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The percentage of individuals identifying as a person of color were broken into 0 to 5 priority classes using a natural breaks slice classification. The break points for the moderate to high priority classes were as follows:Moderate (3) = 72% to 87 %Moderate to High (4) = 87.1% to 95%High (5) = 95.1% to 100%Block groups with less than 100 people and parks and natural areas were removed.The model is based on data collected for the EPA Environmental Justice Screening Tool. \"EPA should pay particular attention to the vulnerabilities of these populations because they have historically been exposed to a combination of physical, chemical, biological, social, and cultural factors that have imposed greater environmental burdens on them than those imposed on the general population. 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The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model identifies socially vulnerable populations based on the percent of people age 25 and older in a block group that do not have a high school diploma. Block groups with populations without a high school degree were broken into 0 to 5 priority classes using a natural breaks slice classification. The break points for the moderate to high priority classes were as follows:Moderate (3) = 18% to 25%Moderate to High (4) = 25.1% to 40%High (5) = 40.1% to 89%Block groups with less than 100 people and parks and natural areas were removed.The model is based on data collected for the EPA Environmental Justice Screening Tool. \"EPA should pay particular attention to the vulnerabilities of these populations because they have historically been exposed to a combination of physical, chemical, biological, social, and cultural factors that have imposed greater environmental burdens on them than those imposed on the general population. 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The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model identifies socially vulnerable populations based on the percent of people in a block group living in linguistically isolated households. A linguistically isolated household is a household in which all members age 14 years and over speak a language other than English and also speak English less than \"very well\" (have difficulty with English). Block groups with linguistically isolated households were broken into 0 to 5 priority classes using a natural breaks slice classification. The break points for the moderate to high priority classes were as follows:Moderate (3) = 13.5% to 25.1 %Moderate to High (4) = 25.2% to 45.6%High (5) = 45.7% to 100%Zero block groups and parks and natural areas were removed.The model is based on data collected for the EPA Environmental Justice Screening Tool. \"EPA should pay particular attention to the vulnerabilities of these populations because they have historically been exposed to a combination of physical, chemical, biological, social, and cultural factors that have imposed greater environmental burdens on them than those imposed on the general population. 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The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model identifies socially vulnerable populations based on the percent of people in a block group over the age of 64. Block groups with individuals over age 64 were broken into 0 to 5 priority classes using a natural breaks slice classification. The break points for the moderate to high priority classes were as follows:Moderate (3) = 10% to14%Moderate to High (4) = 14.1% to 20%High (5) = 20.1% to 100%Block groups with less than 100 people and parks and natural areas were removed.The model is based on data collected for the EPA Environmental Justice Screening Tool. \"EPA should pay particular attention to the vulnerabilities of these populations because they have historically been exposed to a combination of physical, chemical, biological, social, and cultural factors that have imposed greater environmental burdens on them than those imposed on the general population. 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The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). his model identifies socially vulnerable populations based on the percent of people in a block group under the age of 5. Block groups with individuals under the age of 5 were broken into 0 to 5 priority classes using a natural breaks slice classification. The break points for the moderate to high priority classes were as follows:Moderate (3) =7% to10%Moderate to High (4) = 10.1% to 21%High (5) = 21.1% to 38%Block groups with less than 100 people and parks and natural areas were removed.The model is based on data collected for the EPA Environmental Justice Screening Tool. \"EPA should pay particular attention to the vulnerabilities of these populations because they have historically been exposed to a combination of physical, chemical, biological, social, and cultural factors that have imposed greater environmental burdens on them than those imposed on the general population. (http://www.epa.gov/sites/production/files/2015-05/documents/ejscreen_technical_document_20150505.pdf)\"Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 7, "name": "Population Density", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model assigns social vulnerability based upon population density from US Census Block Group data.The input data is from Esri's 2014 Estimated Demographics and includes Population per Square Mile.Population Density is pre-calculated by Esri. Geometrical Interval Breaks are used to determine 6 classes with the top 3 being classified as High Vulnerability 6153 - 38422 (5)Moderate to High Vulnerability 1001- 6152 (4) and Moderate Vulnerability 178 - 1000(3).