FOR PLAT MAPS AND OTHER LAND DOCUMENTS, PLEASE VISIT THE COUNTY CLERK’S OFFICIAL RECORDS SEARCH: HTTPS://BEXAR.TX.PUBLICSEARCH.US.The Bexar County GIS Team does not have purview over plat maps and other land records. Please visit the Bexar County Clerk’s Official Records Search.

This dataset is about books. It has 1 row and is filtered where the book is The encyclopedia of nineteenth-century land warfare : an illustrated world view. It features 7 columns including author, publication date, language, and book publisher.

Dataset SummaryPlease note: this data is live (updated nightly) to reflect the latest changes in the City's systems of record.About this data:The operational purpose of the vacant land dataset is to facilitate the tracking and mapping of vacant land for the purposes of promoting redevelopment of lots to increase the City's tax base and spur increased economic activity. These properties are both City owned and privately owned. The vast majority of vacant lots are the result of a demolition of a structure that once stood on the property. Vacant lots are noted in the official tax parcel assessment records with a class code beginning with 3, which denotes the category vacant land.Related Resources:For a searchable interactive mapping application, please visit the City of Rochester's Property Information explorer tool. For further information about the city's property tax assessments, please contact the City of Rochester Assessment Bureau. To access the City's zoning code, please click here.Data Dictionary: SBL: The twenty-digit unique identifier assigned to a tax parcel. PRINTKEY: A unique identifier for a tax parcel, typically in the format of “Tax map section – Block – Lot". Street Number: The street number where the tax parcel is located. Street Name: The street name where the tax parcel is located. NAME: The street number and street name for the tax parcel. City: The city where the tax parcel is located. Property Class Code: The standardized code to identify the type and/or use of the tax parcel. For a full list of codes, view the NYS Real Property System (RPS) property classification codes guide. Property Class: The name of the property class associated with the property class code. Property Type: The type of property associated with the property class code. There are nine different types of property according to RPS: 100: Agricultural 200: Residential 300: Vacant Land 400: Commercial 500: Recreation & Entertainment 600: Community Services 700: Industrial 800: Public Services 900: Wild, forested, conservation lands and public parks First Owner Name: The name of the property owner of the vacant tax parcel. If there are multiple owners, then the first one is displayed. Postal Address: The USPS postal address for the vacant landowner. Postal City: The USPS postal city, state, and zip code for the vacant landowner. Lot Frontage: The length (in feet) of how wide the lot is across the street. Lot Depth: The length (in feet) of how far the lot goes back from the street. Stated Area: The area of the vacant tax parcel. Current Land Value: The current value (in USD) of the tax parcel. Current Total Assessed Value: The current value (in USD) assigned by a tax assessor, which takes into consideration both the land value, buildings on the land, etc. Current Taxable Value: The amount (in USD) of the assessed value that can be taxed. Tentative Land Value: The current value (in USD) of the land on the tax parcel, subject to change based on appeals, reassessments, and public review. Tentative Total Assessed Value: The preliminary estimate (in USD) of the tax parcel’s assessed value, which includes tentative land value and tentative improvement value. Tentative Taxable Value: The preliminary estimate (in USD) of the tax parcel’s value used to calculate property taxes. Sale Date: The date (MM/DD/YYYY) of when the vacant tax parcel was sold. Sale Price: The price (in USD) of what the vacant tax parcel was sold for. Book: The record book that the property deed or sale is recorded in. Page: The page in the record book where the property deed or sale is recorded in. Deed Type: The type of deed associated with the vacant tax parcel sale. RESCOM: Notes whether the vacant tax parcel is zoned for residential or commercial use. R: Residential C: Commercial BISZONING: Notes the zoning district the vacant tax parcel is in. For more information on zoning, visit the City’s Zoning District map. OWNERSHIPCODE: Code to note type of ownership (if applicable). Number of Residential Units: Notes how many residential units are available on the tax parcel (if applicable). LOW_STREET_NUM: The street number of the vacant tax parcel. HIGH_STREET_NUM: The street number of the vacant tax parcel. GISEXTDATE: The date and time when the data was last updated. SALE_DATE_datefield: The recorded date of sale of the vacant tax parcel (if available). Source: This data comes from the department of Neighborhood and Business Development, Bureau of Business and Zoning.

