These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are short-wave and long-wave radiation emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product.Other products are based on the enhancement of channel data for a single wavelength, also aimed at highlighting meteorological features of the observed surface or clouds, but in a simpler way since only a single wavelength is involved. This older approach is still useful today, as its simplicity makes image interpretation easier in some cases.

Polygons containing the date of capture of the Landsat images used to create the first version of the Baseline Thematic Mapping v1 (BTM1). This spatial view is only meaningful in conjunction with the satellite images or the BTM data derived from the satellite images. The images were captured from 1990 to 1997

This dataset was developed to document the procedures for acquiring underwater images in the Banc-des-Américains Marine Protected Area (MPA). Its primary objective is to provide a comprehensive inventory of metadata linked to imagery campaigns that allowed us to conduct a basic characterization of the area, and now that are used for ecological monitoring of the benthic habitats within the MPA.Metadata were collected during imagery surveys conducted since 2012, using three main methods: drop cameras on the crest, baited drop stereoscopic cameras on both the crest and plains, and towed cameras on the plains. For each operation are shared the type of gear used, sampling method, date, geographic coordinates, and acquisition depth.The released dataset contains only descriptive information related to the acquisition of images : file identifier, location, sampling methodology, depth, and technical imaging parameters. It does not include image files themselves, visual content, or the results of image analyses.A systematic quality control is applied to ensure completeness and consistency of the metadata: field format standardization, validation of GPS coordinates, verification of dates and recorded depths. Clear instructions guide the recording of metadata to guarantee their reliability for management and scientific monitoring purposes.

High-resolution false-color Landsat image composite of Canada's forested ecosystems (2022). This national image product represents the Composite to Change (C2C) proxy composite image derived from thousands of Landsat images acquired between July 1 and August 30, 2022. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The overall process followed is described in (Hermosilla et al. 2016 ) with details on the generation of gap-free surface reflectance composites in ( Hermosilla et al. 2015). Following the motivation and rationale presented in White et al. (White et al. 2014), Landsat imagery is subjected to a series of processing steps to remove clouds and shadows as well as haze and other unwanted atmospheric effects. Year-on-year time series of Landsat imagery are interrogated to avoid missing values, and to ensure exhaustive spatial coverage of the national surface reflectance composites. False-colour 3-channel image (bands: shortwave infrared, SWIR1; near infrared; red)When using these data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054 (Hermosilla et al. 2016 ).

This layer represents Land use polygons as determined by a combination of analytic techniques, mostly using Landsat 5 image mosaics . BTM 1 was done on a federal satellite image base that was only accurate to about 250m. The images were geo-corrected, not ortho-corrected, so there is distortion in areas of high relief. This is not a multipart feature

Digital orthorectified imagery acquired at a variety of image resolutions, available in New Brunswick Stereographic Double Projection (NBSDP).

Groundwater flow is the movement of water in an aquifer or hydrogeological unit. The dataset shows groundwater flow rate and direction in the hydrogeological unit. Groundwater flow is establish from piezometric surface map. The method used to create the dataset is described in the metadata associated with the dataset. The dataset represents a description of the flow, including rate in m/d, direction, date and source. Typically, the data provided will not be in the form of a shapefile with linked properties but in the form of an image that sketches the groundwater flow. The image could also represent a cross section of the hydrogeologic units showing the regional trends of the groundwater flow.

On July 6, a train of 72 cars, carrying 100 tons of crude oil each, exploded in Lac-Mégantic. A high-resolution aerial photograph was collected by Aéro-Photo after the train derailment. This aerial photograph was provided and georeferenced by Aéro-Photo (1961) inc. Purpose: This aerial photograph makes it possible to identify the impact radius of the accident. The image web service (WMS) is offered as an open service. However, to obtain the raw image, please contact Aéro-Photo (1961) inc.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This Shaded Relief Image has a resolution of 500 meters and was derived from the United States Geological Survey "30 Arc-second Digital Elevation Model".Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)