**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Ownership_Layers/MapServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Base_Layers/MapServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Base_Layers/FeatureServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Water_Estate_Layers/MapServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Water_Estate_Layers/FeatureServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Surface_Classification/FeatureServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Land_Estate_Layers/FeatureServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Ownership_Layers/FeatureServer

**Suggested to use 'Download' button instead of 'Open in ArcGIS Pro'The REST service page displays all data provided in this layer package: https://arcgis.dnr.alaska.gov/arcgis/rest/services/Mapper/Mineral_Estate_Layers/MapServer

State of Alaska tax parcel data by authoritative data source. This map is for use within the Alaska Geospatial Council Cadastre Technical Working Group's Hub site.

RS 2477 stands for Revised Statute 2477 from the Mining Act of 1866, which states:

"The right-of-way for the construction of highways over public lands, not reserved for public uses, is hereby granted."

The act granted a public right-of-way across unreserved federal land to guarantee access as land transferred to state or private ownership. Rights-of-way were created and granted under RS 2477 until its repeal in 1976. In Alaska, federal land was "reserved for public uses" in December 1968, with passage of PLO 4582, also known as the "land freeze." This date ends the window of RS 2477 qualification in Alaska.

This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the RS2477 Trails category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction.

Each feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.

