DELINEATING POTENTIAL NORTH DAKOTA
FOREST STEWARDSHIP AREAS USING
OVERLAYS AND SUITABILITY ANALYSES
PROJECT REPORT
Forest Service Coordinator
Larry Kotchman,
State Forester,
North Dakota Forest Service,
Molberg Center,
307 1st. St. East,
Bottineau, ND 58318-1100
GIS Coordinator
Peter Oduor,
Assistant Professor,
Department of Geosciences,
North Dakota State University,
227 Stevens Hall,
Fargo, ND 58105-5517
Report Date: AUGUST 18, 2006
Spatial Analysis Project Report, Page 3
ABSTRACT
A common ingredient to most GIS-based spatial analyses of land-cover change is
the empirical modeling of transition potentials–the likelihood that land use would change
from one cover type to another, based on factors such as the suitability of land for the
transition in question and the presence of driving forces of change. The rationale for
constructing a land-cover model is threefold: to illustrate the driving forces and the
dynamics of land-cover change, to understand the future economic and environmental
implications of current conversion processes, and to serve as a means of projecting the
impact of policy changes to the current trajectory. The current project provided key
information concerning not only resource potential and vulnerability, but also the extent
of professional management occurring around a given tract, respecting private property
rights and confidential information.
Landowners may find new opportunities to
complement the activities already begun in a geographic area, or learn of a need to
protect their tracts from a significant vulnerability such as fire threats. The analysis
provided an ability to conserve and consolidate forest patch size in critical areas. In
addressing a plan request backlog or as new opportunities arise to promote the Forest
Stewardship Program, service and consultant foresters can target areas around a core base
of forest land. They will be able to identify forest lands of high stewardship potential
based either on richness of forest resources or on vulnerabilities, or a combination of the
two. They will have enhanced information at their fingertips as they approach and work
with forest landowners. The objectives of this spatial analyses project were primarily: (1)
To determine and delineate potential stewardship tracts within North Dakota state by
creating georeferenced spatial data, and (2) To determine priority lands (those lands of
highest potential to benefit from the FSP) by providing tools necessary for the North
Dakota Forest Service to effectively and efficiently address critical forest resource issues.
The analyses were based on extraction of significant facts embodied in the spatial and
attribute databases generated. These analyses mapped out patterns and associations to
help characterize the stewardship areas that were generated.
Spatial Analysis Project Report, Page 4
ACKNOWLEDGMENTS
This project was sub-contracted to North Dakota State University Geosciences
department by North Dakota Forest Service from USDA Forest Service funding. Most of
the data sources are listed in the report, however, we would like to acknowledge the
assistance of the following: Kathy Duttenhefner (Natural Resources Coordinator),
Christine Dirk of North Dakota Parks and Recreation Department, Joe Brennan (GIS
Specialist) and Steve Sieler (ND State Soil Liaison) of USDA/NRCS in Bismarck for
help with Highly Erodible Land data. We extend our appreciation to the following ND
District Conservationists: Rebecca Clow of Devils Lake Field Office, Stanley T. Schrupp
of Lakota Field Office, Karyn Neve of Minnewaukan Field Office, and Steve Kassian of
New Rockford Field Office. We also would like to acknowledge the following county
Executive Directors: Duane Twedt (Lakota, ND), Mark Dahlen (Minnewaukan, ND),
Loren R. Nelson (Devils Lake, ND). We extend our sincere gratitude to Jennifer Sweet
(Soil Scientist) currently at Fort Worth, TX.
Spatial Analysis Project Report, Page 5
TABLE OF CONTENTS
Page
ABSTRACT........................................................................................................................ 3
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF ILLUSTRATIONS.............................................................................................. 6
LIST OF TABLES.............................................................................................................. 7
ACRONYMS...................................................................................................................... 8
INTRODUCTION .............................................................................................................. 9
LAND COVER BASED MODELS .......................................................................... 9
Forest Stewardship Program. ............................................................................. 9
Datalayer development..................................................................................... 12
Study area. . ..................................................................................................... 12
Data layers in current geodatabases. ............................................................... 14
GEODATABASES CREATED AND SIGNIFICANCE: Primary Datasets .......... 14
SPATIAL ANALYSIS PROJECT IMPLEMENTATION .......................................... 26
ANALYSIS STRATEGY........................................................................................ 26
Results............................................................................................................................... 28
SUMMARY AND CONCLUSIONS ............................................................................... 36
References......................................................................................................................... 39
APPENDIX A................................................................................................................... 40
NORTH DAKOTA STATE MAPS USED IN FSP ......................................................... 40
APPENDIX B ................................................................................................................... 52
FOREST STEWARDSHIP AREAS COUNTY MAPS ................................................... 52
Spatial Analysis Project Report, Page 6
LIST OF ILLUSTRATIONS
Figure
Page
Figure 1. Soil and elevation data for North Dakota ......................................................... 12
Figure 2. Land cover and elevation data.......................................................................... 13
Figure 3. Land ownership and housing density. .............................................................. 13
Figure 4. Personal geodatabases created for analyses ..................................................... 15
Plate 1.
