An on-screen navigator can also be used to pan, zoom, rotate, and tilt the view.In this tutorial, you'll navigate a map and a scene using the Explore tool and the navigator. You'll also learn how to link views so your map and scene pan, zoom, and rotate together.Estimated time: 15 minutesSoftware requirements: ArcGIS Pro

Rotating cultivation practiced in last 12 months(0 no; 1 yes; 9 no response)Data Source: Lao Agriculture Census 2011Contact: Ministry of Agriculture and Forestry (MAF) URL: www.maf.gov.la Tel: 021-412345 Fax: 021-412344 E-mail: maf.infro@gmail.com P.O.BOX: 811ການປູກພືດ ໝູນ ວຽນໃນ 12 ເດືອນຜ່ານມາ (0 ບໍ່; 1 ແມ່ນແລ້ວ; 9 ບໍ່ມີການຕອບສະ ໜອງ)ການສຳຫລວດກະສີກຳ 2011ກະຊວງກະສີກຳ ແລະ ປ່າໄມ້ URL: www.maf.gov.la Tel: 021-412345 Fax: 021-412344 E-mail: maf.infro@gmail.com P.O.BOX: 811

Bike Hazard Locations.Jurisdiction (Jurisdiction) Maintaining organization. Public or private. Blank entry assumed public.Source (Source) Source of data - paper map, ortho photoComments (Comments) Rotation (Rotation) Used for cartographic purposesExternal ID (ExtID) Unique ID

Summary: Parcel Addresses Label Text - Rotate using the Rotation Field Disclaimer: The User acknowledges and agrees that the Data is provided by the City to the User for the User's convenience and reference, and that the City makes no guarantees, representations or warranties, whether express or implied, as to the Data or as to any results to be or intended to be achieved from use of the Data, including without limitation guarantees, representations or warranties as to the accuracy, quality or completeness of the Data, merchantability or fitness for use for any particular purpose, and the User hereby waives all guarantees, representations and warranties in respect of the Data, whether express, implied by statute or otherwise. The User hereby releases The City from, and hereby indemnifies and holds harmless The City from and against, any liability, obligation, costs (including without limitation legal costs), expenses, claims, actions, proceedings, damages and penalties to the User or any other person or legal entity resulting from or related to the use, disclosure or reproduction of or reliance on the Data.Specific information regarding land, including lot sizes, legal descriptions, and charges must be confirmed at the Land Title Office and the User must not rely on the City of Port Moody for this information.

