We propose a physically-based methodology for sea-surface skin-temperature (SST) retrievals from daytime spectra recorded by the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI). The approach, which takes sun light into account, minimizes the differences between measured and computed radiances at numerous points within two windows centered near 3.7 and 4.0 μm. We demonstrate that,

Calibration and validation of aboveground biomass (AGB) (AGB) products retrieved from satellite-borne sensors require accurate AGB estimates across hectare scales (1 to 100 ha). Recent studies recommend making use of non-destructive terrestrial laser scanning (TLS) based techniques for individual tree AGB estimation that provide unbiased AGB predictors. However, applying these techniques across large

Various types of floating macroalgae and other floating matters have been reported in the global oceans and inland waters, and their remote detection has relied primarily on passive optical sensors. These sensors provide multiple spectral bands and frequent revisits, yet they all suffer from clouds. Synthetic aperture radar (SAR) imagers are active sensors that overcome this obstacle, yet their capacity

This paper introduces a method for estimating a series of sea state parameters from satellite-borne synthetic aperture radar (SAR). The method was realized in a near real time (NRT) application which allows for the processing of data from different satellites and modes. The algorithm estimates the total significant wave height Hs, dominant and secondary swell and windsea wave heights, first, and second

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60

In recent years, various techniques have been developed to generate crop-type maps based on remote sensing data. Wheat and barley are two major cereal crops cultivated as the first and fourth largest grain crops across the globe. The variations in spectral temporal profile of both crops are generally insignificant at small scales and therefore the two crops are phenologically fairly clearly separated;

Estimating proportion of area from a stratified random sample and reference class labels obtained by ground visit or interpretation of satellite imagery is a common strategy in land cover monitoring. Confidence intervals for the proportion of area are typically estimated using the Wald interval, a procedure that is known to yield less than nominal coverage (i.e., undercoverage) when the proportion

Accurate and up-to-date maps of built-up areas are crucial to support sustainable urban development. Earth Observation (EO) is a valuable data source to cover this demand. In particular, Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) missions offer new opportunities to map built-up areas on a global scale. Using Sentinel-2 images, recent urban mapping efforts

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress

The availability and quality of quad-pol synthetic aperture radar (SAR) datasets has increased substantially since the early 2000s, allowing for polarimetrically complete investigations of freshwater ice. These investigations have lead to improved ice classification methods, new understanding of microwave-ice scattering processes, and the potential for new methods to extract ice observables. Such analyses

Quantitative evidence for the fundamental spectral shape similarity existing between different soils is presented utilizing Pearson's correlation and SAM (Spectral Angle Mapper) analysis in-between signatures representing thousands of soil samples collected from different environments around the world. A universal quadratic soil line (UQSL) was found to highly fit these representative signatures as

Global surface temperature has been setting new record highs in the recent decades, imposing increasing environmental challenges for societies and ecosystems worldwide. Global warming rates of the 20th century have been documented by a number of studies, nevertheless, the warming rates in the most recent decades in the 21st century are of particular interest for understanding the ongoing climate change

This paper discusses the differences, due to different measuring mechanisms, of satellite-derived and ground measured surface solar irradiance (SSI) direct and diffuse components, and the impacts of the differences when validating satellite-derived data using ground measurements, using SSI products derived from the Advanced Himawari Imager. The issue of satellite-ground mismatch, though previously

The mapping of sugarcane plantations and their changes is relevant to the economy and the environment, notably due to sugarcane's interface in the biofuel industry through ethanol. The necessary mapping of sugarcane crop changes is especially challenging when plantation occurs under smallholders' land ownership structures used for heterogeneous crop management. We evaluated two approaches to address

For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change. Despite considerable progress, accurate estimates of daily ocean productivity from space have not been realized because polar-orbiting satellites are

Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets

Agricultural irrigation, as an important practice to protect crops from drought and promote grain yield, has a long history in China. A timely and precise dataset about the extent and dynamics of irrigated areas is necessary for water allocation and agricultural management but is scarce in China. Here we developed annual irrigated cropland maps across China (IrriMap_CN) at 500-m resolution from 2000