Gom (left) and Jason (right) logging data and groundtruthing delineated areas
for ND SAP...................................................................................................... 21
Plate 2.
Peter (foreground) and Jason (back) determining the best locale for GPS
station............................................................................................................... 22
Plate 3.
Correlating delineated areas for ND SAP west of Walcot city, Richland
County.............................................................................................................. 23
Plate 4. Forested land near Kindred, off of Sheyenne River in Richland County. ........ 24
Plate 5. Xiana logging data into an iPAQ computer...................................................... 25
Figure 6. Site map of first groundtruthing visit. Map shows potential stewardship areas
in Richland County ......................................................................................... 30
Figure 7. Site map for the second groundtruthing visit. Areas targeted included
potential stewardship areas in Traill County.. ................................................. 31
Figure 8. Site map for the second groundtruthing visit. Areas targeted included
potential stewardship areas in Steele County................................................... 32
Figure 9. Forests on private land in Stutsman County (A, C and E) and in Steele
County (B, D, and F)........................................................................................ 33
Spatial Analysis Project Report, Page 7
LIST OF TABLES
Table
Page
Table 1. Resource richness data layers and data sources................................................. 14
Table 2. Summary of Spatial Analysis results for each North Dakota county. ............... 28
Table 2 (contd.). Summary of Spatial Analysis results for each North Dakota county... 29
Table 3 Prioritization of FSP areas in North Dakota. .................................................... 35
Spatial Analysis Project Report, Page 8
ACRONYMS
Acronym
Description
SAP
Spatial Analysis Project
FSP
Forest Stewardship Program
USDA
U.S. Department of Agriculture
FGDC
Federal Geographic Data Committee
USC
U.S. Code
GIS
Geographic Information System
DEM
Digital Elevation Model
NLCD
National Land Cover Data
SSURGO
Soil Survey Geographic Database
NED
National Elevation Data
USC
U.S. Code
HUC
Hydrologic Unit Code
Spatial Analysis Project Report, Page 9
INTRODUCTION
LAND COVER BASED MODELS
A common ingredient to most GIS-based spatial analyses of land-cover change is
the empirical modeling of transition potentials–the likelihood that land use would change
from one cover type to another, based on factors such as the suitability of land for the
transition in question and the presence of driving forces of change. A commonly used
technique is suitability and proximity analyses, that is, prioritization with respect to
location of a potential driving force in order to delineate areas in terms of relative
importance and thereafter using overlays to delineate areas meeting the specific criteria.
The rationale for constructing a land-cover model is threefold: to illustrate the driving
forces and the dynamics of land-cover change, to understand the future economic and
environmental implications of current conversion processes, and to serve as a means of
projecting the impact of policy changes to the current trajectory (Pijanowzki et al., 2002).
Forest Stewardship Program. Since 1991,
the U.S. Department of Agriculture (USDA)
Forest Stewardship Program (FSP) has
assisted
over
200,000
landowners
in
preparing multipurpose management plans in
areas encompassing more than 25 million
acres of family forest. These plans promote the long-term sustainability of private forests
by balancing future public needs for forest products with the need for protecting and
enhancing watershed productivity, air and water quality, fish and wildlife habitat, and
threatened and endangered species. As established in the Forest Stewardship Program’s
National Standards and Guidelines (FSP National Standards and Guidelines, 2005), the
plans must meet certain minimum standards, that is, plans must identify and describe
actions to protect, manage, maintain and enhance relevant resources listed in the law
(soil, range, aesthetic quality, recreation, timber, water, and fish and wildlife) in a manner
Spatial Analysis Project Report, Page 10
compatible with landowner objectives. The plan must be approved by the State Forester
or a representative of the State Forester.
The FSP is authorized by the
Cooperative Forestry Assistance Act of
1978, as amended, 16 U.S.C. 2103A. The
program
encourages
private
forest
landowners to manage their lands using
professionally prepared forest stewardship
plans. These plans consider and integrate
forest resources, including timber, wildlife
and fish, water, aesthetics, and all associated resources to meet landowner objectives as
per the stipulated USDA guidelines. Nationally, the FSP has been successful in meeting
the intent of the program; more than 25 million acres of private forests have been placed
under professional forestry management. Since its inception, FSP has been delivered and
made available to family forest landowners on a first-come, first-served basis. This
customer-friendly approach assists landowners in improving their forest resources.
The North Dakota FSP provided the state
with a consistent methodology to spatially
display: (1) Important forest lands (rich in
natural resources, vulnerable to threat, or both);
(2) Existing stewardship tracts (properties under
stewardship plans); and (3) Areas of opportunity
to
focus
future
FSP
efforts
(stewardship
potential).
The ND FSP Spatial Analysis Project (SAP) addressed the following: (a)
Provided baseline data on the forest resources of North Dakota. (b) Ascertained forest
resource threats and opportunities, both environmental and socioeconomic.
(c)
Delineated areas to target interested landowners. (d) Provided a tool for state specific
FSP content guidelines.
(e) Provided managers with tools to address problems,
opportunities and objectives associated with intermingled federal, state and private land
Spatial Analysis Project Report, Page 11
ownership patterns within North Dakota.
