Vector polygon map data of property parcels from the State of Arizona containing 1,422,231 features.

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Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.

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Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.

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Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.

Arizona State Land Department Beneficiaries

The purpose of this dataset is to fulfill the public and Government’s need to know which agency is managing Federal land in a given area. For example, there may be a need to know what agency is managing a certain tract of land for the purpose of paying permit fees, obtaining licenses, or becoming informed about current laws, regulations, and restrictions governing access to and use of the land. This dataset serves as a tool to determine and illustrate the boundaries of a particular Federal agency’s “managing” area and to quantify these areas in terms of geographic acreage. These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities. The geographic acreages contained in this dataset are not derived from legal documents associated with title documents or survey records. Rather, they are computed by mathematical programs and are described in detail in the supplemental section of the definition document referenced at the end of this section.The data can be used for small scale (1:24,000 and smaller) analysis and cartographic products.SMA was originally derived from the land dataset produced by the Arizona State Land Dept (ASLD), and the Arizona Land Resource Information System (ALRIS). The land dataset was initiated in 1984 and updated in the spring of 1988 by the State Land Department Forestry Division and ALRIS. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD Land Status Map Digitizing Procedure guide. The land dataset covers the entire State of Arizona and includes surface management, public land survey system (PLSS) provided by the Department of Transportation (ADOT), and county and state boundaries.

This dataset is known as Surface Management Agency (SMA) and was originally derived from the LAND dataset produced by the Arizona State Land Dept., Arizona Land Resource Information System (ALRIS). The LAND dataset was first started in 1984 and updated in the spring 1988 by the State Land Department Forestry Division and ALRIS. The original PLSS data is from the Department of Transportation (ADOT) and was digitized at 1:100,000 scale. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD 'Land Status Map Digitizing Procedure' guide. The dataset covers the entire State of Arizona. Changes in federal agencies are done through the Bureau of Land Management (BLM). BLM incorporates the federal land changes such as the BLM, Forest Service, Bureau of Reclamation, Fish & Wildlife Service, National Park Service, etc. BLM and State of Arizona surface management is updated approximately every six months in a cooperative effort with the Arizona State Land Department (ASLD). In 2011, the BLM contracted with Premier Data Services to conflate the SMA with the latest and more accurate PLSS known as the Cadastral National Spatial Data Infrastructure (CadNSDI) which is the most accurate PLSS available. This procedure has greatly improved the locational accuracy of the SMA. For purposes of simplicity, the BLM has also reduced the complexity of the dataset by removing all data except for the surface management information.

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

This data set is known as Surface Management Agency (SMA) and was originally derived from the LAND data set produced by the Arizona State Land Dept., Arizona Land Resource Information System (ALRIS). The LAND data set was first started in 1984 and updated in the spring 1988 by the State Land Department Forestry Division and ALRIS. The original PLSS data is from the Department of Transportation (ADOT) and was digitized at 1:100,000 scale. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD 'Land Status Map Digitizing Procedure' guide. The data set covers the entire State of Arizona and includes surface management, the original plss, and county and state boundaries. Changes in federal agencies are done through the Bureau of Land Management (BLM). BLM incorporates the federal land changes such as the BLM, Forest Service, Bureau of Reclamation, Fish & Wildlife Service, National Park Service, etc. BLM and State of Arizona surface management is updated approximately every six months in a cooperative effort with the Arizona State Land Department (ASLDIn 2011, the BLM contracted with Premier Data Services to conflate the SMA with the latest and more accurate PLSS know as the Cadastral National Spatial Data Infrastructure (CadNSDI) which is the most accurate PLSS available. This procedure has greatly improved the locational accuracy of the SMA. For purposes of simplicity, the BLM has also reduced the complexity of the data set by removing all data except for the surface management information.

