This street centerline lines feature class represents current right of way in the City of Los Angeles. It shows the official street names and is related to the official street name data. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way. The right of way information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works. Street Centerline layer was created in geographical information systems (GIS) software to display Dedicated street centerlines. The street centerline layer is a feature class in the LACityCenterlineData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. City of LA District Offices use Street Centerline layer to determine dedication and street improvement requirements. Engineering street standards are followed to dedicate the street for development. The Bureau of Street Services tracks the location of existing streets, who need to maintain that road. Additional information was added to Street Centerline layer. Address range attributes were added make layer useful for geocoding. Section ID values from Bureau of Street Services were added to make layer useful for pavement management. Department of City Planning added street designation attributes taken from Community Plan maps. The street centerline relates to the Official Street Name table named EASIS, Engineering Automated Street Inventory System, which contains data describing the limits of the street segment. A street centerline segment should only be added to the Street Centerline layer if documentation exists, such as a Deed or a Plan approved by the City Council. Paper streets are street lines shown on a recorded plan but have not yet come into existence on the ground. These street centerline segments are in the Street Centerline layer because there is documentation such as a Deed or a Plan for the construction of that street. Previously, some street line features were added although documentation did not exist. Currently, a Deed, Tract, or a Plan must exist in order to add street line features. Many street line features were edited by viewing the Thomas Bros Map's Transportation layer, TRNL_037 coverage, back when the street centerline coverage was created. When TBM and BOE street centerline layers were compared visually, TBM's layer contained many valid streets that BOE layer did not contain. In addition to TBM streets, Planning Department requested adding street line segments they use for reference. Further, the street centerline layer features are split where the lines intersect. The intersection point is created and maintained in the Intersection layer. The intersection attributes are used in the Intersection search function on NavigateLA on BOE's web mapping application NavigateLA. The City of Los Angeles Municipal code states, all public right-of-ways (roads, alleys, etc) are streets, thus all of them have intersections. Note that there are named alleys in the BOE Street Centerline layer. Since the line features for named alleys are stored in the Street Centerline layer, there are no line features for named alleys in those areas that are geographically coincident in the Alley layer. For a named alley , the corresponding record contains the street designation field value of ST_DESIG = 20, and there is a name stored in the STNAME and STSFX fields.List of Fields:SHAPE: Feature geometry.OBJECTID: Internal feature number.STNAME_A: Street name Alias.ST_SUBTYPE: Street subtype.SV_STATUS: Status of street in service, whether the street is an accessible roadway. Values: • Y - Yes • N - NoTDIR: Street direction. Values: • S - South • N - North • E - East • W - WestADLF: From address range, left side.ZIP_R: Zip code right.ADRT: To address range, right side.INT_ID_TO: Street intersection identification number at the line segment's end node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.SECT_ID: Section ID used by the Bureau of Street Services. Values: • none - No Section ID value • private - Private street • closed - Street is closed from service • temp - Temporary • propose - Proposed construction of a street • walk - Street line is a walk or walkway • known as - • numeric value - A 7 digit numeric value for street resurfacing • outside - Street line segment is outside the City of Los Angeles boundary • pierce - Street segment type • alley - Named alleySTSFX_A: Street suffix Alias.SFXDIR: Street direction suffix Values: • N - North • E - East • W - West • S - SouthCRTN_DT: Creation date of the polygon feature.STNAME: Street name.ZIP_L: Zip code left.STSFX: Street suffix. Values: • BLVD - BoulevardADLT: To address range, left side.ID: Unique line segment identifierMAPSHEET: The alpha-numeric mapsheet number, which refers to a valid B-map or A-map number on the Cadastral tract index map. Values: • B, A, -5A - Any of these alpha-numeric combinations are used, whereas the underlined spaces are the numbers.STNUM: Street identification number. This field relates to the Official Street Name table named EASIS, to the corresponding STR_ID field.ASSETID: User-defined feature autonumber.TEMP: This attribute is no longer used. This attribute was used to enter 'R' for reference arc line segments that were added to the spatial data, in coverage format. Reference lines were temporary and not part of the final data layer. After editing the permanent line segments, the user would delete temporary lines given by this attribute.LST_MODF_DT: Last modification date of the polygon feature.REMARKS: This attribute is a combination of remarks about the street centerline. Values include a general remark, the Council File number, which refers the street status, or whether a private street is a private driveway. The Council File number can be researched on the City Clerk's website http://cityclerk.lacity.org/lacityclerkconnect/INT_ID_FROM: Street intersection identification number at the line segment's start node. The value relates to the intersection layer attribute table, to the CL_NODE_ID field. The values are assigned automatically and consecutively by the ArcGIS software first to the street centerline data layer and then the intersections data layer, during the creation of new intersection points. Each intersection identification number is a unique value.ADRF: From address range, right side.

