Under various scenarios, land use changes in Belgium are simulated at 10-meter resolution. Three SSP-RCP scenarios were used to model the land use trends in the present (2020) and the year 2050 at the national level in Belgium. Key inputs to the model include regional land use demand, quantification of the suitability of grid cells for different land use types, and a reference land cover map. The 10 meter-resolution baseline land use map of Belgium was sourced from the European Space Agency (ESA) WorldCover for the reference year 2020. The classification systems ESA is different from LUH2. To make these datasets comparable for land use simulations, we performed reclassification based on the guidelines provided by Pérez-Hoyos et al. (2012); Dong et al. (2018); Liao et al. (2020) to unify the land use classes, except water, into six general categories: 1) urban, 2) cropland, 3) pasture, 4) forestry, 5) bare/sparse vegetation, and 6) undefined.

The Federal Emergency Management Agency (FEMA) produces Flood Insurance Rate maps and identifies Special Flood Hazard Areas as part of the National Flood Insurance Program's floodplain management. Special Flood Hazard Areas have regulations that include the mandatory purchase of flood insurance for holders of federally regulated mortgages. In addition, this layer can help planners and firms avoid areas of flood risk and also avoid additional cost to carry insurance for certain planned activities. Dataset SummaryPhenomenon Mapped: Flood Hazard AreasGeographic Extent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Northern Mariana Islands and American Samoa.Projection: Web Mercator Auxiliary SphereData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Northern Mariana Islands, and American Samoa)Cell Sizes: 10 meters (default), 30 meters, and 90 metersUnits: NoneSource Type: ThematicPixel Type: Unsigned integerSource: Federal Emergency Management Agency (FEMA)Update Frequency: AnnualPublication Date: May 7, 2025 This layer is derived from the May 7, 2025 version Flood Insurance Rate Map feature class S_FLD_HAZ_AR. The vector data were then flagged with an index of 94 classes, representing a unique combination of values displayed by three renderers. (In three resolutions the three renderers make nine processing templates.) Repair Geometry was run on the set of features, then the features were rasterized using the 94 class index at a resolutions of 10, 30, and 90 meters, using the Polygon to Raster tool and the "MAXIMUM_COMBINED_AREA" option. Not every part of the United States is covered by flood rate maps. This layer compiles all the flood insurance maps available at the time of publication. To make analysis easier, areas that were NOT mapped by FEMA for flood insurance rates no longer are served as NODATA but are filled in with a value of 250, representing any unmapped areas which appear in the US Census boundary of the USA states and territories. The attribute table corresponding to value 250 will indicate that the area was not mapped.What can you do with this layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application. Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "flood hazard areas" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "flood hazard areas" in the search box, browse to the layer then click OK. In ArcGIS Pro you can use the built-in raster functions to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro. The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one. Processing TemplatesCartographic Renderer - The default. These are meaningful classes grouped by FEMA which group its own Flood Zone Type and Subtype fields. This renderer uses FEMA's own cartographic interpretations of its flood zone and zone subtype fields to help you identify and assess risk. Flood Zone Type Renderer - Specifically renders FEMA FLD_ZONE (flood zone) attribute, which distinguishes the original, broadest categories of flood zones. This renderer displays high level categories of flood zones, and is less nuanced than the Cartographic Renderer. For example, a fld_zone value of X can either have moderate or low risk depending on location. This renderer will simply render fld_zone X as its own color without identifying "500 year" flood zones within that category.Flood Insurance Requirement Renderer - Shows Special Flood Hazard Area (SFHA) true-false status. This may be helpful if you want to show just the places where flood insurance is required. A value of True means flood insurance is mandatory in a majority of the area covered by each 10m pixel. Each of these three renderers have templates at three different raster resolutions depending on your analysis needs. To include the layer in web maps to serve maps and queries, the 10 meter renderers are the preferred option. These are served