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 Moderate Resolution Imaging Spectroradiometer (MODIS) is a satellite-based sensor used for earth and climate measurements. There are two MODIS sensors in Earth orbit: one on board the Terra satellite, launched by NASA in 1999; and one on board the Aqua satellite, launched in 2002. MODIS has now been replaced by the VIIRS, which first launched in 2011 aboard the Suomi NPP satellite.
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.
Red edge refers to the region of rapid change in reflectance of vegetation in the near infrared range of the electromagnetic spectrum. Chlorophyll contained in vegetation absorbs most of the light in the visible part of the spectrum but becomes almost transparent at wavelengths greater than 700 nm. The cellular structure of the vegetation then causes this infrared light to be reflected because each cell acts something like an elementary corner reflector. The change can be from 5% to 50% reflectance going from 680 nm to 730 nm. This is an advantage to plants in avoiding overheating during photosynthesis. For a more detailed explanation and a graph of the photosynthetically active radiation (PAR) spectral region, see Normalized difference vegetation index § Rationale.
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.
Hyperspectral imaging collects and processes information from across the electromagnetic spectrum. The goal of hyperspectral imaging is to obtain the spectrum for each pixel in the image of a scene, with the purpose of finding objects, identifying materials, or detecting processes. There are three general types of spectral imagers. There are push broom scanners and the related whisk broom scanners, which read images over time, band sequential scanners, which acquire images of an area at different wavelengths, and snapshot hyperspectral imagers, which uses a staring array to generate an image in an instant.
The fraction of absorbed photosynthetically active radiation is the fraction of the incoming solar radiation in the photosynthetically active radiation spectral region that is absorbed by a photosynthetic organism, typically describing the light absorption across an integrated plant canopy.
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:
The Operational Land Imager (OLI) is a remote sensing instrument aboard Landsat 8, built by Ball Aerospace & Technologies. Landsat 8 is the successor to Landsat 7 and was launched on February 11, 2013.
Ecosystem Functional Type (EFT) is an ecological concept to characterize ecosystem functioning. Ecosystem Functional Types are defined as groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges between the biota and the physical environment. The EFT concept is analogous to the Plant Functional Types (PFTs) concept, but defined at a higher level of the biological organization. As plant species can be grouped according to common functional characteristics, ecosystems can be grouped according to their common functional behavior.
Empirically derived NDVI products have been shown to be unstable, varying with soil colour, soil moisture, and saturation effects from high density vegetation. In an attempt to improve NDVI, Huete developed a vegetation index that accounted for the differential red and near-infrared extinction through the vegetation canopy. The index is a transformation technique that minimizes soil brightness influences from spectral vegetation indices involving red and near-infrared (NIR) wavelengths.
Gaofen is a series of Chinese high-resolution Earth imaging satellites launched as part of the China High-resolution Earth Observation System (CHEOS) program. CHEOS is a state-sponsored, civilian Earth-observation program used for agricultural, disaster, resource, and environmental monitoring. Proposed in 2006 and approved in 2010, the CHEOS program consists of the Gaofen series of space-based satellites, near-space and airborne systems such as airships and UAVs, ground systems that conduct data receipt, processing, calibration, and taskings, and a system of applications that fuse observation data with other sources to produce usable information and knowledge.
Normalized Difference Water Index (NDWI) may refer to one of at least two remote sensing-derived indexes related to liquid water:
Remote sensing is used in the geological sciences as a data acquisition method complementary to field observation, because it allows mapping of geological characteristics of regions without physical contact with the areas being explored. About one-fourth of the Earth's total surface area is exposed land where information is ready to be extracted from detailed earth observation via remote sensing. Remote sensing is conducted via detection of electromagnetic radiation by sensors. The radiation can be naturally sourced, or produced by machines and reflected off of the Earth surface. The electromagnetic radiation acts as an information carrier for two main variables. First, the intensities of reflectance at different wavelengths are detected, and plotted on a spectral reflectance curve. This spectral fingerprint is governed by the physio-chemical properties of the surface of the target object and therefore helps mineral identification and hence geological mapping, for example by hyperspectral imaging. Second, the two-way travel time of radiation from and back to the sensor can calculate the distance in active remote sensing systems, for example, Interferometric synthetic-aperture radar. This helps geomorphological studies of ground motion, and thus can illuminate deformations associated with landslides, earthquakes, etc.
The moment distance index (MDI) is a shape-based metric or shape index that can be used to analyze spectral reflectance curves and waveform LiDAR, proposed by Salas and Henebry in 2014. In the case of spectral data, the shape of the reflectance curve should unmask fine points of the spectra usually not considered by existing band-specific indices. It has been used to identify spectral regions for chlorophyll and carotenoids, detect greenhouses using WorldView-2, Landsat, and Sentinel-2 satellite data, identify greenhouse crops, compute canopy heights, estimate green vegetation fraction, and optimize Fourier-transform infrared (FTIR) scans for soil spectroscopy.
BAITSSS is biophysical Evapotranspiration (ET) computer model that determines water use, primarily in agriculture landscape, using remote sensing-based information. It was developed and refined by Ramesh Dhungel and the water resources group at University of Idaho's Kimberly Research and Extension Center since 2010. It has been used in different areas in the United States including Southern Idaho, Northern California, northwest Kansas, Texas, and Arizona.
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.
Applications of machine learning in earth sciences include geological mapping, gas leakage detection and geological features identification. Machine learning (ML) is a type of artificial intelligence (AI) that enables computer systems to classify, cluster, identify and analyze vast and complex sets of data while eliminating the need for explicit instructions and programming. Earth science is the study of the origin, evolution, and future of the planet Earth. The Earth system can be subdivided into four major components including the solid earth, atmosphere, hydrosphere and biosphere.
The Hyperspectral Imager for the Coastal Ocean (HICO) was a hyperspectral earth observation sensor that operated on the International Space Station (ISS) from 2009 to 2014. HICO collected hyperspectral satellite imagery of the Earth's surface from the ISS.
