This data release contains field sampling data collected on a farm located in Talbot County. Maryland, roadside survey data from the area surrounding the farm, and WorldView-3 satellite data of the study area. Datasets include: 1) CropResidueDataset.csv: Tabular data for 174 photo sampling locations with crop residue cover ranging from 0% to 98%, as well as line-point transect residue cover measurements and lat-long geolocations 2) Roadside_Survey_May14th2015.zip: Zipfile containing roadside survey data for 63 fields documenting percent crop residue cover, including shapefile of field boundaries 3) GroundCoverPhotographs.zip: Zipfile containing 174 nadir photographs that were the basis for ground cover calculations 4) WorldView-3 satellite imagery collected May 14, 2015 and converted to surface reflectance using MODTRAN. The data support a manuscript published in Remote Sensing journal: Hively, W.D; Lamb, B.T. Daughtry, C.S.T. Shermeyer, J. McCarty, G.W., and Quemada, M., 2018, Mapping Crop Residue and Tillage Intensity Using WorldView-3 Satellite Shortwave Infrared Residue Indices: Remote Sensing, vol. 10, p. 1657. https://doi.org/10.3390/rs10101657

This layer presents detectable thermal activity from MODIS satellites for the last 7 days. MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World.

Area Covered: World

What can I do with this layer?
The MODIS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.


It takes approximately 2 – 4 hours after satellite overpass for MODIS Rapid Response to process the data, and for the Fire Information for Resource Management System (FIRMS) to update the website. Occasionally, hardware errors can result in processing delays beyond the 2-4 hour range. Additional information on the MODIS system status can be found at MODIS Rapid Response.

Attribute Information

• Latitude and Longitude: The center point location of the 1km (approx.) pixel flagged as containing one or more fires/hotspots (fire size is not 1km, but variable). Stored by Point Geometry. See What does a hotspot/fire detection mean on the ground?
• Brightness: The brightness temperature measured (in Kelvin) using the MODIS channels 21/22 and channel 31.
• Scan and Track: The actual spatial resolution of the scanned pixel. Although the algorithm works at 1km resolution, the MODIS pixels get bigger toward the edge of the scan. See What does scan and track mean?
• Date and Time: Acquisition date of the hotspot/active fire pixel and time of satellite overpass in UTC (client presentation in local time). Stored by Acquisition Date.
  
• Acquisition Date: Derived Date/Time field combining Date and Time attributes.
• Satellite: Whether the detection was picked up by the Terra or Aqua satellite.
• Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel.
• Version: Version refers to the processing collection and source of data. The number before the decimal refers to the collection (e.g. MODIS Collection 6). The number after the decimal indicates the source of Level 1B data; data processed in near-real time by MODIS Rapid Response will have the source code “CollectionNumber.0”. Data sourced from MODAPS (with a 2-month lag) and processed by FIRMS using the standard MOD14/MYD14 Thermal Anomalies algorithm will have a source code “CollectionNumber.x”. For example, data with the version listed as 5.0 is collection 5, processed by MRR, data with the version listed as 5.1 is collection 5 data processed by FIRMS using Level 1B data from MODAPS.
• Bright.T31: Channel 31 brightness temperature (in Kelvins) of the hotspot/active fire pixel.
• FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).
• DayNight: The standard processing algorithm uses the solar zenith angle (SZA) to threshold the day/night value; if the SZA exceeds 85 degrees it is assigned a night value. SZA values less than 85 degrees are assigned a day time value. For the NRT algorithm the day/night flag is assigned by ascending (day) vs descending (night) observation. It is expected that the NRT assignment of the day/night flag will be amended to be consistent with the standard processing.
• Hours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.

This map is provided for informational purposes and is not monitored 24/7 for accuracy and

The objective of the ESA TropForest project was to create a harmonised geo-database of ready-to-use satellite imagery to support 2010 global forest assessment performed by the Joint Research Centre (JRC) of the European Commission and by the Food and Agriculture Organization (FAO). Assessments for year 2010 were essential for building realistic deforestation benchmark rates at global to regional levels. To reach this objective, the project aimed to create a harmonised ortho-rectified/pre-processed imagery geo-database based on satellite data acquisitions (ALOS AVNIR-2, GEOSAT-1 SLIM6, KOMPSAT-2 MSC) performed during year 2009 and 2010, for the Tropical Latin America (excluding Mexico) and for the Tropical South and Southeast Asia (excluding China), resulting in 1971 sites located at 1° x 1° geographical lat/long intersections. The project finally delivered 1866 sites (94.7% of target) due to cloud coverages too high for missing sites. Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service.

The Gridded Satellite (GridSat-B1) data provides a uniform set of quality controlled geostationary satellite observations for the visible, infrared window and infrared water vapor channels. GridSat-B1 uses the International Satellite Cloud Climatology Project (ISCCP) B1 dataset providing coverage every 3 hours from 1980 to the present, and is updated quarterly as possible. The ISCCP B1 data have been quality controlled, calibrated, remapped and merged together to provide a nearly global coverage of top of the atmosphere radiances. Long-term temporal normalization is performed via calibration against HIRS channel 12 data during the period of record. The IR window channel data has received more extensive inter-satellite calibration and is thus identified as a Climate Data Record (CDR) by the NOAA CDR Program. GridSat-B1 data are projected on an equal angle grid, which facilitates the mapping and subsetting of the data. Since the ISCCP B1 native resolution is approximately 8km, the resolution of the equal area grid is 0.07 degrees latitude (approximately 8km at the Equator). The data span the globe in longitude and range from 70 degrees South to 70 degrees North latitude. GridSat version 2 differs from version 1 in the following ways: a) three channels are provided instead of just one, b) more quality control on the calibration, navigation and flagging of bad data, and c) extension of the period of record. Data are stored using netCDF-4 file format following the Climate and Forecast (CF) Conventions and the Attribute Convention for Dataset Discovery (ACDD) which facilitates usage with compatible software applications. Documentation and source code are available for the dataset.