The November 30, 2018, magnitude (Mw) 7.1 Anchorage, Alaska earthquake triggered substantial ground failure throughout Anchorage and surrounding areas (Grant and others, 2020; Jibson and others, 2020). The earthquake was an intraslab event with a focal depth of about 47 km and an epicenter about 16 km north of the city of Anchorage. Peak ground accelerations reached ∼30% g. Despite the relatively low severity of most of the ground failure occurrences, geotechnical damage to buildings and structures was widespread (Franke and others, 2019). Here, we present an inventory of the earthquake-triggered ground failure based on information compiled from numerous data sources. The inventory is comprised of 886 points that each correspond to the location of earthquake triggered ground failure associated with the 2018 event (Figure 1). For each instance of ground failure, the direct observation is reported and, where possible, is categorized based on the process interpreted to have caused it. For example, an observation of a rock fall would be categorized as a landslide. Similarly, a sand boil would be categorized as evidence of liquefaction. Where possible, the features were more precisely mapped with an additional polygon (n=179) and or line feature (n=32). To determine the existence and location of ground failure features, we relied on a variety of mapping methods and data sources. As such, the certainty in the mapping of each feature within the inventory varies (Figure 2). Details on how uncertainty is reported as well as the methods and data sources used are discussed in the following sections. Data and Methods The inventory was compiled using a variety of different sources and methods with varying levels of success (Martinez and others, 2021). To convey this, the overall mapping certainty for each feature within the inventory is determined by assigning a semi-quantitative grade for categories related to the certainty of the existence of the feature, the positional accuracy of the mapped feature, and the mapped delineation quality. Those categories are denoted as presence, location, and delineation certainty in the inventory attribute table. Confidence grade definitions, and all other inventory attributes, are described in Table 1. As previously mentioned, we relied on a variety of methods and data sources to develop the ground failure inventory. We primarily relied on field observation data and information shared from federal, state, and local agencies. These data sources were particularly helpful where remotely sensed data were not available or insufficient for mapping ground failure. Here, we summarize how remotely sensed data were used and in which ways they were advantageous or insufficient. High resolution digital elevation models (DEMs) are typically used to develop high-quality ground failure inventories. We began our ground failure mapping efforts by differencing high resolution pre- and post-earthquake lidar derived DEMs from the Alaska Department of Natural Resources (AK DNR) Division of Geological and Geophysical Surveys (DGGS) elevation portal (DGGS Elevation Portal (alaska.gov)). The pre- and post-earthquake DEMs used to identify and map the extent of ground failure in this study had an areal overlap of approximately 321 km2. These data cover only a small portion of the area that experienced moderate to severe shaking during the earthquake (60,690 km2) as estimated from the USGS ShakeMap. In regions lacking sufficient DEM coverage we used Normalized Difference Vegetation Index (NDVI) differencing to identify and map ground failure. NDVI maps are derived from multispectral imagery and display the relative health or existence of vegetation in a landscape. For this study, NDVI maps were derived using imagery from the European Space Agency’s Sentinel-2 (S2) Multispectral Instrument (MSI) (Drusch and others, 2012). Ground failure that is severe enough to disturb vegetation can be mapped by differencing pre- and post- earthquake NDVI maps. However, efforts to create NDVI maps of the landscape following the earthquake were hindered due to snowfall that began to accumulate shortly after the earthquake (2 December 2018). To overcome this limitation, we used Google Earth Engine (Gorelick and others, 2017) to create composites of multispectral images of the summers (May 1 to July 30) before and after the earthquake instead. The image composites were then used to create NDVI maps that were differenced to determine where there were any significant changes in vegetation that could potentially correspond to ground failure. While the resolution of the data used for the NDVI differencing (10-m) is lower than that used for DEM differencing (1-m) it is advantageous as it is available globally, and thus, for the entire earthquake affected region of Southcentral, Alaska. Despite the advantage of globally available NDVI data, the method is still limited in its ability to detect smaller and more subtle vegetation changes. Our comparisons may also include some landslides that were not triggered by the earthquake but happened in the time spanned by the images. When possible, satellite and aerial imagery alone were also used to map ground failure features. However, in most instances the imagery alone was inadequate for mapping because many features were not visible in available satellite imagery. In addition, the ground surface was obscured in satellite imagery as a result of snow fall that occurred shortly after the earthquake. Some features, such as large road cracks, were not visible following snowmelt as they were quickly repaired by The Alaska Department of Transportation and Public Facilities. Other ephemeral features, such as sand boils or cracks on tidal flats, were no longer visible in satellite imagery after snowmelt and several tidal cycles. Remotely sensed data alone were found to be insufficient for mapping ground failure associated with this event (see Martinez and others, 2021). In addition to the limitations of remotely sensed data, the aforementioned snowfall that occurred immediately after the earthquake obscured large swaths of land and subsequently hindered efforts to gather ground failure observations while in the field. Thus, in addition to the remotely sensed data, the inventory was supplemented with field observations gathered by U.S. Geological Survey scientists shortly after the event (Grant and others, 2020), information on earthquake damage supplied from federal (FEMA Region X), state (The Alaska Department of Transportation and Public Facilities) and local agencies (Municipality of Anchorage, Kenai Peninsula Borough, Matanuska-Susitna Borough Department of Emergency Services, 673 Civil Engineers Squadron at the Joint Base Elmendorf-Richardson, Anchorage Fire Station 12) as well as compiled social media information and data from literature on the 2018 earthquake event. Using the data mentioned above, we inferred which ground failure process to assign to each ground failure location based on contextual information such as the environment and presence of evidence that suggests ground failure may have occurred. We assigned the “landslide” process to locations where there are indications of the downhill movement of material. A modified classification scheme based on Keefer (1984) was used to classify the observed landslide features within our inventory (see Table 1 for landslide classification scheme). Evidence that liquefaction processes may have occurred include the presence of ground cracks, sand boils, lateral spreads, the settlement of structures, and rapid soil flows. In cases where direct evidence of liquefaction is lacking (i.e., sand boils), the classification is based on proximity to identified sand boils. Liquefaction was interpreted to be the process for observed lateral spreading features parallel to water bodies. Low-lying features on flat slopes (e.g., settlement alone) for which there is no direct evidence to suggest that liquefaction occurred are given the label “Liquefaction (Ambiguous)” to reflect the uncertain nature in their process designation. Despite the use of supplemental data, the inventory is still considered incomplete, with varying levels of completeness throughout the region. Adverse environmental conditions including snow fall, limited daylight hours, a large earthquake-affected area, and accessibility constraints limited the extent to which both field and remotely sensed observations could be reliably used to compile a ground failure inventory. To communicate this variability in inventory completeness and quality, Figure 2 displays the region, highlighted in white, in which direct observations of ground failure were made in addition to where high-resolution pre- and post-earthquake lidar data are available. This higher-confidence mapping region displays where the inventory is considered complete and high quality due to the nature of the data (i.e., direct observations, high-quality lidar) used for mapping in this region. To minimize human error, two co-authors carefully reviewed the inventory for inconsistencies and errors. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References Cited: Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., Meygret, A., Spoto, F., Sy, O., Marchese, F., and Bargellini, P., 2012, Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services: Remote Sensing of Environment, v. 120, p. 25–36. https://doi.org/10.1016/j.rse.2011.11.026 Franke, K.W., Koehler, R., Beyzaei, C.Z., Cabas, A., Christie, S., Dickenson, S., Pierce, I., Stuedlein, A., and Yang, Z., 2019, Geotechnical Engineering Reconnaissance of the 30 November 2018 Mw 7.1 Anchorage, Alaska Earthquake, Version 2.0: Geotechnical Extreme Events Reconnaissance Association. Gorelick, N., Hancher,

The Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed Standards for Production of Alaska Vegetation Map Version 1.1 (August 2022) to set technical goals for the production of a vegetation map that consistently covers all of Alaska with high spatial and ecological resolution. We compared vegetation maps and mapping frameworks with statewide coverage to the standards to determine the most appropriate map to select as the implementation of a statewide map and found that the AKVEG Map is the only map or mapping framework that fulfills all VTWG goals.

