Maxent software (http://www.cs.princeton.edu/~schapire/maxent) is frequently used for presence-only species distribution modeling. Maxent requires, however, that input ASCII raster files be aligned with one another and have the same spatial extent. This tool pre-processes raster data in preparation for Maxent modeling to ensure that all rasters have the same extent, same cell size, and aren't missing data. There are two version of this geoprocessing modeling. The advanced version is for the ArcGIS Advanced license. The basic version is the the ArcGIS Advanced license. Both versions require Spatial Analyst. The difference between the two is that the advanced version creates a polygon shapefile that shows the difference between the template raster and the processed raster. Ideally, this should generate a polygon with empty output, but if it doesn't you can use it to diagnose problems. The tool first resamples the raster, then uses a focalmean (3x3 and 5x5) to fill gaps, and mosaics the resampled, 3x3, and 5x5 rasters together, and converts to ASCII.Recommended citation format: Dilts, T.E. (2015) Prepare Rasters for Maxent Tool for ArcGIS 10.1. University of Nevada Reno. Available at: http://www.arcgis.com/home/item.html?id=11bf7e689c92413f8d31933b3e1f56b1

Dataset contains information on Tempeans receiving post-secondary education, licenses, certificates. Data supports City's Achieve65Tempe goal that 65 percent of Tempe’s adult population access post-secondary education, resulting in a certification to an advanced degree by 2030.This page provides data for the Post-Secondary School Achievement Rate performance measure. Certificate and License estimates from the Arizona Board of Regents.The performance measure dashboard is available at 3.09 Post-Secondary School Achievement Rate.Additional InformationSource: US Census, Arizona Board of RegentsContact: Marie RaymondContact E-Mail: Marie_Raymond@tempe.govData Source Type: Excel / CSVPreparation Method: Numbers retrieved from US Census and Arizona Board of Regents, then combined into a summary spreadsheet. The supporting data sources are also provided.Publish Frequency: annuallyPublish Method: manualData Dictionary

Urban fabrics for the Helsinki region 2016, 2030 and 2050 GIS dataset represents modelled urban fabric areas (walking, transit, and automobile urban fabrics) in the Helsinki city region (14 municipalities) in Finland. The data is associated with the regional MAL 2019 (land use, housing, and transport) work and was developed at the Finnish Environment Institute (Syke). The method used to produce the data has also been applied to other city regions in Finland (Helminen et al., 2020) and is an application of Newman et al.'s (2016) theory of three urban fabrics. The method is based on the overlay analysis of three variables: population and job density, accessibility to local services, and public transportation supply, with threshold values set for each variable. The definition of threshold values is based on previous applications of urban fabrics (Ristimäki et al., 2017) and a workshop conducted for urban planning and transportation professionals in the Helsinki metropolitan area. All accessibility measures used in creating the data were calculated as Euclidean distances.

The data was created using ArcMap Advanced software (version 10.6) and includes shapefiles for each modeling year's urban structures (UF_2016, UF_2030, and UF_2050) as well as description styles (UF_Fi.qml and UF_En.qml) in Finnish and English for the QGIS software. The names of the structures are in the fields 'Kudos' (in Finnish) and 'UrbFab' (in English). The coordinate system of the data is EPSG:3067. Detailed descriptions of the data and the method can be found in the report 'Helsingin seudun kaupunkikudokset 2016, 2030 a 2050' (Tiitu et al., 2018, in Finnish) and in the downloadable ReadMe files below (both in Finnish and English).

Helsingin seudun kaupunkikudokset 2016, 2030 ja 2050 -paikkatietoaineisto

Helsingin seudun kaupunkikudokset 2016, 2030 ja 2050 -paikkatietoaineisto kuvaa mallinnettuja kaupunkikudosten alueita (jalankulku-, joukkoliikenne- ja autokaupunki) Helsingin seudun (14 kuntaa) alueelta Suomesta. Aineisto liittyy seudun MAL 2019 -työhön, ja se on kehitetty Suomen ympäristökeskuksessa (Syke). Menetelmää, jolla aineisto on tuotettu, on sovellettu myös muille Suomen kaupunkiseuduille (Helminen ym. 2020), ja se on sovellutus Newmanin ym. (2016) kolmen kaupunkikudoksen teoriasta. Menetelmä perustuu päällekkäisanalyysiin kolmesta muuttujasta: asukas- ja työpaikkatiheys, lähikaupan saavutettavuus ja joukkoliikenteen tarjonta, sekä muuttujille asetettuihin kynnysarvoihin. Kynnysarvojen määrittely perustui kaupunkikudosten aiempiin sovellutuksiin (Ristimäki ym. 2017) sekä Helsingin seudun maankäytön ja liikenteen suunnittelijoille suunnattuun työpajaan. Kaikki aineiston muodostamiseen käytetyt saavutettavuudet on laskettu linnuntie-etäisyyksinä.