GIS-datasets for the Street networks of Stockholm, Gothenburg and Eskilstuna produced as part of the Spatial Morphology Lab (SMoL). The goal of the SMoL project is to develop a strong theory and methodology for urban planning & design research with an analytical approach. Three frequently recurring variables of spatial urban form are studied that together quite well capture and describe the central characteristics and qualities of the built environment: density, diversity and proximity. The first measure describes how intensive a place can be used depending on how much built up area is found there. The second measure captures how differentiated the use of a place can be depending on the division in smaller units such as plots. The third measure describes how accessible a place is depending on how it relates with other places. Empirical studies have shown strong links between these metrics and people's use of cities such as pedestrian movement patterns. To support this goal, a central objective of the project is the establishment of an international platform of GIS data models for comparative studies in spatial urban form comprising three European capitals: London in the UK, Amsterdam in the Netherlands and Stockholm in Sweden, as well as two additional Swedish cities of smaller size than Stockholm: Gothenburg and Eskilstuna. The result of the project is a GIS database for the five cities covering the three basic layers of urban form: street network (motorised and non-motorised), buildings and plots systems. The data is shared via SND to create a research infrastructure that is open to new study initiatives. The datasets for Amsterdam will also be uploaded to SND. The datasets of London cannot be uploaded because of licensing restrictions. The street network GIS-maps include motorised and non-motorised networks. The non-motorized networks include all streets and paths that are accessible for people walking or cycling, including those that are shared with vehicles. All streets where walking or cycling is forbidden, such as motorways, highways, or high-speed tunnels, are not included in the network. The non-motorised network layers for Stockholm and Eskilstuna are based on the Swedish national road database, NVDB (Nationell Vägdatabas), downloaded from Trafikverket (https://lastkajen.trafikverket.se, date of download 15-5-2016, last update 8-11-2015) . For Gothenburg, it is based on Open Street Maps (openstreetmap.org, http://download.geofabrik.de, date of download 29-4-2016), because the NVDB did not provide enough detail for the non-motorized network, as in the other cities. The original road-centre-line maps of all cities were edited based on the same basic representational principles and were converted into line-segment maps, using the following software: FME, Mapinfo professional and PST (Place Syntax Tool). The coordinate system is SWEREF99TM. In the final line-segment maps (GIS-layers) all streets or paths are represented with one line irrespectively of the number of lanes or type, meaning that parallel lines representing a street and a pedestrian or a cycle path running on the side, are reduced to one line. The reason is that these parallel lines are nor physically or perceptually separated, and thus are accessible and recognized from pedestrians as one “line of movement” in the street network. If there are obstacles or great distance between parallel streets and paths, then the multiple lines remain. The aim is to make a skeletal network that better represents the total space, which is accessible for pedestrians to move, irrespectively of the typical separations or distinctions of streets and paths. This representational choice follows the Space Syntax methodology in representing the public space and the street network. We followed the same editing and generalizing procedure for all maps aiming to remove errors and to increase comparability between networks. This process included removing duplicate and isolated lines, snapping and generalizing. The snapping threshold used was 2m (end points closer than 2m were snapped together). The generalizing threshold used was 1m (successive line segments with angular deviation less than 1m were merged into one). In the final editing step, all road polylines were segmented to their constituting line-segments. The aim was to create appropriate line-segment maps to be analysed using Angular Segment Analysis, a network centrality analysis method introduced in Space Syntax. All network layers are complemented with an “Unlink points” layer; a GIS point layer with the locations of all non-level intersections, such as pedestrian bridges and tunnels. The Unlink point layer is necessary to conduct network analysis that takes into account the non-planarity of the street network, using such software as PST (Place Syntax Tool). For more detailed documentation on the creation of the non-motorised network of Gothenburg, please download the specific documentati...

The friction (cost allocation/effort) surface was assembled using three primary input datasets on land surface characteristics that help or hinder travel speeds: land cover, roads and topography. Landcover data were from the ESA CCI Landcover map for Africa 2016, roads data were merged from Open-Street Map (OSM) and the MapwithAi project and topography was taken from the SRTM Digital Elevation Model. The costs for travel consider walking/pedestrian travel in this data, but the software is supplied with an easy to change set of travel speeds so they can be adapted easily to consider travel speeds reflecting motorised transportation use. We have reduced the walking speeds to reflect the fact that adults walking with children move approximately 22% slower. There are two friction surfaces provided, the first defines open water as a barrier to travel and so the speed allocated to this landcover is NA. The second defines open water with an associated speed (1 km/hr). To create a walking speed array, first the road walking speeds were used and then missing values were filled with landcover walking speed values. This walking speed array was multiplied by the slope impact grid. The speed for each cell was converted from kilometers per hour to meters per second. Finally, the time (in seconds) to walk across each cell was calculated. The outputs are 20-m spatial resolution geotiffs indicating the time to walk across each cell. They are subsequently used in the least cost path analysis to estimate travel time to the nearest health facilities. However,these friction surfaces can be used by others to estimate travel speed to other destinations in a GIS.

This dataset is relative to the paper entitled: "First Three-dimensional Quantification of Planktic Food Chain lower levels (Copepods) for the Ross Sea region Marine Protected Area (RSRMPA), Antarctica: Using FAIR-inspired legacy data with Machine Learning, and Open Source GIS" publishing in journal Diversity (MPDI).