The Animal Tracking Facility (formerly known as the Australian Animal Tracking And Monitoring System (AATAMS)) is a coordinated marine animal tagging project. Satellite Relay Data Loggers (SRDL) (most with CTDs, and some also with fluorometers) are used to explore how marine mammal behaviour relates to their oceanic environment. Loggers developed at the University of St Andrews Sea Mammal Research Unit transmit data in near real time via the Argo satellite system. The Satellite Relay Data Loggers are deployed on marine mammals, including Elephant Seals, Weddell Seals, Australian Fur Seals, Australian Sea Lions, New Zealand Fur Seals. Data is being collected in the Southern Ocean, the Great Australian Bight, and off the South-East Coast of Australia. This metadata record, represents several different datasets listed hereafter, which can all be accessed through a multi-WFS service. The data represented by this record are presented in delayed mode. CTD - parameters measured by the instruments include time, conductivity (salinity), temperature, speed, fluorescence (available in the future) and depth. Diving - parameters measured by the instruments include start and end time and longitude/latitude of each individual dive, post-dive surface duration, dive duration, maximum dive depth, intermediate dive depths and times. Haulout - a haulout begins when the SRDL has been continuously dry for a specified length of time (usually 10 minutes). It ends when continuously wet for another interval (usually 40 seconds). Haulout data parameters measured by the instruments include haulout start and end dates and longitude/latitude, and haulout number. Argos locations - location data parameters measured by the instruments include time, longitude, latitude, location quality, along with other diagnostic information provided by Argos (http://www.argos-system.org/). Summary Statistics - as well as sending records of individual events such as dives and haulouts, the SRDL also calculates summary statistics of those events over a specified time period (usually 3, 4 or 6 hours). Summary statistics computed by the instruments include the proportion of time spent diving, at the surface and hauled-out, the number of dives, and the average, standard deviation and maximum dive duration and dive depth during each summary period. These statistics are based on all the data recorded by the SRDL and so are not prone to distortion by variations in the efficiency of transmission via Argos. ** For data after October 2018, please consult IMOS - Animal Tracking Facility - Satellite Relay Tagging Program - Delayed mode data with quality-controlled locations (https://catalogue-imos.aodn.org.au:443/geonetwork/srv/api/records/70f148b1-7040-4fad-944a-456413c95472), to access data with improved satellite locations. In the near future all historical delayed mode data will be reprocessed with the new quality control (QC) process, to improve the accuracy of the satellite location data, and this dataset will be replaced by the new QC’d one. **

Visualization OverviewThis visualization represents a "false color" band combination (Red = DNB, Green = DNB, Blue = Inverted M15) of data collected by the VIIRS instrument on the joint NASA/NOAA Suomi-NPP satellite. The imagery is most useful for identifying nighttime lights from cities, fires, boats, and other phenomena. At its highest resolution, this visualization represents the underlying data scaled to a resolution of 500m per pixel at the equator.The algorithm to combine the VIIRS DNB and M15 bands into an RGB composite was originally designed by the Naval Research Lab and was subsequently incorporated into NASA research and applications efforts. As you will see, nighttime city lights appear in shades of yellow, while clouds appear in shades of blue to yellow/white as the illumination from the moon changes over the lunar month. Hence, this visualization is colloquially referred to as a "blue-yellow RGB."The following guidelines will aid in understanding this visualization.Interpretation of both the presence and relative brightness of the city lights will be affected by the lunar cycle. This composite offers a qualitative assessment of the light conditions and should not be used as the sole source of information concerning power outages. During bright moonlight conditions, moonlight reflected from cloud tops and the land surface may also provide a yellow hue to those features. Comparisons of cloud-free conditions before and after a period of significant change, such as new city growth, disasters, fires, or other factors, may exhibit a change in emitted light (yellows) from those features over time.Multi-Spectral BandsAt its highest resolution, this visualization represents the underlying data scaled from its native 750m per pixel resolution to 500m per pixel at the equator. The following table lists the VIIRS bands that are utilized to create this visualization. See here for a full description of all VIIRS bands.BandDescriptionWavelength (µm)Resolution (m)DNBVisible (reflective)0.5 - 0.9750DNBVisible (reflective)0.5 - 0.9750M15 (Inverted)Longwave IR10.26 - 11.26750Temporal CoverageBy default, this layer will display the imagery currently available for today’s date. This imagery is a "daily composite" that is assembled from hundreds of individual data files. When viewing imagery for “today,” you may notice that only a portion of the map has imagery. This is because the visualization is continually updated as the satellite collects more data. To view imagery over time, you can update the layer properties to enable time animation and configure time settings. Currently, this layer is available from present back to April 30th, 2021. In the coming months, this will be extended to the start of the mission (October 28th, 2011).Data AccessThis visualization is generated from hourly and daily Near-Real Time versions of the "VIIRS/NPP Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night" (VNP46A1_NRT) data product distributed by the Land, Atmosphere Near real-time Capability for EOS (LANCE). A standard quality version of the data product (VNP46A1), which is distributed by the Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC), is also available within 1-2 days of acquisition. You may use the Earthdata Search client to search for near real-time and science quality data files and associated documentation and services. Additionally, you may use the Worldview Snapshots tool to download custom images in a GeoTIFF , JPEG, PNG, or KMZ format for offline use.NASA Global Imagery Browse Services (GIBS), NASA Worldview, & NASA LANCEThis visualization is provided through the NASA Global Imagery Browse Services (GIBS), which are a set of standard services to deliver global, full-resolution satellite imagery for hundreds of NASA Earth science datasets and science parameters. Through its services, and the NASA Worldview client, GIBS enables interactive exploration of NASA's Earth imagery for a broad range of users. The data and imagery are generated within 3 hours of acquisition through the NASA LANCE capability.Esri and NASA Collaborative ServicesThis visualization is made available through an ArcGIS image service hosted on Esri servers and facilitates access to a NASA GIBS service endpoint. For each image service request, the Esri server issues multiple requests to the GIBS service, processes and assembles the responses, and returns a proper mosaic image to the user. Processing occurs on-the-fly for each and every request to ensure that any update to the GIBS imagery is immediately available to the user. As such, availability of this visualization is dependent on both the Esri and the NASA GIBS services.

