EcoService Models Library (ESML)
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Variables Details
: (EM-849)
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EM Identity and Description
EM-849 | |
Document Author
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The Natural Capital Project.org |
Document Year
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Variable General Info
Geomorphology class ?Comment:Optional. Rocky cliffs are less prone to erosion and inundation than bluffs, beaches or deltas. Consequently, a relative ranking of exposure scheme based on geomorphology similar to the one proposed by Hammar-Klose and Thieler (2001) has been adopted. Supplied in Appendix A is a definition of the terms used in this classification, which applies mostly to the North American continent. The Geomorphology input should be a polyline vector with segments that categorize – in an attribute field called ‘RANK’ – the shoreline geomorphology based on the scheme presented in Example Ranking Table. The model joins the geomorphology ranks to shore points by searching around each point with a radius of half the model resolution and then taking the average of all the ranks found in the search. If the user’s geomorphology data source has more categories than the ones presented in Example Ranking Table, it is left to the user’s discretion to reclassify their data to match the provided ranking system, as explained in the Data Needs section, and in Appendix B. It is recommend that the user include shore parallel hard structures (seawalls, bulkheads, etc.) in this classification and that they apply a low to moderate rank (1-3), depending on their characteristics. For example, a large, concrete seawall should be assigned a rank 1 as they are typically designed to prevent inundation during storm events and are designed to withstand damage or failure during the most powerful storms. It is recommended that low revetments or riprap walls be assigned a rank of 3 as they do not prevent inundation and may fail during extreme events. The ranking presented in the above table is only a suggestion. Users should change the ranking of different shoreline types as they see fit, based on local research and knowledge, and by following directions presented in the Data Needs section. |
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Variable ID
variable.detail.varIdHelp
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20132 |
Not reported | |
Qualitative-Quantitative
variable.detail.continuousCategoricalHelp
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Qualitative (Class, Rating or Ranking) |
Cardinal-Ordinal
variable.detail.cardinalOrdinalHelp
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Non-Ordinal |
Not applicable |
Variable Typology
Geomorphology class ?Comment:Optional. Rocky cliffs are less prone to erosion and inundation than bluffs, beaches or deltas. Consequently, a relative ranking of exposure scheme based on geomorphology similar to the one proposed by Hammar-Klose and Thieler (2001) has been adopted. Supplied in Appendix A is a definition of the terms used in this classification, which applies mostly to the North American continent. The Geomorphology input should be a polyline vector with segments that categorize – in an attribute field called ‘RANK’ – the shoreline geomorphology based on the scheme presented in Example Ranking Table. The model joins the geomorphology ranks to shore points by searching around each point with a radius of half the model resolution and then taking the average of all the ranks found in the search. If the user’s geomorphology data source has more categories than the ones presented in Example Ranking Table, it is left to the user’s discretion to reclassify their data to match the provided ranking system, as explained in the Data Needs section, and in Appendix B. It is recommend that the user include shore parallel hard structures (seawalls, bulkheads, etc.) in this classification and that they apply a low to moderate rank (1-3), depending on their characteristics. For example, a large, concrete seawall should be assigned a rank 1 as they are typically designed to prevent inundation during storm events and are designed to withstand damage or failure during the most powerful storms. It is recommended that low revetments or riprap walls be assigned a rank of 3 as they do not prevent inundation and may fail during extreme events. The ranking presented in the above table is only a suggestion. Users should change the ranking of different shoreline types as they see fit, based on local research and knowledge, and by following directions presented in the Data Needs section. |
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Predictor-Intermediate-Response
variable.detail.displayVariableTypeHelp
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Predictor |
Predictor Variable Type
variable.detail.displayPredictorVariableTypeHelp
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Time- or Space-varying Variable |
Response Variable Type
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Not applicable |
Data Source/Type
variable.detail.dataTypeHelp
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Not applicable |
Variable Classification Hierarchy
variable.detail.vchLevel1Help