Abstract:

Zooplankton is a fundamental group in all aquatic ecosystems located the base of the food chain. It forms a link between the lower trophic levels with secondary consumers and shows marked fluctuations of populations with environmental change, especially reacting to heating and water acidification. At sea copepod crustaceans account for app. 70% in abundance of zooplankton and are a target of monitoring activities in key areas such as the Southern Ocean. In this study we have used FAIR-inspired legacy data (dating back to the ‘80s) collected in the Ross Sea by the Italian National Antarctic Program in GBIF.org. Together with other open-access GIS data sources and tools it allows generating, for the first time, three-dimensional predictive distribution maps for twenty-six copepod species. These predictive maps were obtained by applying machine learning techniques to grey literature data, which were visualized in open-source GIS platforms. In a Species Distribution Modeling (SDM) framework we used machine learning with three types of algorithms (TreeNet, RandomForest and Ensemble) to analyze the presence and absence of copepods at different areas and depth classes in function of environmental descriptors obtained from the Polar Macroscope Layers present in Quantartica. The models allow for the first time to map-predict the food chain in quantitative terms showing the relative index of occurrence (RIO) and identified the presence for each copepod species analyzed in the Ross Sea. Our results show marked geographical preferences that vary with species and trophic strategy. This study demonstrates that machine learning is a successful method in accurately predicting Antarctic copepod presence, also providing useful data to orient future sampling and management of wildlife and conservation.

Contents: This is an ArcGIS Pro zip file that you can download and use for creating map books based on United States National Grid (USNG). It contains a geodatabase, layouts, and tasks designed to teach you how to create a basic map book.Version 1.0.0 Uploaded on May 24th and created with ArcGIS Pro 2.1.3 - Please see the README below before getting started!Updated to 1.1.0 on August 20thUpdated to 1.2.0 on September 7thUpdated to 2.0.0 on October 12thUpdate to 2.1.0 on December 29thBack to 1.2.0 due to breaking changes in the templateBack to 1.0.0 due to breaking changes in the template as of June 11th 2019Updated to 2.1.1 on October 8th 2019Audience: GIS Professionals and new users of ArcGIS Pro who support Public Safety agencies with map books. If you are looking for apps that can be used by any public safety professional, see the USNG Lookup Viewer.Purpose: To teach you how to make a map book with critical infrastructure and a basemap, based on USNG. You NEED to follow the steps in the task and not try to take shortcuts the first time you use this task in order to receive the full benefits. Background: This ArcGIS Pro template is meant to be a starting point for your map book projects and is based on best practices by the USNG National Implementation Center (TUNIC) at Delta State University and is hosted by the NAPSG Foundation. This does not replace previous templates created in ArcMap, but is a new experimental approach to making map books. We will continue to refine this template and work with other organizations to make improvements over time. So please send us your feedback admin@publicsafetygis.org and comments below. Instructions: Download the zip file by clicking on the thumbnail or the Download button.Unzip the file to an appropriate location on your computer (C:\Users\YourUsername\Documents\ArcGIS\Projects is a common location for ArcGIS Pro Projects).Open the USNG Map book Project File (APRX).If the Task is not already open by default, navigate to Catalog > Tasks > and open 'Create a US National Grid Map Book' Follow the instructions! This task will have some automated processes and models that run in the background but you should pay close attention to the instructions so you also learn all of the steps. This will allow you to innovate and customize the template for your own use.FAQsWhat is US National Grid? The US National Grid (USNG) is a point and area reference system that provides for actionable location information in a uniform format. Its use helps achieve consistent situational awareness across all levels of government, disciplines, and threats & hazards – regardless of your role in an incident.One of the key resources NAPSG makes available to support emergency responders is a basic USNG situational awareness application. See the NAPSG Foundation and USNG Center websites for more information.What is an ArcGIS Pro Task? A task is a set of preconfigured steps that guide you and others through a workflow or business process. A task can be used to implement a best-practice workflow, improve the efficiency of a workflow, or create a series of interactive tutorial steps. See "What is a Task?" for more information.Do I need to be proficient in ArcGIS Pro to use this template? We feel that this is a good starting point if you have already taken the ArcGIS Pro QuickStart Tutorials. While the task will automate many steps, you will want to get comfortable with the map layouts and other new features in ArcGIS Pro.Is this template free? This resources is provided at no-cost, but also with no guarantees of quality assurance or support at this time. Can't I just use ArcMap? Ok - here you go. USNG 1:24K Map Template for ArcMapKnown Limitations and BugsZoom To: It appears there may be a bug or limitation with automatically zooming the map to the proper extent, so get comfortable with navigation or zoom to feature via the attribute table.FGDC Compliance: We are seeking feedback from experts in the field to make sure that this meets minimum requirements. At this point in time we do not claim to have any official endorsement of standardization. File Size: Highly detailed basemaps can really add up and contribute to your overall file size, especially over a large area / many pages. Consider making a simple "Basemap" of street centerlines and building footprints.We will do the best we can to address limitations and are very open to feedback!

