You can get all global flight information in 1 API call or track flights based on flight number, airline, departure/arrival airport, and more. The data updates frequently, around every 5 minutes. The details of the data include:

Geography: Location information such as latitude, longitude, altitude, and direction. Speed: Vertical and horizontal speed of aircraft. Departure and arrival: IATA codes and ICAO codes of the departure and arrival airport. Aircraft and flight: IATA and ICAO number of flight and registration number, ICAO code, and ICAO24 code of aircraft. Airline: IATA code, and ICAO code of airline. System information: Squawk, status, and last updated in Epoch.

Here's an example response from the API: [ { "geography": { "latitude": 43.5033, "longitude": -79.1297, "altitude": 7833.36, "direction": 70 }, "speed": { "horizontal": 833.4, "isGround": 0, "vertical": 0 }, "departure": { "iataCode": "YHM", "icaoCode": "CYHM" }, "arrival": { "iataCode": "YQM", "icaoCode": "CYQM" }, "aircraft": { "icaoCode": "B763", "regNumber": "CGYAJ", "icao24": "C08412" }, "airline": { "iataCode": "W8", "icaoCode": "CJT" }, "flight": { "iataNumber": "W8620", "icaoNumber": "CJT620", "number": "620" }, "system": { "updated": 1513148168, "squawk": "0000" }, "status": "en-route" } ]

Developer Information:

1) Available Endpoints &depIata= &depIcao= &arrIata= &arrIcao= &aircraftIcao= &regNum= &aircraftIcao24= &airlineIata= &airlineIcao= &flightIata= &flightIcao= &flightNum= &status= &limit= &lat=&lng=&distance=

2) Flights Tracker API Output

Specific flight based on: Flight IATA Number: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&flightIata=W8519

All flights of a specific Airlines: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&airlineIata=W8

Flights from departure location: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&depIata=MAD

Flights from arrival location: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&arrIata=GIG

Flights within a circle area based on lat and lng values and radius as the distance: GET https://aviation-edge.com/v2/public/flights?key=[API_KEY]&lat=51.5074&lng=0.1278&distance=100&arrIata=LHR

Combinations: two airports and a specific airline flying between them: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&depIata=ATL&arrIata=ORD&airlineIata=UA

Air traffic network-product is a link-knot routing dataset compliant with INSPIRE requirements. It includes f.ex. flight routes and aerodromes. Data shall not be used for operational flight activities or flight planning.

INSPIRE Air Traffic Network-product includes spatial information of air traffic network in accordance with the INSPIRE Directive. The data has been retrieved from the EAD database maintained by Eurocontrol. Information is updated regularly but is not constantly up to date. Data can be used for purposes that are in accordance with the INSPIRE Directive, but shall not be used for operational flight activities or flight planning. ANS Finland www.ais.fi –site provides information for operational flight activities or flight planning

Available layers

Aerodrome Node: Node located at the aerodrome reference point of an airport/heliport, which is used to represent it in a simplified way.DEFINITION Aerodrome Reference Point (ARP): The designated geographical location of an aerodrome, located near the initial or planned geometric centre of the aerodrome and normally remaining where originally established [AIXM3.3].DEFINITION Airport/heliport: A defined area on land or water (including any buildings, installations and equipment) intended to be used either wholly or in part for the arrival, departure and surface movement of aircraft/helicopters [AIXM5.0].

Air Route Link: A portion of a route to be flown usually without an intermediate stop, as defined by two consecutive significant points

Air Space Area: A defined volume in the air, described as horizontal projection with vertical limits.

Designated Point: A geographical location not marked by the site of a radio navigation aid, used in defining an ATS route, the flight path of an aircraft or for other navigation or ATS purposes.

Instrument Approach Procedure: A series of predetermined manoeuvres by reference to flight instruments with specified protection from obstacles from the initial approach fix, or where applicable, from the beginning of a defined arrival route to a point from which a landing can be completed and thereafter, if a landing is not completed, to a position at which holding or en route obstacle clearance criteria apply.

Navaid: One or more Navaid Equipments providing navigation services.DEFINITION Navaid equipment: A physical navaid equipment like VOR, DME, localizer, TACAN or etc.

Procedure Link: A series of predetermined manoeuvres with specified protection from obstacles.

