
Includes topography, bathymetry,
hydrology, transportation, energy, geographic names, and built-up areas. |
Provides the reference map
against which all other types of data are positioned and displayed. |
|
Cultural data and traditional
knowledge |
Includes the places and objects
with aesthetic, historic, scientific, or social value for past, present or
future generations. |
Used to capture the culture
aspects of community and incorporate traditional (often First Nation)
knowledge in the ILM process. |
|
Landscape management and values |
Includes protected areas, zoning,
community values, economic potential (e.g., areas suitable for wind farms),
and activities to manage or administer the land use (e.g., forestry activities
or ILM projects). |
Focus is on integrating zoning
and resource regulations into the planning and decision making process. |
|
Natural environment |
Includes vegetation, forests,
land cover/use, soils, geology, etc... This category also could describe
aspects that relate to the health of these phenomena (e.g., fire history). |
Representation in map form of the
components comprising natural capital (forests, fisheries, wildlife, water,
etc.) to support future scenario planning to address allocation, risk and
mitigation of cumulative effects. |
|
Land ownership and control |
Includes administrative
boundaries, ownership parcels, and crown dispositions (including tenures and
leases). |
Generally to capture the
separation of crown interest versus private interests. |
|
Population distribution and
health |
The distribution of humans and
other living creatures. This category also could describe the health or
well-being of populations (e.g., population health statistics). |
In scenario planning used to
capture the impact of development on local residents and infrastructure. |
|
Socio-economic environment |
Includes jobs and economic
activities that affect the landscape (e.g., mining and forestry). Also
includes such concepts as recreation, education, and living standards that
contribute to well-being and non-medical determinants of health. |
Identified as necessary for
scenario planning to compare alternative futures for allocation of natural
capital between competing uses. |
It is interesting to note that the highest-priority
datasets currently used for ILM fall in just three of the seven classes:
Base/Framework, Natural Environment and Land Ownership and Control. This could
be explained by the ecological bias of most ILM projects at present, although
socio-economic and cultural datasets were identified as critical gaps not
currently available in a form that can be effectively integrated into the ILM,
or place-based planning and decision-making process.
The data needs assessment had two key objectives: 1)
to identify new geospatial, or place-based data sets needed to support and
enhance the process and 2) to identify any barriers for accessing, using and/or
sharing currently used geospatial data sets. The results were to be used to
identify opportunities and provide recommendations to GeoConnections and the
ILM Network for overcoming gaps and barriers. The following two listings
capture, in-turn, data gaps and barriers to effective uptake of data by the ILM
process that were widely shared by the four case studies. Column Two describes
the impact if the gap or barrier is not addressed and Column Three states the
number of the recommendation made to address the gap or barrier.
|
Gap in major data needs |
Impact of gap |
Rec. |
|
Authoritative watersheds at
landscape scale (1:20K-1:50K) |
Provides a common boundary for all
stakeholders involved in the ILM process. |
2 |
|
Data from Statistics Canada that
supports seamless planning and comparison. |
Data should be aggregated to local
management units, using an aggregation method that makes sense for rural and
urban areas. |
1 |
|
Geocoded economic data (e.g.,
jobs, GDP), Demographic data (e.g., age, sex,
households) and public health data (e.g., age, sex, households). All
aggregated to local management units with more detailed attribution than is
presently provided by Statistics Canada. |
Geocoding these data sets will
make them useable in ILM future scenario planning to more holistically
address “quality of life” outcomes. |
1 |
|
Imagery and remotely sensed data
across jurisdictional boundaries. |
ILM requires consideration of the
landscape as a whole, across jurisdictions. |
3 |
|
Assignment of community values to
the landscape. |
Decision-makers need to know who
would be affected by prospective development, including intangible impacts. |
6 |
|
Barrier |
Impact of Barrier |
Rec. |
|
Simplified data exchange (without
the necessity of human intervention) |
If data sharing is too
troublesome, users are more likely to obtain copies from informal channels,
which devolve to inconsistent versions. |
4 |
|
Simplified agreements for data
sharing to reduce costs and delays. |
As above. |
5 |
|
Clear policy and guidelines for
sharing or “sanitizing” sensitive and private data. |
Social, cultural, ownership, and
public health data often are unavailable to decision-makers. But policy is
judged on how well it addresses these factors. |
5 |
|
Simplified sharing and discovery
of project data. |
Some of the most current,
highest-resolution data result from projects whose data are not shared. This
data not being made available to ILM process in a timely fashion |
4,5 |
|
Simplified sharing, discovery, and
custodianship of data collected locally within federal jurisdictions. |
Locally relevant federal data not
being made available to regional ILM initiatives. |
4,5 |
|
Simplified flow of updates between
data users and custodians with automated version management to ensure that
all copies receive notification of updates. |
If data sharing is too
troublesome, users are more likely to obtain copies from informal channels,
which devolve to incoherent versions. |
7 |
|
Decision-support tools that
provide the information needed by decision-makers |
Maps are in high demand by
decision-makers, and consistency and high-quality in the maps used will shine
a light on the issue at hand. |
8 |
Issues and Recommendations
The
following recommendations address key ILM issues and challenges. The
recommendations for GeoConnections address both its role as a national leader
in online geospatial information and its federal role to be a leader in
enabling the federal government to manage its geospatial data holdings in
support of federal and national ILM programs. The first two issues,
if addressed, will have the greatest impact on the future success of ILM
because they will improve geospatial data resources to support the ILM process
and expand the use of geospatial information and knowledge by ILM practitioners
in the performance of their daily work.