(g) Prioritized areas that would be of
immediate concern by displaying areas close to a clustering of endangered biota.
The objectives of this spatial analyses project were primarily: (1) To determine
and delineate potential stewardship tracts within North Dakota state by creating
georeferenced spatial data, and (2) To determine priority lands (those lands of highest
potential to benefit from the FSP) by providing tools necessary for North Dakota Forest
Service to effectively and efficiently address critical forest resource issues.
Ultimately the spatial analyses
will
help:
(1)
Develop
a
historic
stewardship plan database and associated
geo-referenced
maps
of
existing
stewardship plans in the State, to be
maintained by NDFS on an ongoing basis
following initial project completion. (2)
Develop
a
statewide
assessment
of
important forest lands incorporating spatial and tabular display of natural resource data
critical to the sustainability of forest resources and the risks or vulnerabilities facing those
resources. (3) Analyze the location of lands under stewardship plans and how they relate
to the important forest lands in the State, and assess how North Dakota intends to use the
results of the SAP to guide future FSP activities in conjunction with other assistance
programs available to nonindustrial private forest landowners (see also Russel and Stein,
2002).
The methodology used here followed spatial analysis programs successfully
implemented in other pilot states including Connecticut and Colorado.
The ND FSP
will help determine priority lands (those lands of highest potential to benefit from the
FSP) by providing tools necessary for North Dakota Forest Service to effectively and
efficiently address critical forest resource issues like those forest lands on highly erodible
land. The analyses were based on extraction of significant facts embodied in the spatial
and attribute databases generated. These analyses mapped out patterns and associations
to help characterize stewardship areas generated.
Spatial Analysis Project Report, Page 12
METHODS
Datalayer development. Datasets compiled by North Dakota Forest Service were
sorted and sifted for quality control. Personal geodatabases were created containing
pertinent datasets for suitability analyses. The datasets were organized in this manner for
easy retrieval and logical modeling. Initial analyses included creation of custom tools
and scripts in ArcObjects.
Study area. The figure below shows the state of North Dakota soils and elevation data.
The map is a combination of USGS DEM data at 1 arc second strips and soils data from
SSURGO correlated with ND GIS soils data. Figure 1 shows also an overlay of counties
comprising North Dakota together with stream data from National Hydrography Data
(nhd.usgs.gov).
Figure 1. Soil and elevation data for North Dakota
Figure 2 shows land cover data draped on North Dakota DEM. Figure 3 shows
Land ownership and housing density data for North Dakota.
Spatial Analysis Project Report, Page 13
Figure 2. Land cover and elevation data.
Figure 3. Land ownership and housing density.
Spatial Analysis Project Report, Page 14
Data layers in current geodatabases. Table 1 shows datasets used for ND SAP. The
table displays resource rich data layers, scale and data sources. This table for the initial
analyses had data initially considered as primary data.
Table 1. Resource richness data layers and data sources.
Data Layer
Source
Scale
Wildfire assessment
Vector data from NDFS
variable1
Forest canopy
NLCD
TM 30 m
Private forested lands
NLCD
30 meter
Developing areas
USFS, Census block data
30 meter
Wetlands
USGS
1:24000
Riparian corridors
Derived from DEP hydro
1:24000
streams (300’ buffers)
Native American lands
ND State Gov
variable
Slope
Statewide NED DEM layer,
30 meter
USGS
Priority watersheds
HUC from USGS or EPA
1:100000
Soil erodibility
NED, NLCD, SSURGO
variable
Agro-forestry suitability
NLCD, NED
30 m and 1”
Drinking water supplies
ND GIS
variable
Wildland-Urban Interface
NDFS
variable
Highly erodible land
USDA
variable
GEODATABASES CREATED AND SIGNIFICANCE: Primary Datasets
Figure 4 shows geodatabases created in ArcGIS. All the initial analyses were
based on each personal geodatabase created but eventually all the processed data was
added to only one geodatabase named fs_geodatabase. A custom toolbox was created to
1
Variable implies that the dataset is GIS ready and therefore the scale can be matched to any relative
source. GIS data is scaleless.
Spatial Analysis Project Report, Page 15
enable ease of retrieving data and changing parameters as the state forester deems fit.
Organizing data in this manner allowed for ease of sharing, portability, and building
topology. In addition to the data listed in Table 1, the following data sources, listed and
ones not listed and their FSP significance were considered for current and future FSPs.
Figure 4. Personal geodatabases created for analyses
(a) Analysis mask – An analysis mask defining delineated forested areas was used.
This was dependent on NLCD data. The mask eliminated areas with open water
(NLCD value 11), perennial ice/snow covers (NLCD value 12), Low intensity
residential area (NLCD value 21), High intensity residential area (NLCD value
22),
Commercial/Industrial/Transportation
(NLCD
value
23),
Bare
rock/Sand/Clay (NLCD value 31), and Quarries/Strip Mines/Gravel Pits (NLCD
Spatial Analysis Project Report, Page 16
value 32). The land ownership dataset was converted from a vector dataset to a
raster dataset. Public land derived from this dataset was then reclassified as
“NoData” and the rest of the land was reclassified to a value of 1. The final grid
was a combination of grid generated from the first and last analyses.