The EnviroAtlas Phoenix, AZ Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near-infrared) aerial photography taken from June through September, 2010 at 1 m spatial resolution. Seven land cover classes were mapped: water, impervious surfaces, soil and barren land, trees and forest, shrubs, grass and herbaceous non-woody vegetation, and agriculture. An accuracy assessment using a completely random sampling of 598 land cover reference points yielded an overall user's accuracy (MAX) of 69.2% and an overall fuzzy user's accuracy of 75.4%. The area mapped includes the entirety of the Central Arizona-Phoenix Long-Term Ecological Research (CAP-LTER) area, which was classified by the Environmental Remote Sensing and Geoinformatics Lab (ERSG) at Arizona State University. The land cover dataset also includes an area of approximately 625 square kilometers which is located north of Phoenix. This section was classified by the EPA land cover classification team. This dataset was produced by the Environmental Remote Sensing and Geoinformatics Lab (ERSG) at Arizona State University and the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Annual (1986-2020) land-use/land cover maps at 30-meter resolution of the Tucson metropolitan area, Arizona and the greater Santa Cruz Watershed including Nogales, Sonora, Mexico. Maps were created using a combination of Landsat imagery, derived transformation and indices, texture analysis and other ancillary data fed to a Random Forest classifier in Google Earth Engine. The maps contain 13 classes based on the National Land Cover Classification scheme and modified to reflect local land cover types. Data are presented as a stacked, multi-band raster with one "band" for each year (Band 1 = 1986, Band 2 = 1987 and so on). Note that the year 2012 was left out of our time series because of lack of quality Landsat data. A color file (.clr) is included that can be imported to match the color of the National Land Cover Classification scheme. This data release also contains two JavaScript files with the Google Earth Engine code developed for pre-processing Landsat imagery and for image ...

This is the digitized version of a map of the Hohokam canal system in what is now the Phoenix metropolitan area. It is based on the thesis research by J. B. Howard (Howard, J. (1990). Paleohydraulics : techniques for modeling the operation and growth of prehistoric canal systems. Thesis (M.A.)--Arizona State University, 1990). The original paper map is based on previous archaeological data, overlayed onto USGS 7.5 minute quadrangle maps to recreate the canal pattern.

This dataset has been created to meet the needs of the research community of Arizona State University. Apart from purely vizualization purposes (i.e. displaying the data on various maps) it can potentially be used for spatial modeling. The data consist of engineering-quality contours, also known as isolines, created from the NED 10-meter Digital Elevation Model subset to the extent somewhat exceeding Cetral Arizona - Phoenix LTER. Contours ( lines connecting points of equal height above sea level) are drawn at 15 meter intervals with the base set at 145 m of elevation. Contours are an exact interpretation of the grid surface model and may sometimes appear blocky looking, may cross, appear to intersect, or form an unclosed branching line. All these are valid engineering-quality interpretations of the elevation surface that cartographers typically modify (smooth) for aesthetic purposes.

