This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

Geospatial data about Placer County, California MAC Boundaries. Export to CAD, GIS, PDF, CSV and access via API.

The Geology of the Northern Jetty Peninsula GIS dataset contains the shapefiles and tables of the basement geology of the Northern Jetty Peninsula in East Antarctica. This dataset is derived from the map product ‘Geology of Northern Jetty Peninsula, Mac.Robertson Land, Antarctica'.

Northern Jetty Peninsula, incorporating Else Platform (~140 km2) and Kamenistaja Platform (~15 km2), represents a mostly ice-free low-lying region located on the western flanks of the Lambert Graben. The region is underlain by granulite-facies Proterozoic gneisses and unmetamorphosed Permian sediments.

For more information about this tool see Batch Metadata Modifier Tool Toolbar Help.Modifying multiple files simultaneously that don't have identical structures is possible but not advised. Be especially careful modifying repeatable elements in multiple files that do not have and identical structureTool can be run as an ArcGIS Add-In or as a stand-alone Windows executableExecutable runs on PC only. (Not supported on Mac.)The ArcGIS Add-In requires ArcGIS Desktop version 10.2 or 10.3Metadata formats accepted: FGDC CSDGM, ArcGIS 1.0, ArcGIS ISO, and ISO 19115Contact Bruce Godfrey (bgodfrey@uidaho.edu, Ph. 208-292-1407) if you have questions or wish to collaborate on further developing this tool.Modifying and maintaining metadata for large batches of ArcGIS items can be a daunting task. Out-of-the-box graphical user interface metadata tools within ArcCatalog 10.x are designed primarily to allow users to interact with metadata for one item at a time. There are, however, a limited number of tools for performing metadata operations on multiple items. Therefore, the need exists to develop tools to modify metadata for numerous items more effectively and efficiently. The Batch Metadata Modifier Tools toolbar is a step in that direction. The Toolbar, which is available as an ArcGIS Add-In, currently contains two tools. The first tool, which is additionally available as a standalone Windows executable application, allows users to update metadata on multiple items iteratively. The tool enables users to modify existing elements, find and replace element content, delete metadata elements, and import metadata elements from external templates. The second tool of the Toolbar, a batch thumbnail creator, enables the batch-creation of the graphic that appears in an item’s metadata, illustrating the data an item contains. Both of these tools make updating metadata in ArcCatalog more efficient, since the tools are able to operate on numerous items iteratively through an easy-to-use graphic interface.This tool, developed by INSIDE Idaho at the University of Idaho Library, was created to assist researchers with modifying FGDC CSDGM, ArcGIS 1.0 Format and ISO 19115 metadata for numerous data products generated under EPSCoR award EPS-0814387.This tool is primarily designed to be used by those familiar with metadata, metadata standards, and metadata schemas. The tool is for use by metadata librarians and metadata managers and those having experience modifying standardized metadata. The tool is designed to expedite batch metadata maintenance. Users of this tool must fully understand the files they are modifying. No responsibility is assumed by the Idaho Geospatial Data Clearinghouse or the University of Idaho in the use of this tool. A portion of the development of this tool was made possible by an Idaho EPSCoR Office award.

Geospatial data about Dakota County, Minnesota MAC Noise Levels. Export to CAD, GIS, PDF, CSV and access via API.

DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

DNRGPS does not require installation. Simply run the application .exe

See the DNRGPS application documentation for more details.

Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

Prerequisite: .NET 4 Framework

DNR Data and Software License Agreement

Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.

GIS-Sebahagian Senarai Inventori Pokok Presint 14 sehingga Mac 2018

MACs - Municipal Advisory Councils, and CCs - Community Councils, are established by the Board of Supervisors. They are bodies appointed by the Board to provide an extra avenue for communication from the affected communities back to the Board member who represents them, about issues of concern to them. Their boundaries come from the Supervisors who established them. Data was spatially adjusted in 2020. NAME: CAC/MAC nameTYPE: "MAC" = Municipal Advisory Councils, "CC" = Community CouncilMaintained by Mickey Zoleizo, 9/2015

This dataset contains 63 shapefiles that represent the areas of relevance for each research project under the National Environmental Science Program Marine and Coastal Hub, northern and southern node projects for Rounds 1, 2 & 3.

Methods: Each project map is developed using the following steps: 1. The project map was drawn based on the information provided in the research project proposals. 2. The map was refined based on feedback during the first data discussions with the project leader. 3. Where projects are finished most maps were updated based on the extents of datasets generated by the project and followup checks with the project leader.

