Great Smoky Mountains National Park 1949 Park Topographic Map

How should this data set be cited?

United States Geologic Survey, 1949 , Topographic Map. Great Smoky Mountains National Park. Tennessee and North Carolina. Online Links:

http://science.nature.nps.gov/nrdata

What geographic area does the data set cover?

West_Bounding_Coordinate: -84.007769 East_Bounding_Coordinate: -83.037582 North_Bounding_Coordinate: 35.790660 South_Bounding_Coordinate: 35.418718

What does it look like?

Does the data set describe conditions during a particular time period?

Calendar_Date: 09-Mar-2015Currentness_Reference: publication date

What is the general form of this data set?

Geospatial_Data_Presentation_Form: raster digital data

How does the data set represent geographic features?

How are geographic features stored in the data set? This is a Raster data set.

What coordinate system is used to represent geographic features? Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.000000. Longitudes are given to the nearest 0.000000. Latitude and longitude values are specified in Decimal degrees.

The horizontal datum used is North American Datum of 1983. The ellipsoid used is Geodetic Reference System 80. The semi-major axis of the ellipsoid used is 6378137.000000. The flattening of the ellipsoid used is 1/298.257222.

Vertical_Coordinate_System_Definition:

Altitude_System_Definition:

Altitude_Datum_Name: North American Vertical Datum of 1988 Altitude_Resolution: 0.000025 Altitude_Distance_Units: feet Altitude_Encoding_Method:

Explicit elevation coordinate included with horizontal coordinates

How does the data set describe geographic features?

Entity_and_Attribute_Overview:

Where possible entity attribute population is completed automatically by the GIS/SQL database software. Enclosed herein are Attribute Domains and lists of legal values (LOV) where attributes are populated by "Picklists".

Who produced the data set?

Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

United States Geologic Survey

Who also contributed to the data set?

To whom should users address questions about the data?

National Park Service Attn: Thomas Colson GIS Specialist 107 Park Headquarters Road Gatlinburg, Tennessee 37738 United States

(865)436-1701 (voice) GRSM_Resource_Management@nps.gov

Hours_of_Service: 0800-1730

Why was the data set created?

For the display, query, and analysis of spatial and tabular data.

How was the data set created?

From what previous works were the data drawn?

How were the data generated, processed, and modified?

Date: 28-Mar-2015 (process 1 of 1)

These data contain location values from numerous resource research, inventory, and monitoring projects spanning over many decades. The National Park Service is unable to determin the process steps used to depict many locations, citing lack of reliable data. When known, map source is given as a range of values.

What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

How well have the observations been checked? Attribute accuracy is tested by manual comparison of the source with hard copy plots and/or symbolized display of the map data on an interactive computer graphic system. Selected attributes that cannot be visually verified on plots or on screen are interactively queried and verified on screen. In addition, the attributes are tested against a master set of valid attributes. All attribute data conform to the attribute codes in the signed classification and correlation document and amendment(s).

How accurate are the geographic locations? These data contain location values from numerous resource research, inventory, and monitoring projects spanning over many decades. The National Park Service is unable to asses the positional accuracy of many locations, citing lack of reliable data. When known, estimated horizontal precision is given as a range of possible values.

Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.

This hardcopy map was scanned and georectified using current USGS 1:24k-scale topographic maps. This map is for reference purpose only, and there are likey several gross horizontal errors committed during rectification.

How accurate are the heights or depths? Statements of vertical positional accuracy for elevation of these points are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of points printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map. This statement is generally true for the most common sources of these data. Other sources and methods may have been used to create or update these data. In some cases, additional information may be found in the feature-level metadata report.

Where are the gaps in the data? What is missing? Data completeness for these data reflect content of the source data. Features may have been eliminated or generalized on the source data due to scale and legibility constraints. For information on collection and inclusion criteria, see U.S. Geological Survey, 1994, Standards for 1:24,000-Scale Digital Line Graphs and Quadrangle Maps: National Mapping Program Technical Instructions and U.S. Geological Survey, 1994, Standards for Digital Line Graphs: National Mapping Program Technical Instructions.

How consistent are the relationships among the observations, including topology? No duplicate features exist nor duplicate points in a data string. Point data are represented by two sets of coordinate pairs, each with the same coordinate values, contained in the "Shape" Column, and "X_COORD, Y_COORD" Columns.

Database engine scripts automatically populate many of the possible "List of Values" for those columns that derive their attrtibute from other source data (see Entity Attribute Section of this document for details), thereby enforcing Attribute Accuracy. Database engine scripts also prevent the entry of duplication location coordinates, ensure the consistency and format of binary data representing geographic coordinates, and spatial and attribute index integrity.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Who distributes the data set? (Distributor 1 of 1)

Thomas Colson National Park Service GIS Specialist 107 Park Headquarters Rd. Gatlinburg, Tennessee 37738 United States

(865)436-1701 (voice) GRSM_Resource_Management@nps.gov

Hours_of_Service: 0800-1730 EST

What's the catalog number I need to order this data set? Downloadable Data

What legal disclaimers am I supposed to read?