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 8, "name": "Households Receiving SNAP", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model assigns social vulnerability based upon areas with a high percentage of households receiving snap benefits.The input data is from American Community Survey 5 year estimates of percent households calculated using households receiving SNAP estimate and total households by block group. Geometrical Interval Breaks are used to determine 6 classes with the top 3 being classified as High Vulnerability 47% -49% (5)Moderate to High Vulnerability 49.1% - 57% (4) and Moderate Vulnerability 57.1%-96%(3).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 9, "name": "Single Parent Households", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model assigns social vulnerability based upon areas with a high percentage of single parents.The input data is from American Community Survey 5 year estimates of percent households calculated using single parent household estimates and total households by block group. Geometrical Interval Breaks are used to determine 6 classes with the top 3 being classified as High Vulnerability 34% -67% (5)Moderate to High Vulnerability 67.1% - 76% (4) and Moderate Vulnerability 76.1%-100%(3).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 10, "name": "Households Disabilities", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). Identify areas with a high percentage of population with a disabilityThe input data is from American Community Survey 5 year estimates of percent households with disabilities. Percent household was calculated using households with disabilities estimates and total households by block group. Geometrical Interval Breaks are used to determine 6 classes with the top 3 being classified as High Vulnerability 6.6% -10% (5)Moderate to High Vulnerability 1% - 6.5% (4) and Moderate Vulnerability 0.3%-1%(3).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 11, "name": "Vehicle Availability", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model assigns social vulnerability based upon areas with a high percentage of households that do not have access to a carThe input data is from American Community Survey 5 year estimates of percent of households with vehicles available .Geometrical Interval Breaks are used to determine 6 classes with the top 3 being classified as High Vulnerability <5% (5)Moderate to High Vulnerability 5.1% - 7% (4) and Moderate Vulnerability 7.1% - 10%(3).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 12, "name": "Rent Burden", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the climate equity geodatabase help explore demographic and socioeconomic data of populations that are particularly vulnerable to the impacts of climate change. (Highest priority areas are in red). This model assigns social vulnerability based on areas where a high percentage of households have monthly rent more than 30% of household income. The input data is from the New Orleans Redevelopment AuthorityManual breaks were used to determine the top 3 classesVery High Vulnerability >49.9% (5)High Vulnerability 40% - 49.9% (4) and Moderate Vulnerability 30%-39.9%(3).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 0, "name": "Social Vulnerability" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 13, "name": "Assets and Essential Services", "type": "Group Layer", "description": "", "geometryType": null, "copyrightText": "", "parentLayer": null, "subLayers": [ { "id": 14, "name": "People To Essential Services" }, { "id": 15, "name": "People to Employment Centers" }, { "id": 16, "name": "Access to Public Schools" }, { "id": 17, "name": "Access to Parks" } ], "minScale": 0, "maxScale": 0, "defaultVisibility": true, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 14, "name": "People To Essential Services", "type": "Raster Layer", "description": "Identifies potential corridor with high demand for getting people to essential services. ", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 13, "name": "Assets and Essential Services" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 15, "name": "People to Employment Centers", "type": "Raster Layer", "description": "A primary goal in the Resilient New Orleans Strategic Vision Plan is transform city systems to better connect people employment and essential services. This model identifies key corridors that connect people to employment. Using Network Analyst Closest Facility tool we identified the most direct routes with potential for active transportation demand from center of block groups to anchor institutions (businesses with greater than 1000 employees), 2) from center of block groups to employment centers (areas with high density of large businesses of greater than 50 employees and less than 1000). All routes were buffered by 200ft to identify general corridors and assigned moderate priority (3) and routes overlapping areas with dense population were assigned additional priority high (4) and very high (5) using natural breaks classification.