Aineisto on muodostettu ArcMap Advanced -ohjelmistolla (versio 10.6.) ja se sisältää shp-tiedostot kunkin mallinnusvuoden kaupunkikudoksille (UF_2016, UF_2030 ja UF_2050) sekä kuvaustekniikan (UF_Fi.qml ja UF_En.qml) suomeksi ja englanniksi QGIS-ohjelmistolle. Kudosten nimet ovat sarakkeissa Kudos (suomeksi) ja UrbFab (englanniksi). Aineiston koordinaattijärjestelmä on EPSG:3067. Aineiston ja menetelmän tarkka kuvaus on luettavissa raportista Helsingin seudun kaupunkikudokset 2016, 2030 ja 2050 (Tiitu ym. 2018) sekä alla ladattavista ReadMe-tiedostoista.

References

Helminen V., Tiitu M., Kosonen, L. & Ristimäki, M. (2020). Identifying the areas of walking, transit and automobile urban fabrics in Finnish intermediate cities. Transportation Research Interdisciplinary Perspectives 8, 100257. https://doi.org/10.1016/j.trip.2020.100257

Newman, L. Kosonen & J. Kenworthy (2016). Theory of urban fabrics; planning the walking, transit/public transport and automobile/motor car cities for reduced car dependency. Town planning Review 87 (4): 429–458. http://hdl.handle.net/20.500.11937/11247

Ristimäki M., Tiitu M., Helminen V., Nieminen H., Rosengren K., Vihanninjoki V., Rehunen A., Strandell A., Kotilainen A., Kosonen L., Kalenoja H., Nieminen J., Niskanen S. & Söderström P. (2017). Yhdyskuntarakenteen tulevaisuus kaupunkiseuduilla – Kaupunkikudokset ja vyöhykkeet. Suomen ympäristökeskuksen raportteja 4/2017. Suomen ympäristökeskus, Helsinki. http://hdl.handle.net/10138/176782

Tiitu M., Helminen V., Nurmio K. & Ristimäki M. (2018). Helsingin seudun kaupunkikudokset 2016, 2030 ja 2050. MAL 2019 publication. https://www.hsl.fi/sites/default/files/uploads/helsingin_seudun_kaupunkikudokset_loppuraportti_27082018_0.pdf

License / Lisenssi

Syke applies Creative Commons By 4.0 International license for open datasets.
This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation. The source references for credits can be found in the metadata of each data product.

Suomen ympäristökeskuksen (Syke) avointen aineistojen käyttölupa on Creative Commons Nimeä 4.0 Kansainvälinen.
Lisenssin kohteena olevaa dataa voi vapaasti käyttää kaikin mahdollisin tavoin edellyttäen, että datan lähde mainitaan: Lisenssinantajan nimi ja aineiston nimi.

Credits / Lähdemerkintä

Urban Fabrics for the Helsinki Region / Source: Finnish Environment Institute Syke 2018.
Where applicable, please also cite the references listed above.

Helsingin seudun kaupunkikudokset / Lähde: Syke 2018.
Viittaa myös soveltuvin osin yllä listattuihin lähteisiin, jos hyödynnät näitä aineistoja esimerkiksi raporteissa tai tutkimusartikkeleissa.