with overviews and render at all resolutions. However, when doing analysis of larger areas, we now offer two coarser resolutions of 30 and 90 meters in processing templates for added convenience and time savings.Data DictionaryMaking a copy of your area of interest using copyraster in arcgis pro will copy the layer's attribute table to your network alongside the local output raster. The raster attribute table in the copied raster will contain the flood zone, zone subtype, and special flood hazard area true/false flag which corresponds to each value in the layer for your area of interest. For your convienence, we also included a table in CSV format in the box below as a data dictionary you can use as an index to every value in the layer. Value,FLD_ZONE,ZONE_SUBTY,SFHA_TF 2,A,, 3,A,,F 4,A,,T 5,A,,T 6,A,,T 7,A,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN CHANNEL,T 8,A,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN STRUCTURE,T 9,A,ADMINISTRATIVE FLOODWAY,T 10,A,COASTAL FLOODPLAIN,T 11,A,FLOWAGE EASEMENT AREA,T 12,A99,,T 13,A99,AREA WITH REDUCED FLOOD RISK DUE TO LEVEE,T 14,AE,,F 15,AE,,T 16,AE,,T 17,AE,,T 18,AE,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN CHANNEL,T 19,AE,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN STRUCTURE,T 20,AE,"1 PCT CONTAINED IN STRUCTURE, COMMUNITY ENCROACHMENT",T 21,AE,"1 PCT CONTAINED IN STRUCTURE, FLOODWAY",T 22,AE,ADMINISTRATIVE FLOODWAY,T 23,AE,AREA OF SPECIAL CONSIDERATION,T 24,AE,COASTAL FLOODPLAIN,T 25,AE,COLORADO RIVER FLOODWAY,T 26,AE,COMBINED RIVERINE AND COASTAL FLOODPLAIN,T 27,AE,COMMUNITY ENCROACHMENT,T 28,AE,COMMUNITY ENCROACHMENT AREA,T 29,AE,DENSITY FRINGE AREA,T 30,AE,FLOODWAY,T 31,AE,FLOODWAY CONTAINED IN CHANNEL,T 32,AE,FLOODWAY CONTAINED IN STRUCTURE,T 33,AE,FLOWAGE EASEMENT AREA,T 34,AE,RIVERINE FLOODWAY IN COMBINED RIVERINE AND COASTAL ZONE,T 35,AE,RIVERINE FLOODWAY SHOWN IN COASTAL ZONE,T 36,AE,STATE ENCROACHMENT AREA,T 37,AH,,T 38,AH,,T 39,AH,FLOODWAY,T 40,AO,,T 41,AO,COASTAL FLOODPLAIN,T 42,AO,FLOODWAY,T 43,AREA NOT INCLUDED,,F 44,AREA NOT INCLUDED,,T 45,AREA NOT INCLUDED,,U 46,D,,F 47,D,,T 48,D,AREA WITH FLOOD RISK DUE TO LEVEE,F 49,OPEN WATER,,F 50,OPEN WATER,,T 51,OPEN WATER,,U 52,V,,T 53,V,COASTAL FLOODPLAIN,T 54,VE,,T 55,VE,,T 56,VE,COASTAL FLOODPLAIN,T 57,VE,RIVERINE FLOODWAY SHOWN IN COASTAL ZONE,T 58,X,,F 59,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD,F 60,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD,T 61,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD,U 62,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN CHANNEL,F 63,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN STRUCTURE,F 64,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD IN COASTAL ZONE,F 65,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD IN COMBINED RIVERINE AND COASTAL ZONE,F 66,X,"1 PCT CONTAINED IN STRUCTURE, COMMUNITY ENCROACHMENT",F 67,X,"1 PCT CONTAINED IN STRUCTURE, FLOODWAY",F 68,X,1 PCT DEPTH LESS THAN 1 FOOT,F 69,X,1 PCT DRAINAGE AREA LESS THAN 1 SQUARE MILE,F 70,X,1 PCT FUTURE CONDITIONS,F 71,X,1 PCT FUTURE CONDITIONS CONTAINED IN STRUCTURE,F 72,X,"1 PCT FUTURE CONDITIONS, COMMUNITY ENCROACHMENT",F 73,X,"1 PCT FUTURE CONDITIONS, FLOODWAY",F 74,X,"1 PCT FUTURE IN STRUCTURE, COMMUNITY ENCROACHMENT",F 75,X,"1 PCT FUTURE IN STRUCTURE, FLOODWAY",F 76,X,AREA OF MINIMAL FLOOD HAZARD, 77,X,AREA OF MINIMAL FLOOD HAZARD,F 78,X,AREA OF MINIMAL FLOOD HAZARD,T 79,X,AREA OF MINIMAL FLOOD HAZARD,U 80,X,AREA OF SPECIAL CONSIDERATION,F 81,X,AREA WITH REDUCED FLOOD RISK DUE TO LEVEE,F 82,X,AREA WITH REDUCED FLOOD RISK DUE TO LEVEE,T 83,X,FLOWAGE EASEMENT AREA,F 84,X,1 PCT FUTURE CONDITIONS,T 85,AH,COASTAL FLOODPLAIN,T 86,AE,,U 87,AE,FLOODWAY,F 88,X,AREA WITH REDUCED FLOOD HAZARD DUE TO ACCREDITED LEVEE SYSTEM,F 89,X,530,F 90,VE,100,T 91,AE,100,T 92,A99,AREA WITH REDUCED FLOOD HAZARD DUE TO LEVEE SYSTEM,T 93,A99,AREA WITH REDUCED FLOOD HAZARD DUE TO NON-ACCREDITED LEVEE SYSTEM,T 94,A,COMBINED RIVERINE AND COASTAL FLOODPLAIN,T 250,AREA NOT INCLUDED,Not Mapped by FEMA, Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

Vector data from the basic DLM are generalized for the digital topographic maps and processed according to the ATKIS signature catalogue. The digital data can be submitted via download or on other media carriers. They are available in a maximum of 22 content levels (according to the technical regulations of the AdV) in three forms (individual levels, gray combination and color combination). It should be noted that a UTM grid is only output in the individual levels. The standard resolution is 200L/cm = 508dpi. The TK (ATKIS) presents a map issue with the same content as a printed map. The data is provided free of charge via automated processes or by self-extraction. When using the data, the license conditions must be observed.