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 13, "name": "Assets and Essential Services" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 16, "name": "Access to Public Schools", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the connect geodatabasehelp explore priority areas of the city for connecting and expanding walk-bike corridors. (Highest priority areas are in red). CT04 identifies areas within a 10-minute walk of a public school as well as closest routes from pubic transportation to middle and high schools.A primary goal in the Resilient New Orleans Strategic Vision Plan is to provide transportation options that improve getting students to schools. This model identifies key corridors that connect middle and high school students from nearest bus stops as well as areas within 10 minute walk of existing schools. Using Network Analyst Closest facility tool, we identified the 5 most direct routes from existing middle and high schools to the nearest bus stops. All routes were buffered by 200ft to identify general corridors students might use to get from public transit to their school and assigned very high priority (5). A ten minute walk from every school was then derived to identify opportunities for transportation improvement for younger students walking and biking to school and assigned high priority value (4).", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 13, "name": "Assets and Essential Services" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 17, "name": "Access to Parks", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the connect geodatabasehelp explore priority areas of the city for connecting and expanding walk-bike corridors. (Highest priority areas are in red). CT05 identifies areas within the city that are more than a 10-minute walk from a park.Connecting neighborhood residents to parks and open space for walking, jogging, and bicycling is a key goal for promoting active and healthy lifestyles . The Trust for Public Land's ParkScore® index is based on the percentage of the population living within a ten-minute (half-mile) walk of a public park. The half-mile is defined as entirely within the public road network and uninterrupted by physical barriers such as highways, train tracks, rivers, and fences. TPL's mapping technology identifies which neighborhoods and demographics are underserved by parks and how many people are able to reach a park within a ten-minute walk. org. Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 13, "name": "Assets and Essential Services" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 18, "name": "Transportation", "type": "Group Layer", "description": "", "geometryType": null, "copyrightText": "", "parentLayer": null, "subLayers": [ { "id": 19, "name": "Pedestrian Safety" }, { "id": 20, "name": "Bicycle Safety" }, { "id": 21, "name": "Gaps In Existing Bike Network" }, { "id": 22, "name": "Gaps In Public Transportation" }, { "id": 23, "name": "Tourists To Tourist Destinations" } ], "minScale": 0, "maxScale": 0, "defaultVisibility": true, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 19, "name": "Pedestrian Safety", "type": "Raster Layer", "description": "Improving pedestrian and bicycle safety is key objective of New Orleans complete street policy. In a recent report (Dangerous by Design), Louisiana ranked as the 3rd most dangerous state for pedestrian safety and New Orleans was the 38th worst metropolitan area for bicycle and pedestrian safety. This model identifies areas where risk of collision is highest based on past collision locations. Hot spots of pedestrian collisions within the neighborhood of 1/8 mile from 2010 to 2015 were derived using a kernel density where added value was given to accidents that resulted in fatalities and serious injury. Priority value assigned using a natural breaks classification. ", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 18, "name": "Transportation" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 20, "name": "Bicycle Safety", "type": "Raster Layer", "description": "Improving pedestrian and bicycle safety is key objective of New Orleans complete street policy. In a recent report (Dangerous by Design), Louisiana ranked as the 3rd most dangerous state for pedestrian safety and New Orleans was the 38th worst metropolitan area for bicycle and pedestrian safety. This model identifies areas where risk of collision is highest based on past collision locations. Hot spots of bicycle collisions within the neighborhood of 1/8 mile from 2010 to 2015 were derived using a kernel density where added value was given to accidents that resulted in fatalities and serious injury. Priority value assigned using a natural breaks classification. ", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 18, "name": "Transportation" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 21, "name": "Gaps In Existing Bike Network", "type": "Raster Layer", "description": "Using Network Analyst Closest facility tool, we identified the most direct routes that would connect gaps in the existing bike network. This model was re-run using scaled cost for routes that did not provide access to employment centers. All routes were buffered by 200ft to identify general corridors and assigned moderate priority (3). Corridors with more overlap were assigned additional priority high (4) and very high (5) using natural breaks classification.