The Animal Tagging Sub-Facility of the IMOS Animal Tracking Facility (formerly known as the Australian Animal Tracking And Monitoring System (AATAMS)) is a coordinated marine animal satellite-tracking project. Satellite Relay Data Loggers (SRDL) (most with Conductivity-Temperature-Depth (CTD) sensors, and some with CTD/fluorometers) are used to explore how marine animals (e.g. mammals) interact with their oceanic environment. The primary focus of this program is to collect CTD data from marine mammals, such as southern elephant seals (Mirounga leonina) and Weddell seals (Leptonychotes weddellii), in the southern Indian Ocean and along the East Antarctic coast. This is achieved through international collaborations with the French national polar program's long-term National Observatory Services: Mammals as Ocean Bio-Samplers (SNO-MEMO), the National Institute of Water and Atmospheric Research as part of the Ross Sea Research and Monitoring Programme, and the CNES (Centre National d'Etudes Spatiales) TOSCA programme (Phoques de Weddell bio-oceanographes de la banquise antarctique et outils satellites) in Terre Adelie. SRDL loggers developed at the Sea Mammal Research Unit (SMRU, University of St Andrews, UK) transmit data in near real time via the Argos satellite system. This metadata record, represents several different datasets listed hereafter, which can all be accessed through a multi-WFS service. The data represented by this record are presented in near real-time. CTD - parameters measured by the instruments include time, depth, conductivity (salinity), temperature, speed and fluorescence (available in some deployments). Diving - parameters measured by the instruments include individual dive start and end time, longitude/latitude at dive end time, post-dive surface duration, dive duration, maximum dive depth, intermediate dive depths and times. Haulout - a haulout begins when the SRDL has been continuously dry for a specified length of time (usually 10 minutes). It ends when continuously wet for another interval (usually 40 seconds). Haulout data parameters measured by the instruments include haulout start and end dates and longitude/latitude, and haulout number. Argos Locations - location data parameters measured by the instruments include time, longitude, latitude, location quality, along with other diagnostic information provided by Argos (http://www.argos-system.org/). Summary Statistics - as well as sending records of individual events such as dives and haulouts, the SRDL also calculates summary statistics of those events over a specified time period (usually 3, 4 or 6 hours). Summary statistics computed by the instruments include the proportion of time spent diving, at the surface and hauled-out, the number of dives, and the average, standard deviation and maximum dive duration and dive depth during each summary period. These statistics are based on all the data recorded by the SRDL and thus are not prone to distortion by variations in the efficiency of transmission via Argos. SSM QC Locations - SSM-predicted locations and uncertainty at 6-h intervals from the location quality-control process. SSM-predicted locations are also appended to records in the CTD, Diving, Haulout, Argos Locations, and Summary Statistics datasets. See Jonsen et al. 2020 for further details on the SSM used for location quality control

EOS-WEBSTER has agreed to serve satellite image subsets for the Forest Watch ("http://www.forestwatch.sr.unh.edu") program and other educational programs which make use of satellite imagery. Forest Watch is a New England-wide environmental education activity designed to introduce teachers and students to field, laboratory, and satellite data analysis methods for assessing the state-of-health of local forest stands. One of the activities in Forest Watch involves image processing and data analysis of Landsat Thematic Mapper data (TM/ETM+) for the area around a participant's school. The image processing of local Landsat data allows the students to use their ground truth data from field-based activities to better interpret the satellite data for their own back yard. Schools use a freely available image processing software, MultiSpec ("http://dynamo.ecn.purdue.edu/%7Ebiehl/MultiSpec/"), to analyze the imagery. Value-added Landsat data, typically in a 512 x 512 pixel subset, are supplied by this collection. The Forest Watch program has supplied the data subsets in this collection based on the schools involved with their activities.

Satellite data subsets may be searched by state or other category, and by spectral type. These images may be previewed through this system, ordered, and downloaded. Some historic Landsat 5 data subsets, which were acquired for this program, are also provided through this system. Landsat 5 subsets are multispectral data with 5 bands of data (TM bands 1-5). Landsat 7 subsets contain all bands of data and each subset has three spectral file types: 1) multispectral (ETM+ bands 1-5 and 7), 2) panchromatic (ETM+ band 8), and 3) Thermal (ETM+ band 6 high and low gain channels). Each spectral type must be ordered separately; this can be accomplished by choosing more than one spectral file type in your search parameters.

These image subsets are served in the ERDAS Imagine (.img) format, which can be opened by newer versions of the MultiSpec program (versions greater than Nov. 1999). The MultiSpec program can be downloaded via the Internet at: "http://dynamo.ecn.purdue.edu/%7Ebiehl/MultiSpec/"

A header file is provided with most Landsat 7 subsets giving the specifics of the image.

Please refer to the references to learn more about Forest Watch, Landsat, and the data this satellite acquires.

In the near future we hope to release a new Satellite Interface, which would allow a user to search for satellite data from a number of platforms based on user-selected search parameters and then sub-set the data and choose an appropriate output format.

If you have any other questions regarding our Forest Watch Satellite data holdings, please contact our User Services Personnel (support@eos-webster.sr.unh.edu).

Available Data Sets:

Many New England subsets are available, based on the location of participating schools in the Forest Watch program. Additional scenes are also included based on historical use within the Forest Watch program. Other scenes may be added in the future. If you don't see a scene of the location you are interested in, and that location is within New England, then please contact User Services (support@eos-webster.sr.unh.edu) to see if we can custom-create a subset for you.

Data Format

The data are currently held in EOS-WEBSTER in ERDAS Imagine (.img) format. This format is used by new versions of the MultiSpec program, and other image processing programs. Most of the subset scenes provided through this system have been projected to a Lambert Projection so that MultiSpec can display Latitude and Longitude values for each image cell (see "http://www.forestwatch.sr.unh.edu/online/" Using Mac MultiSpec to display Lat./Lon. Coordinates).

Data can be ordered by spectral type. For Landsat 7, three spectral types are available: 1) Multispectral (bands 1-5 & 7), 2) Panchromatic (pan), and 3) Thermal (bands 6 a&b) (see Table 2). The multispectral (ms) files contain six bands of data, the panchromatic (pan) files contains one band of data, and the thermal (therm) files contain two bands of data representing a high and low sensor gain.

A header file is provided for most Landsat 7 subsets which have been projected in the Lambert projection. This header file provides the necessary information for importing the data into MultiSpec for Latitude/Longitude display.

Satellite tags were deployed on 48 east Australian humpback whales (breeding stock E1) in 2008, 2009 and 2010 on their southward migration, northward migration and feeding grounds in order to identify and describe migratory pathways, feeding grounds and possible calving areas. At the time, these movements were not well understood and calving grounds not clearly identified. To the best of our knowledge, this dataset details all long-term tag deployments that have occurred to date on breeding stock E1.

Satellite tags were deployed on whales in the following locations:
• Eden, southern NSW (Australia), October 2008: whales were tagged off Eden during their southern migration.
• Evans Head, northern NSW (Australia), June and July 2009: whales were tagged off Evans Head during their northern migration.
• East Antarctica, February 2010: whales were tagged on their feeding grounds within IWC Management Area V.
• Sunshine Coast, QLD (Australia), October 2010: whales were tagged off the Sunshine Coast during their southern migration.