(b) Priority watersheds – The 8-digit HUC code was used for defining watershed
boundaries. EPA also has a process for designating high priority watersheds, for
example, Category I (those most impaired) watersheds are often those with the
least amount of forestland.
After discussions with the ND
Staff Forester, Thomas Berg,
all watersheds within North
Dakota were treated as priority
watersheds.
(c) Slope – This layer was used as
a basemap for all the other
datasets, and also to highlight
ease of operability for forest harvesting operations, which can be seen as a good
thing – productive forests are more likely to remain forests. The slope was also
used as an indicator of a site’s erodibility. Determination of what constitutes low,
medium, and high slope was done using USDA guidelines and in consultation
with the soil scientists and resource conservationists affiliated to USDA. Extent
of area covered by high priority slopes aided in refining the use of this layer.
(d) Riparian Areas – This layer was deemed an important one in stewardship impact
analysis. The buffer used was 100 m (300 ft) to determine riparian corridors
within North Dakota.
(e) Threatened and endangered species – This dataset was obtained from the North
Dakota Natural Heritage Inventory. The dataset most likely will change in the
future simply because an exhaustive study within the state has not been performed
yet.
Spatial Analysis Project Report, Page 17
(f) Wetlands – Forested wetlands data was derived from this layer. The source of
this dataset was USGS and forested wetlands were selected by using a customized
script listed below.
Private Sub UIButtonControl1_Click()
Dim pMxDoc As IMxDocument
Set pMxDoc = ThisDocument
Dim pMap As IMap
Set pMap = pMxDoc.FocusMap
Dim pLayer As IFeatureSelection
Dim strQuery As String
strQuery = "WETLAND_TY = 'Freshwater Forested/Shrub Wetland'"
For i = 1 To pMap.LayerCount - 1
Set pLayer = pMap.Layer(i)
Dim pFilter As IQueryFilter
Set pFilter = New QueryFilter
pFilter.WhereClause = strQuery
pLayer.SelectFeatures _
pFilter, esriSelectionResultNew, True
Next i
End Sub
The script listed above only did a partial selection. To overcome this, forested
wetlands were selected from each quad. Each wetlands shapefile was copied and
pasted into a “master” shapefile using the ArcMap editor. Forested wetlands were
then selected via the “select by attributes” function and a new layer was
subsequently created from the selected features. The forested wetlands layer was
then exported as a shapefile to the Forested Wetlands Geodatabase. Data that was
either missing or unavailable was documented. The following USGS wetland
quads missed data: Bonetraill, Buford, Cartwright NE, Camp Creek West, Camp
Creek East, Watford City NW, Watford City NE, Watford City, Rawson,
Arnegard, Butte, Lone Butte SE, Hootowl Creek West, Hootowl Creek SW, New
Hradec North, Center, Beach East, Sentinel Butte, Fryburg NW, Fargo North,
Spatial Analysis Project Report, Page 18
Fargo South, Thelan, Sentinel Butte SE, Bullion Butte, Bentley, Leith, Bowman,
Bowman SW, Bowman SE, and Lake Jessie. They represented a total of 30 quads
out of 1464 or in data accuracy terms, the wetlands data was 98% accurate.
(g) Forest Health / History of Traditional Pests – There was no data available to
assess diseases or pests that would threaten North Dakota forests. However,
invasive species such as emerald ash borer pose an impending threat to native
forests, shade trees and woody horticulture crops in North Dakota.
(h) Aquifers – North Dakota aquifer data was obtained from the North Dakota GIS
depot. Since most of the public drinking water supplies in North Dakota come
from open water sources, less emphasis was placed on this dataset.
(i) Highly Erodible Land – Highly Erodible Land (HEL) by water and wind was
obtained from USDA geodatabases. This data is not currently maintained and
USDA cannot vouch for its accuracy. Most of the counties of North Dakota have
“frozen” HEL lists whereas about 20% of the counties did a new soil survey to
update their database records. Different map symbols were used for displaying
HEL land that were classified as “Class 1” or highly erodible lands.
To
corroborate this data, we carried out a preliminary survey of James subregion of
Missouri watershed.
Figure 5. Highly Erodible Land (HEL) shown on the background. Note the gently
rolling terrain and absence of significant vegetation.
Spatial Analysis Project Report, Page 19
We took soil and water samples and assessed leachable ions, this data coupled
with other data may be used in future FSP studies to assess: (1) impact of slope on
erodibility, (2) impact of deforestation on soil erodibility (3) impact of overland
flow on water quality. This information can be used for preliminary models on
watershed scales.
(j) Wildfire Assessment – The wildfire assessment layer was obtained from
http://www.fs.fed.us/r2/arnf/fire/aoplrx.doc with 7 fire classes: Class A (0 to .25
acres), Class B (.25 to 9 acres), Class C (10 to 99 acres), Class D (100 to 299
acres), Class E (300 to 999 acres), Class F (1000 to 5000 acres) and Class G
(5000 + acres).
This layer was symbolized according to the classes.