The National Park Service shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics (i.e. GIF or JPG format files) are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The National Park Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on computer systems at the National Park Service, no warranty expressed or implied is made regarding the utility of the data on other

Great Smoky Mountains National Park 1931 Park East Topographic Map

How should this data set be cited?

United States Geologic Survey, 1931, Topographic Map. Great Smoky Mountains National Park. Tennessee and North Carolina. (East Half). Online Links:

http://science.nature.nps.gov/nrdata

What geographic area does the data set cover?

West_Bounding_Coordinate: -84.007769 East_Bounding_Coordinate: -83.037582 North_Bounding_Coordinate: 35.790660 South_Bounding_Coordinate: 35.418718

What does it look like?

Does the data set describe conditions during a particular time period?

Calendar_Date: 09-Mar-2015Currentness_Reference: publication date

What is the general form of this data set?

Geospatial_Data_Presentation_Form: raster digital data

How does the data set represent geographic features?

How are geographic features stored in the data set? This is a Raster data set.

What coordinate system is used to represent geographic features? Horizontal positions are specified in geographic coordinates, that is, latitude and longitude. Latitudes are given to the nearest 0.000000. Longitudes are given to the nearest 0.000000. Latitude and longitude values are specified in Decimal degrees.

The horizontal datum used is North American Datum of 1983. The ellipsoid used is Geodetic Reference System 80. The semi-major axis of the ellipsoid used is 6378137.000000. The flattening of the ellipsoid used is 1/298.257222.

Vertical_Coordinate_System_Definition:

Altitude_System_Definition:

Altitude_Datum_Name: North American Vertical Datum of 1988 Altitude_Resolution: 0.000025 Altitude_Distance_Units: feet Altitude_Encoding_Method:

Explicit elevation coordinate included with horizontal coordinates

How does the data set describe geographic features?

Entity_and_Attribute_Overview:

Where possible entity attribute population is completed automatically by the GIS/SQL database software. Enclosed herein are Attribute Domains and lists of legal values (LOV) where attributes are populated by "Picklists".

Who produced the data set?

Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

United States Geologic Survey

Who also contributed to the data set?

To whom should users address questions about the data?

National Park Service Attn: Thomas Colson GIS Specialist 107 Park Headquarters Road Gatlinburg, Tennessee 37738 United States

(865)436-1701 (voice) GRSM_Resource_Management@nps.gov

Hours_of_Service: 0800-1730

Why was the data set created?

For the display, query, and analysis of spatial and tabular data.

How was the data set created?

From what previous works were the data drawn?

How were the data generated, processed, and modified?

Date: 28-Mar-2015 (process 1 of 1)

These data contain location values from numerous resource research, inventory, and monitoring projects spanning over many decades. The National Park Service is unable to determin the process steps used to depict many locations, citing lack of reliable data. When known, map source is given as a range of values.

What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

How well have the observations been checked? Attribute accuracy is tested by manual comparison of the source with hard copy plots and/or symbolized display of the map data on an interactive computer graphic system. Selected attributes that cannot be visually verified on plots or on screen are interactively queried and verified on screen. In addition, the attributes are tested against a master set of valid attributes. All attribute data conform to the attribute codes in the signed classification and correlation document and amendment(s).

How accurate are the geographic locations? These data contain location values from numerous resource research, inventory, and monitoring projects spanning over many decades. The National Park Service is unable to asses the positional accuracy of many locations, citing lack of reliable data. When known, estimated horizontal precision is given as a range of possible values.

Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features.

This hardcopy map was scanned and georectified using current USGS 1:24k-scale topographic maps. This map is for reference purpose only, and there are likey several gross horizontal errors committed during rectification.

How accurate are the heights or depths? Statements of vertical positional accuracy for elevation of these points are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of points printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map. This statement is generally true for the most common sources of these data. Other sources and methods may have been used to create or update these data. In some cases, additional information may be found in the feature-level metadata report.

Where are the gaps in the data? What is missing? Data completeness for these data reflect content of the source data. Features may have been eliminated or generalized on the source data due to scale and legibility constraints. For information on collection and inclusion criteria, see U.S. Geological Survey, 1994, Standards for 1:24,000-Scale Digital Line Graphs and Quadrangle Maps: National Mapping Program Technical Instructions and U.S. Geological Survey, 1994, Standards for Digital Line Graphs: National Mapping Program Technical Instructions.

How consistent are the relationships among the observations, including topology? No duplicate features exist nor duplicate points in a data string. Point data are represented by two sets of coordinate pairs, each with the same coordinate values, contained in the "Shape" Column, and "X_COORD, Y_COORD" Columns.