Description of files ✔️

• clean_map.png - a clean map with no player designations, bombs;

• mask_map.png - map mask for marking its borders;

• map_1.mp4 - Recorded map of 10 professional CS matches:GO on the map "Dust 2".

Video Characteristics ✔️

• size - 364x364px; • frame rate - 23.98 frames/s; • duration - 2 hours 5 minutes 5 seconds.

List of matches 🎉 👇

• PGL Major Antwerp 2022 Challengers Stage bad news eagles vs eternal fire;
• PGL Major Antwerp 2022 Challengers Stage ence vs g2;
• PGL Major Antwerp 2022 Challengers Stage g2 vs spirit;
• PGL Major Antwerp 2022 ence vs natus vincere;
• PGL Major Antwerp 2022 Europe RMR A faze vs big;
• PGL Major Antwerp 2022 Europe RMR A vitality vs eternal fire;
• PGL Major Antwerp 2022 faze vs spirit;
• PGL Major Antwerp 2022 g2 vs outsiders;
• PGL Major Stockholm 2021 astralis vs vitality;
• PGL Major Stockholm 2021 natus vincere vs vitality.

About creating a dataset 👇

I spent a lot of time and effort to create this video minimap of cs go matches. My goal was to find out which places for CT and TT are most often visited. I hope you liked this dataset and it will be useful 🤓.

Duration of all matches 👀

All demos of the matches lasted 622 minutes (or 10 hours and 22 minutes). I was recording a minimap at a speed of (x4), so I managed to spend 4 times less time on it. But it took a long time to remove the "breaks" for the CT and TT sides, which removed the minutes of inactivity of the players on the map. It turned out to put 10 hours 22 minutes in 2 hours 5 minutes, which is 4.9 times less.

These images were produced by aggregating 1' gridded data layers derived from the polygon-based Peatlands of Canada Database (Tarnocai et al., 2000) to 10' (horizontal) by 5' (vertical) and to 0.5 degree by 0.5 degree (or 30' by 30') pixel sizes in straight latitude/longitude grids. See the Peatlands Map of Canada data set for more information on the original data product that this is based on.

10-foot elevation contours for the extent of the state of Indiana, created from downloading, projecting and combining several datasets from USGS based on 7.5-minute quadrangle boundaries. These vector contour lines are derived from the 3D Elevation Program using automated and semi-automated processes. They were created to support 1:24,000-scale CONUS and Hawaii, 1:25,000-scale Alaska, and 1:20,000-scale Puerto Rico / US Virgin Island topographic map products, but are also published in this GIS vector format. Contour intervals are assigned by 7.5-minute quadrangle, so this vector dataset is not visually seamless across quadrangle boundaries. The vector lines have elevation attributes (in feet above mean sea level on NAVD88), but this dataset does not carry line symbols or annotation. Description from the original source metadata: These vector contour lines are derived from the 3D Elevation Program using automated and semi-automated processes. They were created to support 1:24,000-scale CONUS and Hawaii, 1:25,000-scale Alaska, and 1:20,000-scale Puerto Rico / US Virgin Island topographic map products, but are also published in this GIS vector format. Contour intervals are assigned by 7.5-minute quadrangle, so this vector dataset is not visually seamless across quadrangle boundaries. The vector lines have elevation attributes (in feet above mean sea level on NAVD88), but this dataset does not carry line symbols or annotation.Source files downloaded from The National Map on 11/18/2019:https://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Muncie_W_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Danville_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Vincennes_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Louisville_W_KY_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Cincinnati_W_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Indianapolis_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Fort_Wayne_W_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Chicago_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Indianapolis_W_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Danville_W_IL_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Vincennes_W_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Chicago_W_IL_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Cincinnati_E_OH_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Muncie_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Louisville_E_KY_1X1_GDB.zip https://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Fort_Wayne_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Evansville_E_IN_1X1_GDB.ziphttps://prd-tnm.s3.amazonaws.com/StagedProducts/Contours/GDB/ELEV_Evansville_W_IN_1X1_GDB.zip