This layer represents current city parcels within the City of Los Angeles. It shares topology with the Landbase parcel lines feature class. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most current geographic information of the public right of way, ownership and land record information. The legal boundaries are determined on the ground by license surveyors in the State of California, and by recorded documents from the Los Angeles County Recorder's office and the City Clerk's office of the City of Los Angeles. Parcel and ownership information are available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Associated information about the landbase parcels is entered into attributes. Principal attributes include:PIN and PIND: represents the unique auto-generated parcel identifier and key to related features and tables. This field is related to the LA_LEGAL, LA_APN and LA_HSE_NBR tables. PIN contains spaces and PIND replaces those spaces with a dash (-).LA_LEGAL - Table attributes containing legal description. Principal attributes include the following:TRACT: The subdivision tract number as recorded by the County of Los AngelesMAP_REF: Identifies the subdivision map book reference as recorded by the County of Los Angeles.LOT: The subdivision lot number as recorded by the County of Los Angeles.ENG_DIST: The four engineering Districts (W=Westla, C=Central, V= Valley and H=Harbor).CNCL_DIST: Council Districts 1-15 of the City of Los Angeles. OUTLA means parcel is outside the City.LA_APN- Table attributes containing County of Los Angeles Assessors information. Principal attributes include the following:BPP: The Book, Page and Parcel from the Los Angeles County Assessors office. SITUS*: Address for the property.LA_HSE_NBR - Table attributes containing housenumber information. Principal attributes include the following:HSE_ID: Unique id of each housenumber record.HSE_NBR: housenumber numerical valueSTR_*: Official housenumber addressFor a complete list of attribute values, please refer to Landbase_parcel_polygons_data_dictionary.

© Randy Price Division Manager Mapping and Land Records Division Bureau of Engineering / Department of Public Works City of Los Angeles This layer is sourced from lacitydbs.org

A book of one km2 sampling cell habitat cover maps generated using the OSi PRIME 2 dataset (OSi 2022a) and enhanced using OSi orthoimagery and Google Street View interpretation. The book includes two sets of 15 sampling cells: 1) a baseline set generated using OSi Ortho 2000 imagery [reference year: 2000], and 2) a second, updated set generated using OSi Digital Globe imagery reference year: 2013

References: ​​OSi, 2022a. PRIME2 Data, The National Map. Ordinance Survey Ireland. ​〈https://osi.ie/about/future-developments/the-national-map/〉. (Accessed 1 May 2021).​ ​​OSi, 2022b. Aerial Imagery Maps and Data. Ordinance Survey Ireland. ​〈https://osi.ie/products/professional-mapping/osi-aerial-imagery/〉. (Accessed 1 May 2021).​