Runway Area: A defined rectangular area on a land aerodrome/heliport prepared for the landing and take-off of aircraft.

Runway Centerline Point: An operationally significant position on the center line of a runway direction.

Standard Instrument Arrival: A designated instrument flight rule (IFR) arrival route linking a significant point, normally on an ATS route, with a point from which a published instrument approach procedure can be commenced.

Standard Instrument Departure: A designated instrument flight rule (IFR) departure route linking the aerodrome or a specific runway of the aerodrome with a specified significant point, normally on a designated ATS route, at which the en-route phase of a flight commences.

Surface Composition: Runway surface material

CTR (Not INSPIRE): A control zone (CTR) is a block of Controlled Airspace extending from the surface of the earth to a specified upper limit.

A polygon features class representing low-level and high-level Special Use Airspace in the member states of the Western Governor's Association (excludes Pacific Islands). Dataset was extracted from the National Geospatial Intelligence Agency (NGA), Digital Aeronautical Flight Information File (DAFIF). This data set is subject to review and updates. Please refer to appropriate FAA and DoD Publications (AP/1A and AP/1B) for the most current information.

Special Use Airspace (SUA) is airspace of defined dimensions identified by an area on the surface of the earth wherein activities must be confined because of their nature, and/or wherein limitations may be imposed upon aircraft operations that are not a part of those activities (FAA Order 7610.4K CHG 1, Section 1.3). Types of special use airspace include Military Operating Areas (MOAs), Restricted Areas, and Warning Areas.

© National Geospatial Intelligence Agency, Digital Aeronautical Flight Information File (DAFIF)

The dataset contains locations and attributes of P56A and P56B flight restrictions in the District of Columbia. A dataset provided by the National Geospatial-Intelligence Agency (NGA) identified P56A and P56B flight restrictions in DC. The data specifically comes from NGA's Digital Aeronautical Flight Information File (DAFIF).

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Elevation Contours for the Northern Experimental Forest

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

This data layer contains elevation contours for the 10 X 10 km area located within the Northern Experimental Forest. Contours and elevation benchmarks from the United States Geological Survey 7.5" Maine quadsheets for Howland and Lagrange were digitized, and elevation data in feet were added.

The data was revised by projecting it into NAD83 datum by L. Prihodko at NASA Goddard Space Flight Center. Although the data was received at GSFC with an undeclared datum, it was assumed to be in North American Datum of 1927 (NAD27) because the original map from which the data were digitized was in NAD27. Also, the data fit exactly within the bounds of the FED site grid (even Universal Transverse Mercator projections) in NAD27. After projecting the data into NAD83 it was checked to insure that the change was a linear translation of the coordinates.

The map service provides the following information.

Flight noise:

Air noise protection areas Settlement restriction area Langenhagen

Ambient noise:

Roads NDS Municipalities Noise protection structures Agglomeration Street noise Lden Street noise Ln Flight noise Lden Flight noise Ln

Air pollutant calculations:

Average PM10 load 2020 in µg/m³ Mean PM10 load 2019 in µg/m³ Average PM10 load 2018 in µg/m³ Average PM10 load 2017 in µg/m³ Average PM10 load 2016 in µg/m³ Nitrogen dioxide NO2 — total load as annual mean value 2010 Nitrogen dioxide NO2 — Total load as annual mean value 2015 Nitrogen dioxide NO2 — total load as annual mean value 2015 M Particulate matter PM10 — probability of exceedance of the 35-day criterion as annual mean value 2010 Particulate matter PM10 — probability of exceedance of the 35-day criterion as annual mean value 2015 Environmental zones Places with Air Pollutant Calculation

Industrial plants:

G-systems IED installations Large combustion plants Operating Areas

Air quality monitoring:

Locations of the LUEN measuring stations Assessment areas and agglomerations — air Ecosystem Protected Areas — Air

Hermelin:

Total Immission: Total NO2 emissions PM10 Total Immission

Preload: NOx immission, 500 m grid NOx-Immission, 2 km grid NO2 emission, 500 m grid NO2-Immission, 2 km grid PM10 immission, 500 m grid PM10-Immission, 2 km grid O3-Immission, 500 m grid O3-Immission, 2 km grid

Total emissions: Total NOx emission PM10 Total Emission System Environment: ArcGIS-Server Explanation on the subject reference: The technical data will be updated as required.