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2. Land Surface (or Water Body) Cover, Use, Substrate, or Metric |
--Land use/land cover type or dominant habitat type |
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----Other, multiple, unspecified or unclear |
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Variable Spatial Characteristics
Geomorphology class ?Comment:Optional. Rocky cliffs are less prone to erosion and inundation than bluffs, beaches or deltas. Consequently, a relative ranking of exposure scheme based on geomorphology similar to the one proposed by Hammar-Klose and Thieler (2001) has been adopted. Supplied in Appendix A is a definition of the terms used in this classification, which applies mostly to the North American continent. The Geomorphology input should be a polyline vector with segments that categorize – in an attribute field called ‘RANK’ – the shoreline geomorphology based on the scheme presented in Example Ranking Table. The model joins the geomorphology ranks to shore points by searching around each point with a radius of half the model resolution and then taking the average of all the ranks found in the search. If the user’s geomorphology data source has more categories than the ones presented in Example Ranking Table, it is left to the user’s discretion to reclassify their data to match the provided ranking system, as explained in the Data Needs section, and in Appendix B. It is recommend that the user include shore parallel hard structures (seawalls, bulkheads, etc.) in this classification and that they apply a low to moderate rank (1-3), depending on their characteristics. For example, a large, concrete seawall should be assigned a rank 1 as they are typically designed to prevent inundation during storm events and are designed to withstand damage or failure during the most powerful storms. It is recommended that low revetments or riprap walls be assigned a rank of 3 as they do not prevent inundation and may fail during extreme events. The ranking presented in the above table is only a suggestion. Users should change the ranking of different shoreline types as they see fit, based on local research and knowledge, and by following directions presented in the Data Needs section. |
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Spatial Extent Area
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Not applicable |
Spatially Distributed?
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Yes |
Observations Spatially Patterned?
variable.detail.regularSpGrainHelp
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Yes |
Spatial Grain Type
variable.detail.spGrainTypeHelp
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area, for pixel or radial feature |
Spatial Grain Size
variable.detail.spGrainSizeHelp
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user defined |
Spatial Density
variable.detail.spDensityHelp
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Not applicable |
EnviroAtlas URL
variable.detail.enviroAtlasURLHelp
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Variable Temporal Characteristics
Geomorphology class ?Comment:Optional. Rocky cliffs are less prone to erosion and inundation than bluffs, beaches or deltas. Consequently, a relative ranking of exposure scheme based on geomorphology similar to the one proposed by Hammar-Klose and Thieler (2001) has been adopted. Supplied in Appendix A is a definition of the terms used in this classification, which applies mostly to the North American continent. The Geomorphology input should be a polyline vector with segments that categorize – in an attribute field called ‘RANK’ – the shoreline geomorphology based on the scheme presented in Example Ranking Table. The model joins the geomorphology ranks to shore points by searching around each point with a radius of half the model resolution and then taking the average of all the ranks found in the search. If the user’s geomorphology data source has more categories than the ones presented in Example Ranking Table, it is left to the user’s discretion to reclassify their data to match the provided ranking system, as explained in the Data Needs section, and in Appendix B. It is recommend that the user include shore parallel hard structures (seawalls, bulkheads, etc.) in this classification and that they apply a low to moderate rank (1-3), depending on their characteristics. For example, a large, concrete seawall should be assigned a rank 1 as they are typically designed to prevent inundation during storm events and are designed to withstand damage or failure during the most powerful storms. It is recommended that low revetments or riprap walls be assigned a rank of 3 as they do not prevent inundation and may fail during extreme events. The ranking presented in the above table is only a suggestion. Users should change the ranking of different shoreline types as they see fit, based on local research and knowledge, and by following directions presented in the Data Needs section. |
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Temporal Extent
variable.detail.tempExtentHelp
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Not applicable |
Temporally Distributed?
variable.detail.tempDistributedHelp
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Not applicable |
Regular Temporal Grain?