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 18, "name": "Transportation" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 22, "name": "Gaps In Public Transportation", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the connect geodatabasehelp explore priority areas of the city for connecting and expanding walk-bike corridors. (Highest priority areas are in red). CT07 idenitifies areas in the city that are more than 10-minute walk from public transportation as well as those areas with significant number of people that lack access to frequent public transit.Access to reliable and affordable public transportation is essential to enhancing quality of life as well as reducing green house emissions for a city's population. This model prioritizes areas where city residents are more than a 10 minute walk from available public transportation as well as areas where there is a need for additional public transportation. Areas more than a 10 minute walk from public transportation stop were assigned a very high priority value (5). Areas within a 10 minute walk of public transit where the max wait time is more than 60 minutues and that have a significant number of people was assigned high priority value of (4). Areas within a 10 minute walk of public transit where the max wait time is more than 30 minutues and that have a significant number of people was assigned moderate priority value of (3).Service Areas were derived using network analyst. Areas of significant population were determined using ESRI's 2014 Estimated Demographics and u=includes Population per square mile. Significant population was condisered population >= 6153. Frequency of transit was derived using the Better Bus Buffer tools developed by ESRI (https://github.com/Esri/public-transit-tools/tree/master/better-bus-buffers).Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 18, "name": "Transportation" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 23, "name": "Tourists To Tourist Destinations", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the connect geodatabasehelp explore priority areas of the city for connecting and expanding walk-bike corridors. (Highest priority areas are in red). CT03 identifies corridors with potential demand for connecting tourists to key tourist destinations.New Orleans has a thriving tourist industry and ensuring safe walkable/bikeable paths to major tourist destinations is a key component of Resilient New Orleans Plan. This model identifies key corridors that connect people key cultural facilities used by tourists . Using Network Analyst Closest facility tool, we identified the most direct routes with potential for active transportation demand from hotels to key cultural facilities. Additional routes where major arterials entered into and traversed key historic districts. All routes were buffered by 200ft to identify general corridors and assigned moderate priority (3). Corridors with more overlap were assigned additional priority high (4) and very high (5) using natural breaks classification.Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 18, "name": "Transportation" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 24, "name": "Density of Critical Infrastructure", "type": "Group Layer", "description": "", "geometryType": null, "copyrightText": "", "parentLayer": null, "subLayers": [ { "id": 25, "name": "Density Essential Services Facilities" }, { "id": 26, "name": "Denisty of Other Essential Services" }, { "id": 27, "name": "Density Dependent of Population Facilities" }, { "id": 28, "name": "Density High Potential Loss Facilities" }, { "id": 29, "name": "Density Cultural Institution Facilities" }, { "id": 30, "name": "Density Sewer and Water Infrastructure" }, { "id": 31, "name": "Density Transporation Infrastructure" } ], "minScale": 0, "maxScale": 0, "defaultVisibility": true, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 25, "name": "Density Essential Services Facilities", "type": "Raster Layer", "description": "This model assigns critical infrastructure risk based upon density of locations of essential service facilities. Essential Services facilities include evacuation pick-up points shelters, police stations, fire stations, EMS stations, and hospitals. Kernel Density of essential service facilities was derived using 1/4 mile (equivalent to 5 minute walk) circular radius. The resulting density raster was broken into priority classes using slice tool and a natural breaks classification using scale of 0 to 5.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 24, "name": "Density of Critical Infrastructure" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 26, "name": "Denisty of Other Essential Services", "type": "Raster Layer", "description": "This model assigns critical infrastructure risk based upon density of locations of other emergency facilities. Other emergency facilities include community centers and other medical facilitiesKernel Density of high potential loss facilities was derived using 1/4 mile (equivalent to 5 minute walk) circular radius. 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Dependent Population facilities include long-term care facilities, nursing homes, daycare facilities, and prisons.