The area mapped includes on-ground activities of the project, but also where the outputs of the project are likely to be relevant. The maps were refined by project leads, by showing them the initial map developed from the proposal, then asking them "How would you change this map to better represent the area where your project is relevant?". In general, this would result in changes such as removing areas where they were no longer intending research to be, or trimming of the extents to better represent the habitats that are relevant.

The project extent maps are intentionally low resolution (low number of polygon vertices), limiting the number of vertices 100s of points. This is to allow their easy integration into project metadata records and for presenting via interactive web maps and spatial searching. The goal of the maps was to define the project extent in a manner that was significantly more accurate than a bounding box, reducing the number of false positives generated from a spatial search. The geometry was intended to be simple enough that projects leaders could describe the locations verbally and the rough nature of the mapping made it clear that the regions of relevance are approximate.

In some cases, boundaries were drawn manually using a low number of vertices, in the process adjusting them to be more relevant to the project. In others, high resolution GIS datasets (such as the EEZ, or the Australian coastline) were used, but simplified at a resolution of 5-10km to ensure an appopriate vertices count for the final polygon extent. Reference datasets were frequently used to make adjustments to the maps, for example maps of wetlands and rivers were used to better represent the inner boundary of projects that were relevant for wetlands.

In general, the areas represented in the maps tend to show an area larger then the actual project activities, for example a project focusing on coastal restoration might include marine areas up to 50 km offshore and 50 km inshore. This buffering allows the coastline to be represented with a low number of verticies without leading to false negatives, where a project doesn't come up in a search because the area being searched is just outside the core area of a project.

Limitations of the data: The areas represented in this data are intentionally low resolution. The polygon features from the various projects overlap significantly and thus many boundaries are hidden with default styling. This dataset is not a complete representation of the work being done by the NESP MaC projects as it was collected only 3 years into a 7 year program.

Format of the data: The maps were drawn in QGIS using relevant reference layers and saved as shapefiles. These are then converted to GeoJSON or WKT (Well-known Text) and incorporated into the ISO19115-3 project metadata records in GeoNetwork. Updates to the map are made to the original shapefiles, and the metadata record subsequently updated.

All projects are represented as a single multi-polygon. The multiple polygons was developed by merging of separate areas into a single multi-polygon. This was done to improve compatibility with web platforms, allowing easy conversion to GeoJSON and WKT.

This dataset will be updated periodically as new NESP MaC projects are developed and as project progress and the map layers are improved. These updates will typically be annual.

Data dictionary: NAME - Title of the layer PROJ - Project code of the project relating to the layer NODE - Whether the project is part of the Northern or Southern Nodes TITLE - Title of the project P_LEADER - Name of the Project leader and institution managing the project PROJ_LINK - Link to the project metadata MAP_DESC - Brief text description of the map area MAP_TYPE - Describes whether the map extent is a 'general' area of relevance for the project work, or 'specific' where there is on ground survey or sampling activities MOD_DATE - Last modification date to the individual map layer (prior to merging)

Updates & Processing: These maps were created by eAtlas and IMAS Data Wranglers as part of the NESP MaC Data Management activities. As new project information is made available, the maps may be updated and republished. The update log will appear below with notes to indicate when individual project maps are updated: 20220626 - Dataset published (All shapefiles have MOD_DATE 20230626)

Location of the data: This dataset is filed in the eAtlas enduring data repository at: data\custodian esp-mac-3\AU_AIMS-UTAS_NESP-MaC_Project-extents-maps

This record provides an overview of the NESP Marine and Coastal Hub Research Plan 2024 project "Unbroken whispers: the ripples connecting sea kin". For specific data outputs from this project, please see child records associated with this metadata. Knowledge, in all its forms, is key to effectively protecting and recovering threatened and migratory whales and dolphins. Indigenous ecological knowledge (IEK) has guided Indigenous peoples through many uncertain climate and ecological fluctuations. IEK has also been used as part of protected area and species management for many thousands of years. More recently, IEK has shown huge potential to contribute to our understanding of threatened and migratory whales and dolphins, but this knowledge has not historically been collated, analysed or properly considered. Consequently, there is an absence of Indigenous perspectives and use of cultural knowledge informing the protection and recovery of EPBC listed threatened and migratory species. This Indigenous-led project will identify and share (where appropriate) cultural knowledge of relationships with whales and dolphins, and connections between land, sea and sky. Indigenous communities will participate in research that explores cultural ideology around kinship and responsibilities to kin, through expressing the knowledge, values and concerns they hold for whales and dolphins. The acquired knowledge and methods will support the cultural governance of sea Country by Indigenous communities and organisations, and policymaking, implementation and review by government agencies in relation to resource use and conservation. Outputs • GIS visualisation package of key geospatial layers related to connecting land and sea in the context of cultural keystone species [dataset] • Final project report [written]

The approximate extent of seabird colonies on Scullin Monolith, Mac.Robertson Land, Antarctica in 1986/87.