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. userdata and unzip the LayerFiles.zip folder.Data from the four SSURGO tables were assembled into the single table included in each map package. Data from the component table were aggregated using a dominant component model (listed below under Component Table - Dominant Component) or a weighted average model (listed below under Component Table - Weighted Average) using custom Python scripts. The the Mapunit table - the MUAGATTAT table and the processed Component table data were joined to the Mapunit Feature Class. Field aliases were added and indexes calculated. A field named Map Symbol was created and populated with random integers from 1-10 for symbolizing the soil units in the map package.For documentation of the SSURGO dataset see:http://soildatamart.nrcs.usda.gov/SSURGOMetadata.aspxFor documentation of the Watershed Boundary Dataset see: http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/water/watersheds/datasetThe map packages contain the following attributes in the Map Units layer:Mapunit Feature Class:Survey AreaSpatial VersionMapunit SymbolMapunit KeyNational Mapunit SymbolMapunit Table:Mapunit NameMapunit KindFarmland ClassHighly Erodible Lands Classification - Wind and WaterHighly Erodible Lands Classification - WaterHighly Erodible Lands Classification - WindInterpretive FocusIntensity of MappingLegend KeyMapunit SequenceIowa Corn Suitability RatingLegend Table:Project ScaleTabular VersionMUAGGATT Table:Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - PresenceRating for Manure and Food Processing Waste - Weighted AverageComponent Table - Weighted Average:Mean Annual Air Temperature - High Value Mean Annual Air Temperature - Low Value Mean Annual Air Temperature - Representative Value Albedo - High Value Albedo - Low Value Albedo - Representative Value Slope - High Value Slope - Low Value Slope - Representative Value Slope Length - High Value Slope Length - Low Value Slope Length - Representative Value Elevation - High Value Elevation - Low Value Elevation - Representative Value Mean Annual Precipitation - High Value Mean Annual Precipitation - Low Value Mean Annual Precipitation - Representative Value Days between Last and First Frost - High Value Days between Last and First Frost - Low Value Days between Last and First Frost - Representative Value Crop Production Index Range Forage Annual Potential Production - High Value Range Forage Annual Potential Production - Low Value Range Forage Annual Potential Production - Representative Value Initial Subsidence - High Value Initial Subsidence - Low Value Initial Subsidence - Representative Value Total Subsidence - High ValueTotal Subsidence - Low Value Total Subsidence - Representative Value Component Table - Dominant Component:Component KeyComponent Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoffSoil Loss Tolerance FactorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupForage Suitability GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic Class NameOrderSuborderGreat GroupSubgroupParticle SizeParticle Size ModifierCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoisture SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilThe U.S. Department of Agriculture - Natural Resources Conservation Service - should be acknowledged as the data source in products derived from these data. This data set is not designed for use as a primary regulatory tool in permitting or citing decisions - but may be used as a reference source. This is public information and may be interpreted by organizations - agencies - units of government - or others based on needs; however - they are responsible for the appropriate application. Federal - State - or local regulatory bodies are not to reassign to the Natural Resources Conservation Service any authority for the decisions that they make. The Natural Resources Conservation Service will not perform any evaluations of these maps for purposes related solely to State or local regulatory programs. Photographic or digital enlargement of these maps to scales greater than at which they were originally mapped can cause misinterpretation of the data. If enlarged - maps do not show the small areas of contrasting soils that could have been shown at a larger scale. The depicted soil boundaries - interpretations - and analysis derived from them do not eliminate the need for onsite sampling - testing - and detailed study of specific sites for intensive uses. Thus - these data and their interpretations are intended for planning purposes only. Digital data files are periodically updated. Files are dated - and users are responsible for obtaining the latest version of the data.The 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). Last Updated: Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/Geoscientific/MD_SSURGOSoils/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.

This pipe feature class represents current wastewater information of the mainline sewer in the City of Los Angeles. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most rigorous geographic information of the storm drain system using a geometric network model, to ensure that its storm drains reflect current ground conditions. The conduits and inlets represent the storm drain infrastructure in the City of Los Angeles. Storm drain information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Associated information about the wastewater Pipe is entered into attributes. Principal attributes include:PIPE_SUBTYPE: pipe subtype is the principal field that describes various types of lines as either Airline, Force Main, Gravity, Siphon, or Special Lateral.For a complete list of attribute values, please refer to (TBA Wastewater data dictionary). Wastewater pipe lines layer was created in geographical information systems (GIS) software to display the location of sewer pipes. The pipe lines layer is a feature class in the LACityWastewaterData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. The lines are entered manually based on wastewater sewer maps and BOE standard plans, and information about the lines is