1: The Interstellar Boundary Explorer (IBEX) has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 15 releases of IBEX-HI and/or IBEX-LO data covering 2009-2017. 2: This data set is from the Release 10 (6 months-cadence) IBEX-Lo map data for the first seven years 2009-2015 in the form of omnidirectional ENA (hydrogen) fluxes with no Compton-Getting correction (nocg) of flux spectra for spacecraft motion and correction for ENA survival probability (sp) between 1 and 100 AU. 3: The data consist of all-sky maps in Solar Ecliptic Longitude (east and west) and Latitude angles for ENA (hydrogen) fluxes from IBEX-Lo energy bands 5-8 in numerical data form. Energy channels 5-8 have FWHM center-point energies at 0.209, 0.439, 0.872, 1.821 keV, respectively. Details of the data and enabled science from Release 10 are given in the following journal publication: 4: S.A. Fuselier et al., The IBEX-Lo Sensor. Space Sci Rev (2009) 146: 117...147; DOI 10.1007/s11214-009-9495-8 5: https://link.springer.com/article/10.1007/s11214-009-9495-8 6. The following codes are used to define dataset types:- cg = Compton-Getting corrections have been applied to the data to account for the speed of the spacecraft relative to the direction of arrival of the ENAs.- nocg = no Compton-Getting corrections- sp = survival probability corrections have been applied to the data to account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to ~100 AU. In the original data this mode is denoted as Tabular.- noSP - no survival probability corrections have been applied to the data.- omni = data from all directions.- ram = data was collected when the spacecraft was ramming into the incoming ENAs.- antiram = data was collected when the spacecraft was moving away from the incoming ENAs. 7. The following list associates Release 10 map numbers (1-14) with mission year (1-7), orbits (11-310b), and dates (12/25/2008-12/23/2015):- Map 1: Map2009A, year 1, orbits 11-34, dates 12/25/2008-06/25/2009- Map 2: Map2009B, year 1, orbits 35-58, dates 06/25/2009-12/25/2009- Map 3: Map2010A, year 2, orbits 59-82, dates 12/25/2009-06/26/2010- Map 4: Map2010B, year 2, orbits 83-106, dates 06/26/2010-12/26/2010- Map 5: Map2011A, year 3, orbits 107-130a, dates 12/26/2010-06/25/2011- Map 6: Map2011B, year 3, orbits 130b-150a, dates 06/25/2011-12/24/2011- Map 7: Map2012A, year 4, orbits 150b-170a, dates 12/24/2011-06/22/2012- Map 8: Map2012B, year 4, orbits 170b-190b, dates 06/22/2012-12/26/2012- Map 9: Map2013A, year 5, orbits 191a-210b, dates 12/26/2012-06/26/2013- Map 10: Map2013B, year 5, orbits 211a-230b, dates 06/26/2013-12/26/2013- Map 11: Map2014A, year 6, orbits 231a-250b, dates 12/26/2013-06/26/2014- Map 12: Map2014B, year 6, orbits 251a-270b, dates 06/26/2014-12/24/2014- Map 13: Map2015A, year 7, orbits 271a-290b, dates 12/24/2014-06/24/2015- Map 14: Map2015B, year 7, orbits 291a-310b, dates 06/24/2015-12/23/2015 8: The energy resolution is delta-E/E = 0.8 for all channels:Energy channel 1: center energy = 0.015 keVEnergy channel 2: center energy = 0.029 keVEnergy channel 3: center energy = 0.055 keVEnergy channel 4: center energy = 0.11 keVEnergy channel 5: center energy = 0.209 keVEnergy channel 6: center energy = 0.439 keVEnergy channel 7: center energy = 0.872 keVEnergy channel 8: center energy = 1.821 keV 9: This particular data set, denoted in the original ascii files as lvset_h_tabular_mapN for N=1,14, includes pixel map data from all directions (omnidirectional), no CG, SP, 6 month cadence.

The topographic map on a scale of 1:10,000 is the basic scale of Brandenburg's topographical maps. The earth's surface is relatively complete (only slightly generalized) and geometrically exact to scale. It is the cartographic implementation of a comprehensive topographical survey of the country (photogrammetric aerial image evaluation, incorporation of topographical additional information, topographical field comparison). The historical editions of the TK10 are available from different years from 1992 (basic up-to-dateness of individual sheets older). From 2002, the TK10 (ATKIS) was created by deriving from the basic landscape model (basic DLM). In different map layouts and representations, the historical map sheets depict a piece of Brandenburg's contemporary history. They are available in analogue plot output (paper) and are available free of charge as downloads. When using the data, the license conditions must be observed.