The species include Adélie Penguin, Antarctic Petrel, Cape Petrel, Southern Fulmar and South Polar Skua.

Database created for replication of GeoStoryTelling. Our life stories evolve in specific and contextualized places. Although our homes may be our primarily shaping environment, our homes are themselves situated in neighborhoods that expose us to the immediate “real world” outside home. Indeed, the places where we are currently experiencing, and have experienced life, play a fundamental role in gaining a deeper and more nuanced understanding of our beliefs, fears, perceptions of the world, and even our prospects of social mobility. Despite the immediate impact of the places where we experience life in reaching a better understanding of our life stories, to date most qualitative and mixed methods researchers forego the analytic and elucidating power that geo-contextualizing our narratives bring to social and health research. From this view then, most research findings and conclusions may have been ignoring the spatial contexts that most likely have shaped the experiences of research participants. The main reason for the underuse of these geo-contextualized stories is the requirement of specialized training in geographical information systems and/or computer and statistical programming along with the absence of cost-free and user-friendly geo-visualization tools that may allow non-GIS experts to benefit from geo-contextualized outputs. To address this gap, we present GeoStoryTelling, an analytic framework and user-friendly, cost-free, multi-platform software that enables researchers to visualize their geo-contextualized data narratives. The use of this software (available in Mac and Windows operative systems) does not require users to learn GIS nor computer programming to obtain state-of-the-art, and visually appealing maps. In addition to providing a toy database to fully replicate the outputs presented, we detail the process that researchers need to follow to build their own databases without the need of specialized external software nor hardware. We show how the resulting HTML outputs are capable of integrating a variety of multi-media inputs (i.e., text, image, videos, sound recordings/music, and hyperlinks to other websites) to provide further context to the geo-located stories we are sharing (example https://cutt.ly/k7X9tfN). Accordingly, the goals of this paper are to describe the components of the methodology, the steps to construct the database, and to provide unrestricted access to the software tool, along with a toy dataset so that researchers may interact first-hand with GeoStoryTelling and fully replicate the outputs discussed herein. Since GeoStoryTelling relied on OpenStreetMap its applications may be used worldwide, thus strengthening its potential reach to the mixed methods and qualitative scientific communities, regardless of location around the world. Keywords: Geographical Information Systems; Interactive Visualizations; Data StoryTelling; Mixed Methods & Qualitative Research Methodologies; Spatial Data Science; Geo-Computation.

GIS-Sebahagian Senarai Inventori Pokok Presint 1 sehingga Mac 2018

GIS-Sebahagian Senarai Inventori Pokok Presint 3 sehingga Mac 2018

OWTS Community Clusters were grouped based on parcels intersecting the APMP boundary and presence adjacent to a city sphere of influence or sanitation distraction, or those that share the same supervisor district, MAC, or resource conservation district (RCD). The RCD boundary was modified to include parcels which were excluded from the original RCD dataset.Fields:OWTSCategory: known or suspectedAPN: from parcel dataUseCode: from parcel dataUseCodeDescription: from parcel dataUseCodeType: from parcel dataSitusFormatted: from parcel dataBuildingPrimaryUnitCount: from parcel dataBuildingPrimaryYearBuilt: from parcel dataBuildingSecondaryUnitCount: from parcel dataVacationRental: vacation rental informationGMResult: GAMA wells nitrate levels that exceed 10 mg/LGMUnits: units for GMResultSystemType: concatenated from OWTS permitsImplications: whether system type implies a standard or non-standard OWTSOWTSCount: assumed number of OWTSOWTSPermits: number of OWTS permitsAcres: parcel acresinOWTSDensityID: cluster ID for OWTS parcel density categories (see criteria report)ClusterDensityExceeded: is maximum allowable density exceeded for density cluster?GovCity: city majority of the parcel is withinGovWaterSys: water system majority of parcel is withinGovResourceConserv: resource conservation district majority of parcel is withinGovSupervisorMAC: supervisor MAC majority of parcel is withinGovSupervisorDist: supervisor district majority of parcel is withinGovTribal: tribal area majority of parcel is withinGovDACBlock: DAC block group majority of parcel is withinGovSDACBlock: SDAC block group majority of parcel is withinGovDACTract: DAC tract majority of parcel is withinGovSDACTract: SDAC tract majority of parcel is withinIntersectsAPMP: does the parcel intersect an APMPStillWater200ft: is the parcel within 200-ft of still waterFlowingWater100ft: is the parcel within 200-ft of flowing waterGWBasin: is the parcel in a groundwater basin?WWTreatmentPlantHalfMi: is there a wastewater treatment plant within a half mile of the parcel?StreamHighPointBuffer: intersects with 200 or 400ft buffer from stream's high point depending on distance to intake pointWells100ft: is there a drinking water well within 100-ft of the parcel?UtilityLineDistance: distance to closest utility line based on available data (see criteria report)ElecEsmntPrcl: distance to closest electric easement parcelGasEsmntPrcl: distance to closest gas easement parcelMeanSlope: average slope (percent rise) on the parcelRtngSepTnkDC: Rating for Septic Tank Absorption Fields - Dominant ConditionF2Floodplain: is the parcel in an F2 floodplainF1Floodway: is the parcel in an F1 floodwayHUC12Name: name of the HUC12 watershed the parcel falls. Uses majority for parcels that fall in multiple.OWTSCommunityID: community cluster IDCommunityCluster: is the parcel in a community cluster?CommunityGroup: what criteria was used to create the groupCommunityGrouping: the jurisdictions the parcel was grouped according toTechRating: technical score rating for the parcelCreatedDate: date analysis was run

