Motivation

The data in this dataset is a spatial inventory of urban agriculture (UA) carried out in the city of Rome (Italy) (Grande Raccordo Anulare (GRA)). UA areas where identified with a multi-step and iterative procedure by using different web-mapping tools, especially multitemporal Google Earth images, and ancillary data such as Google Street View and Bing Maps.

License

Creative Commons CC-BY

Disclaimer

Despite our best efforts to validate the data, some information may be incorrect.

Description of the dataset

Typologies of UA

• Residential garden: Private parcel near single houses (e.g. backyard), villas, buildings, industrial and commercial activities, generally managed by property owners. Cultivation is diversified ranging from leafy vegetables to herbs and fruit trees. Production is intended for self-consumption and/or for hobby purposes.
• Community garden: A large area subdivided into multipleplots managed individually (i.e. allotment) or collectively by a group of people. Crop production is intended for self-consumption. Land is assigned by the Municipality; several cases of land cultivated without authorization are also common.
• Urban farm: Parcel managed by professional farmers with an intensive and an advanced cropping system. The cultivation can be specialized or oriented to high diversity vegetables. The production is intended for market. The mapping procedure focus exclusively on horticulture, vineyard, olive groves and orchard.
• Institutional garden: Parcel managed by institutions or organizations like schools, religious center, prisons and non-profit organizations. The production is generally intended for self-consumption and less frequently for trade. Several gardens in this category are intended for social purposes (e.g. recreation,education, etc.).
• Illegal garden: Parcel isolated, cultivated without authorization organized and managed individually or by a few people. Localization occurs on unused or abandoned areas owned by public bodies or private subjects. The production is intended for self-consumption.

Land use typologies

• Horticulture: annual crops generally seed sown in spring or summer (tomatoes, lettuce, zucchini, cucumbers, peppers).
• Vineyard: grape vines grown in order to produce wine or table grape.
• Olive groves: olive trees grown in order to produce olive oil or table olives.
• Orchards: mixed trees such as orange, stone fruit, pome fruit, olive trees.
• Mixed crops: an area grown with a mix of horticulture crops and fruit trees, not divisible.

Credit

Pulighe G., Lupia F. (2016) Mapping spatial patterns of urban agriculture in Rome (Italy) using Google Earth and web-mapping services. Land Use Policy 59(2016) 49-58.

www.sciencedirect.com/science/article/pii/S0264837716300059

This dataset contains Global Plant Functional Types (PFT) data, from the ESA Medium Resolution Land Cover (MRLC) Climate Change Initiative project. The data provides yearly data, and initially covers the time period from 1992 to 2020. It is anticipated that the dataset will be updated annually going forward.

The PFT v2.0.8 global dataset has 14 layers, each describing the percentage cover (0-100%) of a plant functional type at a spatial resolution of 300 m: broadleaved evergreen trees, broadleaved deciduous trees, needleleaved evergreen trees, needleleaved deciduous trees, broadleaved evergreen shrubs, broadleaved deciduous shrubs, needleleaved evergreen shrubs, needleleaved deciduous shrubs, natural grasses, herbaceous cropland (i.e., managed grasses), built, water, bare areas, and snow and ice.

"Plant Functional Types” (PFTs) refer to globally representative and similarly behaving plant types. PFTs can be related to physiognomy and phenology, climate (which defines the geographical ranges in which a plant type can grow and reproduce under natural conditions, and physiological activity (e.g., C3/C4 photosynthetic pathways).

All terrestrial zones of the Earth between the parallels 90°N and 90°S are covered. The PFT dataset has a regular latitude-longitude grid with a grid spacing of 0.002777777777778°, corresponding to ~300 m at the equator and ~200 m in the midlatitudes. The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid.

The plant functional type (PFT) distribution was created by combining auxiliary data products with the CCI MRLC map series. The LC classification provides the broad characteristics of the 300 m pixel, including the expected vegetation form(s) (tree, shrub, grass) and/or abiotic land type(s) (water, bare area, snow and ice, built-up) in the pixel. For some classes, the class legend specifies an expected range for the fractional covers of the contributing PFTs and broadly differentiates between natural and cultivated vegetation. We used a quantitative, globally consistent method that fuses the 300-metre MRLC product with a suite of existing high-resolution datasets to develop spatially explicit annual maps of PFT fractional composition at 300 metres. The new PFT product exhibits intraclass spatial variability in PFT fractional cover at the 300-metre pixel level and is complementary to the MRLC maps since the derived PFT fractions maintain consistency with the original LC class legend.

This dataset was generated to reduce the cross-walking component of uncertainty by adding spatial variability to the PFT composition within a LC class. This work moved beyond fine-tuning the cross-walking approach for specific LC classes or regions and, instead, separately quantifies the PFT fractional composition for each 300 m pixel globally. The result is a dataset representing the cover fractions of 14 PFTs at 300 m for each year within the time range, consistent with the CCI MRLC LC maps for the corresponding year.