Please note: this data is live (updated nightly) to reflect the latest changes in the City's systems of record.Overview of the Data:This dataset is a polygon feature layer with the boundaries of all tax parcels owned by the City of Rochester. This includes all public parks, and municipal buildings, as well as vacant land and structures currently owned by the City. The data includes fields with features about each property including property type, date of sale, land value, dimensions, and more.About City Owned Properties:The City's real estate inventory is managed by the Division of Real Estate in the Department of Neighborhood and Business Development. Properties like municipal buildings and parks are expected to be in long term ownership of the City. Properties such as vacant land and vacant structures are ones the City is actively seeking to reposition for redevelopment to increase the City's tax base and economic activity. The City acquires many of these properties through the tax foreclosure auction process when no private entity bids the minimum bid. Some of these properties stay in the City's ownership for years, while others are quickly sold to development partners. For more information please visit the City's webpage for the Division of Real Estate: https://www.cityofrochester.gov/realestate/Data Dictionary: SBL: The twenty-digit unique identifier assigned to a tax parcel. PRINTKEY: A unique identifier for a tax parcel, typically in the format of “Tax map section – Block – Lot". Street Number: The street number where the tax parcel is located. Street Name: The street name where the tax parcel is located. NAME: The street number and street name for the tax parcel. City: The city where the tax parcel is located. Property Class Code: The standardized code to identify the type and/or use of the tax parcel. For a full list of codes, view the NYS Real Property System (RPS) property classification codes guide. Property Class: The name of the property class associated with the property class code. Property Type: The type of property associated with the property class code. There are nine different types of property according to RPS: 100: Agricultural 200: Residential 300: Vacant Land 400: Commercial 500: Recreation & Entertainment 600: Community Services 700: Industrial 800: Public Services 900: Wild, forested, conservation lands and public parks First Owner Name: The name of the property owner of the vacant tax parcel. If there are multiple owners, then the first one is displayed. Postal Address: The USPS postal address for the vacant landowner. Postal City: The USPS postal city, state, and zip code for the vacant landowner. Lot Frontage: The length (in feet) of how wide the lot is across the street. Lot Depth: The length (in feet) of how far the lot goes back from the street. Stated Area: The area of the vacant tax parcel. Current Land Value: The current value (in USD) of the tax parcel. Current Total Assessed Value: The current value (in USD) assigned by a tax assessor, which takes into consideration both the land value, buildings on the land, etc. Current Taxable Value: The amount (in USD) of the assessed value that can be taxed. Tentative Land Value: The current value (in USD) of the land on the tax parcel, subject to change based on appeals, reassessments, and public review. Tentative Total Assessed Value: The preliminary estimate (in USD) of the tax parcel’s assessed value, which includes tentative land value and tentative improvement value. Tentative Taxable Value: The preliminary estimate (in USD) of the tax parcel’s value used to calculate property taxes. Sale Date: The date (MM/DD/YYYY) of when the vacant tax parcel was sold. Sale Price: The price (in USD) of what the vacant tax parcel was sold for. Book: The record book that the property deed or sale is recorded in. Page: The page in the record book where the property deed or sale is recorded in. Deed Type: The type of deed associated with the vacant tax parcel sale. RESCOM: Notes whether the vacant tax parcel is zoned for residential or commercial use. R: Residential C: Commercial BISZONING: Notes the zoning district the vacant tax parcel is in. For more information on zoning, visit the City’s Zoning District map. OWNERSHIPCODE: Code to note type of ownership (if applicable). Number of Residential Units: Notes how many residential units are available on the tax parcel (if applicable). LOW_STREET_NUM: The street number of the vacant tax parcel. HIGH_STREET_NUM: The street number of the vacant tax parcel. GISEXTDATE: The date and time when the data was last updated. SALE_DATE_datefield: The recorded date of sale of the vacant tax parcel (if available). Source: This data comes from the department of Neighborhood and Business Development, Bureau of Real Estate.