This IBEX-Hi data set is from Release 10 of all-sky map data for the first seven years, 2009-2015, in the form of ram direction Hydrogen, H, energetic neutral atom fluxes with Compton-Getting corrections for spacecraft motion and with corrections for ENA survival probability between 1 and 100 AU. All-sky maps have been compiled for each consecutive 1 year time interval. The Interstellar Boundary Explorer, IBEX, has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 14 releases of IBEX-Hi and/or IBEX-Lo data covering 2009-2017. The data consist of all-sky maps in Solar Ecliptic Longitude, east and west, and Latitude angles for Energetic Neutral Atom, ENA, Hydrogen fluxes from IBEX-Hi from energy band 2 through energy band 6, see the first table below, in numerical data form. This particular data set is from IBEX Release 10 which includes observation from the first seven years, 2009-2015, of the IBEX mission. Details of the data and enabled science from Release 10 are given in the following journal publication: McComas, D.J., et al. (2017), Seven Years of Imaging the Global Heliosphere with IBEX, Astrophys. J. Supp. Ser., 229(2), 41 (32 pp.), http://doi.org/10.3847/1538-4365/aa66d8 The IBEX-Hi band/channel center energies and full width half maximum, FWHM, energy ranges are listed in a table below: +-----------------------------------------------------+ Energy Band Center Energy Energy Range ----------------------------------------------------- Channel 2 ~0.71 keV 0.52 keV to 0.95 keV Channel 3 ~1.11 keV 0.84 keV to 1.55 keV Channel 4 ~1.74 keV 1.36 keV to 2.50 keV Channel 5 ~2.73 keV 1.99 keV to 3.75 keV Channel 6 ~4.29 keV 3.13 keV to 6.00 keV +-----------------------------------------------------+ This particular IBEX-Hi CDF data product was constructed from the original ascii files named using the pattern hvset_tabular_ram_cg_yearN for N=1,7, includes pixel map data from the ram direction, with corrections, cg, for the Compton-Getting effect corrections, sp, for ENA survival probability between 1 AU and 100 AU, and a map compilation cadence equal to 1 year. In all, there are 12 IBEX-Hi Release 10 CDF data products resulting from the multiplication of options for two Compton-Getting correction settings by two survival probability settings by three directional settings: antiram, ram, omni. The table below defines how the file naming pattern is constructed for each data product. Note that "ibex_h3_ena_hi_r10" is the file naming pattern root for all twelve of these IBEX-Hi CDF data products. The asterisk symbols in the last column of the table shows the line corresponding to this CDF data product within the expanded file naming pattern schema. +-----------------------------------------------------------------------------------------------------+ C-G Corr. SP Corr. Dir. Acronym Map Cadence File Naming Pattern for 1 yr Skymaps ----------------------------------------------------------------------------------------------------- cg nosp antiram 1 year ibex_h3_ena_hi_r10_cg_nosp_antiram_1yr cg sp antiram 1 year ibex_h3_ena_hi_r10_cg_sp_antiram_1yr nocg nosp antiram 1 year ibex_h3_ena_hi_r10_nocg_nosp_antiram_1yr nocg sp antiram 1 year ibex_h3_ena_hi_r10_nocg_sp_antiram_1yr ----------------------------------------------------------------------------------------------------- cg nosp ram 1 year ibex_h3_ena_hi_r10_cg_nosp_ram_1yr cg sp ram 1 year ibex_h3_ena_hi_r10_cg_sp_ram_1yr *** nocg nosp ram 1 year ibex_h3_ena_hi_r10_nocg_nosp_ram_1yr nocg sp ram 1 year ibex_h3_ena_hi_r10_nocg_sp_ram_1yr ----------------------------------------------------------------------------------------------------- cg nosp omni 6 months ibex_h3_ena_hi_r10_cg_nosp_omni_6mo cg sp omni 6 months ibex_h3_ena_hi_r10_cg_sp_omni_6mo nocg nosp omni 6 months ibex_h3_ena_hi_r10_nocg_nosp_omni_6mo nocg sp omni 6 months ibex_h3_ena_hi_r10_nocg_sp_omni_6mo +-----------------------------------------------------------------------------------------------------+ The first column in the above table shows whether Compton-Getting, C-G, corrections have been applied to the data. C-G corrections account for how ENA measurements are affected by the the orientation of the IBEX spacecraft velocity vector relative to the arrival direction of the ENAs. cg: Compton-Getting corrections applied nocg: Compton-Getting corrections not applied The second column in the above table shows whether Survival Probability, SP, corrections have been applied to the data. SP corrections account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to ~100 AU. In the original data this mode is denoted as Tabular. sp: Survival Probability corrections applied nosp: Survival Probability corrections not applied The third column in the above table shows the constraint placed on the ENA arrival direction relative to spacecraft motion used in the construction of each of the various IBEX-Hi Skymaps. omni: All data, no Constraint on the IBEX velocity vector relative to the ram direction of incoming ENAs ram: Data constrained to times when the IBEX velocity vector pointed into the ram direction of the incoming ENAs antiram: Data constrained to times when the IBEX velocity vector pointed away from the ram direction of the incoming ENAs The data in IBEX Release 10 are separated into 6 month and 1 year segments. The following table shows the association between Release 10 map numbers from 1 to 14 with mission year from 1 to 7, orbits from 11 to 310b, and dates from 2008-12-25 to 2015-12-23. +-------------------------------------------------------------------------+ Skymap # Year Start-End of Orbit or Arcs Start Date to Stop Date ------------------------------------------------------------------------- 1 1 11-34 2008-12-25 to 2009-06-25 2 1 35-58 2009-06-25 to 2009-12-25 3 2 59-82 2009-12-25 to 2010-06-26 4 2 83-106 2010-06-26 to 2010-12-26 5 3 107-130a 2010-12-26 to 2011-06-25 6 3 130b-150a 2011-06-25 to 2011-12-24 7 4 150b-170a 2011-12-24 to 2012-06-22 8 4 170b-190b 2012-06-22 to 2012-12-26 9 5 191a-210b 2012-12-26 to 2013-06-26 10 5 211a-230b 2013-06-26 to 2013-12-26 11 6 231a-250b 2013-12-26 to 2014-06-26 12 6 251a-270b 2014-06-26 to 2014-12-24 13 7 271a-290b 2014-12-24 to 2015-06-24 14 7 291a-310b 2015-06-24 to 2015-12-23 +-------------------------------------------------------------------------+