The various files in the download are:
Argos locations generated by tagging of East Australian (breeding stock E1) humpback whale

This file contains all Argos locations generated by satellite tags deployed on humpback whales. Deployment details can be found separately (dataset title: 'Summary of satellite tag deployments on breeding stock E1 humpback whales'). Locations were calculated by Argos using a least-squares analysis. Columns are: Argos PTT: The unique satellite tag identification number. GMT: The date and time (dd/mm/yyyy hh:mm) of each Argos location in UTC. Argos location class: The location class retrieved from Argos, Argos diagnostic data. Classes are based on the type of location (Argos Doppler Shift) and the number of messages received during the satellite pass. Location classes in order of decreasing accuracy are 3, 2, 1, 0, A, B and Z (definition from Argos User's Manual V1.6.6, 2016). Longitude: The longitude of the Argos location estimate. Units: decimal degrees, WGS84 reference system. Latitude: The latitude of the Argos location estimate. Units: decimal degrees, WGS84 reference system.

Speed-distance-angle filter applied to Argos locations generated by tagging of East Australian (breeding stock E1) humpback whale.

This file contains all Argos locations generated by satellite tags deployed on humpback whales. Deployment details can be found separately (dataset title: 'Summary of satellite tag deployments on breeding stock E1 humpback whales'). Locations were calculated by Argos using a least-squares analysis. Additionally, this file contains a column detailing the outcome of the application of the sdafilter - an algorithm based on swimming speed, distance between successive locations, and turning angles to remove unlikely position estimates (speed of 10 ms , spike angles of 15° and 25°, spike lengths of 2500m and 5000m; Freitas et al. 2008). Freitas C, Lydersen C, Fedak M, Kovacs K (2008) A simple new algorithm for filtering marine mammal Argos locations. Marine Mammal Science 24 (2): 315‑325. Columns are: Argos PTT: The unique satellite tag identification number. GMT: The date and time (dd/mm/yyyy hh:mm) of each Argos location in UTC. Argos location class: The location class retrieved from Argos, Argos diagnostic data. Classes are based on the type of location (Argos Doppler Shift) and the number of messages received during the satellite pass. Location classes in order of decreasing accuracy are 3, 2, 1, 0, A, B and Z (definition from Argos User's Manual V1.6.6, 2016). Longitude: The longitude of the Argos location estimate. Units: decimal degrees, WGS84 reference system. Latitude: The latitude of the Argos location estimate. Units: decimal degrees, WGS84 reference system. Argosfilter outcome: The result of the Argos sdafilter - "removed" (location removed by the filter), "not" (location not removed) and "end_location" (location at the end of the track where the algorithm could not be applied).

State-space model location estimates of satellite tagged East Australian (breeding stock E1) humpback whales.

Using the raw Argos tracking data set (Dataset name: Argos locations generated by tagging of East Australian (breeding stock E1) humpback whale), we accounted for the spatial error associated with Argos locations by fitting a correlated random walk state-space model to generate a location estimate at each observed location time. Within this state-space model, we applied the sdafilter to remove unlikely position estimates (speed of 10 ms, spike angles of 15° and 25°, spike lengths of 2500m and 5000m). See: Jonsen ID, Grecian WJ, Phillips L, Carroll G, McMahon C, Harcourt RG, Hindell MA, Patterson TA (2023) aniMotum, an R package for animal movement data: Rapid quality control, behavioural estimation and simulation. Methods in Ecology and Evolution 14(3): 806‑816. This dataset contains the state-space modelled location estimates of tagged east Australian humpback whales. Associated tag deployment details can be found separately (dataset title: 'Summary of satellite tag deployments on breeding stock E1 humpback whales'). The columns are: Argos PTT: The unique satellite tag identification number. GMT: The date and time (dd/mm/yyyy hh:mm) of each state-space model location estimate in UTC. Longitude: The longitude of the state-space model location estimate. Units: decimal degrees, WGS84 reference system. Latitude: The latitude of the state-space model location estimate. Units: decimal degrees, WGS84 reference system.

Summary of satellite tag deployments on breeding stock E1 humpback whales

A summary of satellite tag deployments on breeding stock E1 humpback whales. Argos PTT = the unique tag identification number; Deploy year = year of deployment; Deploy date = date of deployment; End date = date of final transmitted location; Tracking duration = duration of tag deployment from tag deployment date to last location date; Deploy location = broad geographic location where satellite tag was deployed; Deploy latitude = tag deployment latitude; Deploy longitude = tag deployment longitude; Stage of annual cycle upon deployment = migration direction or feeding grounds; Sex = determined genetically where a biopsy sample was collection; Maturity = an estimate of maturity relative to body size and behaviour; Initial activity = whale behaviour at tagging; Number of locations = the number of Argos locations transmitted; Tag programming = duty cycle applied to tag on and off time as a strategy to extend battery life; Retained for SSM = whether the state space model was applied to the Argos locations generated to account for Argos location error; SSM derived track distance estimate = the length of the satellite track from the state space modelled location estimates in kilometres; Movement captured = the types of movement and behaviour detailed in each satellite track.

This dataset provides daily estimates of global sea surface temperature (SST) based on observations from multiple satellite sensors since September 1981. SST is known to be a significant driver of global weather and climate patterns and to play important roles in the exchanges of energy, momentum, moisture and gases between the ocean and atmosphere. As such, its knowledge is essential to understand and assess variability and long-term changes in the Earth’s climate. The SST data provided here are based on measurements carried out by the following infrared sensors flown onboard multiple polar-orbiting satellites: the series of Advanced Very High Resolution Radiometers (AVHRRs), the series of Along Track Scanning Radiometers (ATSRs), and the Sea and Land Surface Temperature Radiometer (SLSTR). The dataset provides SST products of different processing levels. Only Level-3 Collated and Level-4 and served through this entry in the Catalogue. Due to the large number of files at Level-2 Pre-processed and Level-3 Collated these products are served through the Climate Data Store API. For more information on how to access these levels consult the documentation. The four types of products are:

Level-2 Pre-processed (L2P): SST data on the native satellite swath grid and derived from single-sensor measurements. Level-3 Uncollated (L3U): SST product generated by regridding L2P data onto a global latitude-longitude grid. Level-3 Collated (L3C): global daily (day and night) single-sensor SST product based on collated L3U data. Level-4 (L4): spatially complete global SST product based on data from multiple sensors.