Recommendations for issues 1 and 2 are the most
important ways for GeoConnections to support ILM.
1 Geospatially enabling social,
economic, and health data
Currently most ILM projects or programs have a strong land or resource
values bias. Cultural values are being taken into consideration in more recent
ILM efforts. But effective integration of socio-economic and health data into
the ILM process is still rare.
Rural planners in
This is one of the two top priorities given that
the data already exists; it just needs to be transformed and packaged to meet a
new set of needs. Thus, it is a high-payoff, low risk task. Without this data,
place-based analyses remain narrowly focused on resources rather than
landscapes (which include humans). ILM user needs can feed into future
Statistics Canada data collection cycles; thus, the sooner the better. Quick
action is needed, because the multidisciplinary demand for this data means a
high risk of incoherent or duplicated efforts to define standards, models,
policies, and datasets.
Recommendation:
·
Support the development of standard geospatial data
products to meet ILM needs for social, economic and health data.
2 Nation-wide watershed boundaries at landscape
scale
Watersheds
are used extensively in ILM processes. Different stakeholders can use these
boundaries as aggregation units to collect or integrate a variety of data for
ILM analysis. In effect, they become the “master" geographical units used
for large scale, local analysis.
If
watersheds are consistent at a landscape level, and nested in larger
watersheds, results of analysis can be rolled up across jurisdictional
boundaries (e.g., National Park and adjacent lands, inter-provincial
boundaries) to allow for true ecosystem views. Nested watersheds can provide
the framework to aggregate social, economic, and health data to use in
conjunction with other ecosystem-based data for analysis.
Given
the importance and potential efficiencies of watersheds to ILM, an
authoritative boundary for each watershed nationwide would be a boon to ILM
practitioners. A watershed data model that is appropriate for watershed
analysis, nationally standardized, also would simplify the task of watershed
modelling by removing the complexity of format conversion.
Recommendation
·
Support
the development of a nation-wide authoritative watershed boundary dataset to be
used as aggregation units for environmental, social, economic and health data.
Recommendations for issues 3 to 8 address the national role that
GeoConnections should fulfill to support the practice of ILM.
3 Improve access to digital remote
sensing data at local scales
Remote
sensing data is highly prized for ILM. At local scales (<1:20,000) it can be
processed to derive elevations and other information about the natural world,
ordered for special purposes (e.g., to identify forests infested by pine
beetles), and serves as a useful base map for presentations to stakeholders and
decision-makers. It is often more current than any other data source. LIDAR and
Hyperspectral data are cited as particularly useful.
Every
site listed remote sensing data as a high-priority resource.
This
is a priority because gaps prevent the use of remote sensing data in analysis
and for cross-jurisdictional decision-making; restrictive licensing can impede
collaboration with regional partners; high cost may preclude its use by some
users and federal lands are often the area where the coverage is missing.
Recommendations:
·
Seek to arrange matching funding among agencies for
intergovernmental and P3 data acquisition. Encourage partnerships to fund
joint-use remote sensing data collection.