Creates points from the x-, y-, and z-coordinate information stored in geotagged photos. This tool reads the longitude, latitude, and altitude coordinate information from JPEG and TIFF photo files with valid Exif (exchangeable image file format) metadata and writes these coordinates and associated attributes to an output point feature class. These photos are often captured using digital cameras with built-in or accessory GPS units or with smart phones.Also, there's an easy way to display the photos associated with the output points, just follow these steps. 1. You'll need to calculate the photo path field into a new HTML formatted value; start by adding a new text field with a large length (>200 characters), then use field calculator with the Python expression below (including quotation marks) "" % r'!Path!' 2. Right-click on your point layer, go to Properties, and go to the HTML popup tab. Make sure the “Show content for this layer…” option is checked, then select to display HTML formatting “As a table of the visible fields…”. You can choose which fields you want displayed in the main Fields tab, just make sure the new HTML formatted picture field is visible. You can press the Verify button back on the HTML popup page to see what the popup will look like. In the expression above the image is set with a width of 300, so the thumbnails that get displayed will be 300 pixels wide. You can change this if you would like a different size. 3. Use the HTML popup tool in ArcMap, and click on the points to see a popup. Software Requirements:ArcGIS 10.0 or laterArcView (Basic) license or higherNote: The download contains two toolboxes, one for use in ArcGIS 10.0 and one for use in ArcGIS 10.1. The 101 toolbox tool is the same as the Geotagged Photos To Points system tool in the Data Management Tools toolbox, and has more advanced features (importing photos to the geodatabase as attachments and photo direction) and faster processing than the 10.0 version tool.

This web map sample includes the active storms, track points, track lines, and rainfall hazards (inches) layers for all active tropical cyclone systems around the world as a web map. DATA OVERVIEWKinetic Analysis Tropical Cyclone datasets draw on a broad array of real-time weather and forecast data to drive in-house, advanced numerical modeling that computes the spatial distribution of maximum wind speedwinds by Saffir-Simpson categorieswave heightsstorm surge inundationcumulative rainfallUSE CASESWhile this data may be used in a variety of ways, the most common ways we see it in action is by insurance, emergency management, disaster relief, supply chain, and governmental agencies/organization in making decisions about actions to take before, during, and after a tropical cyclone. Adjustors, for example, can use modeled hazards to determine which sites to visit and with what level of urgency. Government agencies can use impact data to determine where to focus on building climate resilience safeguards and resources next.DATA SOURCEHazard footprints are based on observed and forecasted storm track, intensity and wind radii provided by the designated expert-reviewed sources NHC (National Hurricane Center), JTWC (Joint Typhoon Warning Center), CPHC (Central Pacific Hurricane Center) - collectively termed OFCL (Official). UPDATE FREQUENCYData from Kinetic Analysis model runs are updated every time a new forecast is released by one of the aforementioned sources.SCALE/RESOLUTIONThis near real-time data is provided at 60 arc-second (~2 km) resolution. Shortly after a storm dissipates or transitions to a non-tropical cyclone, a post-event wind and storm surge dataset can be provided at a 30 arc-second (~1 km) resolution upon request.AREA COVEREDWorldINTERESTED IN MORE?Our full ArcGIS Marketplace listing grants you a monthly license for access to the Kinetic Analysis Corporation's proprietary near real-time data, which includes industry-standard shapefile datasets of multiple hazard footprints for all active hurricanes, typhoons, cyclones and tropical storms around the globe. Discounted price options are available for those who wish to purchase an annual license instead of a monthly one. Customized resolutions, forecast agencies, and data units (default is SI) are available upon request to sales@kinanco.com. Learn more on the Kinetic Analysis website.NOTE: Preview images of data on ArcGIS Marketplace only show rain footprints for confidentiality purposes. Licensors of the full listing will receive access to all hazard footprints.GLOSSARY/DATA LAYERS AND FIELDSActive Storms - These points indicate the most-recently-updated location of active storms around the world, as observed by the National Hurricane Center (NHC), the Central Pacific Hurricane Center (CPHC), or the Joint Typhoon Warning Center (JTWC) - together termed "Official" (OFCL).Track Points - These points indicate the locations of a storm over time - where it has been, where it currently is, and where it is forecast to be. They are generated by forecast agencies and numerical model guidance.Track Line - This is the line formed by connecting all the track points. It depicts a continuous path for the storm by interpolating between any two track points.ATCF ID - Unique ID associated with a tropical cyclone, defined using the Automated Tropical Cyclone Forecasting (ATCF) system. The format is usually a two-letter abbreviation of the ocean basin (see "Storm Basin" below for list) in which the storm can be found, the annual cyclone number starting from 1 for the first storm in each basin per year, and the 4-digit year. For example, AL112017 (Hurricane Irma) refers to AL (Atlantic basin), 11th storm of the year in that basin, in the year 2017.Storm Name - The World Meteorological Organization (WMO) tropical cyclone name, such as Irma, Katrina, and Rai.Storm Basin - Ocean basin in which the storm is taking place. These include AL (North Atlantic), WP (Western North Pacific), CP (Central North Pacific), EP (Eastern North Pacific), IO (North Indian Ocean), SH (South-West Indian Ocean, Australian region, and South Pacific Ocean), and LS (Southern Atlantic).Storm Age - Number of days the storm has been active at time of forecastCategory Description - How the selected layer would be categorized against similar data. For example, data in a wind layer may be categorized into groups of 5 mph each, such as 100-105 mph for one group and 105-110 mph for another group. In such a case, the category description field displays which grouping the selected location belongs to. This is a variable/field separate from the name of each map layer.Latitude & Longitude - Geographic indicators of a storm's past, current, or forecast location derived from dividing the Earth into grids measured in degrees.Wind Speed - Maximum wind speed of the storm at that location. The units are knots for track points and track line layers and miles per hour (mph) for the wind speed hazard layer. These represent terrain-adjusted, 2-minute sustained winds at 10-meter elevation and are consistent with wind speeds reported by Automated Surface Observing Stations (ASOS weather stations). They can differ from wind speed forecast by different agencies because, in contrast with winds forecast by agencies such as the NHC, Kinetic Analysis-generated winds account for the effects of surface roughness and topography. In addition, different agencies can report winds based on different averaging times. For example, the NHC and JTWC report 1-minute sustained winds while the World Meteorological Organization (WMO) standard is 10-minute sustained winds.Minimum Sea Level Pressure - The lowest sea level pressure at that storm location. Measured in millibars.Radius of Max Winds - The distance between the storm's center, where the central pressure is lowest, and the maximum winds of a storm. Measured in nautical miles. Forward Speed - How fast a storm is moving at the selected location. Measured in meters per second (m/s).Storm Direction - The direction toward which a storm is moving at the selected location. Measured with a 360-degree system where North is represented by 0 degrees and East by 90 degrees.Current Latitude & Longitude - The latitude and longitude of the storm at its current location, which might not be the selected location. The current location of the storm is indicated by the active storms layer.Current Wind Speed - The wind speed of the storm at its current location, which might not be the selected location. Measured in knots and mph depending on the layer type (see "Wind Speed" above for more information).Current Forward Speed - How fast a storm is moving at its current location, which might not be the selected location. Measured in knots.Current Storm Direction - The direction toward which a storm is moving at its current location, which might not be the selected location.Forecast Time - Time at which an agency (such as OFCL) released its newest update of storm track data. This is the set of data used to simulate the model results displayed. Simulation Time - Time at which Kinetic Analysis's models processed the current data.Model in Simulation - The forecast agency, or model that generated the inputs for the Kinetic Analysis-simulated storm hazard data.Valid Time Relative to Current Position - The time in hours relative to "Forecast Time" that a storm position represents. For example, a point with a valid time of 12 would represent the storm forecast position 12 hours after the current forecast time.NOTE: This map and its data are provided for informational purposes only. Due to limitations in modern modeling technology, this data may not reflect the ultimate path, hazards, and/or impacts of a storm with 100% accuracy. Usage of this map and its data voids Kinetic Analysis of any responsibilities for consequences that may arise from using it to make personal or business decisions.