The Canadian County Parcel Data Public View is a set of geospatial features representing the surface ownership of property in fee simple for property tax purposes as required by 68 O.S. § 2821 and other related data used to produce the parcels such as subdivision boundaries and subdivision lots. The data is created from source documentation filed with the Canadian County Clerk's Office including deeds, easements, and plats. Other data sources such as filed Certified Corner Records filed with the State of Oklahoma or highway plans produced by the Department of Transportation may be used to adjust parcel boundaries. Single legal descriptions may be split up into two or more parcels if the description crosses the boundaries of multiple taxing jurisdictions or crosses quarter section boundaries. Accuracy of parcel data can vary considerably due to a combination of factors. Most parcels and subdivision legal descriptions reference a quarter section or quarter section corner. The accuracy of the quarter section corners is discussed with Canadian County's Public Land Survey System Data. Accuracy is further enhanced or degraded by the quality of the legal description used to create the feature. Generally, legal descriptions created from surveys will have higher accuracy the newer they were created due to improvements in the field of surveying. However, it can be difficult to determine the age of a legal description as descriptions are generally reused on subsequent deeds after the description was first created. Legal descriptions can occasionally contain updated bearings and distances and may denote the updates. The Assessor's Office uses the latest available legal description for creating parcels. Legal descriptions may lack specificity such as the use of "North" instead of a measured bearing or have missing parameters such as missing bearings for curved boundaries. In these cases, parcel data accuracy can be degraded. Further, if a legal description contains a specific landmark or boundary, sometimes called a "bound", the boundary is drawn to that point or landmark regardless of whether the bearing and/or distance accurately arrive at that point. For instance, if a legal description reads "...to the south line of the southeast quarter", the boundary is drawn to the south line of the quarter section even if the bearing and distance are short of or extend beyond that point. Because parcel data must be created for the entire county regardless of the accuracy of the descriptions used to create those parcels, parcels may need to be "stretched" or "squeezed" to make them fit together. When possible, the Assessor's Office relies on the most accurate legal descriptions to set the boundaries and then fits older boundaries to them. Due to the large number of variables, parcel data accuracy cannot be guaranteed nor can the level of accuracy be described for the entire dataset. While Canadian County makes every reasonable effort to make sure parcel data is accurate, this data cannot be used in place of a survey performed by an Oklahoma Licensed Professional Land Surveyor.ParcelDataExternal - Polygons representing surface fee simple title. This parcel data formatted and prepared for public use. Some fields may be blank to comply with 22 O.S. § 60.14 & 68 O.S. § 2899.1Attributes:Account (account): The unique identifier for parcel data generated by the appraisal software used by the Assessor's Office"A" Number (a_number): An integer assigned in approximate chronological order to represent each parcel divided per quarter sectionParcel ID (parcel_id): Number used to identify parcels geographically, see Parcel Data Export Appendix A for an in-depth explanation. This identifier is not unique for all parcelsParcel Size (parcel_size): Size of the parcels, must be used in conjunction with following units fieldParcel Size Units (parcel_size_units): Units for the size of the parcel. Can be "Acres" or "Lots" for parcels within subdivisions that are valued per lotOwner's Name (owners_name): Name of the surface owner of the property in fee simple on recordMailing Information (mail_info): Extra space for the owners name if needed or trustee namesMailing Information 2 (mail_info2): Forwarded mail or "In care of" mailing informationMailing Address (mail_address): Mailing address for the owner or forwarding mailing addressMailing City (mail_city): Mailing or postal cityMailing State (mail_state): Mailing state abbreviated to standard United States Postal Service codesMailing ZIP Code (mail_zip): Mailing ZIP code as determined by the United States Postal ServiceTax Area Code (tax_area): Integer numeric code representing an area in which all the taxing jurisdictions are the same. See Parcel Data Appendix B for a more detailed description of each tax areaTax Area Description (tax_area_desc): Character string code representing the tax area. See Parcel Data Appendix B for a more detailed description of each tax areaProperty Class (prop_class): The Assessor's Office classification of each parcel by rural (no city taxes) or urban (subject to city taxes) and exempt, residential, commercial, or agriculture. This classification system is for property appraisal purposes and does not reflect zoning classifications in use by municipalities. See Parcel Data Appendix B for a more detailed description of each property classificationLegal Description (legal): A highly abbreviated version of the legal description for each parcel. This legal description may not match the most recent legal description for any given property due to administrative divisions as described above, or changes made to the property by way of recorded instruments dividing smaller parcels from the original description. This description may NOT be used in place of a true legal descriptionSubdivision Code (subdiv_code): A numeric code representing a recorded subdivision plat which contains the parcel. This value will be "0" for any parcel not part of a recorded subdivision plat.Subdivision Name (subdiv_name): The name of the recorded subdivision plat abbreviated as needed to adapt to appraisal software field limitationsSubdivision Block Number (subdiv_block): Numeric field representing the block number of a parcel. This value will be "0" if the parcel is not in a recorded subdivision plat or if the plat did not contain block numbersSubdivision Lot Number (subdiv_lot): Numeric field representing the lot number of a parcel. This value will be "0" if the parcel is not in a recorded subdivision platTownship Number (township): Numeric field representing the Public Land Survey System tier or township the parcel is located in. All townships or tiers in Canadian County are north of the base line of the Indian Meridian.Range Number (range): Numeric field representing the Public Land Survey System range the parcel is located in. All Ranges in Canadian County are west of the Indian MeridianSection Number (section): Numeric field representing the Public Land Survey System section number the parcel is located inQuarter Section Code (quarter_sec): Numeric field with a code representing the quarter section a majority of the parcel is located in, 1 = Northeast Quarter, 2 = Northwest Quarter, 3 = Southwest Quarter, 4 = Southeast QuarterSitus Address (situs): Address of the property itself if it is knownSitus City (situs_city): Name of the city the parcel is actually located in (regardless of the postal city) or "Unincorporated" if the parcel is outside any incorporated city limitsSitus ZIP Code (situs_zip): ZIP Code as determined by the United States Postal Service for the property itself if it is knownLand Value (land_val): Appraised value of the land encompassed by the parcel as determined by the Assessor's OfficeImprovement Value (impr_val): Appraised value of the improvements (house, commercial building, etc.) on the property as determined by the Assessor's OfficeManufactured Home Value (mh_val): Appraised value of any manufactured homes on the property and owned by the same owner of the land as determined by the Assessor's OfficeTotal Value (total_val): Total appraised value for the property as determined by the Assessor's OfficeTotal Capped Value (cap_val): The capped value as required by Article X, Section 8B of the Oklahoma ConstitutionTotal Assessed Value (total_assess): The capped value multiplied by the assessment ratio of Canadian County, which is 12% of the capped valueHomestead Exempt Amount (hs_ex_amount): The amount exempt from the assessed value if a homestead exemption is in placeOther Exempt Value (other_ex_amount): The amount exempt from the assessed value if other exemptions are in placeTaxable Value (taxable_val): The amount taxes are calculated on which is the total assessed value minus all exemptionsSubdivisions - Polygons representing a plat or subdivision filed with the County Clerk of Canadian County. Subdivision boundaries may be revised by vacations of the plat or subdivision or by replatting a portion or all of a subdivision. Therefore, subdivision boundaries may not match the boundaries as shown on the originally filed plat.Attributes:Subdivision Name (subdivision_name): The name of the plat or subdivisionSubdivision Number (subdivision_number): An ID for each subdivision created as a portion of the parcel ID discussed in Parcel Data Export Appendix APlat Book Number (book): The book number for the recorded documentPlat Book Page Number (page): The page number for the recorded documentRecorded Acres (acres): The number of acres within the subdivision if knownRecorded Date (recorded_date): The date the document creating the subdivision was recordedDocument URL (clerk_url): URL to download a copy of the document recorded by the Canadian County Clerk's OfficeBlocks - Polygons derived from subdivision lots representing the blocks

