Remote sensing can be classified as active or passive based on the energy source. For ocean color, active remote sensing shots signal from the sensor platform (satellite or aircraft) to the water body and detects the return signal from it. Passive remote sensing observes the light that is reflected or emitted by the water body. The most commonly used light source for passive remote sensing is sunlight. Sensors detect the light backscattered out of the ocean after interaction with water and its constituents. This light signal calculated as remote-sensing refectance are reported by NASA as a standard output for sensors.
Phytoplankton form the bottom levels of the marine and aquatic food webs, and their existence not only makes life in the water possible but also makes the ocean an important food source for mankind. They live near the water surface to capture sufficient light for photosynthesis and act as the primary producer of the plankton community. The resulting photosynthesis and its products, especially the oxygen and organic compounds, all rely on the light energy captured by chlorophyll a, the dominant pigment inside phytoplankton cells, and accessory pigments (e.g. chlorophylls b and c, carotenoids, and phycobiliproteins). In the past decades, the identification of phytoplankton from satellite remote sensing has been mainly focused on chlorophyll a, and the products have been widely used to represent the phytoplankton biomass in the primary productivity estimation and biogeochemical models.
Downwelling Irradiance (more precisely downwelling spectral irradiance) is a measurement of the solar illumination incident downward on the water surface. When sunlight hit the water surface, a portion of the light transmits into the water column. How deep the light can go? It depends on the property of the water column. The propagation of downwelling irradiance at wavelength λ from surface to a depth (z) in the ocean is governed by the diffuse attenuation coefficient, Kd(λ). The diffuse attenuation coefficient at 490nm, Kd(490), is an indicator of the turbidity of the water column, and is directly related to the concentration of scattering particles in the water column.
For PACE KD products, refer to the Spectral Diffuse Attenuation Coefficient ATBD.
Particulate carbon
Particles present in water can be categorized into two main groups: organic and inorganic. These particles are typically larger, measuring over 0.2 micrometers in diameter, rendering them unable to pass through the filtration system designed to isolate dissolved carbon.
Particulate organic carbon (POC) is operationally defined as all combustible, non-carbonate carbon, including suspended and sinking particles, such as living microbial cells, detrital material (e.g. dead cells, fecal pellets), other aggregated material, and terrestrially-derived organic matter. Organic matter plays a crucial role in regulating global marine biogeochemical cycles and events. Scientists developed algorithms to estimate the surface layer particulate organic carbon from remote sensing reflectance and observe them in the global scale.
Particulate inorganic carbon (PIC) is defined as the inorganic carbon in particulate form and usually takes the form of calcium carbonate (CaCO3). PIC plays a key part in the global ocean carbon cycle. Through the process of calcification, marine organisms produce PIC shells and carbon dioxide from calcium ions and bicarbonate in seawater. There are many calcifying marine organisms, including coral, foraminifera, and pteropods, but coccolithophores are a major producer of PIC in the pelagic zone of oceanic regimes. Calcium carbonate production leads to an increase in partial pressure of dissolved carbon dioxide in the surface layer of the ocean, weakening the effectiveness of the carbon dioxide sink produced by photosynthesis.
Phytoplankton pigments absorb sunlight and use it for photosynthesis, but not all light can be absorbed and used, such as ultraviolet light can damage the cell. Phytoplankton pigments (chlorophyll and accessory pigments) absorb light in the wavelength range of 400-700 nm. This part of the solar radiation can be used in photosynthesis and the quantum energy flux of this wavelength range is called photosynthetically available radiation. PAR changes seasonally and varies depending on the latitude and time of day.
A portion of the light absorbed by phytoplankton pigments can be emitted at a longer wavelength in a physical process called fluorescence. The energy dissipated in fluorescence is secondary to the amount absorbed and used for photosynthesis, but it is still significant enough to be observed in ocean color remote sensing data. Chlorophyll a fluorescence has been the most significantly used fluorescence feature, and the detection and products from satellite ocean color sensors have been widely used. A commonly used parameter is the fluorescence line height (FLH) which extracts chlorophyll fluorescence signal excited by sunlight from remote sensing reflectance (Rrs) and relies on three bands for calculation: the central wavelength of the maximum value of chlorophyll fluorescence (near 685 nm) and the two other bands used to generate the baseline under the fluorescence peak, which are located on opposite sides of the fluorescence peak. Many ocean color sensors have fluorescent bands (e.g., MODIS, OLCI on Sentinel-3A/B).
When light interacts with matter one of two things can happen. The light can disappear, with its energy being converted to another form such as heat or the energy contained in a chemical bond. This process is called absorption. The light can also change its direction and/or wavelength. Either of these processes is called scattering. The absorption and scattering properties of a medium such as sea water are described by its inherent optical properties, or IOPs. IOPs are properties of the medium and do not depend on the ambient light ?eld. NASA ocean color data provide absorption or scattering coefficients of the water constitutes (e.g. particulate backscattering coefficient, absorption coefficient of phytoplankton, non-algal particles and colored dissolved organic carbon) calculated using the default global configuration of the Generalized Inherent Optical Property (GIOP) model.