Department of Conservation (DOC) - Huts and bivvies. Dataset shows all huts and bivvies.

If you intend to stay in a hut/bivvy, please confirm with your local office or the DOC website that it is available and not under a temporary or more permanent closure before departing.

Please note some huts require advance booking, contact your local office or visit the DOC Website for more information.

Refreshed weekly and reflects the content on the website.*****LICENCE*****This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA.*****DISCLAIMER***** 1. DOC makes no express or implied warranties as to the accuracy or completeness of the data or information, nor its suitability for any purpose. Errors are inevitably part of any database, and can arise by a number of means, from errors during field data collection, to errors during data entry. 2. DOC makes no warranties or representations as to possible infringement upon copyrights or other intellectual property rights of others in the data or information. 3. DOC will not accept liability for any direct, indirect, special or consequential damages, losses or expenses howsoever arising and relating to use, or lack of use, of the data or information supplied.*****GUIDELINES FOR THE USE OF THE INFORMATION***** 4. Care should be taken in deriving conclusions from any data or information supplied. 5. Any use of the data or information supplied should state when the data or information was acquired and that it may now be out-of-date.*****COPYRIGHT OBLIGATIONS***** 6. All proprietary rights to the intellectual property in the data or information remain with the Crown as its sole property. 7. Modification of the data and information or the addition of the information does not confer copyright or any other form of property of the original material to a user. 8. All maps or reports that are derived from the data or information must acknowledge the Crown copyright, in the following way: Crown Copyright: Department of Conservation Te Papa Atawhai [year]. 9. This information resource may be passed onto another party, in either hard copy or electronic form. If a user does this, then it is recommended that they also supply this metadata record with the information resource.

