Environmental conditions are very changeable; fluctuations in temperature, precipitation, illumination intensity, and other factors can decrease a plant productivity and crop. The remote sensing of plants under these conditions is the basis for the p...
Acquiring a large number of in situ water spectral measurements is fundamental for constructing water color remote-sensing retrieval models and validating the accuracy of water color remote-sensing products. However, traditional manual site-based wat...
Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This p...
The Geostationary Ocean Color Imager (GOCI) is the world’s first ocean color sensor in geostationary orbit. Although the GOCI has shown excellent radiometric performance with little long-term radiometric degradation and a high signal-to-noise ratio,...
This paper presents a model of upwelling radiation above the seawater surface in the event of a threat of dispersed oil. The Monte Carlo method was used to simulate a large number of solar photons in the water, eventually obtaining values of remote s...
Remote sensing techniques currently used to detect oil spills have not yet demonstrated their applicability to dispersed forms of oil. However, oil droplets dispersed in seawater are known to modify the local optical properties and, consequently, the...
Determining the dominant optically active substances in water bodies via classification can improve the accuracy of bio-optical and water quality parameters estimated by remote sensing. This study provides four robust centroid sets from in situ remot...
Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical depth of the atmosphere and the spectral slope of its spectrum, the so-called Angstrom parameter....
The study focuses on modeling the remote sensing reflectance (Rrs) for optically complex waters based on the absorption (a), scattering (b), and backscattering (bb) coefficients measured at selected wavelengths (420 nm, 488 nm, 555 nm, and 620 nm). R...
Surface glint significantly reduces the measurement accuracy of remote sensing reflectance of water, Rrs, making it difficult to effectively use field measurements for studying water optical properties, accurately retrieving water quality parameters,...
Coastal waters are the richest parts of ocean ecosystems characterised by dynamic changes in water biology, physical and chemical features. Establishing local relationships between water constituents and optical properties in these areas will help to...
Ocean color remote sensing is important for monitoring marine biogeochemical processes. The accuracy of remote sensing reflectance (Rrs), a fundamental data product, is critical yet challenged by the scale mismatch between in situ point measurements...
Land surface reflectance is a basic physical parameter in many quantitative remote sensing models. However, the existing reflectance conversion techniques for drone-based (or UAV-based) remote sensing need further improvement and optimization due to...
Optical water types (OWTs) were identified from remote sensing reflectance (Rrs(λ)) values in a field-measured dataset of several large lakes in the lower reaches of the Yangtze and Huai River (LYHR) Basin. Four OWTs were determined from norma...
Unmanned aerial vehicle (UAV) hyperspectral remote sensing imaging systems have demonstrated significant potential for water quality monitoring. However, accurately obtaining water-leaving reflectance from UAV imagery remains challenging due to compl...
Many standard methods used for the remote sensing of ocean colour have been developed, though mainly for clean, open ocean waters. This means that they may not always be effective in complex waters potentially containing high concentrations of optica...
In the application of ocean color remote sensing, remote sensing reflectance spectral (Rrs(λ)) is the most important and basic parameter for the development of bio-optical algorithms. Atmospheric correction of ocean color data is a key factor...
The emergence of hyperspectral optical satellite sensors for ocean observation provides potential for more detailed information from aquatic ecosystems. The German hyperspectral satellite mission EnMAP (enmap.org) currently in the production phase is...
The topographic shadow effect can cause surface reflectance distortions in the shadow areas of remote sensing images, particularly in complex mountainous areas. In this study, based on the difference in solar radiation received at the surface of sunl...
Spectral remote sensing reflectance (Rrs(λ), sr−1) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian...
The Pomeranian lakes in Northern Poland and the nearby coastal waters of the Baltic Sea belong to optically complex water bodies characterised by high eutrophication levels. These water types require a local approach when developing bio-optical algor...
Microphones have been extensively studied for many decades and their related theories are well-established. However, the physical presence of the sensor itself limits its practicality in many sound field control applications. Laser Doppler vibrometer...
The aim of this study was to follow the response to drought stress in a Poa pratensis canopy exposed to various levels of soil moisture deficit. We tracked the changes in the canopy reflectance (450–2450 nm) and retrieved vegetation properties (Leaf...
Hyperspectral images possess properties such as rich spectral information, narrow bandwidth, and large numbers of bands. Finding effective methods to retrieve land features from an image by using similarity assessment indices with specific spectral c...
The rapid growth of phytoplankton and microalgae has presented considerable environmental and societal challenges to the sustainable development of human society. Given the inherent limitations of satellite-based algal bloom detection techniques that...