Macon Transit Authority bus Routes. For more information about Macon Transit Authority visit http://mta-mac.com.

The Federal Housing Enterprises Financial Safety and Soundness Act of 1992 establishes a duty for Fannie Mae and Freddie Mac (the Enterprises) to serve the housing needs of very low-, low-, and moderate-income families in rural areas. FHFA has issued a final rule that provides eligibility for Duty to Serve credit for Enterprise mortgage purchases and other activities in “rural areas,” as defined in the rule. Additionally, the final rule specifies supportfor high-needs rural regions as a Regulatory Activity that the Enterprises may consider when developing their plans for the Duty to Serve program. FHFA’s 2017 Rural Areas File designates census tracts in the Metropolitan Statistical Areas (MSAs) and outside of MSAs of the 50 states, the District of Columbia, and Puerto Rico that are considered rural areas or non-rural areas under the final rule. The File also identifies whether census tracts are located in “high-needs” counties in order to determine whether tracts meet the definition of “high-needs rural regions” in the final rule.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/BusinessEconomy/MD_HousingDesignatedAreas/FeatureServer/5

Identifies the locations where red light cameras have been installed on regional roads and under the jurisdiction of the Regional Municipality of York.

The Federal Housing Finance Agency (FHFA) is an independent regulatory agency that is not part of the Department of Housing and Urban Development (HUD).

The FHFA was established by the Housing and Economic Recovery Act of 2008 (HERA) and is responsible for the effective supervision, regulation, and housing mission oversight of Fannie Mae, Freddie Mac (the Enterprises), Common Securitization Solutions, LLC (CSS), and the Federal Home Loan Bank System, which includes the 11 Federal Home Loan Banks (FHLBanks) and the Office of Finance. Since 2008, FHFA has also served as conservator of Fannie Mae and Freddie Mac.

Conforming Loan Limits are mortgage limits set annually (as required by HERA) by the FHFA. In order for a mortgage loan to be eligible to be insured by Freddie Mac or Fannie Mae, the loan amount must be less than the loan limit. Mortgage exceeding the Conforming Loan Limit are referred to as "non-conforming loans" or "jumbo loans." While most counties use a single set of Conforming Loan Limits based on the number of units, high cost of living counties use higher Conforming Loan Limits. The FHFA analyzes year-over-year change in average home prices in October of each year using the Monthly Interest Rate Survey (MIRS) to adjust the Conforming Loan Limits for the upcoming year.

Geospatial data in this feature service uses the Census 2010 County geographies.

To learn more about about the FHFA, please visit:https://www.fhfa.gov/AboutUs



For more information about FHFA Conforming Loan Limits, please visit:https://www.fhfa.gov/DataTools/Downloads/Pages/Conforming-Loan-Limits.aspx, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. 

Date of Coverage: 2022 Data Dictionary:DD_FHFA Conforming Loan Limits

Attachment regarding request by MAC Development Company for subdivision final plat approval of Cedar Grove Subdivision, Phase V, consisting of 7 lots on 23 acres, located off SR-1540, Jones Ferry Road, Baldwin Township.