PIC Color Index is an algorithm calculates the concentration of particulate inorganic carbon (PIC) from remote sensing reflectance using a parameter called color index. The color index uses blue, green and red wavebands and is calculated as the difference between the green-band reflectance and a reference formed linearly by the blue and red bands.
Apparent visible wavelength is a one-dimensional geophysical metric to describe the color of the water. It is calculated using a weighted harmonic mean of Rrs(λ) spectra. AVW is inherently correlated to Rrs(λ) spectral shape and can be used as an optical water classification index.
Quality Water Index Polynomial
Influenced by many factors (such as operational errors, instrument calibration and validation, and environmental conditions), the remote sensing reflectance measured in field or by satellite sensors may contain unwanted errors and fall outside of the general trends. The Quality Water Index Polynomial (QWIP) score, representing a quantitative metric to evaluate the quality of ocean color remote sensing reflectance (Rrs) data and identify spectra that fall outside the general trends observed in aquatic optics for optically deep waters. The approach was developed with a large global dataset representing waters dominated by different constitutes and was further tested extensively with field and satellite datasets. This simple approach can provide a level of uncertainty about a retrieved spectrum and flag questionable or unusual spectra for further analysis.
The carbon inside phytoplankton is an important part of the carbon cycle and biogeochemical cycles of the global ocean. Identify phytoplankton carbon concentration and separate them from non-algal particles is an important step to study the phytoplankton community in the water column. This provisional algorithm empirically estimated phytoplankton carbon concentration from particulate backscattering coefficient derived from GIOP.
GSM and QAA algorithms are analytical algorithms that developed to obtain the optical properties of the water constitutes from satellite remote sensing reflectance based on physical principles instead of empirical relationships. They use remote sensing reflectance as input and derive absorption coefficients of phytoplankton, non-algal particles, and colored dissolved organic carbon, and particulate backscattering coefficients.
Euphotic zone depth reflects the depth where only 1% of the surface photosynthetic available radiation (PAR) remains. Euphotic zone depth is a measure of water clarity, which is not only a quality index of an ecosystem but also an important property for primary production and heat transfer in the upper water column. Lee algorithm used Rrs derived IOPs to estimate the euphotic zone depth.
Phytoplankton are primary producers and also consumers. They produce oxygen and organic carbon when there is light, at the same time consume the oxygen and organic carbon they produced for their growth. Net primary production (NPP) is the amount of biomass or carbon produced by primary producers per unit area and time, obtained by subtracting plant respiratory costs from gross primary productivity or total photosynthesis.
Scientists study Earth's land ecosystems using data on surface reflectance, which shows how much light is reflected by the ground. Since satellite measurements are taken from space, they must be adjusted to remove the effects of gases and particles in the atmosphere—a process called atmospheric correction. A special algorithm was used to perform this correction, producing surface reflectance data that can be used to study vegetation and other environmental features.
The LANDVI product provides important data to help scientists study vegetation health and environmental changes. LANDVI includes traditional vegetation indices (VIs) that have been used for decades to monitor plant health, along with four new VIs designed specifically for hyperspectral data. These new indices offer more detailed insights into the pigments in leaves, such as chlorophyll, carotenoids, and anthocyanins, which are crucial for photosynthesis and plant protection. By combining both traditional and new VIs, LANDVI helps researchers better understand how vegetation responds to changing environmental conditions around the world. The following VIs are included:
- Normalized difference vegetation index (NDVI): Empirical metric related to vegetation abundance and health, corrected for atmospheric scattering and absorption.
- Enhanced vegetation index (EVI): Empirical metric related to vegetation abundance and health, similar to NDVI, with additional resistance to atmospheric effects and sensitivity in densely vegetated regions.
- Normalized Difference Water Index (NDWI): Empirical metric using NIR and SWIR (1250 nm) bands to investigate vegetation water content and stress.
- Normalized Difference Infrared Index (NDII): Empirical metric using NIR and SWIR (1618 nm) bands to investigate vegetation water content and stress.
- Chlorophyll-Carotenoid Index (CCI): Empirical metric related to photosynthesis through chlorophyll/carotenoid pigment dynamics.
- Normalized Difference Snow Index (NDSI): Empirical metric for evaluating the presence of snow in any given pixel.
- Photochemical reflectance index (PRI): Hyperspectral vegetation index designed to capture subtle shifts in carotenoids and provides information on stress in plants.
- Chlorophyll Index Red Edge (CIRE): Hyperspectral vegetation index related to canopy chlorophyll content using red edge (NIR) surface reflectance measurements.
- Carotenoid Content Index (Car): Hyperspectral vegetation index related to canopy carotenoid content, a pigment which plays a role in photosynthesis and photo-protection.
- Modified Anthocyanin Reflectance Index (mARI): Hyperspectral vegetation index related to canopy anthocyanin content, a pigment which protects leaves from excess light.