entered into attributes. The pipe lines are the main sewers constructed within the public right-of-way in the City of Los Angeles. The ends of line segments, of the pipe lines data, are coincident with the wastewater connectivity nodes, cleanout nodes, non-structures, and physical structures points data. Refer to those layers for more information. The wastewater pipe lines are inherited from a sewer spatial database originally created by the City's Wastewater program. The database was known as SIMMS, Sewer Inventory and Maintenance Management System. For the historical information of the wastewater pipe lines layer, refer to the metadata nested under the sections Data Quality Information, Lineage, Process Step section. Pipe information should only be added to the Wastewater Pipes layer if documentation exists, such as a wastewater map approved by the City Engineer. Sewers plans and specifications proposed under private development are reviewed and approved by Bureau of Engineering. The Department of Public Works, Bureau of Engineering's, Brown Book (current as of 2010) outlines standard specifications for public works construction. For more information on sewer materials and structures, look at the Bureau of Engineering Manual, Part F, Sewer Design, F 400 Sewer Materials and Structures section, and a copy can be viewed at http://eng.lacity.org/techdocs/sewer-ma/f400.pdf.List of Fields:STREET: This is the street name and street suffix on which the pipe is located.PIPE_LABEL: This attribute identifies the arc segment between two nodes, which represents the pipe segment. There could be any number of pipes between the same two maintenance holes and at least one. If there is more than one pipe between the same two maintenance holes, then a value other than 'A' is assigned to each pipe, such as the value 'B', 'C', and so on consecutively. Also, when a new pipe is constructed, some old pipes are not removed from the ground and the new pipe is added around the existing pipe. In this case, if the original pipe was assigned an 'A', the new pipe is assigned a 'B'.C_UP_INV: This is the calculated pipe upstream invert elevation value.PIPE_MAT: The value signifies the various materials that define LA City's sewer system. Values: • TCP - Terra Cotta pipe. • CMP - Corrugated metal pipe. • RCP - Reinforced concrete pipe. Used for sewers larger than 42inch, with exceptions. • PCT - Polymer concrete pipe. • CON - Concrete or cement. • DIP - Ductile iron pipe. • ABS - Acrylonitrile butadiene styrene. • STL - Steel. • UNK - Unknown. • ACP - Asbestos cement pipe. • RCL - Reinforced concrete pipe lined. • OTH - Other or unknown. • VCP - Vitrified clay pipe. • TRS - Truss pipe. • CIP - Cast iron pipe. • PVC - Polyvinyl chloride. • BRK - Brick. • RCPL - Lined Reinforced concrete pipe. Used for sewers larger than 42inch, with exceptions. • B/C - Concrete brick pipe. • FRP - Centrifugally cast fiberglass reinforced plastic mortar pipe.DN_INV: This is the downstream invert elevation value.PIPE_WIDTH: This value is the pipe dimension for shapes other than round.C_SLOPE: This is the calculated slope.ENABLED: Internal feature number.DN_STRUCT: This attribute identifies a number at one of two end points of the line segment that represents a sewer pipe. A sewer pipe line has a value for the UP_STRUCT and DN_STRUCT fields. This point is the downstream structure that may be a maintenance hole, pump station, junction, etc. Each of these structures is assigned an identifying number that corresponds to a Sewer Wye data record. The 8 digit value is based on an S-Map index map using a standardized numbering scheme. The S-Map is divided into 16 grids, each numbered sequentially from west to east and north to south. The first three digits represent the S-Map number, the following two digits represent the grid number, and the last three digits represent the structure number within the grid. This field also relates to the (name of table or layer) node attribute table.PIPE_SIZE: This value is the inside pipe diameter in inches.MON_INST: This is the month of the pipe installation.PIPE_ID: The value is a combination of the values in the UP_STRUCT, DN_STRUCT, and PIPE_LABEL fields. This is the 17 digit identifier of each pipe segment and is a key attribute of the pipe line data layer. This field named PIPE_ID relates to the field in the Annotation Pipe feature class and to the field in the Wye line feature class data layers.REMARKS: This attribute contains additional comments regarding the pipe line segment.DN_STA_PLS: This is the tens value of the downstream stationing.EASEMENT: This value denotes whether or not the pipe is within an easement.DN_STA_100: This is the hundreds value of the downstream stationing.PIPE_SHAPE: The value signifies the shape of the pipe cross section. Values: • SE - Semi-Elliptical. • O1 - Semi-Elliptical. • UNK - Unknown. • BM - Burns and McDonald. • S2 - Semi-Elliptical. • EL - Elliptical. • O2 - Semi-Elliptical. • CIR - Circular. • Box - Box (Rectangular).PIPE_STATUS: This attribute contains the pipe status. Values: • U - Unknown. • P - Proposed. • T - Abandoned. • F - As Built. • S - Siphon. • L - Lateral. • A - As Bid. • N - Non-City. • R - Airline.ENG_DIST: LA City Engineering District. The boundaries are displayed in the Engineering Districts index map. Values: • O - Out LA. • V - Valley Engineering District. • W - West LA Engineering District. • H - Harbor Engineering District. • C - Central Engineering District.C_PIPE_LEN: This is the calculated pipe length.OWNER: This value is the agency or municipality that constructed the pipe. Values: • PVT - Private. • CTY - City of LA. • FED - Federal Facilities. • COSA - LA County Sanitation. • OUTLA - Adjoining cities.CRTN_DT: Creation date of the line feature.TRTMNT_LOC: This value is the treatment plant used to treat the pipe wastewater.PCT_ENTRY2: This is the flag determining if the second slope value, in SLOPE2 field, was entered in percent as opposed to a decimal. Values: • Y - The value is expressed as a percent. • N - The value is not expressed as a percent.UP_STA_100: This is the hundreds value of the