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 24, "name": "Density of Critical Infrastructure" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 28, "name": "Density High Potential Loss Facilities", "type": "Raster Layer", "description": "This model assigns critical infrastructure risk based upon density of locations of high potential loss facilities. High potential loss facilities include flood gates, hydraulic section points, locks, pump stations, other structures, water treatment plant, and sewer treatment plant.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 24, "name": "Density of Critical Infrastructure" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 29, "name": "Density Cultural Institution Facilities", "type": "Raster Layer", "description": "This model assigns critical infrastructure risk based upon density of locations of institutional facilities. Institutional facilities include colleges, universities, historic facilities, and museums.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 24, "name": "Density of Critical Infrastructure" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 30, "name": "Density Sewer and Water Infrastructure", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the absorb geodatabase help identify features of the landscape are that particularly vulnerable to the impacts of climate change. (Highest priority areas are in red).This model assigns critical infrastructure risk based upon density of locations of utility and communication facilities. Utility and communication facilities include pump stations It does not include power substations. The point locations were unavailable due to security concerns.Kernel Density of utility and communication facilities was derived using 1/4 mile (equivalent to 5 minute walk) circular radius. The resulting density raster was broken into priority classes using slice tool and a natural breaks classification using scale of 0 to 5.Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 24, "name": "Density of Critical Infrastructure" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } }, { "currentVersion": 10.4, "id": 31, "name": "Density Transporation Infrastructure", "type": "Raster Layer", "description": "The Trust for Public Land\u2019s Climate-Smart Cities Program is founded on the principle that to respond to climate change, cities must restore natural functions of the land by weaving green elements into the built environment. The Climate Smart Cities Program helps cities meet the challenges through the development of spatial data and decision support tools that translate the goals from a city\u2019s strategic climate planning into priority sites for green infrastructure development. The Climate Smart Cities Program categorizes these strategies under the climate objectives of Connect, Cool, Absorb, and Protect. The rasters in the absorb geodatabase help identify features of the landscape are that particularly vulnerable to the impacts of climate change. (Highest priority areas are in red).This model assigns critical infrastructure risk based upon density of locations of key transportation infrastructure. Key transportation infrastructure includes evacuation routes, ports, and bridges, Kernel Density of key transportation infrastructure including ports and the entrance and exits of bridges was derived using 1/4 mile (equivalent to 5 minute walk) circular radius. The resulting density raster was broken into priority classes using slice tool and a natural breaks classification using scale of 0 to 5. A Kernel Density of evacuation routes was derived using 1/8 mile search radius. The resulting line density raster was broken into priority classes using slice tool and a natural breaks classification using scale of 0 to 5. The point and line priority rasters were combined using equal weights.Data interpretation:5 = Very High Priority for Green Infrastructure4 = High Priority for Green Infrastructure 3 = Medium Priority for Green Infrastructure 0-2 = Low ValueValues 3, 4, and 5 should be used when assessing highest prioritization from the model.", "geometryType": null, "copyrightText": "The Trust for Public Land, 2017", "parentLayer": { "id": 24, "name": "Density of Critical Infrastructure" }, "subLayers": [], "minScale": 0, "maxScale": 0, "defaultVisibility": false, "extent": { "xmin": 3658766.209989965, "ymin": 499081.44552256167, "xmax": 3820622.209989965, "ymax": 620557.4455225617, "spatialReference": { "wkid": 102682, "latestWkid": 3452 } }, "hasAttachments": false, "htmlPopupType": "esriServerHTMLPopupTypeNone", "displayField": "", "typeIdField": null, "fields": null, "indexes": [], "relationships": [], "canModifyLayer": false, "canScaleSymbols": false, "hasLabels": false, "capabilities": "Map,Query", "supportsStatistics": false, "supportsAdvancedQueries": false, "supportedQueryFormats": "JSON, AMF, geoJSON", "ownershipBasedAccessControlForFeatures": {"allowOthersToQuery": true}, "useStandardizedQueries": true, "advancedQueryCapabilities": { "useStandardizedQueries": true, "supportsStatistics": false, "supportsOrderBy": false, "supportsDistinct": false, "supportsPagination": false, "supportsTrueCurve": false, "supportsReturningQueryExtent": true, "supportsQueryWithDistance": true } } ], "tables": [] }