This study was carried out with the continued support of the European Space Agency Climate Change Initiative under the contract ESA/No.4000126564 Land_Cover_cci.

Contour lines derived from 2011 aerial photography.

A global map of anthropogenic transformations of terrestrial biomes has been produced to characterize the ecosystem changes due to anthropogenic influences before and during the Industrial Revolution, from 1700 to 2000. Patterns of anthropogenic transformations were assessed at 5 min resolution by comparing potential natural vegetation maps (Ramankutty and Foley, 1999; Olson et al., 2001) with the anthrome map of Ellis and Ramankutty (2008) circa 2000, global, historical gridded data for human population density and agricultural and urban land use from the HYDE data model (Klein Goldewijk and van Drecht, 2006), ORNL LandScan population data, irrigated land data (Siebert et al., 2007), rice cover data (Monfreda et al., 2008), and other agricultural census data at century intervals (1700, 1800, 1900, and 2000). The investigators used overlay analysis and other analytical geographic information system (GIS) software tools to produce the four data sets and maps. For more information, see Ellis, E.C., Kees Klein Goldewijk, K., Siebert, S., Lightman, D., and Ramankutty, N. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography 19: 589-606. References: Ellis, E.C., and N. Ramankutty. 2008. Putting people in the map: anthropogenic biomes of the world. Frontiers in Ecology and the Environment 6(8): 439-447. Monfreda, C., N. Ramankutty, and J. A. Foley. 2008. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000, Global Biogeochem. Cycles, 22, GB1022, doi:10.1029/2007GB002947; Ramankutty, N., A.T. Evan, C. Monfreda, and J.A. Foleyl. 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles 22, GB1003, doi:10.1029/2007GB002952; Siebert, S., P. Doll, S. Feick, J. Hoogeveen, and K. Frenken. 2007. Global map of irrigation areas version 4.0.1. Johann Wolfgang Goethe University, Frankfurt am Main, Germany/Food and Agriculture Organization of the United Nations, Rome, Italy; Oak Ridge National Laboratory (2006) LandScan Global Population Database. Oak RidgeNational Laboratory, Oak Ridge, TN. [http://www.ornl.gov/landscan]; and Olson, D.M., E. Dinerstein, E.D. Wikramanayake, N.D. Burgess, G.V.N Powell, E.C. Underwood, J.A. D’Amico, I. Itoua, H.E. Strand, J.C. Morrison, C.J. Loucks, T.F. Allnutt, T.H. Ricketts, Y. Kura, J.F. Lamoreux, W.W. Wettengel, P. Hedao, and K.R. Kassem. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. BioScience 51: 933–938.

This data collection includes land-use scenarios calculated with the LandSHIFT model for four scenarios as GIS-raster maps and Excel files used to calculate land-use change effects on biodiversity with the BII indicator.

New-ID: NBI16

Agro-ecological zones datasets is made up of AEZBLL08, AEZBLL09, AEZBLL10.

The Africa Agro-ecological Zones Dataset documentation

Files: AEZBLL08.E00 Code: 100025-011 AEZBLL09.E00 100025-012 AEZBLL10.E00 100025-013

Vector Members The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename.

The Africa agro-ecological zones dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. The daset was developed by United Nations Environment Program (UNEP), Kenya. The base maps that were used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the Global Navigation and Planning Charts (various 1976-1982) and the National Geographic Atlas of the World (1975). basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. This edit step required appending the country boundaries from Administrative Unit map and then producing the computer plot.

Contact: UNEP/GRID-Nairobi, P O Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA 92373, USA

The AEZBLL08 data covers North-West of African continent The AEZBLL09 data covers North-East of African continent The AEZBLL10 data covers South of African continent

References:

ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP

FAO/UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris

Defence Mapping Agency. Global Navigation and Planning Charts for Africa (various dates:1976-1982). Scale 1:5000000. Washington DC.

G.M. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society, Washington DC.

FAO. Statistical Data on Existing Animal Units by Agro-ecological Zones for Africa (1983). Prepared by Todor Boyadgiev of the Soil Resources, Management and Conservation Services Division.

FAO. Statistical Data on Existing and Potential Populations by Agro-ecological Zones for Africa (1983). Prepared by Marina Zanetti of the Soil Resources, Management and Conservation Services Division. FAO. Report on the Agro-ecological Zones Project. Vol.I (1978), Methodology & Result for Africa. World Soil Resources No.48.

