Satellite temperature measurements are inferences of the temperature of the atmosphere at various altitudes as well as sea and land surface temperatures obtained from radiometric measurements by satellites. These measurements can be used to locate weather fronts, monitor the El Niño-Southern Oscillation, determine the strength of tropical cyclones, study urban heat islands and monitor the global climate. Wildfires, volcanos, and industrial hot spots can also be found via thermal imaging from weather satellites.
Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object, in contrast to in situ or on-site observation. The term is applied especially to acquiring information about Earth and other planets. Remote sensing is used in numerous fields, including geophysics, geography, land surveying and most Earth science disciplines ; it also has military, intelligence, commercial, economic, planning, and humanitarian applications, among others.
The Landsat program is the longest-running enterprise for acquisition of satellite imagery of Earth. It is a joint NASA / USGS program. On 23 July 1972, the Earth Resources Technology Satellite was launched. This was eventually renamed to Landsat 1 in 1975. The most recent, Landsat 9, was launched on 27 September 2021.
Landsat 3 is the third satellite of the Landsat program. It was launched on March 5, 1978, with the primary goal of providing a global archive of satellite imagery. Unlike later Landsat satellites, Landsat 3 was managed solely by NASA. Landsat 3 decommissioned on September 7, 1983, beyond its design life of one year. The data collected during Landsat 3's lifetime was used by 31 countries. Countries that cannot afford their own satellite are able to use the data for ecological preservation efforts and to determine the location of natural resources.
Multispectral imaging captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or detected with the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, i.e. infrared and ultra-violet. It can allow extraction of additional information the human eye fails to capture with its visible receptors for red, green and blue. It was originally developed for military target identification and reconnaissance. Early space-based imaging platforms incorporated multispectral imaging technology to map details of the Earth related to coastal boundaries, vegetation, and landforms. Multispectral imaging has also found use in document and painting analysis.
The normalized difference vegetation index (NDVI) is a widely-used metric for quantifying the health and density of vegetation using sensor data. It is calculated from spectrometric data at two specific bands: red and near-infrared. The spectrometric data is usually sourced from remote sensors, such as satellites.
The Advanced Very-High-Resolution Radiometer (AVHRR) instrument is a space-borne sensor that measures the reflectance of the Earth in five spectral bands that are relatively wide by today's standards. AVHRR instruments are or have been carried by the National Oceanic and Atmospheric Administration (NOAA) family of polar orbiting platforms (POES) and European MetOp satellites. The instrument scans several channels; two are centered on the red (0.6 micrometres) and near-infrared (0.9 micrometres) regions, a third one is located around 3.5 micrometres, and another two the thermal radiation emitted by the planet, around 11 and 12 micrometres.
The enhanced vegetation index (EVI) is an 'optimized' vegetation index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a de-coupling of the canopy background signal and a reduction in atmosphere influences. EVI is computed following this equation:
Ocean color is the branch of ocean optics that specifically studies the color of the water and information that can be gained from looking at variations in color. The color of the ocean, while mainly blue, actually varies from blue to green or even yellow, brown or red in some cases. This field of study developed alongside water remote sensing, so it is focused mainly on how color is measured by instruments.
An atmospheric radiative transfer model, code, or simulator calculates radiative transfer of electromagnetic radiation through a planetary atmosphere.
The image fusion process is defined as gathering all the important information from multiple images, and their inclusion into fewer images, usually a single one. This single image is more informative and accurate than any single source image, and it consists of all the necessary information. The purpose of image fusion is not only to reduce the amount of data but also to construct images that are more appropriate and understandable for the human and machine perception. In computer vision, multisensor image fusion is the process of combining relevant information from two or more images into a single image. The resulting image will be more informative than any of the input images.