Database engine scripts automatically populate many of the possible "List of Values" for those columns that derive their attrtibute from other source data (see Entity Attribute Section of this document for details), thereby enforcing Attribute Accuracy. Database engine scripts also prevent the entry of duplication location coordinates, ensure the consistency and format of binary data representing geographic coordinates, and spatial and attribute index integrity.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Who distributes the data set? (Distributor 1 of 1)

Thomas Colson National Park Service GIS Specialist 107 Park Headquarters Rd. Gatlinburg, Tennessee 37738 United States

(865)436-1701 (voice) GRSM_Resource_Management@nps.gov

Hours_of_Service: 0800-1730 EST

What's the catalog number I need to order this data set? Downloadable Data

What legal disclaimers am I supposed to read?

The National Park Service shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics (i.e. GIF or JPG format files) are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived. It is the responsibility of the data user to use the data appropriately and consistent within the limitations of geospatial data in general and these data in particular. The related graphics are intended to aid the data user in acquiring relevant data; it is not appropriate to use the related graphics as data. The National Park Service gives no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data. It is strongly recommended that these data are directly acquired from an NPS server and not indirectly through other sources which may have changed the data in some way. Although these data have been processed successfully on computer systems at the National Park Service, no warranty expressed or implied is made regarding the utility of the data

Table of Content: 1. General context of the data set "LUSzoning”; 2. Background and aims of the study using the data set LUSzoning; 3. The data set LUSzoning. 1. General context of the data set "LUSzoning". The data set "LUSzoning" stands for Land-use simulations integrating zoning regulations in Spanish functional urban areas. The data set has been generated as part of the CONCUR research project (https://www.wsl.ch/en/projects/concur.html) led by Dr. Anna M. Hersperger and funded by the Swiss National Science Foundation (ERC TBS Consolidator Grant (ID: BSCGIO 157789) for the period 2016-2021. The CONCUR research project is interdisciplinary and aims to develop a scientific basis for adequately integrating spatial policies (in this case, digital zoning plans) into quantitative land-change modelling approaches at the urban regional level. 2. Background and aims of the study using the data set “LUSzoning”. As part of the CONCUR project, a specific task was to integrate planning spatial policies in land-change modelling. Planning can be implemented in modelling using either hard or gradual restrictions. Different studies have addressed the inclusion of spatial planning policies in land-use change modelling. However, the integration of zoning constraints is generally established as hard or Boolean-based restrictions (e.g., whether urban development is allowed or not), while not accounting for the spatial heterogeneity or gradual characteristics within planning zones (e.g., whether planning regulations allow low, medium or high urban density), though these could improve real patterns simulations in urban areas. We assume Spanish General Zoning plans were suitable to explore the integration of planning into land-change modelling as soft constrains because they define land-use intensities in the buildable zoning areas. In light of the above considerations, the overall aim of the study was to model urban land-use changes using a multi-scenario approach that integrates digitized zoning plans for the Functional Urban Areas (FUAs) of Madrid, Barcelona, Valencia, and Zaragoza. The following specific objectives were addressed: i) to analyse the role of planning by defining three future scenarios that integrate digitized zoning plans and one scenario that assumes almost no planning intervention; ii) to introduce zoning constraints that reflect different degrees of urban densities; iii) to generate a transferable spatially-explicit modelling framework to integrate planning into land-use change simulations. Four future land-use demands scenarios were defined for the FUAs. Storylines were created considering probable development scenarios related to zoning plans, current Spanish legislation and sustainability goals defined along two axes: a high market-oriented vs. high planning-intervention axis, and an axis of short-term economic growth vs. long-term sustainable growth. The sustainable development scenario (S1) is characterized by low gross floor area (GFA) growth that is limited to areas that are currently under development according to zoning plans. The business-as-usual scenario (S2) is characterized by medium GFA growth in the range of on-going trends. The strong development scenario (S3) is characterized by high GFA growth rates. Growth is restricted to buildable areas without urbanization project designated in zoning plans. The unrestricted development scenario (S4) prioritizes a high degree of market liberalization characterized by high GFA growth that surpasses population demands. S4 follows a rapid economic growth pattern with almost no planning intervention. 3. The data set “LUSzoning”. The dataset includes 16 .asc raster layers providing the simulated land-uses under four defined scenarios for Barcelona, Madrid, Valencia and Zaragoza Functional Urban Areas (FUAs) for 2030. The simulated raster layers were created using CLUMondo simulation framework and have a spatial resolution of 30m. The .asc layers name include the name of the FUA and scenario number. For example, the output from simulating the urban growth for the city of Zaragoza under Scenario 2 is named “Zaragoza_S2.tif”. Furthermore, a .txt file named “Legend.txt” includes the numeric value of the land-use and the category of land-use that represents to interpret the .asc raster layers. The name of the land-use classes is a reclassification of the Urban Atlas 2012 land-use classes within the four Spanish FUAs analyzed.