·
Build a place-based forum within the IMAGINE
website where potential partners can identify mutual interests for data
collection.
4 Improve data sharing via better
catalogues and search engines
It is
a challenge to discover data and determine its fitness for use, despite federal
and provincial portals and services. Search engines return multiple or
irrelevant hits with no simple way to compare them. The technology that
surrounds data sharing works well if the user knows precisely what to search
for and download (i.e., a dataset name and tile). ILM will increasingly involve
users who are not familiar with the CGDI or federal data products. Interviewees
at the IMAGINE sites expressed some degree of frustration at the effort
required to locate appropriate place-based data for their studies (Bras d’Or
Lakes) or the time involved in going to multiple sources to gather required
datasets (Newfoundland & Labrador).
This
is a priority because: 1) users may not be selecting the best-available data; 2) users
in the same area may be using different versions of the same data; or 3) users
may waste time downloading data that does not meet their requirements.
Recommendations:
·
Define desirable process flows and test cases for data
discovery.
·
Ensure that metadata and search engines perform as
intended.
·
Support user-friendly enhancements to data portals
that are targeted at data seekers.
·
Solicit and showcase user corrections to metadata, and
reviews of data products.
·
Solicit and showcase new catalogue entries by local
users.
5 Facilitate data sharing
agreements
ILM
is interdisciplinary and cross-jurisdictional; as such, data sharing is
essential. The overhead and difficulty of data sharing was mentioned by
stakeholders at every site. Human interaction is required to track data sharing
agreements, which creates an administrative burden and causes delays in
accessing data. Sites exhibited a mixed bag of data sharing practices, with
some agencies having formal, signed agreements and others being more ad-hoc.
GeoConnections
has expended considerable resources to reduce the burden of data sharing. Most
recently, the GeoConnections Policy Advisory node provided advice on how to
build data sharing agreements, including on-line sources.
This
is a priority as it could reduce legal and administrative costs; reduce delays
in acquiring data; improve sharing of sensitive data because of increased
confidence in the rigour of the agreement; help track dataset usage, and build
a business case for maintenance or enhancement and could remove bias in who
obtains access to data. Also, the hardest work has already been done by the
GeoConnections Policy Advisory node. Now it needs to be made accessible to
benefit users.
Recommendation:
·
Develop a web tool to generate geospatial data sharing
agreements, which builds on the work of the GeoConnections Policy Advisory
node.
6 Sponsor best practices on
values-mapping software
Ecological
values are relatively well understood in ILM. However economic, social and
culture values, and how they relate to environmental values, are less well
understood in an ILM context. Effective ILM requires that stakeholders
understand values and how they interact—including values beyond those of the
individual stakeholder. An understanding of community values aids in the
support of local communities.
The
IMAGINE sites have a present or future interest in values mapping.
Many tools have been developed to meet the needs of
values mapping, but objectives, inputs and outputs differ. In addition to the
work being done by EOMF, existing tools include the following.
·
Canadian Forest Service’s Landscape Values Mapping Tool.
·
EcoTrust’s Marine Map (
·
World Wildlife Fund’s Protected Areas Benefits Assessment Tool (PABAT)
for social/cultural values.
·
·
Recommendation:
·
IMAGINE
7 Improve geospatial data update
and integration
Despite
advances in data, infrastructure, and technology, geospatial analysts are
spending more time integrating data than they are in analyzing it. Problems
with geospatial data and information integration also hinder the effective
uptake of desk-top tools by planners and decision makers; often, they do not
have the background to understand or address the problem. This reduces
confidence in both ILM tools and process.
At
IMAGINE
Reducing
the time spent in geospatial data integration will allow Geospatial Analysts to
focus on analysis and product and will increase acceptance of ILM geospatial
planning and decision support tools by policy analysts, resource planners and
regional/local resource management decision makers.
Recommendations:
·
GeoConnections
should investigate ways to provide subscribed users with updates to major
Framework products.
·
GeoConnections
should support projects similar to FRI Landscape Decision Support System that
integrate data/information via a standard process for the benefit of
participating partners.
·
GeoConnections should continue to improve the
current versions of national framework data.
8 Help to vet planning and
decision-support tools
Geospatial
data has its greatest impact when it is used to create knowledge to support
resource policy development, regional planning, or on-site decision making –
that is where the “rubber meets the road.” ILM planners and decision-makers are faced with
a wide range of choices in desktop tools to support their work.