variable.detail.regularTempGrainHelp
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Not applicable |
Temporal Grain Size Value
variable.detail.tempGrainSizeValHelp
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Not applicable |
Temporal Grain Size Units
variable.detail.tempGrainSizeUnitHelp
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Not applicable |
Temporal Density
variable.detail.tempDensityHelp
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Not applicable |
Variable Values
Geomorphology class ?Comment:Optional. Rocky cliffs are less prone to erosion and inundation than bluffs, beaches or deltas. Consequently, a relative ranking of exposure scheme based on geomorphology similar to the one proposed by Hammar-Klose and Thieler (2001) has been adopted. Supplied in Appendix A is a definition of the terms used in this classification, which applies mostly to the North American continent. The Geomorphology input should be a polyline vector with segments that categorize – in an attribute field called ‘RANK’ – the shoreline geomorphology based on the scheme presented in Example Ranking Table. The model joins the geomorphology ranks to shore points by searching around each point with a radius of half the model resolution and then taking the average of all the ranks found in the search. If the user’s geomorphology data source has more categories than the ones presented in Example Ranking Table, it is left to the user’s discretion to reclassify their data to match the provided ranking system, as explained in the Data Needs section, and in Appendix B. It is recommend that the user include shore parallel hard structures (seawalls, bulkheads, etc.) in this classification and that they apply a low to moderate rank (1-3), depending on their characteristics. For example, a large, concrete seawall should be assigned a rank 1 as they are typically designed to prevent inundation during storm events and are designed to withstand damage or failure during the most powerful storms. It is recommended that low revetments or riprap walls be assigned a rank of 3 as they do not prevent inundation and may fail during extreme events. The ranking presented in the above table is only a suggestion. Users should change the ranking of different shoreline types as they see fit, based on local research and knowledge, and by following directions presented in the Data Needs section. |
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Not applicable | |
Min Value
variable.detail.minEstHelp
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Not applicable |
Max Value
variable.detail.estHelp
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Not applicable |
Other Value Type
variable.detail.natureOtherEstHelp
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Not applicable |
Other Value
variable.detail.otherEstHelp
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Not applicable |
Variable Variability and Sensitivity
Geomorphology class ?Comment:Optional. Rocky cliffs are less prone to erosion and inundation than bluffs, beaches or deltas. Consequently, a relative ranking of exposure scheme based on geomorphology similar to the one proposed by Hammar-Klose and Thieler (2001) has been adopted. Supplied in Appendix A is a definition of the terms used in this classification, which applies mostly to the North American continent. The Geomorphology input should be a polyline vector with segments that categorize – in an attribute field called ‘RANK’ – the shoreline geomorphology based on the scheme presented in Example Ranking Table. The model joins the geomorphology ranks to shore points by searching around each point with a radius of half the model resolution and then taking the average of all the ranks found in the search. If the user’s geomorphology data source has more categories than the ones presented in Example Ranking Table, it is left to the user’s discretion to reclassify their data to match the provided ranking system, as explained in the Data Needs section, and in Appendix B. It is recommend that the user include shore parallel hard structures (seawalls, bulkheads, etc.) in this classification and that they apply a low to moderate rank (1-3), depending on their characteristics. For example, a large, concrete seawall should be assigned a rank 1 as they are typically designed to prevent inundation during storm events and are designed to withstand damage or failure during the most powerful storms. It is recommended that low revetments or riprap walls be assigned a rank of 3 as they do not prevent inundation and may fail during extreme events. The ranking presented in the above table is only a suggestion. Users should change the ranking of different shoreline types as they see fit, based on local research and knowledge, and by following directions presented in the Data Needs section. |
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Variability Expression Given?
variable.detail.variabilityExpHelp
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Not applicable |
Variability Metric
variable.detail.variabilityMetricHelp
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None |
Variability Value
variable.detail.variabilityValueHelp
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None |
Variability Units
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None |
Resampling Used?
variable.detail.bootstrappingHelp
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Not applicable |
Variability Expression Used in Modeling?
variable.detail.variabilityUsedHelp
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Not applicable |
Variable Operational Validation (Response Variables only)
Variable ID
variable.detail.varIdHelp
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Validated?
variable.detail.resValidatedHelp
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Validation Approach (within, between, etc.)
variable.detail.validationApproachHelp
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Validation Quality (Qual/Quant)
variable.detail.validationQualityHelp
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Validation Method (Stat/Deviance)
variable.detail.validationMethodHelp
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Validation Metric
variable.detail.validationMetricHelp
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Validation Value
variable.detail.validationValHelp
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Validation Units
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Use of Measured Response Data
variable.detail.measuredResponseDataHelp
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