Vector data of the area multipurpose map (FMZK) - the digital city map of Vienna as of the reference date 18.1.2024. The inventory reflects the multi-purpose area map based on the aerial image analysis of the aerial flight in 2023. The entire city area is made available as a data collection. http://www.wien.gv.at/urban development/urban survey/geodaten/fmzk/index.html Important note: More information on the data status in the road area and in the interior of the road blocks can be found in the data set Multipurpose Map Sheet Information 1000 Vienna. https://www.data.gv.at/katalog/dataset/b2d17060-b2f4-4cd7-a2e5-64beccfeb4c1.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Stem Map for Northern Experimental Forest Spruce Site

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem. The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

The Stem map data covers a site located on the Southern border of the Howland, Maine township. The data contains tree diameter at breast height (DBH), species, and canopy position. The data were collected during June - September 1990 by Kate LeJeune of the University of Virginia. Original coordinates of tree position were in meters with an origin at 0,0 in the Southeast corner of the map, X increasing to the North and Y increasing to the West. The origin is located on the Howland townline at 184.89 meters from the intersection of the townline with Gunbarrel road. Origin Universal Transverse Mercator (UTM) coordinates were determined from the FED Geographic Information System (GIS). Coordinates of individual trees were calculated based on this information and the X,Y position measured in meters. UTM coordinates were originally calculated in the North American Datum of 1927 (NAD27).

Effective date: 2025-06-12 up to and including 2025-07-09The data contains area navigation routes, helicopter routes and military low flying routes within the Dutch FIR (EHAA).The Military Low Flying Route feature currently does not have data available and will be supplemented at a later time.Data provided conforms to eAIP publication; consult NOTAMs for latest information.For any inquiries regarding the data, please reach out to gis@lvnl.nl.

description: Aeromagnetic data were collected along flight lines by instruments in an aircraft that recorded magnetic-field intensity values and location. In surveys such as this one where the data were originally collected in digital form and not digitized from contour maps, the information we provide typically includes latitude, longitude, magnetic anomaly in nanoTeslas, and intermediate values used to derive the magnetic anomaly such as total magnetic field.; abstract: Aeromagnetic data were collected along flight lines by instruments in an aircraft that recorded magnetic-field intensity values and location. In surveys such as this one where the data were originally collected in digital form and not digitized from contour maps, the information we provide typically includes latitude, longitude, magnetic anomaly in nanoTeslas, and intermediate values used to derive the magnetic anomaly such as total magnetic field.

Location of flight lines of Yukon aerial photographs. Data was produced from heads up digitization of paper flight line index maps . Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

The service dynamically produces the map of the flight plan relating to the aerial shot taken in 2009. The data, spatially referred starting from geographical information, reproduce the encumbrance of the frames that make up the strips of the flight covering the territory of the province of L' Aquila, areas affected by the earthquake and the territory of the province of Chieti. By querying the map, a series of identification information is visible relating to the frame number, the flight altitude, the focal length, the executing company, the date of the photo taking.

This inventory of traffic areas in the city of Brunswick, Germany, is based on image sequences acquired during six flight campaigns at different times of the day and year in 2019 and 2020. Each aerial image is segmented by a neural network into the classes (1) Parking area, (2) Road, and (3) Access way, with the latter two classes differing in terms of their primary transportation function (mobility versus access). The individual segmentations are subsequently merged, since in addition to dedicated parking areas, those traffic areas that are regularly used for parking a motorized vehicle (e.g., at the curbside) are also to be classified as such. Furthermore, the multitemporal fusion enhances the robustness and completeness of the traffic area map (TAM). Potential applications include: urban planning, traffic modeling, and parking management.

For more information about the project, the reader is referred to: https://elib.dlr.de/191145/1/Hellekes_et_al_2022_Parking_space_inventory_from_above.pdf

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Sanborn Mapping Company, Inc. acquired color infrared, stereo pair, 1:12,000 scale aerial photography for a digital orthophoto mosaic of GARI on March 27, 2003, during leaf-off conditions. The aerial photographs were delivered to the NPS, quality checked, accepted as provided, and sent to NCSU. Upon receipt at NCSU, the aerial photographs were counted to make sure that none were missing, scanned and saved in TIFF format, and placed in the data archive that NCSU maintains for the NPS Northeast Region Inventory & Monitoring Program. Associated data and information provided by Sanborn Mapping Company, Inc. that are also stored in the data archive include the airborne global positioning system (GPS) and inertial mapping unit (IMU) data files, the camera calibration certificate, and a digital flight index map.