(See
attached DVD and Appendix B for related maps.) (k) Agroforestry suitability – this dataset was derived from NLCD values 51, 71
and 91 under 10,000 ft of elevation from 1" NED dataset.
Future FSP Spatial Analyses
(a) Proximity to public land – This layer can be easily incorporated in future
analyses.
The public lands were classified in the legend of the maps and
surrounding areas displaying FSP areas in green would be prime target areas
owing to the assumption that public lands are in a permanently protected status.
Future FSP programs will seek to identify private lands under permanent
protection status (easements, or other). From the geodatabase created any buffer
limit can be set by state foresters.
(b) Public water supplies – A variable buffer can be used to determine area used to
protect Municipal Water Resources needing protection within North Dakota.
Most of the public water supplies are open water sources like Red River and
Devils Lake. Some datasets that may be considered in future FSPs may include
aquifers, water catchments, and EPA defined basins.
The spatial analysis focused on pertinent conditions to help identify the highest
need or opportunity for future Forest Stewardship Program delivery. The crux of the
analysis was utilizing the power of GIS to produce composite maps depicting layers
Spatial Analysis Project Report, Page 20
(features) of data needed to spatially map risks or vulnerabilities to existing forest
resources, natural resources important to forest sustainability, current public forest land
management, and existing stewardship plans. The minimum standard of map scale and
resolution was consistent with other successful programs. The results section depicts
selected county maps and final project maps.
Spatial Analysis Project Report, Page 21
Spatial Analysis Project Report, Page 22
Spatial Analysis Project Report, Page 23
Spatial Analysis Project Report, Page 24
Spatial Analysis Project Report, Page 25
Spatial Analysis Project Report, Page 26
SPATIAL ANALYSIS PROJECT IMPLEMENTATION
ANALYSIS STRATEGY.
Personal geodatabases created for each identified resource were analyzed prior to
final analyses. This was done in order to preserve topology rules across each resource
feature initially. The resource potentials were reclassified as primary and secondary
datasets after the June 21, 2006 meeting. Highly erodible land was deemed to be an
important dataset even though North Dakota has not implemented a statewide update.
SCOPE OF THE SPATIAL ANALYSIS
Most of the layers used were raster for faster processing and ease of
reclassification. Appropriate scale value ranges were used. Each layer was not weighted
in agreement with the Staff Forester. Instead, overlays were created from reclassified
rasters, raster datasets, and vector data. Tabular data and accompanying composite maps
were used to contribute to in-depth statewide analyses that considered how stewardship
plans corresponded to lands identified as having high or low potential for Forest
Stewardship Program benefit. For those working with private landowners on a local
level, the results of the analyses can spatially display the potential for stewardship benefit
and guide efforts within a given watershed or service forester area. This will aid not only
in plan preparation but also in implementation of program practices. The analysis and
assessment will lead to informed recommendations, considering the resources and
vulnerabilities beyond the boundaries of the tract the plan addresses.
Various modes were pursued for ‘ground-truthing’ or verifying results of the
spatial analysis.
Apart from consulting expert knowledge and agricultural research
institutes, results were systematically compared with existing research data and statistics.
In particular the following activities will also be conducted intensively by NDFS staff:
(1) Confirmation of estimated potential stewardship areas and distribution.
(2)
Comparison of limits of potential stewardship area distribution showing the actual
distribution of these lands (e.g., by comparison with spatial land use/land cover databases
and forest distribution maps). (3) Critically assess delineated areas, that in the light of
Spatial Analysis Project Report, Page 27
improved knowledge on any part of the analysis procedures and model parameters may
be subject to updating. Also, the analysis and parameters used are expected to benefit
from refinement as a result of follow-up applications.
In the future the NDFS in collaboration with NDSU (logistically permitting) will:
(a) Establish methodology by identifying stewardship plan tract location for the FSP,
determining and mapping components of high-risk and suitability for increased
stewardship planning emphasis.
(b) Collect and enter historic stewardship
implementation data into generated databases. (c) Create GIS data layer linked to the
database with point data or polygonal data files of stewardship tracts. (d) Develop a georeferenced, spatial dataset (ArcView-Arc/Info compatible) of existing plan location and
associated attribute information. (e) Develop common data layers in compliance with
those listed in Table 1. (f) Involve the State Stewardship Coordinating Committee at key
decision points throughout project development. (g) Determine the need for additional
state-specific data layers (either vulnerabilities or natural resources) and develop them
accordingly. (h) Consult the State Stewardship Coordinating Committee concerning
additional data layers.
(i) Prepare metadata for spatial data in conformance with
minimum federal metadata standards. (j) Provide a user-friendly system of updating the
electronic stewardship plan database continually beyond project completion.
Spatial Analysis Project Report, Page 28
RESULTS
Table 2 below shows a summary of deciduous, evergreen, mixed forest, shrubland,
woody wetlands and forested wetlands acreage. From Table 2, it can be surmised that
McKenzie, Dunn, Rolette, Williams, and Slope counties have potential forest stewardship
areas in acreage over 100,000 acres. These counties would immensely benefit from FSP.