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability”. This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in or near the study area, at the time of the analysis of the issues.

Generally speaking, the stakes are people, property, activities, cultural or environmental heritage elements, threatened by a hazard and likely to be affected or damaged by it. The sensitivity of an issue to a hazard is called “vulnerability”. This object class brings together all the issues that have been addressed in the RPP study. An issue is a dated object whose consideration depends on the purpose of the RPP and its vulnerability to the hazards studied. A PPR issue can therefore be considered (or not) depending on the type or types of hazard being addressed. These elements form the basis of knowledge of the land cover necessary for the development of the RPP, in or near the study area, at the time of the analysis of the issues.

The Auditor Books and Pages layer shows the boundaries of the Hamilton County Auditor's Tax Maps Book and Page. These maps act as an index to show property (parcels) throughout Hamilton County, Ohio. The Book numbers correspond to the villages, cities, and townships in the county and are further subdivided into page numbers for each distinct map.Up until the advent of G.I.S. technology these individual maps were maintained by the Hamilton County Engineer in large books. Each property in Hamilton County is assigned a parcel number. The first characters of a parcel number reflect the Book and Page to which it belongs.

We constructed a time-series spatial dataset of parcel boundaries for the period 1962-2005, in roughly 4-year intervals, by digitizing historical plat maps for Dane County and combining them with the 2005 GIS digital parcel dataset. The resulting datasets enable the consistent tracking of subdivision and development for all parcels over a given time frame. The process involved 1) dissolving and merging the 2005 digital Dane County parcel dataset based on contiguity and name, 2) further merging 2005 parcels based on the hard copy 2005 Plat book, and then 3) the reverse chronological merging of parcels to reconstruct previous years, at 4-year intervals, based on historical plat books. Additional land use information such as 1) whether a structure was actually constructed (using the companion digitized aerial photo dataset), 2) cover crop, and 3) permeable surface area, can be added to these datasets at a later date.