This dataset includes the polygon features representing the spatial extent and boundaries of the Bureau of Land Management (BLM) National Landscape Conservation System (NLCS) Wilderness Areas (WLD), Wilderness Study Areas (WSA), and Other Related Lands with wilderness characteristics (LWC) or managed for wilderness characteristics (MWC).The data standard for these boundaries will assist in the management of all eleven designations within the NLCS. Particularly, NLCS data pertains to the following BLM groups and their purposes: Land Use Planners, GIS Specialists, NLCS team leads, BLM managers, and public stakeholder groups.As early as 1926, the earliest advocates of wilderness preservation had acknowledged the beauty and important ecological values of the desert lands under the BLM’s administration as candidates for wilderness protection. In 1964, Congress established the National Wilderness Preservation System and designated the first Wilderness Areas in passing the Wilderness Act. The uniquely American idea of wilderness has become an increasingly significant tool to ensure long-term protection of natural landscapes. Wilderness protects the habitat of numerous wildlife species and serves as a biodiversity bank for many species of plants and animals. Wilderness is also a source of clean water.The Federal Land Policy and Management Act of 1976 directed the BLM to inventory and study its roadless areas for wilderness characteristics. Here identified areas became WSAs. The establishment of a WSA served to identify areas for Congress to consider for addition to the National Wilderness Preservation System. To be designated as a WSA, an area must have the following characteristics: Size - roadless areas of at least 5,000 acres of public lands or of a manageable size; Naturalness - generally appears to have been affected primarily by the forces of nature; Opportunities - provides outstanding opportunities for solitude or primitive and unconfined types of recreation. In addition, WSAs often have special qualities such as ecological, geological, educational, historical, scientific and scenic values.In June 2000, the BLM responded to growing concern over the loss of open space by creating the NLCS. The NLCS brings into a single system some of the BLM's premier designations. The Wilderness Areas, WSAs, and Other Related Lands represent three of these eleven premier designations. By putting these lands into an organized system, the BLM hopes to increase public awareness of these areas' scientific, cultural, educational, ecological and other values.The BLM's management of all public lands included data within the NLCS is guided by the Federal Land Policy and Management Act (FLPMA). FLPMA ensures that many of BLM's traditional activities such as grazing and hunting, continue on the lands within the NLCS, provided these activities are consistent with the overall purpose of the area.A Wilderness is a special place where the earth and its community of life are essentially undisturbed; they retain a primeval character, without permanent improvements and generally appear to have been affected primarily by the forces of nature. BLM NLCS Other Related Lands are lands not in Wilderness or WSAs that have been determined to have wilderness character through inventory or land use planning. These lands fall into one of two categories. The first category are lands with "wilderness value and characteristics". These are inventoried areas not in Wilderness or WSAs that have been determined to meet the size, naturalness, and the outstanding solitude and/or the outstanding primitive and unconfined recreation criteria. The second category are "wilderness characteristic protection areas". These are former lands with "wilderness value and characteristics" where a plan decision has been made to protect them.To be designated as a WSA, an area must have the following characteristics: Size - roadless areas of at least 5,000 acres of public lands or of a manageable size; Naturalness - generally appears to have been affected primarily by the forces of nature; Opportunities - provides outstanding opportunities for solitude or primitive and unconfined types of recreation. In addition, WSAs often have special qualities such as ecological, geological, educational, historical, scientific and scenic values.There were forty-seven Wilderness Areas established under the Arizona Wilderness Act of 1984 and Arizona Desert Wilderness Act of 1990. These Acts require the BLM to file boundary legal descriptions and maps to Congress for each Wilderness Area. The standards, format, and language for the legal descriptions and boundary maps were developed during regular meetings of the NLCS Coordinator, GIS specialists and the Cadastral Surveyors. Guidance was provided from congressionally-required map and legal boundary descriptions detailed in the NLCS Designation Manual 6120 (March, 2010). All Arizona BLM Wilderness Area boundary legal descriptions and maps have been transmitted to Congress and certified by the Chief of Cadastral Survey and Arizona State Director. There should be no changes to Wilderness Boundary GIS data. Boundary changes can only be made through an amendment to the legal description and this would need to be sent back to Congress.

We created a single map of surface water presence by intersecting water classes from available land cover products (National Wetland Inventory, Gap Analysis Program, National Land Cover Database, and Dynamic Surface Water Extent) across the U.S. state of Arizona. We derived classified samples for four wetland classes from the harmonized map: water, herbaceous wetlands, wooded wetlands, and non-wetland cover. In Google Earth Engine (GEE) we developed a random forest model that combined the training data with spatially explicit predictor variables of vegetation greenness indices, wetness indices, seasonal index variation, topographic variables, and hydrologic parameters. The final product is a wall-to-wall map of general wetland types covering all of Arizona. Results show that the final model separates the four wetland classes with an overall accuracy of 86.2%. This data release comprises the raster map file (TIF format) resulting from the training data and random forest model. The 30-m resolution map has 4 classes: not water or wetland (class 0), open water (class 1), herbaceous wetland (class 2), and wooded wetland (class 3).