upstream stationing.DN_MH: The value is the ID of the structure. This point is the structure that may be a maintenance hole, pump station, junction, etc. The field name DN_MH signifies the structure is the point at the downstream end of the pipe line segment. The field DN_MH is a key attribute to relate the pipe lines feature class to the STRUCTURE_ID field in the physical structures feature class.SAN_PIPE_IDUSER_ID: The name of the user carrying out the edits of the pipe data.WYE_MAT: This is the pipe material as shown on the wye card.WYE_DIAM: This is the pipe diameter as shown on the wye card.SLOPE2: This is the second slope value used for pipe segments with a vertical curve.EST_YR_LEV: This value is the year installed level.EST_MATL: This is the flag determining if the pipe material was estimated.LINER_DATE: This value is the year that the pipe was re-lined.LAST_UPDATE: Date of last update of the line feature.SHAPE: Feature geometry.EST_YEAR: This is the flag indicating if the year if installation was estimated.EST_UPINV: This is the flag determining if the pipe upstream elevation value was estimated.WYE_UPDATE: This value indicates whether the wye card was updated.PCT_ENTRY: This is the flag determining if the slope was entered in percent as opposed to a decimal. Values: • N - The value is not expressed as a percent. • Y - The value is expressed as a percent.PROF: This is the profile drawing number.PLAN1: This is the improvement plan drawing number.PLAN2: This is the supplementary improvement plan drawing number.EST_DNINV: This is the flag determining if the pipe downstream elevation value was estimated.UP_STRUCT: This attribute identifies a number at one of two end points of the line segment that represents a sewer pipe. A sewer pipe line has a value for the UP_STRUCT and DN_STRUCT fields. This point is the upstream structure that may be a maintenance hole, pump station, junction, etc. Each of these structures is assigned an identifying number that corresponds to a Sewer Wye data record. The 8 digit value is based on an S-Map index map

This layer presents detectable thermal activity from MODIS satellites for the last 7 days. MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World.Consumption Best Practices:

As a service that is subject to very high usage, ensure peak performance and accessibility of your maps and apps by avoiding the use of non-cacheable relative Date/Time field filters. To accommodate filtering events by Date/Time, we suggest using the included "Age" fields that maintain the number of days or hours since a record was created or last modified, compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be efficiently provided to users in a high demand service environment.When ingesting this service in your applications, avoid using POST requests whenever possible. These requests can compromise performance and scalability during periods of high usage because they too are not cacheable.Source: NASA FIRMS - Active Fire Data - for WorldScale/Resolution: 1kmUpdate Frequency: 1/2 Hour (every 30 minutes) using the Aggregated Live Feed MethodologyArea Covered: WorldWhat can I do with this layer?The MODIS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.Additional InformationMODIS stands for MODerate resolution Imaging Spectroradiometer. The MODIS instrument is on board NASA’s Earth Observing System (EOS) Terra (EOS AM) and Aqua (EOS PM) satellites. The orbit of the Terra satellite goes from north to south across the equator in the morning and Aqua passes south to north over the equator in the afternoon resulting in global coverage every 1 to 2 days. The EOS satellites have a ±55 degree scanning pattern and orbit at 705 km with a 2,330 km swath width.It takes approximately 2 – 4 hours after satellite overpass for MODIS Rapid Response to process the data, and for the Fire Information for Resource Management System (FIRMS) to update the website. Occasionally, hardware errors can result in processing delays beyond the 2-4 hour range. Additional information on the MODIS system status can be found at MODIS Rapid Response.Attribute InformationLatitude and Longitude: The center point location of the 1km (approx.) pixel flagged as containing one or more fires/hotspots (fire size is not 1km, but variable). Stored by Point Geometry. See What does a hotspot/fire detection mean on the ground?Brightness: The brightness temperature measured (in Kelvin) using the MODIS channels 21/22 and channel 31.Scan and Track: The actual spatial resolution of the scanned pixel. Although the algorithm works at 1km resolution, the MODIS pixels get bigger toward the edge of the scan. See What does scan and track mean?Date and Time: Acquisition date of the hotspot/active fire pixel and time of satellite overpass in UTC (client presentation in local time). Stored by Acquisition Date.Acquisition Date: Derived Date/Time field combining Date and Time attributes.Satellite: Whether the detection was picked up by the Terra or Aqua satellite.Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel.Version: Version refers to the processing collection and source of data. The number before the decimal refers to the collection (e.g. MODIS Collection 6). The number after the decimal indicates the source of Level 1B data; data processed in near-real time by MODIS Rapid Response will have the source code “CollectionNumber.0”. Data sourced from MODAPS (with a 2-month lag) and processed by FIRMS using the standard MOD14/MYD14 Thermal Anomalies algorithm will have a source code “CollectionNumber.x”. For example, data with the version listed as 5.0 is collection 5, processed by MRR, data with the version listed as 5.1 is collection 5 data processed by FIRMS using Level 1B data from MODAPS.Bright.T31: Channel 31 brightness temperature (in Kelvins) of the hotspot/active fire pixel.FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).DayNight: The standard processing algorithm uses the solar zenith angle (SZA) to threshold the day/night value; if the SZA exceeds 85 degrees it is assigned a night value. SZA values less than 85 degrees are assigned a day time value. For the NRT algorithm the day/night flag is assigned by ascending (day) vs descending (night) observation. It is expected that the NRT assignment of the day/night flag will be amended to be consistent with the standard processing.Hours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.RevisionsJune 22, 2022: Added 'HOURS_OLD' field to enhance Filtering data. Added 'Last 7 days' Layer to extend data to match time range of VIIRS offering. Added Field level descriptions.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