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. This coverage can be used for basic applications such as viewing, querying and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

Together with the Russian Academy of Sciences, IIASA's Forestry (FOR) project has released a CD-ROM titled Land Resources of Russia, Version 1.1, containing socioeconomic and biophysical data sets on important targets of international conventions — climate change, wetlands, desertification, and biodiversity. The CD-ROM, a country-scale integrated information system, supports sustainable use of land resources in line with Chapter 10 of Agenda 21 (UNCED) and makes a contribution to the Rio+10 Summit.

The Project's analysis of land resources are crucial for doing full greenhouse gas (or carbon) accounting. Integrated land analyses are also important for the introduction of sustainable forest management. FOR's land analyses concentrate on Russia, which is used as a case study for full carbon and greenhouse accounting.

Russia's area of forests, called here the forest zone, covers about 1180 million ha or 69% of the land of the country. The forested area (forests forming closed stands) occupies some 765 million ha constituting 65% of the forest zone. Forests are elements of a land-cover mosaic that direct the features of landscapes, ecosystems, vegetation and land uses. The FOR project attempts to overcome the traditional approach of just considering the direct utilities of forests. Instead, FOR operates with a holistic view of forests in a fully-fledged land concept. Integrated analysis of the land requires extended databases that includes various data for the total land operated in the form of GIS-based tools.

The land databases on Russia are the most comprehensive ever assembled, inside or outside of Russia. The databases have been enriched by remotely sensed data, biogeochemical functionality (carbon analysis), and institutional frameworks. The data included on the CD-ROM have been specially selected and filtered to meet the following criteria: (1) completeness: to meet a variety of the analysis tasks; (2) complexity: to describe a diversity of the task aspects; (3) consistency: to provide compatible results; to be ata compatible scale and, to provide a compatible time horizon; and (4) uniformity: to allow them to be standardized and formatted according to modern data handling routines.

The following databases and coverages are included on the CD-ROM and are available for download:

Socioeconomic Database -- Describes the social environment of each administrative region in Russia with close to 7000 parameters. The data cover the years 1987-1993. Coverages in this section include:

(1) Socioeconomic Statistical Database. This database provides the following statistical data sets: Population; Labor and Salary; Industry; Agriculture; Capital Construction; Communication and Transport; State Trade and Catering; Utilities and Services; Health Care and Sport; Education and Culture; Finance; Public Consumption; Industrial Production; Interregional Trade; Labor Resources; Supply of Materials; Environmental Protection; Foreign Trade; and Price Indices.

(2) Population Database. Adapted from Center for International Earth Science Information Network (CIESIN), Columbia University; International Food Policy Research Institute (IFPRI); and World Resources Institute (WRI). 2000. Gridded Population of the World (GPW), Version 2, this coverage contains population densities for 1995 on a 2.5 degree grid. Data were adjusted to match United Nations national population estimates for 1995.

(3) Administrative Oblasts, Cities & Towns Database. Oblasts coverage contains 92 polygons, 88 of which contain Oblast names, the other four represent waterbodies. The cities coverage contains 37 cities identified by name.

(4) Transportation Database. The statistical data sets and maps cover the transport routes of the railway, road, and river networks spanning the entire country. Railways and roads are classified by type and status, and major rivers are named. Map coverages (line data) were created from the Digital Chart of the World, using the 1993 version at the 1:1,000,000 scale.