Table 2. Summary of Spatial Analysis results for each North Dakota county.
ADAMS
Deciduous
Forest
(acres)
-
Evergreen
Forest
(acres)
-
Mixed
Forest
(acres)
-
BARNES
6,242
81
12
BENSON
38,150
-
BILLINGS
23,209
Woody
Wetlands
(acres)
190
Forested
Wetlands
(acres)
40
-
163
840
7,338
-
1,801
651
1,104
41,706
Shrubland
(acres)
Total
23,440
378
-
-
64,872
86
46
65,382
BOTTINEAU
59,342
-
-
17,384
562
754
78,043
BOWMAN
4,726
1,680
185
87,276
773
59
94,698
492
-
-
-
22
44
559
12,763
-
-
567
513
716
14,559
BURKE
BURLEIGH
CASS
15,371
172
285
5
139
561
16,533
CAVALIER
42,999
28
10
13
415
978
44,442
DICKEY
8,687
-
-
1,362
43
141
10,233
DIVIDE
858
327
-
48,510
3,415
86
53,196
DUNN
404
-
-
167,499
805
1,508
170,217
EDDY
15,922
-
-
7,129
635
1,219
24,905
EMMONS
3,136
-
-
1,431
771
1,242
6,580
FOSTER
3,669
-
-
215
30
135
4,049
GOLDEN VALLEY
7,047
989
68
80,097
93
18
88,312
GRAND FORKS
10,644
24
40
1
899
1,676
13,284
GRANT
142
-
-
28,640
54
1,019
29,856
GRIGGS
4,055
17
4
101
445
814
5,437
-
-
-
13,124
117
137
13,379
HETTINGER
KIDDER
11,095
-
-
385
113
166
11,758
LAMOURE
8,360
-
-
325
39
249
8,973
LOGAN
2,743
-
-
212
48
81
3,085
MCHENRY
34,849
-
-
25,272
2,072
2,693
64,886
MCINTOSH
2,048
-
-
235
192
72
2,546
MCKENZIE
6,947
1,251
130
208,390
13,840
558
231,115
20,133
MCLEAN
5,420
-
-
13,445
506
762
MERCER
1,937
-
-
80,922
120
154
83,133
MORTON
5,618
-
-
20,325
1,483
1,946
29,372
MOUNTRAIL
373
-
-
26,173
70
163
26,780
NELSON
9,433
10
3
946
268
617
11,277
OLIVER
6,017
-
-
2,739
287
359
9,402
PEMBINA
27,792
15
61
3
1,685
3,995
33,552
Spatial Analysis Project Report, Page 29
Table 2 (contd.). Summary of Spatial Analysis results for each North Dakota county.
2,351
Woody
Wetlands
(acres)
145
Forested
Wetlands
(acres)
230
4
214
519
16,450
-
-
725
1,253
25,571
PIERCE
Deciduous
Forest
(acres)
7,909
Evergreen
Forest
(acres)
-
Mixed
Forest
(acres)
-
RAMSEY
15,712
-
-
RANSOM
23,592
-
Shrubland
(acres)
TOTAL
10,636
RENVILLE
868
-
-
100
20
18
1,006
RICHLAND
18,287
18
126
0
642
1,523
20,595
ROLETTE
111,006
-
-
22,590
662
955
135,213
SARGENT
19,051
0
3
-
350
695
20,098
SHERIDAN
3,189
-
-
236
29
63
3,517
SIOUX
1,492
-
-
8,381
740
1,063
11,676
SLOPE
1,435
2,523
54
99,464
551
41
104,067
STARK
-
-
-
48,956
31
65
49,052
STEELE
3,661
14
18
3
133
486
4,314
STUTSMAN
12,702
1
-
301
181
592
13,778
TOWNER
9,511
-
-
32
344
532
10,419
TRAILL
8,211
71
219
-
230
598
9,329
WALSH
18,359
13
25
-
960
2,328
21,684
6,291
WARD
4,662
-
-
571
404
655
WELLS
9,320
-
-
165
88
138
9,711
WILLIAMS
1,587
306
13
124,968
15,568
482
142,925
628,215
7,541
1,256
1,230,732
53,558
37,191
1,958,493
TOTAL
There were sets of maps and digital files generated for the results of the analyses. The
analog maps that were printed included:
1. Potential for Forest Stewardship Program Benefits – County maps were printed to
display areas that would benefit from FSP (see Appendix B and accompanying
DVD). All the county maps depicted also areas where trees are grown as wind
buffers. This was a primary concern for the State Forester. Accompanying each
county map is an attribute table comparing prime levels of stewardship potential
with total stewardship capable lands. All datasets were displayed such that the
FSP implementation would be done on areas deemed as critical areas, that is,
where there exist resource rich and resource threat areas. Each county and state
map compiled also displayed forest stewardship program potential on nonforested / non-developed lands by displaying agroforestry suitability areas.
2. Potential for Forest Stewardships Program Benefits and Existing Stewardship
Plans – A statewide digital and analog map was compiled to show existing
stewardship plans overlay with stewardship potential.