Road Closure Datahttps://gis.charleston-sc.gov/road-closures-regional/Historic Flood Closureshttps://charleston-sc.maps.arcgis.com/home/item.html?id=02788fb440d744d69f9c0a3da27554b3The city began capturing road closure data in October 2015 while responding to the 1000 year flood event. Since then, the City has been refining the process to capture and retain a history of city street closures. Emergency closures are reported based on field reports from first responders and city staff operating in the field. This data is used for situation awareness during flooding events by staff and the public This is not a detailed and accurate survey of inundated roads. Not all flooding events are actively mapped and not all streets the are impacted are captured.This information should be used as a general information tool. Tide and Weather DataTide and weather data is collected and processed from NOAA sources and joined to the road closures using the closure start date and time. The process of calculating the joining the tide and weather data is experimental and subject to change.NOAA Weatherhttps://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USW00013782/detailNOAA tide data api (station=8665530)https://api.tidesandcurrents.noaa.gov/api/prod/

This layer was last updated August 2016. The map presents country boundaries; first-order (State/Province) internal administrative boundaries for most countries; second-order administrative boundaries for the United States (counties), Canada, India, New Zealand, and Europe, South America, and Africa; and place-names for the world. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri or any governing authority. The map was developed by Esri using administrative and cities data from Esri, HERE, and Garmin basemap layers for the world. Data for India sourced from MapmyIndia from ~1:288k and ~1:144k. Data for select areas is provided by the GIS Community. You can contribute your data to this service and have it served by Esri. For details on the users who contributed data for this map via the Community Maps Program, view the list of Contributors for the World Boundaries and Places Map. Data for select areas of Africa and Pacific Island nations was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.This layer is designed for use with maps with lighter backgrounds, such as the World Shaded Relief map, as you can see in this Shaded Relief web map which includes the World Boundaries and Places Alternate and the World Reference Overlay layers which you can turn on in order to compare their utility as reference overlays. A different version of this map is also available, the World Boundaries and Places layer, which is designed for overlaying on basemaps with darker backgrounds, such as the World Imagery map.Scale Range: 1:591,657,528 down to 1:144,448Coordinate System: Web Mercator Auxiliary Sphere (WKID 102100)Tiling Scheme: Web Mercator Auxiliary SphereMap Service Name: World_Boundaries_and_Places_AlternateArcGIS Desktop/Explorer URL: http://services.arcgisonline.com/arcgis/servicesArcGIS Server Manager and Web ADF URL: http://server.arcgisonline.com/arcgis/services/Reference/World_Boundaries_and_Places_Alternate/MapServerREST URL for ArcGIS Web APIs: http://server.arcgisonline.com/ArcGIS/rest/services/Reference/World_Boundaries_and_Places_Alternate/MapServerSOAP API URL: http://services.arcgisonline.com/ArcGIS/services/Reference/World_Boundaries_and_Places_Alternate/MapServer?wsdl

This wye pipes feature class represents current wastewater information connecting the sewer service to either side of the street in the City of Los Angeles. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most rigorous geographic information of the sanitary sewer system using a geometric network model, to ensure that its sewers reflect current ground conditions. The sanitary sewer system, pump plants, wyes, maintenance holes, and other structures represent the sewer infrastructure in the City of Los Angeles. Wye and sewer information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Associated information about the wastewater Wye is entered into attributes. Principal attributes include:WYE_SUBTYPE: wye subtype is the principal field that describes various types of points as either Chimney, Chimney Riser, Offset Chimney Riser, Siphon, Special Case, Spur, Tap, Tee, Unclassified, Vertical Tee, Vertical Tee Riser, Wye, Wye Drawn as a Tap.For a complete list of attribute values, please refer to (TBA Wastewater data dictionary).Wastewater Wye pipes lines layer was created in geographical information systems (GIS) software to display the location of wastewater wye pipes. The wyes lines layer is a feature class in the LACityWastewaterData.gdb Geodatabase dataset. The layer consists of spatial data as a line feature class and attribute data for the features. The lines are entered manually based on wastewater sewer maps and BOE standard plans, and information about the lines is entered into attributes. The wye pipes lines features are sewer pipe connections for buildings. The features in the Wastewater connector wye points layer is a related structure connected with the wye pipe line. The WYE_ID field value is the unique ID. The WYE_ID field relates to the Sewer Permit tables. The annotation wye features are displayed on maps alongside features from the Wastewater Sewer Wye pipes lines layer. The wastewater wye pipes lines are inherited from a sewer spatial database originally created by the City's Wastewater program. The database was known as SIMMS, Sewer Inventory and Maintenance Management System. Wye pipe information should