These products are available as Climate Data Records (CDRs), which have sufficient length, consistency, and continuity to be used to assess climate variability and changes. These SST CDRs are identical to those produced as part of the European Space Agency (ESA) SST Climate Change Initiative (CCI) project. Interim CDRs (ICDRs) are produced at levels L3C and L4 on behalf of the Copernicus Climate Change Service (C3S) to extend the baseline CDRs. Both SST CDRs and ICDRs are generated using software and algorithms developed as part of the ESA SST CCI. Users should use the most recent version of the dataset whenever possible. Data from the previous version are also made available but cover shorter periods.

The Source Protection Information Atlas enables anyone to determine if an address is within a Source Protection Vulnerable Area. The map displays over 20 layers of Source Protection data for Ontario. The map uses a ESRI_GEOCORTEX API (Application Programming Interface). There are 4 vulnerable area types that surround municipal water supplies: Wellhead Protection Areas, Intake Protection Zones, Significant Groundwater Recharge Areas and Highly Vulnerable Aquifers. For details on the assessment reports and plans that contain definitions of these zones please click on one of these links. For access to the raw data contact the Conservation Authority for the jurisdiction you are interested in.

Additional Documentation

Source Protection Plans

WHPA fact sheet

IPZ fact sheet

HVA fact sheet

The layers displayed on the map are:

Source Protection Area (SPA) area boundaries Municipal Boundaries (Upper and Lower Tier) Lots and Concession Boundaries Intake Protection Zones (IPZ 1, 2 and 3) Event Based Areas and related Event Type Surface Water Vulnerability Scores (range of 0.1 to 10) Wellhead Protection Areas (A, B, C, D, E (GUDI)) Groundwater Vulnerability Scores (2,4,6,8,10) WHPA E (GUDI) vulnerability scores Issue Contributing Areas and their related contaminant (issue) Significant Groundwater Recharge Areas (SGRA) and scores (2,4 6) Highly Vulnerable Aquifers (HVA) Niagara Escarpment Development Control Area Oak Ridges Moraine Plan Boundary Satellite Imagery ESRI – Topographic/road Map

Under the source protection program, 19 source protection committees worked with conservation authorities and municipalities across Ontario to assess the vulnerability of sources of municipal drinking water. These assessments were documented in 38 local assessment reports that were approved by the ministry. The data collected from these reports form the foundation for the Source Water Protection Mapping Tool.

This interactive map allows you to search for a location in Ontario and determine if it is in a Source Protection vulnerable area. The map will show the location information, vulnerable zone type and score, as well as provide link(s) to local source protection plans where you can find the policies associated with the search location.

Searches can be performed by street address, geographic coordinates or several other search options listed in the help. Confirm the location by using the satellite imagery. Please note that searches by geographic coordinates (Lat. and Long) will return the most accurate results. Searches performed with a street address, postal code, municipality, lot, concession or township may require you to further refine the location by moving the pin to the accurate location based on your knowledge of the site. Please refer to the help (Primary Navigation Pane) for tips on searching, and the proper syntax of your searches.

Questions? If you have any questions on how to use the map, or are unable to find a location, contact the Source Protection Program by email at source.protection@ontario.ca.

For more information about the Source Protection program see our web site at Source Protection.

For additional information about your local source protection plan contact your Conservation Authority: Source Protection Plans and Resources.

Status

On going: Data is continually being updated

Maintenance and Update Frequency

Not stated

Contact

Derek Hatfield, Information Management Lead/Coordinator, Conservation Source Protection Branch, Ministry of the Environment, Conservation, and Parks, derek.hatfield@ontario.ca

Date of Images:9/25 - PresentVisualization OverviewThis visualization represents a "false color" band combination (Red = DNB, Green = DNB, Blue = Inverted M15) of data collected by the VIIRS instrument on the joint NASA/NOAA Suomi-NPP satellite. The imagery is most useful for identifying nighttime lights from cities, fires, boats, and other phenomena. At its highest resolution, this visualization represents the underlying data scaled to a resolution of 500m per pixel at the equator.The algorithm to combine the VIIRS DNB and M15 bands into an RGB composite was originally designed by the Naval Research Lab and was subsequently incorporated into NASA research and applications efforts. As you will see, nighttime city lights appear in shades of yellow, while clouds appear in shades of blue to yellow/white as the illumination from the moon changes over the lunar month. Hence, this visualization is colloquially referred to as a "blue-yellow RGB."The following guidelines will aid in understanding this visualization.Interpretation of both the presence and relative brightness of the city lights will be affected by the lunar cycle. This composite offers a qualitative assessment of the light conditions and should not be used as the sole source of information concerning power outages. During bright moonlight conditions, moonlight reflected from cloud tops and the land surface may also provide a yellow hue to those features. Comparisons of cloud-free conditions before and after a period of significant change, such as new city growth, disasters, fires, or other factors, may exhibit a change in emitted light (yellows) from those features over time.Multi-Spectral BandsAt its highest resolution, this visualization represents the underlying data scaled from its native 750m per pixel resolution to 500m per pixel at the equator. The following table lists the VIIRS bands that are utilized to create this visualization. See here for a full description of all VIIRS bands.BandDescriptionWavelength (µm)Resolution (m)DNBVisible (reflective)0.5 - 0.9750DNBVisible (reflective)0.5 - 0.9750M15 (Inverted)Longwave IR10.26 - 11.26750Temporal CoverageBy default, this layer will display the imagery currently available for today’s date. This imagery is a "daily composite" that is assembled from hundreds of individual data files. When viewing imagery for “today,” you may notice that only a portion of the map has imagery. This is because the visualization is continually updated as the satellite collects more data. To view imagery over time, you can update the layer properties to enable time animation and configure time settings. Currently, this layer is available from present back to April 30th, 2021. In the coming months, this will be extended to the start of the mission (October 28th, 2011).Data AccessThis visualization is generated from hourly and daily Near-Real Time versions of the "VIIRS/NPP Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night" (VNP46A1_NRT) data product distributed by the Land, Atmosphere Near real-time Capability for EOS (LANCE). A standard quality version of the data product (VNP46A1), which is distributed by the Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC), is also available within 1-2 days of acquisition. You may use the Earthdata Search client to search for near real-time and science quality data files and associated documentation and services. Additionally, you may use the Worldview Snapshots tool to download custom images in a GeoTIFF , JPEG, PNG, or KMZ format for offline use.NASA Global Imagery Browse Services (GIBS), NASA Worldview, & NASA LANCEThis visualization is provided through the NASA Global Imagery Browse Services (GIBS), which are a set of standard services to deliver global, full-resolution satellite imagery for hundreds of NASA Earth science datasets and science parameters. Through its services, and the NASA Worldview client, GIBS enables interactive exploration of NASA's Earth imagery for a broad range of users. The data and imagery are generated within 3 hours of acquisition through the NASA LANCE capability.Esri and NASA Collaborative ServicesThis visualization is made available through an ArcGIS image service hosted on Esri servers and facilitates access to a NASA GIBS service endpoint. For each image service request, the Esri server issues multiple requests to the GIBS service, processes and assembles the responses, and returns a proper mosaic image to the user. Processing occurs on-the-fly for each and every request to ensure that any update to the GIBS imagery is immediately available to the user. As such, availability of this visualization is dependent on both the Esri and the NASA GIBS services.