Spatial Analysis Project Report, Page 30
3. Forest Stewardship Potential on Private Forest Lands – All the county maps
displayed target stewardship potential only on private land (see also Figures 6, 7,
and 8).
Spatial Analysis Project Report, Page 31
Spatial Analysis Project Report, Page 32
Spatial Analysis Project Report, Page 33
Figures 6 and 7 show site maps of areas that were visited for groundtruthing.
A
B
C
D
E
F
Figure 9. Forests on private land in Stutsman County (A, C and E) and in Steele County
(B, D, and F).
Spatial Analysis Project Report, Page 34
Potential FSP were prioritized according to the following criterion:
STEP 1: The following buffers on specific datasets were created:
Endangered Species: An 800m buffer file (en_spec_800) and a 1600m buffer file
(en_spec_1600) were created.
Public Lands: Similarly, an 800m buffer file (pub_land_800), and likewise a
1600m buffer file (pub_land_1600) was also created.
Riparian Areas: A 500m buffer file (rip_area_500) and a 1300m buffer file were
created (rip_area_1300) on the already existing 300 m riparian buffer previously
determined.
STEP 2: The following priority zones were determined from merged datasets:
The endangered species, public land, and riparian areas were merged, using the
following commands:
Merge(en_spec_800, pub_land_800, rip_area_500);
Feature name: high_pri_zone
Merge(en_spec_1600, pub_land_1600, rip_area_1300);
Feature name: med_pri_zone
STEP 3: Raster creation
The Feature "high_pri_zone" was converted to Raster "high_pri_zone"
And a cell size of 0.000277769 used; the grid cells were reclassified and assigned
values "100"s, with NoData cells assigned a value of 0.
The Feature "med_pri_zone" was converted to Raster "med_pri_zone"
with a grid cell size of 0.000277769. The cells were then reclassified and
assigned values of "200"s and NoData cells assigned "0"s
STEP 4: Raster analyses
A) NLCD DATA:
Cells with following values were considered:
41: Deciduous Forest, 42: Evergreen Forest, 43: Mixed Forest, 51: Shrubland, 91: Woody
Wetlands
Raster Calculation: The raster calculator command used was:
[nlcd_mskd_pri] = [nlcd_mskd]+[high_pri_zone]+[med_pri_zone]
Final Cell Values: The resulting cell values were classified as follows:
High Priority Forest included cells with values of: 341, 342, 343, 351, 391 (e.g.
41+100+200=341)
Medium Priority Forest included cells with values: 241, 242, 243, 251, 291 (e.g.
41+0+200=241)
Low Priority Forest included cells with values: 41, 42, 43, 51, 91 (e.g. 41+0+0=41)
Final Reclassification: Finally from the final cell values:
Spatial Analysis Project Report, Page 35
Cell values 341, 342, 343, 351, 391 were reclassified to 300 (High Priority),
Cell values 241, 242, 243, 251, 291 were reclassified to 200 (Medium Priority),
Cell values 41, 42, 43, 51, 91 were reclassified to 100 (Low Priority),
Remaining cells were assigned "0"s. The final raster grid was renamed: nlcd_mskd_pri
B) FORESTED WETLANDS DATA
Reclassification:
All cell values of raster data “frst_wet_mskd” were reclassified to value "1"s, NoData
cells assigned "0"s, and the resulting raster called: frswetmsk_rec
Raster Calculation: The raster calculation performed was as below:
[frswetmsk_pr] = [frswetmsk_rec]+[high_pri_zone]+[med_pri_zone]
Final Cell Values:
High Priority Forest were cells with values: 301 (1+100+200=301)
Medium Priority Forest were cells with values: 201 (1+0+200=201)
Low Priority Forest were cells with values: 1 (1+0+0=1)
The final raster was called: frswetmsk_pr
C) FOREST CANOPY DATA
Raster Calculation:
[can_msk_pri] = [canopy_mskd]+[high_pri_zone]+[med_pri_zone]
Final Cells:
High Priority Forest were cells with values: 301 (1+100+200=301)
Medium Priority Forest were cells with values: 201 (1+0+200=201)
Low Priority Forest were cells with values: 1 (1+0+0=1)
Final Raster: can_msk_pri
The results were tabulated as shown in Table 3 below. The tree canopy data should be
considered as contiguous data occupying a grid cell.
Table 3. Prioritization of FSP areas in North Dakota.