Multispectral remote sensing is the collection and analysis of reflected, emitted, or back-scattered energy from an object or an area of interest in multiple bands of regions of the electromagnetic spectrum. Subcategories of multispectral remote sensing include hyperspectral, in which hundreds of bands are collected and analyzed, and ultraspectral remote sensing where many hundreds of bands are used. The main purpose of multispectral imaging is the potential to classify the image using multispectral classification. This is a much faster method of image analysis than is possible by human interpretation.
Radiometric calibration is a general term used in science and technology for any set of calibration techniques in support of the measurement of electromagnetic radiation and atomic particle radiation. These can be for instance, in the field of radiometry or the measurement of ionising radiation radiated from a source.
Barry N. Haack is an American geographer and Emeritus Professor in the Department of Geography and Geoinformation Science at George Mason University in Fairfax, Virginia. He is an international authority on remote sensing, geographic information systems (GIS), and technology transfer from developed to developing nations. Haack is a visiting physical scientist at the United States Geological Survey and an elected Fellow in the American Society for Photogrammetry and Remote Sensing (ASPRS). Through education and collaboration, Haack has influenced the careers of scientists and decision makers from many United States federal agencies and in universities and agencies in nearly thirty countries. He has held formal arrangements with the United Nations, World Bank, Inter-American Development Bank, NASA, the European Space Agency, the National Geographic Society, and many other international organizations and country governmental agencies.
The airborne visible/infrared imaging spectrometer (AVIRIS) is the second in a series of imaging spectrometer instruments developed at the Jet Propulsion Laboratory (JPL) for Earth remote sensing. This instrument uses scanning optics and four spectrometers to image a 614-pixel swath simultaneously in 224 adjacent spectral bands.
A vegetation index (VI) is a spectral imaging transformation of two or more image bands designed to enhance the contribution of vegetation properties and allow reliable spatial and temporal inter-comparisons of terrestrial photosynthetic activity and canopy structural variations.
Land cover maps are tools that provide vital information about the Earth's land use and cover patterns. They aid policy development, urban planning, and forest and agricultural monitoring.
Remote sensing in oceanography is a widely used observational technique which enables researchers to acquire data of a location without physically measuring at that location. Remote sensing in oceanography mostly refers to measuring properties of the ocean surface with sensors on satellites or planes, which compose an image of captured electromagnetic radiation. A remote sensing instrument can either receive radiation from the earth’s surface (passive), whether reflected from the sun or emitted, or send out radiation to the surface and catch the reflection (active). All remote sensing instruments carry a sensor to capture the intensity of the radiation at specific wavelength windows, to retrieve a spectral signature for every location. The physical and chemical state of the surface determines the emissivity and reflectance for all bands in the electromagnetic spectrum, linking the measurements to physical properties of the surface. Unlike passive instruments, active remote sensing instruments also measure the two-way travel time of the signal; which is used to calculate the distance between the sensor and the imaged surface. Remote sensing satellites often carry other instruments which keep track of their location and measure atmospheric conditions.
Qihao Weng is an American geographer, urban, environmental sustainability, and remote sensing scientist. He has been a Chair Professor at the Hong Kong Polytechnic University since July 2021, and was the Director of the Center for Urban and Environmental Change and is a professor of geography in the Department of Earth and Environmental Systems at the Indiana State University.
Atmospheric correction for Interferometric Synthetic ApertureRadar (InSAR) technique is a set of different methods to remove artefact displacement from an interferogram caused by the effect of weather variables such as humidity, temperature, and pressure. An interferogram is generated by processing two synthetic-aperture radar images before and after a geophysical event like an earthquake. Corrections for atmospheric variations are an important stage of InSAR data processing in many study areas to measure surface displacement because relative humidity differences of 20% can cause inaccuracies of 10–14 cm InSAR due to varying delays in the radar signal. Overall, atmospheric correction methods can be divided into two categories: a) Using Atmospheric Phase Screen (APS) statistical properties and b) Using auxiliary (external) data such as GPS measurements, multi-spectral observations, local meteorological models, and global atmospheric models.