This data file consists of state-space model-derived locations and individual data used to analyze transmitter effects for sea ducks in Eastern North America and is associated with the manuscript "Implanted satellite transmitters affect sea duck movement patterns at short and long time scales" published in Condor. Columns are organized as follows:

id - unique identifier

species - species from which the centroid was obtained (BLSC = black scoter, COEI = common eider, LTDU = long-tailed duck, SUSC = surf scoter, WWSC = white-winged scoter)

date - date of location (mm/dd/yy)

jday - Julian date of location

tracking_day - number of days post-transmitter deployment

year - calendar year of location

lon - longitude of location

lat - latitude of location

b - average assignment of location to either migrant (1) or resident (2) across all runs of the state-space model

b.5 - most probable behavioral category based on average state assignment (1 = b ≤ 1.5 ; 2 = b > 1.5)

sex - sex of individual (M = male, F = female)

age - age of individual (HY = hatch year, SY = second year, TY = third year, ASY = after second year, ATY = after third year, AHY = after hatch year

capture_reg - general area where individual was captured

capture_subreg - specific region within capture region where individual was captured

stage - period of the annual cycle to which the centroid belongs (W = winter, B = breeding, S = spring staging, M = fall staging and molt, WM = winter migration, BM = breeding migration, MM = molt migration, SM = spring migration)

site - position of centroid within season (i.e., W1 = first site occupied during winter, W2 = second site occupied, etc.)

cycle - number of annual cycles following transmitter attachment (1 = first cycle after attachment, 2 = second cycle after attachment, etc.)

season - season of annual cycle in which centroid occurred (W = winter, F = fall, B = breeding, S = spring)

Coordinates of tagged seals in the San Juan Islands are reported. Seals were captured and tagged during 2007 to 2009 at several sites in Padilla Bay and the Rosario Strait of the Pacific Northwest coast. Seals were tagged with satellite-linked time-depth recorders (TDR's) and GPS receivers. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description=Seals were captured and tagged in April or May of 2007 and 2008 following the methods of Jeffries et al. (1993) at three sites: Padilla Bay, Bird/Belle Rocks, and Protection Island. In 2009, seals were captured on Protection Island. In 2007-2008, animals were tagged with time-depth recorders (TDR; Wildlife Computers, model Mk-9 or Mk-10F) and satellite tags. The TDR tags were placed on the dorsal midline of the animals and the satellite tags were placed on top the head. In 2009, animals were tagged with a combined satellite-linked TDR and Fastloc GPS receiver (Wildlife Computers, model Mk10AF). These instruments were epoxied to the animals on the dorsal midline so that satellite tags would be exposed to the air when the back of the seal reached the surface.

Position transmissions were received via the ARGOS satellite network. Tags transmitted locations daily. TDR sensors were programmed to sample every 10 seconds. TDR tags were equipped with a VHF transmitter to allow for the device to be recovered when it was shed during the animal's annual molt.

The Argos system provides 2 position estimates (lat/lon and lat2/lon2). Argos usually picks the correct lat/lon pair (of the two it generates), but occasionally it does not. When working with these data, one of the first steps is to check the lat/lon pairs to see if swapping out the lat/lon pair for the lat2/lon2 pair improves the data and is more biologically reasonable.

The Argos positioning system uses the following system for classifying location quality. These codes are used in the loc_q_flag column. Standard locations are those with > 4 uplinks from the tag; auxiliary locations are those with 4 or less uplinks from the tag.

loc_q_flag codes (according to Ward et al.):
Standard locations:
3 = 68th percentile predicted accuracy < 150 m
2 = 68th percentile predicted accuracy 150 - 350 m
1 = 68th percentile predicted accuracy < 1,000 m

Auxiliary locations:
0 = 4 uplinks, with > 1,000 m predicted accuracy
A = 3 uplinks, with no predicted accuracy
B = 2 uplinks, with no predicted accuracy awards_0_award_nid=54955 awards_0_award_number=OCE-0550443 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0550443 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 cdm_data_type=Other comment=Locations of Harbor Seals tagged and tracked at the San Juan Islands, 2007-2009 Lead PI: Alejandro Acevedo-Gutierrez Version: 28 Nov 2012 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time

The Advanced Very High Resolution Radiometer (AVHRR) and AVHRR/3 sensors have been carried on the US NOAA polar orbiting satellites since the 1980s. These data have been acquired via direct reception from the satellite by reception stations located in Australia. CSIRO has stitched together data received by different stations and agencies to compile a national high quality data set. The daylight satellite overpasses have been extracted from this data set for each day in the 30 year period commencing 1 April 1992. The data have been geolocated, and calibrated to produce imagery channels of solar reflectance and brightness temperature using community published methods. Satellite view and sun illumination angles for each pixel are provided, together with a preliminary cloud mask based on the CLAVR algorithm. The spatial resolution is ~1 km and temporal coverage is daily. The reprojected data set (in EPSG:4326, lon-lat) is available via the CSIRO EASI hub.

Visualization OverviewThis visualization represents a "false color" band combination (Red = DNB, Green = DNB, Blue = Inverted M15) of data collected by the VIIRS instrument on the joint NASA/NOAA Suomi-NPP satellite. The imagery is most useful for identifying nighttime lights from cities, fires, boats, and other phenomena. At its highest resolution, this visualization represents the underlying data scaled to a resolution of 500m per pixel at the equator.The algorithm to combine the VIIRS DNB and M15 bands into an RGB composite was originally designed by the Naval Research Lab and was subsequently incorporated into NASA research and applications efforts. As you will see, nighttime city lights appear in shades of yellow, while clouds appear in shades of blue to yellow/white as the illumination from the moon changes over the lunar month. Hence, this visualization is colloquially referred to as a "blue-yellow RGB."