Aerial photography has been an important means of acquiring spatial data in Antarctica and the subantarctic islands, though satellite imagery is playing an increasingly important role.

The Australian Antarctic Data Centre's collection of aerial photographs includes (but is not limited to) the following.

1 Vertical and oblique aerial photography of the Australian Antarctic Territory coastline and some inland areas, acquired by the US Navy during Operation Highjump in 1946/47.

2 Vertical and oblique aerial photography flown by National Mapping (now part of Geoscience Australia) during 1954 - 1965 from fixed wing aircraft, mainly using a K17 trimetrigon camera. From 1960 the vertical camera in the system was replaced with a Wild RC9. An Eagle V camera was also used in 1963. The photography was acquired along the Australian Antarctic Territory coastline and over the Prince Charles Mountains.

3 Comprehensive and systematic coverages of the Prince Charles Mountains and Enderby Land flown by National Mapping from a fixed wing aircraft in the 1970s using a Wild RC 9 camera.

4 Photography acquired since 1977 from helicopters using non-metric Hasselblad and Linhof cameras. This photography was acquired principally for life science research and was not intended to be used for mapping. The photography was acquired over Heard Island, Macquarie Island, the Larsemann Hills, the Windmill Islands, the Vestfold Hills and Mawson Coast.

5 Photography acquired since 1992/93 by the Australian Antarctic Division and AUSLIG (now part of Geoscience Australia) from helicopters using a Zeiss UMK camera. It has been used to acquire photography for large scale mapping of the Australian Antarctic Territory, Heard Island and Macquarie Island.

6 Photography acquired since 2000 by the Australian Antarctic Division from helicopters using a Wild RC8 camera. A revision of the guidelines for overflight heights over animal colonies required that animal census photography be done with a camera with a longer focal length than the Linhof camera previously used for this type of work. This was in order to maintain the same scale at a greater height. The Wild RC8 camera has also been used for photography for mapping at the Windmill Islands.

7 Photography of sea ice acquired since 2003 by the Australian Antarctic Division from helicopters using a digital Nikon D1X digital camera.

8 Photography of Adelie penguin colonies and other features acquired since 2009/10 by the Australian Antarctic Division from helicopters using a digital Hasselblad H3D-II 50 digital camera.

Digital flight lines and photo centres have been generated to represent the runs along which the photographs were taken and the centres of the photographs.

The photos are scanned on a needs basis. Most of the Operation Highjump photos have been scanned but overall a minority of the photos have been scanned. Preview images have been created of the scanned photos. The scanning of the Operation Highjump photos is described by a separate metadata record: 'Digital images of Operation Highjump aerial photography'.

The collection can be searched in two ways.

1 A web search - see Aerial Photograph Catalogue link below. Preview images of the scanned photos may be viewed using this search. In addition to the search, the Catalogue has tabs with information about viewing or obtaining photographs, the cameras used and further historical information.

2 The flight line and photo centre data can be downloaded as shapefiles (refer to url below) and overlaid on topographic data in GIS software such as ArcGIS. The Australian Antarctic Data Centre (AADC) has mainly large to medium scale data topographic data available for download - refer to url below.

There are some flight lines for which photo centres have not yet been generated and some photo centres for which flight lines have not yet been generated. This is being done gradually over time. The flight line and photo centre shapefiles available for download will be updated about every six months.

Also available for download is a document with information about the cameras and a timeline for the photography - refer to the provided URL.

Effective multi-level autonomous piloting systems require integration with safety-critical functions. The Expandable Variable-Autonomy Architecture (EVAA) project seeks to develop a hierarchal autonomous system framework that will depend on deterministic systems with higher authority to protect against catastrophic piloting faults and allow a lower level certification for the machine learning sub-systems. The multi-layered approach provides the framework for analytical systems that can learn, predict, and adapt to both routine and emergency situations.