A mineral closing order closes state land to all forms of mineral entry, making it unavailable for staking mining claims, leasehold locations or prospecting site locations (A.S. 38.05.195, 38.05.205 AND 38.05.245).

A mineral opening order reopens land closed to mineral entry by a previous mineral closing order.

This shape file characterizes the geographic representation of land parcels within the State of Alaska contained by the Mineral Closing, Opening Order category. It has been extracted from data sets used to produce the State status plats. This data set includes cases noted on the digital status plats up to one day prior to data extraction.

Each feature has an associated attribute record, including a Land Administration System (LAS) file-type and file-number which serves as an index to related LAS case-file information. Additional LAS case-file and customer information may be obtained at: http://dnr.alaska.gov/projects/las/ Those requiring more information regarding State land records should contact the Alaska Department of Natural Resources Public Information Center directly.

The Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed Standards for Production of Alaska Vegetation Map Version 1.1 (August 2022) to set technical goals for the production of a vegetation map that consistently covers all of Alaska with high spatial and ecological resolution. We compared vegetation maps and mapping frameworks with statewide coverage to the standards to determine the most appropriate map to select as the implementation of a statewide map and found that the AKVEG Map is the only map or mapping framework that fulfills all VTWG goals.

The Vegetation Technical Working Group (VTWG) of the Alaska Geospatial Council developed the Standards for Mapping Vegetation in Alaska Version 1.1 (August 2022) to promote consistency among independently produced local, regional, and statewide vegetation maps for Alaska.

Communities, Boroughs, and Regions of Alaska Map - Shows Communities, Boroughs, Regional Education Attendance Areas, and Native Corporations in Alaska. Also shows the current DCCED Certified population counts for all incorporated communities and boroughs. This map is updated yearly after certification of new population numbers, or on an as-needed basis to reflect changes in the data represented on the map. If you see an error on this map, please email dcraresearchandanalysis@alaska.govUpdated for 2024 DCCED Certified Populations. Updated 6/1/2025Note to GIS Admin: DO NOT DELETE. To publish a new version, use the UDPADE button.

Users should note that there is a shift in the position of quad sheet boundaries between NAD27 and NAD83 and should choose the appropriate quad boundaries for their mapping needs.

This is the main page for the Alaska Geospatial Council's Coastal and Ocean Technical Working Group.

Operational level forest inventory data was acquired in 2019 and provided the basis for mapping, quantifying and assessing area-wide forest and commercial timber resources and for establishing the AAC for SSE. Forest inventory data from 2019 and the analysis in 2020 provides the following forest management benefits: Updated Timber Type data layer (map) contained in the State’s GIS for SSE Data acquired and analyzed through the forest inventory project was entered into the State’s GIS to create an updated timber type layer (map) of the commercial forest timber base in SSE containing individual timber stands. Updated timber type descriptors for each individual stand include stand species composition, stand density and per acre timber volume. SSE Forest Inventory Report July 17, 2020 4 Using the GIS to analyze the relationships between the commercial timber resource and other forest resources (transportation network, fish and wildlife habitat, cultural resources, etc.) allows the DOF to undertake and complete complex forest planning documents such as the Five-Year Schedules of Timber Sales (FYSTS), and Forest Land Use Plans (FLUPs) used to guide both broad scale and site-specific forest management activities. The GIS also allows DOF to track changes to the commercial timber base resulting from management activities including timber harvest, stand regeneration/reforestation, and timber stand improvement projects such as precommercial tree thinning. Updated Annual Allowable Cut for SSE The GIS timber type map for SSE, updated with the 2019 forest inventory data, formed the basis for area (acreage) and timber volume (board feet) figures necessary to calculate an updated AAC. The new GIS timber type map and associated data files along with newly available LiDAR data provided the raw data necessary to perform the growth and yield modelling to estimate timber volume and characteristics in the developing young growth stands over the course of the rotation.