Natural Conditions Database. This section of the CD-ROM contains the basic land characteristics. This database provides specialists and scientists in research institutes and international agencies with the capability to perform scientific analysis with a Geographic Information System. These data describe land characteristics that might be applied in various ways, such as individual items (e.g., temperature, elevation, vegetation community, etc.), in combination (e.g., forest-temperature associations, soil spectra for land use types, etc.), and as aggregations based on a conceptual framework of a different level of complexity (e.g., ecosystem establishment, human-induced land cover transformation, biochemical cycle analysis, etc.). Coverage includes:

(1) Climate Database. Temperature (annual and seasonal) and Precipitation... Visit https://dataone.org/datasets/Land_Resources_of_Russia%2C_Version_1.1.xml for complete metadata about this dataset.

Pastoral Inspectors field books contain assessments of improvements to Western Lands Leases, conditional purchases, etc. These records contain the names of holdings, locality, time of inspection and instructions. They are sometimes numbered and most have the name of the Inspector. All volumes are handwritten and some include diagrams.

The Western Lands (Amendment) Act 1949 (Act No.45, 1949) s.2 amended the principal Western Lands Act 1901 (Act No.70, 1901) with the insertion of s.17ccc. This section authorised the withdrawal of areas of land from Lease arrangements upon assessment. There are a number of volumes referring to 17ccc Inspections, these volumes record the assessment of a Lease against the criteria established in the Act.

The volumes record field visits or inspections made by Pastoral Inspectors to holdings to view the activities on the runs and to inspect compliance with lease arrangements. This included notes of improvements to the property, estimated carrying capacity, and lists of items like bores and dams, buildings, bridges and a valuation of the land and the improvements. Some Pastoral Inspectors were trained surveyors and included some survey information.

The records are small bound notebooks and the name of the holding is usually written on the cover.

The digital reading platform market is experiencing robust growth, driven by the increasing adoption of e-readers, smartphones, and tablets, coupled with the rising popularity of audiobooks and digital subscriptions. The convenience and accessibility offered by digital platforms, along with wider availability of diverse content, are key factors fueling this expansion. We estimate the market size to be approximately $25 billion in 2025, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This growth is propelled by several trends, including the emergence of innovative reading apps with personalized recommendations, subscription models offering unlimited access to vast libraries, and the integration of immersive technologies such as augmented reality for enhanced reading experiences. However, challenges remain, such as piracy concerns, price sensitivity among consumers, and the need for robust digital rights management systems to protect intellectual property. The market segmentation is diverse, encompassing subscription services, individual e-book sales, audiobook platforms, and educational platforms. Key players, such as Amazon, Apple, and Adobe, are aggressively expanding their offerings and strengthening their market positions through strategic acquisitions and partnerships. The competitive landscape is highly dynamic, with established players facing competition from newer entrants offering niche services and innovative technologies. The market is segmented by platform type (e-readers, mobile apps, web platforms), content type (eBooks, audiobooks, magazines), and region. North America and Europe currently hold the largest market share, but emerging markets in Asia and Latin America are expected to contribute significantly to market growth in the coming years. Strategic partnerships between publishers, technology providers, and content creators are shaping the future of the digital reading landscape. Furthermore, advancements in artificial intelligence (AI) are leading to personalized reading experiences and improved content recommendations, increasing user engagement and driving market expansion.

The Geographic Information Systems (GIS) Unit falls under the purview of the County of Santa Cruz Information Services Department. The GIS Unit serves all County departments and external customers and provides data on land, features and people of Santa Cruz County. Santa Cruz County encompasses 4 cities and approximately 265,000 people. This coverage can be used for basic applications such as viewing, querying and map output production, or to provide a basemap to support graphical overlays and analyses of geospatial data.

This dataset mainly includes the inventory of the library's audio books, braille books, dual-view books, and other resources for the visually impaired, to facilitate users in querying and using them.

--- DATASET OVERVIEW --- Our Vacation Rental Area KPIs from Direct PM Reservation Data Integrations provides comprehensive market performance metrics for professionally managed vacation rentals sourced directly from property management systems. This dataset delivers authoritative insights into market performance based on actual reservation data rather than listing information, offering an accurate view of booking patterns, revenue generation, and operational metrics across different markets.

The data is sourced directly from property management system integrations, capturing actual reservation details rather than OTA listing information. This direct access to booking data ensures that the performance metrics reflect true market activity rather than just advertised availability or pricing. Our coverage is particularly strong in North America, Europe and Australia, with growing global representation.