The objective of the project is to develop an autonomous piloting system based on analytical and learning algorithms that are capable of making effective decisions, in both nominal and potentially catastrophic situations. This will develop a safety critical framework for certification of complex autonomous systems where a small but sufficient number of levels. The system will be integrated with a certified safety critical decision makers (such as vehicle health monitoring, collision avoidance, loss of control avoidance and restricts commands of higher level critical decision makers not certified to level A software. The project will integrate these systems onto a quad-rotor micro-UAV for inexpensive and quick flight testing of concepts and develop customized, low power hardware to house the control and decision making algorithms.

ASSUMPTIONS AND LIMITATIONS: The purpose of this CIF project is not to develop a full scale aircraft capable of these types of advancements, but only to develop a piloting system which make them possible. Initially, decisions associated with “where to fly” will be focused on and integrated into the algorithms. For this slice of the pie, the system will be required to navigate a potentially changing dense urban landscape. Routes will be planned based on time, distance, and potential risk. Additionally, terrain and obstacle avoidance algorithms will restrict these activities based on preloaded obstacle and terrain maps. Additionally, off nominal conditions such as loss of motor or other non-pre-programmed events will cause the aircraft to select landing or crashing locations based on population density maps, location of buildings, and other information. A hangar or small area will be turned into the urban city-center mockup with maps created of the mockup to facilitate flight test of concepts.

Work to date: The hierarchical decision chain and framework, hardware, and embedded processing related to ground collision avoidance is in place for a sub-scale platform. Flight tests on a quad-rotor model helicopter demonstrated successful limitation of flight decisions when facing imminent ground collision.

Looking ahead: The team is developing a full set of safety-critical functions for the sub-scale platforms and working to scale up to larger UAVs.

Partners: University of California at Berkeley and Stanford University are developing algorithms, and the FAA is participating in the certification process.

Benefits

• Increases safety: Integration of safety-critical functions improves outcomes in emergency situations.
• Certifiable: Removal of safety-critical functions from the autonomous control enables adaptable processes to be certified to a lower level.

Applications

• UAVs and unmanned submersibles
• Autonomous rail transport
• Deep space exploration
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Geophysical maps of the Northern TerritoryNTGS produces four Territory-wide geophysical products: * Magnetic map of the Northern Territory (2004) * Radiometric map of the Northern Territory (2004) * Elevation map of the Northern Territory (2004) * Gravity map of the Northern Territory (2004).These maps represent the culmination of several decades of work since the Bureau of Mineral Resources [BMR, now Geoscience Australia (GA)] first acquired reconnaissance airborne magnetic and radiometric data in the Northern Territory at Rum Jungle in 1952. Dates of first release: Magnetic Map - 2000; Elevation Map - 2002; Radiometric Map - 2003; Gravity Map - 2004.Ninety-one percent of the area of the NT is covered by data from 53 separate NTGS and Geoscience Australia semi-detailed airborne surveys flown since 1974. These data were acquired along flight lines spaced 150-500 m apart. The remaining portion of the NT is made up of reconnaissance BMR surveys, which typically employed flight line spacings of around 1.5-3.2 km.The Magnetic and Radiometric maps make use of data from all 53 surveys, whereas the Elevation Map only includes, where available, GPS-derived height data from surveys flown since 1993. Backdrop to the Elevation Map is provided by the GEODATA 9 Second DEM, resampled to 100 m. The Gravity Map incorporates data primarily from the 11 km grid of stations collected by BMR in the 1960s and 1970s, augmented by many detailed private sector surveys (interpolated to 200 m), two 4 km datasets collected jointly by NTGS and GA in the Tanami and Tennant regions, and more recently (2003) a 2 km airborne dataset.All four maps are updated as new semi-regional surveys are acquired by NTGS and added to the public domain database. They are currently available in several forms: * Hardcopy at 1:2.5M scale. Total Magnetic Intensity, Elevation and Gravity data are rendered in pseudocolour with the intensity stretched and synthetically sun-illuminated. The three elements of Radiometric data, potassium-thorium-uranium, are assigned to red-green-blue, respectively, whereas the intensity is the total count, high-pass filtered. * Digitally, as an ER Mapper .ERS (approximately 700 Mb uncompressed) and MapInfo .TAB, on CD-ROM from the Minerals and Energy Information Centre. Grid-merging of individual datasets has been undertaken using a mesh size of 100 m. * Digitally, as an ER Mapper compressed .ECW (geolocated image) on Image Web Server.Download the: * MapInfo Tab Dataset (2.71MB) * 1:2.5M Elevation Map of the NT, (March 2004) (pdf, 6.13MB) * 1:2.5M Geological Map of the NT, (March 2004) (pdf, 5.13MB) * 1:2.5M Gravity Map of the NT, (March 2004) (pdf, 8.16MB) * 1:2.5M Magnetic Map of the NT, (March 2004) (pdf, 6.49MB) * 1:2.5M Radiometric Map of the NT, (March 2004) (pdf, 19.7MB)Other publications