only be added to the Wastewater wye pipes layer if documentation exists, such as a wastewater map approved by the City Engineer. Sewers plans and specifications proposed under private development are reviewed and approved by by Bureau of Engineering. The Department of Public Works, Bureau of Engineering's, Brown Book (current as of 2010) outlines standard specifications for public works construction. For more information on sewer materials and structures, look at the Bureau of Engineering Manual, Part F, Sewer Design, F 400 Sewer Materials and Structures section, and a copy can be viewed at http://eng.lacity.org/techdocs/sewer-ma/f400.pdf.List of Fields:SPECIAL_STRUCT: This attribute is the basin number.TOP_: When a chimney is present, this is the depth at the top of the chimney.BOTTOM: When a chimney is present, this is the depth at the bottom of the chimney.PL_HUNDS: This value is the hundreds portion of the stationing at the property line.SHAPE: Feature geometry.USER_ID: The name of the user carrying out the edits of the wye pipes data.TYPE: This is the old wye status and is no longer referenced.REMARKS: This attribute contains additional comments regarding the wye line segment, such as a line through in all caps when lined out on wye maps.WYE_NO: This value is the number of the line segment for the wye structure located along the pipe segment. This is a 2 digit value. The number starts at 1 for the first wye connected to a pipe. The numbers increase sequentially with each wye being unique.WYE_ID: The value is a combination of PIPE_ID and WYE_NO fields, forming a unique number. This 19 digit value is a key attribute of the wye lines data layer. This field relates to the Permit tables.C_TENS: This value is the tens portion of the stationing at the curb line.C_HUNDS: This value is the hundreds portion of the stationing at the curb line.WYE_SUBTYPE: This value is the type of sewer connection. Values: • 2 - Tap. • 8 - Siphon. • 13 - Wye Drawn as a Tap. • 9 - Special Case. • 6 - Chimney riser. • 4 - Chimney. • 5 - Vertical Tee Riser. • 7 - Vertical tee. • 10 - Spur. • 11 - Unclassified. • 12 - Offset Chimney Riser. • 1 - Wye. • 3 - Tee.SIDE: The side of the pipe looking up stream to which structure attaches. Values: • U - Unknown. • L - Left. • R - Right. • C - Centered.ASSETID: User-defined unique feature number that is automatically generated.PL_DEPTH: This value is the depth of the service connection at the property line.DEPTH: This value is the depth of the Wye from the surface in feet.STAT_HUND: This value is the hundreds portion of the stationing.ENG_DIST: LA City Engineering District. The boundaries are displayed in the Engineering Districts index map. Values: • H - Harbor Engineering District. • C - Central Engineering District. • V - Valley Engineering District. • W - West LA Engineering District.PIPE_ID: The value is a combination of the values in the UP_STRUCT, DN_STRUCT, and PIPE_LABEL fields. This is the 17 digit identifier of each pipe segment and is a key attribute of the pipe line data layer. This field named PIPE_ID relates to the field in the Annotation Pipe and to the field named PIPE_ID in the Pipe line feature class data layers.OBJECTID: Internal feature number.ENABLED: Internal feature number.REHAB: This attribute indicates if the wye pipe has been rehabilitated.C_DEPTH: This value is the depth of the service connection at the curb line.STAT_TENS: This value is the tens portion of the stationing.BASIN: This attribute is the basin number.LAST_UPDATE: Date of last update of the point feature.STATUS: This value is the active or inactive status of the wye pipes. Values: • Capped - Capped. • INACTIVE - Inactive.PL_TENS: This value is the tens portion of the stationing at the property line.CRTN_DT: Creation date of the point feature.SERVICEID: User-defined unique feature number that is automatically generated.SHAPE_Length: Length of feature in internal units.

This data represents incident reports written to capture incidents of crime that are reported to law enforcement, based on the FBI’s UCR Program Data Collections for the National Incident-Based Reporting System (NIBRS). It is similar to the DPD Incidents (UCR NIBRS Reporting) dataset found on this site, except it is limited to only shooting events where a firearm was criminally discharged (not accidental or self-inflicted). In addition, only the first [hierarchical] offense is listed, which may not have been the offense linked to the shooting activity in some instances. Historical data is available back to 10/1/2018. Available fields include:Case Number – Unique numerical identifier of the incident, which can be joined to the calls for service and arrests datasets.Report Date – The date when the crime occurred, or when it was reported to police, if the date of occurrence is not known.Report Time – The time when the crime occurred, or when it was reported to police, if the time of occurrence is not known.Status – The status of the case at the time the dataset was last updated.Sequence – This will always be ‘1’ as the SRS hierarchical method is being used for this dataset.ATT/COM – Designation of whether the crime was attempted or committed.UCR Code – The FBI’s alphanumeric identifier for the type of crime being reported.Address – The block number and street or intersection of the incident.X – Mapping coordinate of the incident, projected as NC State Plane (feet).Y – Mapping coordinate of the incident, projected as NC State Plane (feet).District – The patrol district where the incident occurred.Beat – The patrol beat where the incident occurred, which is a sub-division of the district.Tract – The census tract where the incident occurred, based on 2010 census data.Premise – The type of location where the incident took place.Weapon – The primary weapon used in violent crimes.This dataset is updated annually. However, other resources for incident data are available and updated nightly, including the DPD Crime dataset on the City and County of Durham Open Data Portal and Community Crime Map web site by LexisNexis. Tools for interacting with census data can be found on TIGERweb.