Most ocean color algorithms are designed for optically deep waters, where the seafloor has little or no effect on remote sensing reflectance. This can lead to inaccurate retrievals of inherent optical properties (IOPs) in optically shallow water envi...
Optically shallow waters (OSW) enable water depth retrieval through passive optical remote sensing, benefiting from the relatively low attenuation of the water column. However, in OSW environments, remote sensing reflectance is influenced by multiple...
In-depth knowledge about soil moisture dynamics is crucial for irrigation management in precision agriculture. This study evaluates the feasibility of high spatial resolution near-infrared remote sensing with unmanned aerial systems for soil moisture...
With the acceleration of urbanization, increasing water pollution means that monitoring and evaluating urban water quality are of great importance. Although highly accurate, traditional evaluation methods are time consuming, laborious, and vastly ins...
Snow surface spectral reflectance is very important in the Earth’s climate system. Traditional land surface models with parameterized schemes can simulate broadband snow surface albedo but cannot accurately simulate snow surface spectral reflec...
HydroColor is a mobile application that utilizes a smartphone’s camera and auxiliary sensors to measure the remote sensing reflectance of natural water bodies. HydroColor uses the smartphone’s digital camera as a three-band radiometer. Users are dire...
In remote sensing, the conversion of at-sensor radiance to surface reflectance for each pixel in a scene is an essential component of many analysis tasks. The empirical line method (ELM) is the most used technique among remote sensing practitioners d...
Suspended Particulate Matter (SPM) is a major constituent in coastal waters, involved in processes such as light attenuation, pollutant propagation, and waterways blockage. The spatial distribution of SPM is an indicator of deposition and erosion pat...
MODIS (Moderate Resolution Imaging Spectroradiometer) land product subsets can provide high-quality prior knowledge for the quantitative inversion of land and atmospheric parameters. Using the LSR (Land Surface Reflectance) dataset, dust storm remote...
For satellite remote sensing, radiances received at the sensor are not only affected by the atmosphere but also by the topographic properties of the terrain surface. As a result, atmospheric correction alone does not yield output images that truly re...
Urban Black and Odorous Water (BOW) has become an environmental problem in many cities in China. The use of satellite remote sensing technology to identify BOW is still in its infancy, and there are many problems that need further solutions. In order...
High-frequency imaging characteristics allow a geostationary satellite (GSS) to capture the diurnal variation in vegetation canopy reflectance spectra, which is of very important practical significance for monitoring vegetation via remote sensing (RS...
Spectral reflectance within the 350–2500 nm range was measured for 17 pelts of arctic mammals (polar bear, caribou, muskox, and ringed, harp and bearded seals) in relation to snow. Reflectance of all pelts was very low at the ultraviolet (UV) end of...
The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is rel...
Semi-analytical algorithms (SAAs) invert spectral remote sensing reflectance
Seawaters exhibit various types of cyclic and trend-like temporal alterations in their biological, physical, and chemical processes. Surface water dynamics may vary, for instance, when the timings, durations, or amplitudes of seasonal developments of...
The atmospheric correction of satellite observations is crucial for both land and ocean remote sensing. However, the optimal approach for each area is different due to the large spectra difference in the ground reflectance between land and ocean. A u...
A scheme to semi-analytically derive waters’ Secchi depth (Zsd) from remote sensing reflectance (Rrs) considering the effects of the residual errors in satellite Rrs was developed for the China Eastern Coastal Zone (CECZ). This approach was evaluated...
Atmospheric correction of satellite optical data is based on an assessment of the optical characteristics of the atmosphere, such as the aerosol optical thickness of the atmosphere and the spectral slope, the so-called Angstrom parameter. Inaccurate...
Many lakes in boreal and arctic regions have high concentrations of CDOM (coloured dissolved organic matter). Remote sensing of such lakes is complicated due to very low water leaving signals. There are extreme (black) lakes where the water reflectan...
There has been an uninterrupted suite of ocean-color missions with global coverage since 1997, a continuity now supported by programs ensuring the launch of a series of platforms such as the Sentinel-3 missions hosting the Ocean and Land Color Imager...
Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostation...
Remote sensing image data from sources such as Landsat or airborne multispectral digital cameras are typically in the form of digital count (DC) values. To compare images acquired by the same sensor system on different dates, or images acquired by di...
Fixed automated (unmanned) above-water radiometric measurements are subject to unavoidable sky conditions and surface perturbations, leading to significant uncertainties in retrieved water surface remote sensing reflectances (Rrs(λ), sr−...
The aim of this study was to develop methods for determining the most significant contrasts in satellite ocean color data arising in the presence of a submesoscale eddy structure, as well as to determine the corresponding depths of the upper layer of...
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