The topographic map on a scale of 1:10,000 is the basic scale of Brandenburg's topographical maps. The earth's surface is relatively complete (only slightly generalized) and geometrically exact to scale. It is the cartographic implementation of a comprehensive topographical survey of the country (photogrammetric aerial image evaluation, incorporation of topographical additional information, topographical field comparison). The historical editions of the TK10 are available from different years from 1992 (basic up-to-dateness of individual sheets older). From 2002, the TK10 (ATKIS) was created by deriving from the basic landscape model (basic DLM). In different map layouts and representations, the historical map sheets depict a piece of Brandenburg's contemporary history. They are available in analogue plot output (paper) and are available free of charge as downloads. When using the data, the license conditions must be observed.

Based on professional technical analysis and AI models, deliver precise price‑prediction data for MAP Protocol on 2025-11-10. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.

Data are derived from 2010-2014 (6-10 years) aerial detection surveys for tree defoliation and mortality from the USFS Forest Health Assessment and Applied Sciences Team (FHAAST) National Forest Pest Conditions Database. Polygons are created by aerial sketch mapping, and coded for defoliation and mortality, in addition to other damage codes. Defoliation and mortality layers were created from the polygon data and the attribute codes. The layers were merged to compensate for difficulties in identifying defoliation separately from mortality in hardwoods vs. conifer forests. Areas that were defoliated during three of the years recorded in the five-year dataset are thought to have significant impacts and likely mortality, so these polygons were added to the mortality layer. The layer includes areas with mortality classed as very light .

This dataset is one of the three separate files that the ICD-10-CM MAP contains. Extended Map contains the core publication of MAP data. There are one or more map records for each source concept mapped, including the ICD-10-CM target codes. This dataset is an update of the SNOMED CT to ICD-10-CM Cross Map. The purpose of this update is to synchronize with the latest release of the US Edition of SNOMED CT by removing obsolete content.

With the field surveys and communications with mangrove experts, the previous version of mangrove map in China for 2019 had the omission problem that some mangrove patches were missing in the product. A mangrove map using an image interpretation and field investigation approach was then released. This mangrove map was checked by field survey in some areas, thus can be a reference to update the previous version of mangrove map. A new mangrove map was derived by integrating existing data sets, eliminating the misclassified patches, and repairing the missing mangrove patches. Based on an evaluation sample dataset (the data was in doi:10.11922/sciencedb.00279), the overall accuracy reached 97.0 ± 0.2%. The accurate rate in metrics of 1096 field sample plots was 96.7%. The total area of ​​mangroves in China in 2019 is estimated to be 27053.07 ha under the asia north albers equal area conic projection, which is highly consistent with the rresult of the third national land survey. This dataset provides a basis for mangrove protection, restoration, and management in China, mangrove related carbon sink estimation, and related studies in China.