The following guidelines will aid in understanding this visualization.

Interpretation of both the presence and relative brightness of the city lights will be affected by the lunar cycle. This composite offers a qualitative assessment of the light conditions and should not be used as the sole source of information concerning power outages. During bright moonlight conditions, moonlight reflected from cloud tops and the land surface may also provide a yellow hue to those features. Comparisons of cloud-free conditions before and after a period of significant change, such as new city growth, disasters, fires, or other factors, may exhibit a change in emitted light (yellows) from those features over time. Multi-Spectral BandsAt its highest resolution, this visualization represents the underlying data scaled from its native 750m per pixel resolution to 500m per pixel at the equator. The following table lists the VIIRS bands that are utilized to create this visualization. See here for a full description of all VIIRS bands.BandDescriptionWavelength (µm)Resolution (m)DNBVisible (reflective)0.5 - 0.9750DNBVisible (reflective)0.5 - 0.9750M15 (Inverted)Longwave IR10.26 - 11.26750Temporal CoverageBy default, this layer will display the imagery currently available for today’s date. This imagery is a "daily composite" that is assembled from hundreds of individual data files. When viewing imagery for “today,” you may notice that only a portion of the map has imagery. This is because the visualization is continually updated as the satellite collects more data. To view imagery over time, you can update the layer properties to enable time animation and configure time settings. Currently, this layer is available from present back to April 30th, 2021. In the coming months, this will be extended to the start of the mission (October 28th, 2011).Data AccessThis visualization is generated from hourly and daily Near-Real Time versions of the "VIIRS/NPP Daily Gridded Day Night Band 500m Linear Lat Lon Grid Night" (VNP46A1_NRT) data product distributed by the Land, Atmosphere Near real-time Capability for EOS (LANCE). A standard quality version of the data product (VNP46A1), which is distributed by the Level-1 and Atmosphere Archive & Distribution System Distributed Active Archive Center (LAADS DAAC), is also available within 1-2 days of acquisition. You may use the Earthdata Search client to search for near real-time and science quality data files and associated documentation and services. Additionally, you may use the Worldview Snapshots tool to download custom images in a GeoTIFF , JPEG, PNG, or KMZ format for offline use.NASA Global Imagery Browse Services (GIBS), NASA Worldview, & NASA LANCEThis visualization is provided through the NASA Global Imagery Browse Services (GIBS), which are a set of standard services to deliver global, full-resolution satellite imagery for hundreds of NASA Earth science datasets and science parameters. Through its services, and the NASA Worldview client, GIBS enables interactive exploration of NASA's Earth imagery for a broad range of users. The data and imagery are generated within 3 hours of acquisition through the NASA LANCE capability.Esri and NASA Collaborative ServicesThis visualization is made available through an ArcGIS image service hosted on Esri servers and facilitates access to a NASA GIBS service endpoint. For each image service request, the Esri server issues multiple requests to the GIBS service, processes and assembles the responses, and returns a proper mosaic image to the user. Processing occurs on-the-fly for each and every request to ensure that any update to the GIBS imagery is immediately available to the user. As such, availability of this visualization is dependent on both the Esri and the NASA GIBS services.

The database provides information on coastal protection structures (containing geosynthetic materials) located on the coast of the South-East Baltic, in the Kaliningrad Oblast (Russia) and the Pomeranian Voivodeship (Poland). The database contains the following sections: the tabular data about coastal protecting structures; the point vector geodata about these structures and used geosynthetic materials on intaractive map; the satellite images and photos. This dataset contains vector geodata only. Spreadsheets (named “ProtectingStructures_tab.xlsx”) contain the coastal protection structures located on the sea coast of the South-East Baltic. Sheet 1 (named “ProtectingStructuresSEB”) shows a list of coastal protection structures in the South-Eastern Baltic that contain geosynthetics and their characteristics. It has 10 columns (Table 1): the number (the conventional two-level number assigned to the structure); the type (type of structure); the location (closest settlement to which the structure is located); the country (country where the structure is located); Building_Reconstruction_year (the year of building or last reconstruction of the structure); Geosyntetic_type (type of geosynthetic material used in the structure); Length_m (length of the structure in m); Width_beach_m (width of the beach in front of the structure, range, m); Lat (latitude, °); Lon (longitude, °). Sheet 2 (named “Legend”) shows the legend described above. Intaractive map data [ProtectingStructures_pnt.kmz] is the point vector layer that contains the information about coastal protection structures located on the sea coast of the South-East Baltic. Projected Coordinate System is WGS 1984, UTM Zone 34N, Projection is Transverse Mercator. The attribute table has the columns: the number (the conventional two-level number assigned to the structure); the type (type of structure); the location (closest settlement to which the structure is located); the country (country where the structure is located); Building_Reconstruction_year (year of building or last reconstruction of the structure); each type of geosynthetics has a separate column (Geotextile, Gabion_coating, Geocontainers, Geocells, Geomat, PVC_sheet_pile), the absence of geosynthetics is designated as “0”, the presence of the geosynthetics is designated as “1”; Length_m (length of the structure in m); Width_beach_m (width of the beach in front of the structure, range, m); Lat (latitude, °); Lon (longitude, °). The satellite images and photos are embedded in the PDF document. They demonstrate the general location (scale 1 : 50 000) of the coastal protection structures in the satellite image (Fig. 1) and their appearance in the photos.