Source : UNESCO/FAO Soil Map of the World, scale 1:5000000 Publication Date : Dec 1984 Projection : Miller Type : Polygon Format : Arc/Info Export non-compressed Related Datasets : All UNEP/FAO/ESRI Datasets, Landuse (100013/05, New-ID: 05 FAO Irrigable Soils Datasets and Water balance (100050/53)

Methodology

The Canterbury irrigated area dataset combines different data, including:

· farm boundary extents (land ownership and GIS data from Land Information New Zealand)

· high resolution aerial imagery and/or satellite photos

· resource consent data

· analysis of satellite data (using normalised different vegetation index (NDVI) imagery)

· agricultural production statistics (Statistics New Zealand).

A summary of the methodology, and tabulated irrigated area data for the Canterbury region and each of its ten water management zones, are found in the report: Canterbury detailed irrigated area mapping (2016). Prepared for Environment Canterbury by Aqualinc Research Limited.

By “irrigated area” we mean the area actually irrigated for productive gain, not the consented area.

Official Environment Canterbury Tech Report: https://api.ecan.govt.nz/TrimPublicAPI/documents/download/3010557

Forest tracts is a base map data layer derived by automated processes and processed for cartographic representation at 1:2400 scale. The polygon features represent the areas of forest or scrub cover as seen from above and are mapped to National Map Accuracy Standards (NMAS). Forest is used by both the private and public sectors for comprehensive planning, facility planning, preservation projects, site design and land cover analysis.

Data are stored in the corporate ArcSDE Geodatabase as a polygon feature class. The coordinate system is Virginia State Plane (North), Zone 4501, datum NAD83 HARN, Vertical datum, NAVD88, US Survey foot units. OMAGI updates all base map data via a photogrammetric process, using aerial imagery that is flown yearly in phases. A different portion of the County is updated each year with the base map maintenance services contract, depending upon development patterns and update funding. See "Lineage" section for the list of extents for each Phase area, which are listed as “Data Sources”. The field “UPD_DATE” indicates the date a feature was last re-mapped, although it may have been reviewed for changes more recently.

New-ID: NBI18

The Africa Major Infrastructure and Human Settlements Dataset

Files: TOWNS2.E00 Code: 100022-002 ROADS2.E00 100021-002

Vector Members: The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename

The Africa major infrastructure and human settlements dataset form part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the DMA Global Navigation and Planning charts for Africa (various dates: 1976-1982) and the Rand-McNally, New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap those of the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. The Population Centers were selected based upon their inclusion in the list of major cities and populated areas in the Rand McNally New International Atlas Contact: UNEP/GRID-Nairobi, P.O. Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA. 92373, USA The ROADS2 file shows major roads of the African continent The TOWNS2 file shows human settlements and airports for the African continent

References:

ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP

FAO. UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris

Defence Mapping Agency. Global Navigation and Planning charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC.

Grosvenor. National Geographic Atlas of the World (1975). Scale 1:850000. National Geographic Society Washington DC.

DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC.

Rand-McNally. The new International Atlas (1982). Scale 1:6,000,000. Rand McNally & Co.Chicago

Source: FAO Soil Map of the World. Scale 1:5000000 Publication Date: Dec 1984 Projection: Miller Type: Points Format: Arc/Info export non-compressed Related Datasets: All UNEP/FAO/ESRI Datasets ADMINLL (100012-002) administrative boundries AFURBAN (100082) urban percentage coverage Comments: There is no outline of Africa

Soil is a key natural resource that provides the foundation of basic ecosystem services. Soil determines the types of farms and forests that can grow on a landscape. Soil filters water. Soil helps regulate the Earth's climate by storing large amounts of carbon. Activities that degrade soils reduce the value of the ecosystem services that soil provides. For example, since 1850 35% of human caused green house gas emissions are linked to land use change. The Soil Science Society of America is a good source of of additional information.The mineral composition of underlying rock, the amount and type of organic material from plants and climatic and other environmental factors affect the chemistry of the soil. Chemical composition and processes determine how and what type of soil forms at a given location and what type of agriculture the areas wil support.Dataset SummaryThis layer provides access to a 30 arc-second (roughly 1 km) cell-sized raster with attributes related to the chemistry of soil derived from the Harmonized World Soil Database v 1.2. The values in this layer are for the dominant soil in each mapping unit (sequence field = 1).Fields for topsoil (0-30 cm) and subsoil (30-100 cm) are available for each of these soil chemistry attributes:Organic Carbon - % weightCalcium Carbonate - % weightGypsum - % weightSalinity - Electrical Conductivity - dS/mpHAdditionally, 4 class description fields were added by Esri based on the document Harmonized World Soil Database Version 1.2 for use in web map pop-ups:pH Class DescriptionCalcium Carbonate Class DescriptionGypsum Class DescriptionSalinity - Electrical Conductivity - Class DescriptionThe layer is symbolized with the Topsoil pH field.The document Harmonized World Soil Database Version 1.2 provides more detail on the soil chemistry attributes contained in this layer.Other attributes contained in this layer include:Soil Mapping Unit Name - the name of the spatially dominant major soil groupSoil Mapping Unit Symbol - a two letter code for labeling the spatially dominant major soil group in thematic mapsData Source - the HWSD is an aggregation of datasets. The data sources are the European Soil Database (ESDB), the 1:1 million soil map of China (CHINA), the Soil and Terrain Database Program (SOTWIS), and the Digital Soil Map of the World (DSMW).Percentage of Mapping Unit covered by dominant componentMore information on the Harmonized World Soil Database is available here.Other layers created from the Harmonized World Soil Database are available on ArcGIS Online:World Soils Harmonized World Soil Database - Bulk DensityWorld Soils Harmonized World Soil Database - Exchange CapacityWorld Soils Harmonized World Soil Database – GeneralWorld Soils Harmonized World Soil Database – HydricWorld Soils Harmonized World Soil Database – TextureThe authors of this data set request that projects using these data include the following citation:FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. The source data for this layer are available here. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:Living Atlas Discussion GroupSoil Data Discussion GroupThe Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. Census Tracts 2010 reviewed 05/15/2015