This IBEX-Hi data set is from Release 10 of all-sky map data for the first seven years, 2009-2015, in the form of ram direction Hydrogen, H, energetic neutral atom fluxes with no Compton-Getting corrections for spacecraft motion and with corrections for ENA survival probability between 1 and 100 AU. All-sky maps have been compiled for each consecutive 1 year time interval. The Interstellar Boundary Explorer, IBEX, has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 14 releases of IBEX-Hi and/or IBEX-Lo data covering 2009-2017. The data consist of all-sky maps in Solar Ecliptic Longitude, east and west, and Latitude angles for Energetic Neutral Atom, ENA, Hydrogen fluxes from IBEX-Hi from energy band 2 through energy band 6, see the first table below, in numerical data form. This particular data set is from IBEX Release 10 which includes observation from the first seven years, 2009-2015, of the IBEX mission. Details of the data and enabled science from Release 10 are given in the following journal publication: McComas, D.J., et al. (2017), Seven Years of Imaging the Global Heliosphere with IBEX, Astrophys. J. Supp. Ser., 229(2), 41 (32 pp.), http://doi.org/10.3847/1538-4365/aa66d8 The IBEX-Hi band/channel center energies and full width half maximum, FWHM, energy ranges are listed in a table below: +-----------------------------------------------------+ Energy Band Center Energy Energy Range ----------------------------------------------------- Channel 2 ~0.71 keV 0.52 keV to 0.95 keV Channel 3 ~1.11 keV 0.84 keV to 1.55 keV Channel 4 ~1.74 keV 1.36 keV to 2.50 keV Channel 5 ~2.73 keV 1.99 keV to 3.75 keV Channel 6 ~4.29 keV 3.13 keV to 6.00 keV +-----------------------------------------------------+ This particular IBEX-Hi CDF data product was constructed from the original ascii files named using the pattern hvset_tabular_ram_yearN for N=1,7, includes pixel map data from the ram direction, with no corrections, nocg, for the Compton-Getting effect corrections, sp, for ENA survival probability between 1 AU and 100 AU, and a map compilation cadence equal to 1 year. In all, there are 12 IBEX-Hi Release 10 CDF data products resulting from the multiplication of options for two Compton-Getting correction settings by two survival probability settings by three directional settings: antiram, ram, omni. The table below defines how the file naming pattern is constructed for each data product. Note that "ibex_h3_ena_hi_r10" is the file naming pattern root for all twelve of these IBEX-Hi CDF data products. The asterisk symbols in the last column of the table shows the line corresponding to this CDF data product within the expanded file naming pattern schema. +-----------------------------------------------------------------------------------------------------+ C-G Corr. SP Corr. Dir. Acronym Map Cadence File Naming Pattern for 1 yr Skymaps ----------------------------------------------------------------------------------------------------- cg nosp antiram 1 year ibex_h3_ena_hi_r10_cg_nosp_antiram_1yr cg sp antiram 1 year ibex_h3_ena_hi_r10_cg_sp_antiram_1yr nocg nosp antiram 1 year ibex_h3_ena_hi_r10_nocg_nosp_antiram_1yr nocg sp antiram 1 year ibex_h3_ena_hi_r10_nocg_sp_antiram_1yr ----------------------------------------------------------------------------------------------------- cg nosp ram 1 year ibex_h3_ena_hi_r10_cg_nosp_ram_1yr cg sp ram 1 year ibex_h3_ena_hi_r10_cg_sp_ram_1yr nocg nosp ram 1 year ibex_h3_ena_hi_r10_nocg_nosp_ram_1yr nocg sp ram 1 year ibex_h3_ena_hi_r10_nocg_sp_ram_1yr *** ----------------------------------------------------------------------------------------------------- cg nosp omni 6 months ibex_h3_ena_hi_r10_cg_nosp_omni_6mo cg sp omni 6 months ibex_h3_ena_hi_r10_cg_sp_omni_6mo nocg nosp omni 6 months ibex_h3_ena_hi_r10_nocg_nosp_omni_6mo nocg sp omni 6 months ibex_h3_ena_hi_r10_nocg_sp_omni_6mo +-----------------------------------------------------------------------------------------------------+ The first column in the above table shows whether Compton-Getting, C-G, corrections have been applied to the data. C-G corrections account for how ENA measurements are affected by the the orientation of the IBEX spacecraft velocity vector relative to the arrival direction of the ENAs. cg: Compton-Getting corrections applied nocg: Compton-Getting corrections not applied The second column in the above table shows whether Survival Probability, SP, corrections have been applied to the data. SP corrections account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to ~100 AU. In the original data this mode is denoted as Tabular. sp: Survival Probability corrections applied nosp: Survival Probability corrections not applied The third column in the above table shows the constraint placed on the ENA arrival direction relative to spacecraft motion used in the construction of each of the various IBEX-Hi Skymaps. omni: All data, no Constraint on the IBEX velocity vector relative to the ram direction of incoming ENAs ram: Data constrained to times when the IBEX velocity vector pointed into the ram direction of the incoming ENAs antiram: Data constrained to times when the IBEX velocity vector pointed away from the ram direction of the incoming ENAs The data in IBEX Release 10 are separated into 6 month and 1 year segments. The following table shows the association between Release 10 map numbers from 1 to 14 with mission year from 1 to 7, orbits from 11 to 310b, and dates from 2008-12-25 to 2015-12-23. +-------------------------------------------------------------------------+ Skymap # Year Start-End of Orbit or Arcs Start Date to Stop Date ------------------------------------------------------------------------- 1 1 11-34 2008-12-25 to 2009-06-25 2 1 35-58 2009-06-25 to 2009-12-25 3 2 59-82 2009-12-25 to 2010-06-26 4 2 83-106 2010-06-26 to 2010-12-26 5 3 107-130a 2010-12-26 to 2011-06-25 6 3 130b-150a 2011-06-25 to 2011-12-24 7 4 150b-170a 2011-12-24 to 2012-06-22 8 4 170b-190b 2012-06-22 to 2012-12-26 9 5 191a-210b 2012-12-26 to 2013-06-26 10 5 211a-230b 2013-06-26 to 2013-12-26 11 6 231a-250b 2013-12-26 to 2014-06-26 12 6 251a-270b 2014-06-26 to 2014-12-24 13 7 271a-290b 2014-12-24 to 2015-06-24 14 7 291a-310b 2015-06-24 to 2015-12-23 +-------------------------------------------------------------------------+