The H09-AHI-L2P-ACSPO-v2.90 dataset contains the Subskin Sea Surface Temperature (SST) produced by the NOAA ACSPO system from the Advanced Himawari Imager (AHI; largely identical to GOES-R/ABI) onboard the Himawari-9 (H09) satellite. The H09 is a Japanese weather satellite, the 9th of the Himawari geostationary weather satellite operated by the Japan Meteorological Agency. It was launched on November 2, 2016 into its nominal position at 140.7-deg E, and declared operational on December 13, 2022, replacing the Himawari-8. The AHI is the primary instrument on the Himawari Series for imaging Earth’s weather, oceans, and environment with high temporal and spatial resolutions. The H08/AHI maps SST in a Full Disk (FD) area from 80E-160W and 60S-60N, with spatial resolution 2km at nadir to 15km/VZA (view zenith angle) 67-deg, and 10-min temporal sampling. The 10-min FD data are subsequently collated in time, to produce the 1-hr product, with improved coverage and reduced cloud leakages and image noise. The L2P data is produced in GHRSST compliant netCDF4 GDS2 format, with 24 granules per day, and a total data volume 1.2 GB/day. The near-real time (NRT) data are updated hourly, with several hours latency. The NRT files are replaced with Delayed Mode (DM) files, with a latency of approximately 2-months. File names remain unchanged, and DM vs NRT can be identified by different time stamps and global attributes inside the files (MERRA instead of GFS for atmospheric profiles, and same day CMC L4 analyses in DM instead of one-day delayed in NRT processing). Pixel earth locations are not reported in the granules, as they remain unchanged from granule to granule. Pixel locations can be obtained using a flat lat/lon file or a Python script available via Documents tab from the dataset landing page. Climate and Forecast (CF) metadata aware software (e.g., Panoply, xarray) can detect and map the data as is via the granule CF projection attributes and variables. The ACSPO H09 HAI SSTs are validated against quality controlled in situ data from the NOAA iQuam system (Xu and Ignatov, 2014) and continuously monitored in the NOAA SQUAM system (Dash et al, 2010). A 0.02-deg equal-angle gridded L3C product 0.7GB/day) is also available.

The entire collection of GEOSAT ERM (Nov.'86 - Dec. '89) data over land and ice regions is held at the National Geophysical Data Center (NGDC). These data will yield reasonable elevation values for land and ice regions of gently varying elevation. This data collection should not be used in regions of highly variable terrain. This satellite altimeter data base contains precise geoid and gravity anomaly profiles which were constructed from the average of 66 repeat cycles of GEOSAT. The data were developed by Professor David T. Sandwell at the University of California in San Diego. The data are contained in two files: (1) geo66asc.bin (2,383,232records) contains the ascending profiles which run southeast to northwest between 72S and 72N, and (2) geo66des.bin (2,397,888 records) contains all of the descending profiles. The dataparameters in addition to time and location are geoid height, gravity anomaly, and uncertainty in gravity anomaly. GEOSAT 66 was updated in 1994 to include the 3rd and last year of data. Thus 66 repeat cycles of data are included in the AVERAGE profile calculation. This satellite altimeter data base was contributed by NOS/Geoscience Laboratory and contains data collected during the first 18 months of the original "Geodetic Mission" of the U.S. Navy Geodetic Satellite (GEOSAT). These digital data are in the form of geophysical data records (GDRs) which are described in NOAA Technical Memorandum NOS NGS-46. The data are observed over a tightly spaced (typically 2 or 3 km at 60 degrees latitude) ground track pattern, and are global in coverage. The Southern Ocean data contained in this subset of the original Geodetic Mission were declassified in 1990 and received at NGDC in mid 1991. GEOSAT GRAVITY ANOMALY GRID SOUTH OF 30 SOUTH K.M. Marks, DC McAdoo, and W.H.F. Smith The Geosciences Laboratory, ocean and Earth Sciences (NOAA), has produced a digital gravity anomaly grid computed from recently declassified Geosat Geodetic Mission data, combined with Exact Repeat Mission data, for the region between 30 S and 72 S latitudes. The grid spacing is 0.04 degrees in latitude, and 0.05 degrees in longitude. The grid file, g30_UNIX.BIN, is a binary file of two-byte signed integers, stored in raster scan line (bands of Latitude) order. There are 1051 scan lines with the first line at 30 S and the last at 72 S latitude. Each line has 7201 integers with the first element at 0 E longitude and the last element at 360 E longitude. Values equal to 32767 indicate land areas where Geosat gravity is unavailable; all other values should be multiplied by 0.01 to yield Free-Air Gravity anomalies in mGals. Data in g30_UNIX.BIN are in "normal" byte order (Sun, Mac, etc.); the equivalent file G30_DOS.DOS is in "swapped" byte order (DEC, PC, etc.). RAPP92: This data base was compiled by Dr. Richard H. Rapp, Ohio State University and was received in April, 1993. The data base consists of the following: One file containing a 0.125 degree grid of free-air gravity anomalies and their standard deviations between +/- 72 degrees latitude. The anomalies in the ocean areas have been derived from a combination of Geos-3, Seasat and Geosat altimeter data and the ETOP05U bathymetric data. Although gravity values are given for land areas they have been, primarily, computed from the OSU91A potential coefficient model that is complete to degree 360. One file containing a 0.125 degree gridded mean sea surface (in the mean tide system), in the same geographic region as the data given in the file above. One file containing 30-minute x 30-minute mean gravity anomalies and geoid undulations (in the tide free system), derived form OSU's 0.125 degree gridded point anomalies and geoid undulations. One file containing 1 degree x 1 degree mean gravity anomalies and geoid undulations (in the tide free system), as derived from the original gridded point values. Principal gravity parameters include mean gravity anomaly and mean geoid undulations. The gravity anomaly computation uses the Geodetic Reference System 1967 (GRS 67) Theoretical Formula. The data are global in coverage where data are available. SANDWELL: The high density Geosat/GM altimeter data south of 30 S have finally arrived. In addition, ERS-1 has completed more than 6 cycles of its 35-day repeat track. These data provide a dramatically improved view of the marine gravity field. The files in this directory contain global marine gravity anomalies gridded on a Mercator projection (see Sandwell and Smith, EOS Trans. AGU, v. 73, p. 133, Fall 1992 AGU meeting supplement). The grid was derived from the following data sources: Seasat - Used in areas north of 30 S latitude. Profiles within 10 km of a Geosat/ERM track were excluded. Geosat/ERM - Average of 62 Geosat Exact Repeat Mission profiles. Geosat/GM - Recently declassified Geosat Geodetic mission data south of 30 S. ERS-1 - Fast delivery IGDR's obtained from Bob Cheney at NOAA. Six, 35-day repeat cycles were used in the grid. ...

Basic raster layers from the MCM-LTER spatial data holdings have been exported and symbolized. The dataset files offered here include: 30m DEM made from USGS Topo map SPOT Satellite Image 39-558 LANDSAT 7 Satellite Image Note - the SPOT and LANDSAT layers are not MCM-LTER data products.  These resources were updated last in 2007, for more up-to-date layers, and potentially, higher resolution layers, please visit the Polar Geospatial Center and other affine geospatial data clearinghouses.Â