Source: United States Census Bureau

Effective Date:

Last Update: 05/15/2015

Update Cycle: As needed, Census is completed every 10 years.

The Chesapeake Bay Preservation Ordinance was adopted to protect our local streams and one of the world's most productive estuaries, the Chesapeake Bay, from pollution due to land use and development. All of Fairfax County drains into the Potomac River and ultimately the Chesapeake Bay. In an effort to protect and improve the quality of these waterways, sensitive areas along streams throughout Fairfax County have been designated as Resource Protection Areas.

State regulations require that Resource Protection Areas (RPAs) be designated around all water bodies with perennial flow. Perennial flow means that water always flows in the stream or other water body except during periods of drought. The Department of Public Works and Environmental Services conducted field studies to identify all perennial streams throughout the county and used this information to prepare a set of maps showing the location of RPAs as defined under the revised Ordinance. The maps were adopted by the Board on November 17, 2003.

The data include the boundaries of the RPAs adopted by the Board in 1993 and the additional RPAs adopted by the Board in 2003. These are general locations of RPA boundaries for planning purposes and the actual limits may be further refined by detailed field studies conducted at the time a plan is submitted to obtain a permit to develop a property.

Any areas within Fairfax County not contained within the RPAs are Resource Management Areas (RMAs). Together, the RPAs and RMAs comprise the Chesapeake Bay Preservation Areas.

The information in the abstract is translated from the archaeological report: Due to the Swedish Rail Administration's plans of extending the railway between Motala and Mjölby, by construction of double-tracks and levelled crossings, the Swedish National Heritage Board's Contract Archaeology Service, UV Öst, has performed several excavations along the railway during the years of 2003-2005. Five separate sites were investigated, together forming the Fågelsta Project, a part of the overall project "The Plain Region - western Östergötland in a long term perspective". The archaeological remains consisted of Neolithic and Pre-Roman Iron Age settlements, furnaces from the transition between the Bronze and Iron Age, graves and a cult building from the Vendel period and the Viking Age and a medieval road (beside RAÄ 21, 27, Västra Stenby parish); abandoned fields from the transition between the Bronze and Iron Age, Late Iron Age settlement, Early Medieval features and a smithy from the Modern Era (RAÄ 225, Västra Stenby parish); settlement remains and stray finds from the Stone Age to the Early Iron Age (beside RAÄ 14-19, Västra Stenby parish); settlement remains from the Early and Late Neolithic, Bronze Age, the transition between the Bronze and Iron Age, the Roman Iron Age, and Vendel period/Viking age, possible village formation (beside RAÄ 32, Fivelstad parish) and finally Neolithic and Bronze Age settlement remains, abandoned fields from the Bronze Age and the Pre-Roman Iron Age, and a Pre-Roman workshop area (beside RAÄ 26, Fivelstad parish). A total of 23 300 m2 was investigated.

Purpose: The information in the purpose is translated from the archaeological report: The main theme of the Fågelsta Project was "People of the plains - settlement changes in a long term perspective". The aim was to describe the landscape development in the area from a comprehensive point of view. This aim was then divided into four sub-themes; Continuity and transitions, Land use in a local perspective, Settlement and settlement structure and Central places and areas. The aim was also to relate the prehistoric development and land use in west Östergötland to the neighbouring regions.

The data is available in two formats: a ZIP file containing GIS shapefiles connected to an Access datafile containing information pertaining to excavation area, finds, object types along with other metadata regarding the archaeological investigation. The second ZIP file consists of corresponding .gml and .xlsx files.