Vegetation Type
High Priority
Medium
Low
Total
Priority
Priority
Area (acres)
288,294
157,271
183,292
Deciduous Forest
628,857
5,035
1,346
1,197
Evergreen Forest
7,579
673
220
366
Mixed Forest
1,259
544,251
321,313
365,095 1,230,660
Shrubland
34,981
12,008
6,547
Woody Wetlands
53,536
361,222
193,377
244,060
Tree Canopy
798,659
16,406
6,837
9,490
Forested Wetlands
32,732
Spatial Analysis Project Report, Page 36
SUMMARY AND CONCLUSIONS
The North Dakota FSP Spatial Analysis Project (SAP) provided the NDFS a
consistent methodology (while offering the ability to customize it according to future
conditions) to spatially display (according to counties the amount and type of work
completed and yet to do): (1) Important forest lands (rich in natural resources, vulnerable
to threat, or both); (2) Existing stewardship tracts (properties under stewardship plans);
and (3) Areas of opportunity to focus future FSP efforts (stewardship potential). This
will aid not only in plan preparation but also in implementation of program practices. The
analysis and assessment will lead to informed recommendations, considering the
resources and vulnerabilities beyond the boundaries that a plan addresses. Based on
where the property is located and surrounding opportunities or challenges, the
professional forester may recommend to the landowner that practices be implemented to
complement the surrounding land base or to respond to the landscape surrounding the
given tract. The ND SAP quantified data (in the form of number of acres and number of
current plans) and displayed it. The ND Spatial Analysis Project will enable resource
managers to demonstrate connectivity in program efforts of plan development and how
they complement other natural resource efforts and other State and Private Forestry
programs. Through time, they will be able to track the accomplishment of plan-prescribed
activities on given stewardship areas.
The SAP addressed the following questions, as they related to the FSP: (a) Where
are the current State’s stewardship tracts? (b) Where are the priority lands (those lands of
highest potential to benefit from the FSP)? (c) Where should greater FSP efforts be
considered in the future? The FSP results will enable the North Dakota Forest Service to
determine the impact of FSP efforts on priority lands and other forest lands and assess
how the state stewardship tracts and priority lands overlap. This in turn will enable
managers and foresters to assess program effectiveness in serving identified critical
resource management needs.
Spatial Analysis Project Report, Page 37
The SAP responded to the issues identified by: (1) Creating geo-referenced,
spatial data displaying stewardship areas relative to FSP potential; (2) Relating factors
such as stewardship practices completed and resource condition to help determine future
practices that might be most effective in addressing critical needs based on the sitespecific resource condition; and (3) Providing tools that help States focus future FSP
efforts to effectively and efficiently address critical forest resource issues.
There were three major components to the FSP Spatial Analysis Project: (A)
Development of a geographic database for FSP and associated geo-referenced map of
existing stewardship plans in the State, to be maintained on an ongoing basis following
initial project completion. (B) Development of a statewide assessment of important
forest lands incorporating spatial and tabular display of natural resource data critical to
the sustainability of forest resources and the risks or vulnerabilities facing those
resources. (C) Analysis of the location of lands currently under stewardship plans and
how they relate to the important forest lands in the State, and assessment of how the State
intends to use the results of the SAP to guide future FSP activities in conjunction with
other assistance programs available to family forest landowners.
A composite map with associated tabular data of all GIS common data layers,
including the 2005 stewardship plan data layer, was developed. The tabular data and
accompanying composite map contributed to in-depth statewide analyses that considered
how stewardship plans corresponded to lands identified as having high, or low potential
for Forest Stewardship Program benefit. The results of this project will give resource
managers the capability to gather and display information according to geographic area,
watershed, county, or service area (such as service forester jurisdiction) to assess the
amount and type of work completed and yet to do. The Forest Stewardship Program
emphasizes addressing the landowner’s objectives through professional forest
management. Often a forest landowner is not aware of the importance of the resources on
his or her land, particularly as they relate to surrounding properties. A professional
forester has an obligation to help the landowner understand the full potential and extent
of the resources on the tract. With that body of information, the landowner then has the
capability of making informed decisions about long- and short-term objectives.
Spatial Analysis Project Report, Page 38
The Spatial Analysis Project provided key information concerning not only
resource potential and vulnerability, but also the extent of professional management
occurring around a given tract, respecting private property rights and confidential
information. Landowners may find new opportunities to complement the activities
already begun in a geographic area, or learn of a need to protect their tracts from a
significant vulnerability such as invasive insects or fire threats. In addressing a plan
request backlog or as new opportunities arise to promote the Forest Stewardship
Program, service and consultant foresters can target areas around a core base of forest
land. They will also be able to identify forest lands of high stewardship potential based
either on richness of forest resources or vulnerabilities, or a combination of the two. They
will have enhanced information at their fingertips as they approach and work with forest
landowners. The results of this project can provide information to NDFS managers so
they can strategically allocate staff resources throughout the State based on the greatest
needs and opportunities. In a similar manner, consultant foresters have the ability to look
at project results across the State, and target their professional forestry services
accordingly. Further, service foresters working within their assigned areas will have the
ability to determine high, and low needs and opportunities to help prioritize their efforts.
Spatial Analysis Project Report, Page 39
REFERENCES
Forest Stewardship Program National Standards and Guidelines, USDA FS/ S & P F/ CF,
2nd Edition, September 2005
Pijanowski, B. C., D. G. Brown, B. A. Shellito, and G. A. Manik. 2002. Using neural
networks and GIS to forecast land use changes: A land transformation model.
Computers, Environment and Urban Systems 26 (6): 553–575.
Russell, D. R., and Stein S., Planning for Forest Stewardship: A Desk Guide, 2002,
USDA FS-733
Spatial Analysis Project Report, Page 40
APPENDIX A
NORTH DAKOTA STATE MAPS USED IN FSP
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APPENDIX B
FOREST STEWARDSHIP AREAS COUNTY MAPS
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