These text files contain tables of the file names, times, and locations of images obtained from an unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. The objective of the fieldwork was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. The UAV was a Skywalker X8 flying wing operated by Raptor Maps, Inc., contractors to the U.S. Geological Survey. U.S. Geological Survey technicians deployed and mapped 28 targets that appear in some of the images for use as ground control points. All activities were conducted according to Federal Aviation Administration regulations and under a National Park Service Scientific Research and Collecting Permit, study number CACO-00285, permit number CACO-2016-SCI-003. Two consecutive UAS missions were flown, each with two cameras, autopilot computer, radios, and a global navigation satellite system (GNSS) positioning system as payload. The first flight (f1) was launched at approximately 1112 EST, and followed north-south flight lines, landing at about 1226 EST. Two Canon Powershot SX280 12-mexapixel digital cameras, designated rgb1 and rgb2 made images during this flight. The second flight (f2) was launched at 1320 EST and followed east-west flight lines, landing at 1450 Eastern Standard Time (EST). Prior to f2, rgb2 was replaced with a Canon SX280 modified with a Schott BG 3 filter to emphasize light at near-infrared wavelengths, designated nir1. Rgb1 and nir1 made images during this second flight. The four files are tables of images obtained from the two cameras during the two flights. These tables, which are text files of comma-separated values, contain the image file name, date and time (Universal Time; UT), longitude and latitude (WGS84 decimal degrees), easting and northing (NAD83(2011) UTM Zone 19 North meters, obtained by conversion of the latitude and longitude), and elevation (approximate meters above mean sea level) determined from the UAS GNSS system. Note that this location information was only used to determine proximity of images, and was replaced with calculated camera locations in photogrammetric processing.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Edinburg Township Forest Map

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

This data layer contains forest polygons with information on cover type, volume, and crown closure for both the forest overstory and understory for the Township of Edinburg located in Penobscot County, Maine. The map was digitized, projected and differentially corrected using Global Positioning System points. Forest types were determined by delineation from color infrared photographs.

Note that the USGS records show that the orthophotoquads from which the data were digitized are in the Transverse Mercator projection. The printed map grid on both Howland and Edinburg maps is in the Universal Transverse Mercator projection. So, although the Edinburg map states that base map and control are from a Polyconic projection, (the Howland does not mention projection) the original base maps were assumed to be in the Transverse Mercator.

Information about the FED project and other datasets can be found at the FED Home Page: "https://forest.gsfc.nasa.gov/".

Current Effective Date: 0901Z 12 Jun 2025 to 0901Z 10 Jul 2025The FAA is providing lateral boundary information related to certain long-term, security related Temporary Flight Restrictions (TFR) to alert users that they should consult NOTAMs when planning to transit these areas. These areas include select Title 14 Code of Federal Regulations (CFR) Part 99.7 (Special Security Instructions), Part 91.141 (Flight Restrictions in the Proximity of the President and Other parties) and Part 91.139 (Emergency Air Traffic Rules) security related TFRs of extended duration with fixed and unchanging boundaries. Please note that these locations, boundaries, and restrictions may change at any time and users must refer to NOTAMs for current information. The data will be updated on a 28 day cycle concurrent with ICAO AIRAC effective dates. Aeronautical Information Services welcomes any comments, suggestions and inquiries regarding this information. Please contact Aeronautical Information Services at: FAA, Aeronautical Information Services SSMC-4 Sta. #4445 1305 East West Highway Silver Spring, MD 20910-3281 Telephone 1-800-638-8972 Email 9-AMCAerochart@faa.gov