--- KEY DATA ELEMENTS --- Our dataset includes the following market-level performance indicators for professionally managed vacation rentals: - Geographic Identifiers: Multiple geographic levels (vacation area, vacation region, county, etc) - Temporal Dimensions: Daily, weekly, monthly, and quarterly performance metrics - Occupancy Metrics: Actual occupancy rates based on confirmed reservations - Revenue Metrics: Total revenue, average daily rate (ADR), and revenue per available rental night (RevPAR) - Booking Patterns: Lead time distribution, length of stay patterns, and booking frequency - Reservation Channel Mix: Distribution of bookings across different reservation channels - Seasonality Indicators: Performance variations across seasons, months, and days of week - Performance Segmentation: Metrics broken down by property type, size, and price tier - Historical Pacing: Snapshots into how stay date ranges developed for tracking pacing trends - Forward Looking Trends: Area KPIs 180-365 days into the future

--- USE CASES --- Performance Benchmarking for Professional Managers: Property management companies can benchmark their portfolio performance against market-wide metrics for professionally managed properties. By comparing company-specific occupancy rates, ADR, and RevPAR against market averages for similar property types, managers can assess relative performance and identify areas for improvement. These benchmarks provide crucial context for performance evaluation and goal setting specific to professional management operations.

Operational Strategy Development: Property management operators can leverage this dataset to develop operational strategies based on industry benchmarks. The reservation patterns, lead time distributions, and cancellation metrics provide insights into optimal staffing levels, maintenance scheduling, and operational workflows. This information supports the development of efficient operational practices aligned with actual booking patterns.

Revenue Management Optimization: Revenue managers can use this dataset to develop sophisticated revenue optimization strategies based on actual booking patterns to benchmark broader, inferred information from OTAs. The detailed revenue metrics and booking patterns provide insights into rate elasticity, optimal minimum stay requirements, and the revenue impact of different pricing approaches. This information supports the development of data-driven revenue management strategies tailored to specific markets and property types.

Distribution Channel Strategy: Property managers can analyze reservation channel performance across different markets to optimize their distribution strategy. By understanding which channels deliver the highest value bookings in specific markets, managers can focus their efforts and investment on the most productive channels for their target areas and property types.

Investment Decision Support: Real estate investors focused on professionally managed vacation rentals can analyze market performance across different regions to identify investment opportunities. The dataset provides insights into revenue potential, seasonality impacts, and overall market health based on actual booking data, supporting data-driven acquisition and portfolio expansion decisions.

--- ADDITIONAL DATASET INFORMATION --- Delivery Details: • Delivery Frequency: daily | weekly | monthly | quarterly • Delivery Method: scheduled file loads • File Formats: csv | parquet • Large File Format: partitioned parquet • Delivery Channels: Google Cloud | Amazon S3 | Azure Blob • Data Refreshes: daily

Dataset Options: • Coverage: North America + Top Global Tourism Markets with Strong Coverage in Europe and Australia • Historic Data: Available (2019 for most areas) • Future Looking Data: Available (Current date + 180 days+) • Point-in-Time: Available (with weekly as of dates) • Aggregation and Filtering Options: • Area/Market (required) • Time Scales (daily, weekly, monthly) • Property Characteris...

View metadata for key information about this resource.PhilaDox is a searchable database of contemporary land records, including deeds, sheriff deeds, mortgages, and land titles. The data is from 1999 to the present with some limited deed data available from 1974.Data is viewable as lists, tables and scanned images of the actual documents. The database is searchable by grantor/grantee names, address, or county record book and page. Scanned documents can be downloaded as PDFs. Full access to PhilaDox records is available with a daily, weekly, monthly, or annual subscription. More limited search for names and address is available for free public access.The PhilaDox Historical Index is a part of the PhilaDox system that contains historical deeds from the 1600s to 1999. This index does not include the full deed, but, rather is a scan of the deed index books and pages. It is available without a subscription fee by selecting "Free Public Search Login".For questions about this resource, contact philadox.support@phila.gov. For technical assistance, email maps@phila.gov.