Alacsony tartományban zóna autómegosztó helyeken szomszédsági szinten (400m és 5 perc séta). (lásd még: geodata portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=autodelen , nyílt geodata portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=autodelen ) számokban kifejezve – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=235073a7-11e4-4d89-9bd6-b8db6ba97bb2 ) Alacsony hatótávolságú (félig) nyilvános töltőállomások szomszédsági szinten (400m és 5 perc séta). (lásd még: geodata portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=autodelen , nyílt geodata portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=autodelen ) számokban kifejezve – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=235073a7-11e4-4d89-9bd6-b8db6ba97bb2 ) A szomszédos parkolók alacsony hatótávolságú övezete a szomszédság szintjén (400m és 5 perc séta). (lásd még: geodata-portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=szomszédsági parkoló , nyitott geodata-portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=szomszédsági parkoló ) számszerűsítve városi számokban – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=3309882d-dd96-45b4-9489-788cdc903c79 ) Kis hatótávolságú forgóparkolók helyi előfizetéssel (400m és 5 perc séta). Alacsony tartományban zóna park & ride szomszédsági szinten (400m és 5 perc séta). (lásd még: geodata portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=parkolás , nyílt geodata portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=parkolás ) számokban kifejezve – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=2e04f9fb-2fa9-44e8-b041-b9522f1fba4a ) Ezeket az adatrétegeket januárban évente frissítik, feltéve, hogy a létesítményt az érintett ágazat/szolgáltatás kezeli és évente frissíti. A létesítmény bizonyos hatótávolsággal rendelkezik a gyalogos távolság alapján, figyelembe véve a fontos akadályokat (víz, gyűrű, autópálya, vasút stb.) és a veszélyeztetett úthasználók számára biztonságos átkelőhelyeket (alagutak, hidak, közlekedési lámpákkal ellátott gyalogos átkelőhelyek). építőelem: 150 méter vagy 2 perc séta - szomszédság létesítmény: 400 méter vagy 5 perc séta - szomszédság létesítmény: 800 méter vagy 10 perc séta / 1000 méter vagy 15 perc séta - kerületi létesítmény: 1600 méter vagy 20 perc séta vagy 10 perc kerékpározás / 2400 méter vagy 30 perc séta vagy 15 perc kerékpározás. Összesen mintegy 50 helyi lakástámogatási létesítmény kap hozzáférési zónákat. A deficitzónával kombinálva ez a réteg képet ad a létesítmény térbeli eloszlásáról. Ez lehetővé teszi a szakpolitika számára, hogy a gyalogos távolság alapján megtervezze a létesítmény kiegyensúlyozott térbeli eloszlását. Alacsony tartományban zóna autómegosztó helyeken szomszédsági szinten (400m és 5 perc séta). (lásd még: geodata portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=autodelen , nyílt geodata portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=autodelen ) számokban kifejezve – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=235073a7-11e4-4d89-9bd6-b8db6ba97bb2 ) Alacsony hatótávolságú (félig) nyilvános töltőállomások szomszédsági szinten (400m és 5 perc séta). (lásd még: geodata portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=autodelen , nyílt geodata portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=autodelen ) számokban kifejezve – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=235073a7-11e4-4d89-9bd6-b8db6ba97bb2 ) A szomszédos parkolók alacsony hatótávolságú övezete a szomszédság szintjén (400m és 5 perc séta). (lásd még: geodata-portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=szomszédsági parkoló , nyitott geodata-portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=szomszédsági parkoló ) számszerűsítve városi számokban – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=3309882d-dd96-45b4-9489-788cdc903c79 ) Kis hatótávolságú forgóparkolók helyi előfizetéssel (400m és 5 perc séta). Alacsony tartományban zóna park & ride szomszédsági szinten (400m és 5 perc séta). (lásd még: geodata portál – https://geoportaal.antwerpen.be/portal/home/search.html?q=parkolás , nyílt geodata portál – http://portaal-stadantwerpen.opendata.arcgis.com/datasets?q=parkolás ) számokban kifejezve – https://stadincijfers.antwerpen.be/Databank/Jive/?workspace_guid=2e04f9fb-2fa9-44e8-b041-b9522f1fba4a ) Ezeket az adatrétegeket januárban évente frissítik, feltéve, hogy a létesítményt az érintett ágazat/szolgáltatás kezeli és évente frissíti. A létesítmény bizonyos hatótávolsággal rendelkezik a gyalogos távolság alapján, figyelembe véve a fontos akadályokat (víz, gyűrű, autópálya, vasút stb.) és a veszélyeztetett úthasználók számára biztonságos átkelőhelyeket (alagutak, hidak, közlekedési lámpákkal ellátott gyalogos átkelőhely

Fire Threat is a combination of two factors: 1) fire probability, or the likelihood of a given area burning, and 2) potential fire behavior (hazard). These two factors are combined to create 5 threat classes ranging from low to extreme.This version (fthrt14_2) is an update created from fthrt14_1 (created for the FRAP 2017 Forest and Rangeland Assessment). Fire Rotation data in fthrt14_1 was replaced with Annual Fire Probability data developed for California by Pyrologix Inc.