Department of Conservation (DOC) - Campsites. Dataset shows all campsites.

If you intend to stay in a campsite, please confirm with your local office or the DOC website that it is available and not under a temporary or more permanent closure before departing.

Please note some campsites require advance booking, contact your local office or visit the DOC Website for more information.

Refreshed weekly and reflects the content on the website.*****LICENCE*****This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA.*****DISCLAIMER***** 1. DOC makes no express or implied warranties as to the accuracy or completeness of the data or information, nor its suitability for any purpose. Errors are inevitably part of any database, and can arise by a number of means, from errors during field data collection, to errors during data entry. 2. DOC makes no warranties or representations as to possible infringement upon copyrights or other intellectual property rights of others in the data or information. 3. DOC will not accept liability for any direct, indirect, special or consequential damages, losses or expenses howsoever arising and relating to use, or lack of use, of the data or information supplied.*****GUIDELINES FOR THE USE OF THE INFORMATION***** 4. Care should be taken in deriving conclusions from any data or information supplied. 5. Any use of the data or information supplied should state when the data or information was acquired and that it may now be out-of-date.*****COPYRIGHT OBLIGATIONS***** 6. All proprietary rights to the intellectual property in the data or information remain with the Crown as its sole property. 7. Modification of the data and information or the addition of the information does not confer copyright or any other form of property of the original material to a user. 8. All maps or reports that are derived from the data or information must acknowledge the Crown copyright, in the following way: Crown Copyright: Department of Conservation Te Papa Atawhai [year]. 9. This information resource may be passed onto another party, in either hard copy or electronic form. If a user does this, then it is recommended that they also supply this metadata record with the information resource

Voting Precincts in Macon-Bibb County. Elections in the county are managed by the Macon-Bibb County Board of Elections.

Voters who cast their votes in person must show one of six forms of photo identification. If the voter votes BY MAIL, they DO NOT need a photo ID. Photo ID rules ONLY APPLY to IN-PERSON voting by absentee, advance voting or at the polling place on Election Day.

· A current or expired Georgia driver’s license (or Department of Driver Services identification card);

· A valid United States military photo identification card;

· A valid photo identification card issued by any branch, department agency, or entity of the United States, Georgia, or any other state authorized by law to issue personal identification, including a FREE Georgia Voter Identification Card;

· A valid employee photo identification card issued by any branch, department, agency, or entity of the United States, Georgia, or any county, municipality, board, authority of other entity of Georgia;

· A valid United States passport; or

· A valid tribal photo identification card.

Any elector who registered for the first time in Georgia by mail, and did not provide identification at the time of registering may provide one of the six (6) items of photo identification listed above, or for the electors first time voting, may provide one of the following forms of identification: copy of a current utility bill, bank statement, government check, paycheck, or other government document that shows the name and address of elector.IF ELECTOR CANNOT PROVIDE ANY OF THE ABOVE LISTED ID’S THEY MAY VOTE A PROVISIONAL BALLOT IN ACCORDANCE WITH O.C.G.A. 21-2-220 and 21-2-417.

If the voter does not have a Georgia driver’s license, or other qualified ID, they can obtain either a FREE Georgia Identification Card from the Department of Driver Services or a FREE Georgia Voter Identification Card at their county registrar’s office. Just contact the Macon-Bibb County Board of Elections located at 2525 Pio Nono Ave., Ste 1200, Macon, GA 31206. Office hours are from 8:30 a.m. to 5:30 p.m. Monday thru Friday. For more information call 478-621-6622 or go to www.gaphotoid.com.

In order to get a FREE Georgia Voter Identification Card, a voter will need to provide the following:

A photo identity document, or a non-photo identity document (must include voter’s full legal name and date of birth); and

· Documentation showing the voter’s date of birth; and

· Evidence that voter is registered to vote in Georgia; and

· Documentation showing the voter’s name and address of principal residence.

The voter may use the same document to satisfy more than one of the above requirements. For additional information, please visit the Secretary of State’s web page at www.sos.state.ga.us.