These images were produced by aggregating 1' gridded data layers derived from the polygon-based Peatlands of Canada Database (Tarnocai et al., 2000) to 10' (horizontal) by 5' (vertical) and to 0.5 degree by 0.5 degree (or 30' by 30') pixel sizes in straight latitude/longitude grids. See the Peatlands Map of Canada data set for more information on the original data product that this is based on.

Here we produced the first 10 m resolution urban green space (UGS) map for the main urban clusters across 371 major Latin American cities as of 2017. Our approach applied a supervised classification of Sentinel-2 satellite imagery and UGS samples derived from OpenStreetMap (OSM). The overall accuracy of this UGS map in 11 randomly selected cities was 0.87, evaluated by independently collected validation samples (‘ground truth’). We further improved mapping quality through a visual inspection and additional sample collection. The resulting UGS map enables studies to measure area, spatial configuration, and human exposures to UGS, facilitating studies about the relationship between UGS and human exposures to environmental hazards, public health outcomes, and environmental justice issues in Latin American cities.UGS in this map series includes grass, shrub, forest, and farmland, and non-UGS included buildings, pavement, roads, barren land, and dry vegetation.The UGS map series includes three sets of files:(1) binary UGS maps at 10 m spatial resolution in GEOTIFF format (UGS.zip), with each of the 371 cities being an individual map. Mapped value of 1 indicates UGS, 0 indicates non-UGS, and no data (with value of -32768) indicates areas outside the mapped boundary or water bodies;(2) a shapefile of mapped boundaries (Boundaries.zip). The boundary file contains city name, country name and its ISO-2 country code, and an ID field linking each city's boundary to the corresponding UGS map.(3) .prj files containing projection information for the binary UGS maps and boundary shapefile. The binary UGS maps are projected with World Geodetic System (WGS) 84 / Pseudo-Mercator projected coordinate system (EPSG: 3857), and the boundary shapefile is projected with WGS 1984 geographic coordinate system (EPSG: 4326)Reference: A 10 m resolution urban green space map for major Latin American cities from Sentinel-2 remote sensing images and OpenStreetMap, published by Scientific Data [link].Citation: Ju, Y., Dronova, I., & Delclòs-Alió, X. (2022). A 10 m resolution urban green space map for major Latin American cities from Sentinel-2 remote sensing images and OpenStreetMap. Scientific Data, 9, Article 1. https://doi.org/10.1038/s41597-022-01701-y

DR: detection rate; FPR: false positive rate; MAP: Mean Arterial Pressure; CI: confidence interval; AUC: area under curve, EO-PE: early-onset preeclampsia; LO-PE: late-onset preeclampsia.*The best model selected for further validation.

Judicial Subdistrict 10 Precinct Map Book - 2022

The BGS collection of 1:10 560 / 1:10 000 National Grid Series geological maps. These maps are based on the Ordnance Survey National Grid series of maps, which are defined by the 10 km intervals of the larger 100 km square identified by a specific two-letter code. Each map is thus denoted by a unique reference, e.g. SP 29 NW. SP=100 km square; 29=10 km square; NW=5 km square. Since field mapping is generally undertaken at the scale of 1:10 000 (or equivalent), these maps are the largest-scale main series of geological maps that BGS holds. A small number of remote areas were mapped at 1:25 000 scale, the subsequent maps are also at 1:25 000 scale and are included in this series. The equivalent to the National Grid Series prior to the 1960s is the County Series (at 1:10 560 scale). In the 1960s, this series started to be replaced by 6 inches to 1 mile (1:10 560 scale) National Grid sheets based on the four quadrants (NW, NE, SW, SE) of a 10 km Ordnance Survey National Grid square. Areal coverage provided by the National Grid series of large-scale maps is limited in extent and the preceding County series of six-inch maps can still be the most up to date map available for some areas. Geological maps represent a geologist's compiled interpretation of the geology of an area. A geologist will consider the data available at the time, including measurements and observations collected during field campaigns, as well as their knowledge of geological processes and the geological context to create a model of the geology of an area. This model is then fitted to a topographic basemap and drawn up at the appropriate scale, with generalization if necessary, to create a geological map, which is a representation of the geological model. Explanatory notes and vertical and horizontal cross sections may be published with the map. Geological maps may be created to show various aspects of the geology, or themes. The most common map themes held by BGS are solid (later referred to as bedrock) and drift (later referred to as superficial). These maps are, for the most part, hard-copy paper records stored in the National Geoscience Data Centre (NGDC) and are delivered as digital scans through the BGS website.