The dataset utilizes satellite imagery raster files from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature/Emissivity 8-Day (MOD11A2) Version 6.1 product. This data provides an average 8-day per-pixel Land Surface Temperature and Emissivity (LST&E) with a spatial resolution of 1 kilometer within a 1,200 by 1,200 km grid.The variables extracted from this dataset are Daytime and Nighttime land surface temperatures in degrees Celsius. The data covers the period from January 1, 2020, to December 31, 2023, offering a comprehensive view over four years. It includes quality control assessments, observation times, view zenith angles, clear-sky coverages, and emissivity values for different land cover types.The dataset integrates spatial boundaries from shapefiles with the imagery raster files to provide data at various geographical levels, including state, county, census tract, and zip code, although your specific analysis seems to focus on the state level in Oklahoma.The data is updated every 8 days, aligning with the ground track repeat period of the Terra and Aqua platforms. The provided data link directs to the Earth Engine catalog, offering access to the MOD11A2 dataset.Variable NameDescriptionStateNameName of the stateStateFipsState FIPS codeDateDate at which temperature is recordedLST_Day_1kmDay land surface temperature in degrees CelsiusLST_Night_1kmNight land surface temperature in degrees Celsius

Fire Threat is a combination of two factors: 1) fire probability, or the likelihood of a given area burning, and 2) potential fire behavior (hazard). These two factors are combined to create 5 threat classes ranging from low to extreme.This version (fthrt14_2) is an update created from fthrt14_1 (created for the FRAP 2017 Forest and Rangeland Assessment). Fire Rotation data in fthrt14_1 was replaced with Annual Fire Probability data developed for California by Pyrologix Inc.

This map shows where soybeans were grown in Minnesota from 2008 to 2022. It was made using data from the US Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), which tracks what crops are grown across the U.S. every year using remote sensing through satellite imagery. Each square on the map is 30x30 meters, and the colors show how often soybeans were planted there during the 15 year period from 2008 to 2022.Whitemeans soybeans were not grown on that square between 2008-2022Deep greenmeanssoybeanswere frequently grown there (more than 5 of the 15 years).Lighter shades of greenshow places where soybeanswere sometimes grown less frequently, often as part of crop rotation practices where farmers switch between multiple different crops.The map shows thatsoybeansare mostly grown in the southern and western parts of Minnesota (lots ofgreen), which is the mainsoybean-growing area. This is because the soil, rain, and temperature conditions are better forsoybeansin these areas than in other parts of the state.Each colored square on the map represents a 30-by-30 meter area of land (about the size of two basketball courts). By looking at these same locations over 15 years, we can see how often they were used for growingsoybeans. This long-term view helps us understand farming practices better than looking at just one year, as it can shows long-term patterns rather than temporary changes.This visualization is useful for:- Understanding where Minnesota's mainsoybean-growing regions are- Seeing how natural conditions like soil and climate affect farming choices- Identifying areas where farmers regularly rotate betweensoybeansand other crops- Showing the boundaries between intensive farming areas and other land uses

This data set provides the boundaries of known oil palm concessions for the state of Sarawak, Malaysia, and was compiled from available public documents. Where available, associated information provided with this data set includes licensee name, permit number (Operational Ticket), corporate grouping, permit date, and official license area. This data set also includes areas under License for Planted Forest (LPF) agreements where oil palm has been planted for one rotation, where availableThe data set combines the boundaries of oil palm licenses obtained from Environmental Impact Assessment (EIA) reports for individual oil palm and LPF concessions (spanning various dates) and a regional State Forestry Department map from 2010 for northern Sarawak. The information drawn from oil palm EIA reports was compiled by Aidenvironment and SADIA, and combined with the other information by Earthsight Investigations. Licenses (and licensee subsidiaries) have been attributed to major corporate groups based on published company records and secondary sources.A number of the oil palm concession licenses are split into non-contiguous parts. In some cases separate boundary entries are given for each part; these are annotated 'Part 1' etc in the title. These 'Parts' are not official names, but rather naming conventions used in the GIS cleaning of the data.