The United States, Caribbean and Pacific Basin Major Land Resource Areas (MLRA) Geographic Database serves as the geospatial expression of the map products presented and described in Agricultural Handbook 296 (2006). Land resource categories historically used at State and national levels are land resource units, land resource areas, and land resource regions. Land resource units (LRUs) are the basic units from which major land resource areas (MLRAs) are determined. They are also the basic units for State land resource maps. LRUs are typically coextensive with State general soil map units, but some general soil map units are subdivided into LRUs because of significant geographic differences in soils, climate, water resources, or land use. LRUs generally are several thousand acres in size. A unit can be one continuous area or several separate areas that are near each other. In 2005, these areas were designated as common resource areas (CRAs) within the Natural Resources Conservation Service (NRCS).CRAs are created by subdividing MLRAs by topography, other landscape features, hydrologic units, resource concerns, resource uses, and human considerations affecting use and soil and water conservation treatment needs. Common resource areas, or land resource units, are not described in this handbook and are not shown on the national map. Major land resource areas are geographically associated land resource units. Land resource regions are a group of geographically associated major land resource areas. Identification of these large areas is important in statewide agricultural planning and has value in interstate, regional, and national planning. In order to make this handbook more useful to other Federal agencies and private parties using ecological regions for planning or evaluation of natural resources programs and policies, Appendix I (Agriculture Handbook 296, 2006) cross-references MLRAs with Environmental Protection Agency Level III Ecoregions (USEPA, 2003; Omernik,

description: Forests and Forest Cover dataset current as of 2004. Natural Vegetation - Digital representation of Brown and Lowe's "Biotic Communites of the Southwest" map (1979) developed by The Nature Conservancy in Arizona (2004)..; abstract: Forests and Forest Cover dataset current as of 2004. Natural Vegetation - Digital representation of Brown and Lowe's "Biotic Communites of the Southwest" map (1979) developed by The Nature Conservancy in Arizona (2004)..

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe’s Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe’s Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS.

This map depicts existing and future land use conditions for Maricopa County, Arizona. The Existing Land Use data are derived from Maricopa County Assessor parcels, public land data from Arizona State Land Department, and numerous other sources.

This location is part of the Arizona Mineral Industry Location System (AzMILS), an inventory of mineral occurences, prospects and mine locations in Arizona. Yavapai1392 is located in T13N R4W Sec 11 NW in the Kirkland - 7.5 Min quad. This collection consists of various reports, maps, records and related materials acquired by the Arizona Department of Mines and Mineral Resources regarding mining properties in Arizona. Information was obtained by various means, including the property owners, exploration companies, consultants, verbal interviews, field visits, newspapers and publications. Some sections may be redacted for copyright. Please see the access statement.

This is map 2 of a 7-map series depicting the Havasu Travel Management Area (TMA) as administered by the Bureau of Land Management. Travel is restricted to designated roads and trails as defined in the map.

This is map 1 of a 7-map series depicting the Havasu Travel Management Area (TMA) as administered by the Bureau of Land Management. Travel is restricted to designated roads and trails as defined in the map.

This data set is known as Surface Management Agency (SMA) and was originally derived from the LAND data set produced by the Arizona State Land Dept., Arizona Land Resource Information System (ALRIS). The LAND data set was first started in 1984 and updated in the spring 1988 by the State Land Department Forestry Division and ALRIS. The original PLSS data is from the Department of Transportation (ADOT) and was digitized at 1:100,000 scale. The data was then projected into ARC/INFO format and edited using the procedures from the ASLD 'Land Status Map Digitizing Procedure' guide. The data set covers the entire State of Arizona and includes surface management, the original plss, and county and state boundaries. Changes in federal agencies are done through the Bureau of Land Management (BLM). BLM incorporates the federal land changes such as the BLM, Forest Service, Bureau of Reclamation, Fish & Wildlife Service, National Park Service, etc. BLM and State of Arizona surface management is updated approximately every six months in a cooperative effort with the Arizona State Land Department (ASLDIn 2011, the BLM contracted with Premier Data Services to conflate the SMA with the latest and more accurate PLSS know as the Cadastral National Spatial Data Infrastructure (CadNSDI) which is the most accurate PLSS available. This procedure has greatly improved the locational accuracy of the SMA. For purposes of simplicity, the BLM has also reduced the complexity of the data set by removing all data except for the surface management information.