GeoConnections
Phase 2 targeted considerable funding at the development of resource planning
and decision-support tools to support ILM and place-based management. There is
a high risk that tools developed via one-time project funding will be
unsupported (not documented, tested, distributed, maintained, or enhanced) when
funding ends, and this is the case for many of the tools developed via
GeoConnections projects. Thus, the return on investment from
GeoConnections-developed tools is still to be determined.
Initial
reviews (e.g., the 2007 First Nations’ Land Referral Forum held on Sept. 12-13)
indicate that many of the GeoConnections-produced tools are very useful.
Reviews also indicate significant variation in how well tools meet the needs of
ILM planners and decision-makers.
The
IMAGINE
·
FRI Landscape Decision Support System
·
Values Mapping Tool – EOMF
·
UINR Resource Planning Tool
·
Handheld tools for forestry operations – Hinton
Wood Products,
·
·
United Counties of Leeds and Grenville GIS on-line
mapping supporting the review of development permits, with its 30 % reduction
in time to address development proposals.
It is
highly desirable that the effort involved in developing tools be leveraged to
the extent possible by making them available to the widest possible audience
for evaluation and use.
Recommendations:
·
IMAGINE
·
GeoConnections should assess past efforts and
define a future direction with respect to tools development.
·
GeoConnections should offer materials to support
the business case for local/regional tool development as a service to users.
The final two recommendations consider how
GeoConnections fits within the ILM strategy of the federal government.
9 Federal ILM Strategy
Federal
lands are part of the ILM region for each of the IMAGINE sites. Coordination
with federal interests was cited as a common problem. The lack of a federal ILM
strategy can result in the following issues.
·
Data coverage differed on federal lands, particularly imagery and
species data. This was in part due to small budgets for data collection in
National Parks.
·
Data sharing was imperfect. Personal contacts were needed to learn about
federal data collected locally. And data are not always shared openly, even
when no specific sensitivities exist.
·
There is no federal agenda for ILM, and no federal representative (at
national or local levels) to consult with for this purpose.
The
Policy Research Institute is currently undertaking a series of critical
conversations on place-based decision-making. The question is how the federal
government can improve place-based analysis and decision-making from the
perspective of sustainable development. Issues relate to the following topics.
·
Jurisdictional overlap/underlap between and within federal departments.
·
Lack of a shared place-based (or geo-spatial) federal strategy.
·
Geospatially enabling federal data holdings when it makes sense to do
so.
·
Integrating non-spatial data types into place-based analysis.
·
Development of tools and systems to support place-based decision-making.
·
Establishing a lead federal agency to define direction, policy, and
standards for place-based decision-making.
Federal
departments that traditionally have not been involved with geospatial data are
starting to leverage geography and move toward place-based analysis and
decision-making. It is important that they recognize that a suite of framework
data, discovery and access tools, and other support services already exist and
should be leveraged to facilitate data access and integration.
NRCAN
and GeoConnections are strategically suited for a stronger federal role in
place-based governance and support. The role extends beyond the resource
sectors to include support of all federal departments.
Recommendations:
·
NRCan
should be the federal government lead for ILM and define an ILM strategy for
the federal government.
·
GeoConnections
should provide geospatial data services to the entire federal government.
10 Federal government data
sharing
A
number of federal government departments, in particular DFO, are involved in
ILM-related research projects. Access to both the results of the research and
to data or information collected as part of the research is often a challenge
for interested parties. In addition, federal government departments may collect
local or regional data as part of their mandate. This data is of interest to
ILM efforts but access is not always straightforward.
Data
discovery and access often depends on direct contact with federal government
researchers or staff by interested parties. This is an inefficient use of
federal resources and is less than ideal for clients. It also creates an inconsistent
service delivery response based on who you know, with the possibility of
perceived favouritism.
Concerns
were raised in the Bras d’Or area about challenges in accessing local DFO data
and in timely access to ongoing research data and results. Similar concerns were
raised in the Alberta Foothills area concerning Parks Canada data, although
these issues are currently being resolved as part of the GeoConnections/FRI
project to develop a Landscape Decision Support System.
Recommendation:
·
Geoconnections
should leverage its expertise to encourage federal government departments to
license, register, and share operational and project data collected locally.