The Bayesian passive microwave retrievals of snowfall often rely on mathematical matching of the observed vectors of brightness temperature with an a priori database of precipitation profiles and their corresponding brightness temperatures. Mathematical proximity does not necessarily lead to consistent retrievals due to limited information content of passive microwave observations. This paper defines

High mountain glaciers (HMGs), called the water towers of the world, are vulnerable to the effects of climate change and thus are rapidly shrinking. Monitoring and evaluating large-scale glacier and snow (GS) mass changes are critical for humans and ecosystems. Although modern gravity satellites monitor GS on a global scale, the contemporary Gravity Recovery and Climate Experiment (GRACE) and GRACE

The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat-2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and

Anthropogenic carbon emissions directly contribute to global warming, which has induced severe environmental concerns like extreme droughts and devastating fires. To evaluate the effects of fires on carbon cycling and climate change, it is crucial to accurately estimate the amount of carbon released during fires. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission offers spaceborne light

Post monsoonal agricultural Crop Residue Burning (CRB) over northwestern India is believed to severely affect the air quality of the megacity of Delhi. However, the mechanistic understanding remains elusive. Long-term satellite observations (2007–2020) of aerosol properties during CRB season (Oct 20th to Nov 20th) indicate a distinct airshed of CRB plume transport from Northwestern India (source region)

From its initial measurements 20 years ago, the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) has produced large validation data sets to assess the ocean color satellite data records. This study, applied to the standard atmospheric correction algorithm l2gen of the National Aeronautics and Space Administration, analyses the populations of residuals (differences between matching

Knowledge of the soil organic carbon (SOC) content is critical for environmental sustainability and carbon neutrality. With the development of remote sensing data and prediction models, the comprehensive utilization of multisource remote sensing data based on a fusion approach and testing its effectiveness in SOC content prediction is an interesting and challenging topic. However, there is no evidence

Many studies have established the strong connections between aboveground biomass and lidar height metrics; however, these relationships are site-specific. Field data required to derive these relationships are not readily available in many cases. We developed a model to estimate plot-level aboveground biomass density (AGBD) directly from large-footprint lidar waveform measurements. An individual tree-based

To minimize systematic differences between soil moisture (SM) time series derived from remote sensing (RS) and land surface model (LSM), RS-based SM climatology information is typically discarded during land data assimilation (DA). However, recent studies have demonstrated that SM climatology estimates provided by L-band microwave RS retrievals can significantly outperform comparable estimates derived

Red snow algal blooms reduce albedo and increase snowmelt, but little is known of their extent, duration, and radiative forcing. We calibrated an established index by comparing snow algal field spectroradiometer measurements with direct counts of algal cell abundance in British Columbia, Canada. We applied the field calibrated index to Sentinel-2, Landsat-8, and MODIS/Terra images to monitor snow algae

The relationship between biodiversity and spectral diversity is highly scale-dependent, and temporal variation in leaf morphological, biochemical traits and canopy structure can alter this relationship. However, the temporal dependence of the spectral diversity – biodiversity relationship is poorly understood, in part due to the difficulties of obtaining consistent measurements across space and time

Sea ice thickness is an important climate indicator and is often monitored in the form of freeboard or total freeboard (with snow cover) using satellite altimetry. However, satellites often have a long revisit interval and freeboard measurements in coastal areas can be challenged by land, deformed ice and limited leads. Using a combination of tide gauge for sea level measurements and a coastal GNSS

The Ocean and Land Color Instrument (OLCI) onboard the Copernicus Sentinel-3A satellite is a medium-resolution and multi-spectral push-broom imager acquiring radiance in 21 spectral bands covering from the visible to the far near-infrared. These measurements are primary dedicated to land & ocean color applications, but actually include also reliable information for atmospheric aerosol and surface brightness

Predicting long-term ground-level nitrogen dioxide (NO2) is important globally to support environmental and public health research and to provide information to governments and society for air pollution control policies. The ozone monitoring instrument (OMI), onboard Aura Satellite, detects monthly global tropospheric column amounts (TrCA) of NO2 molecules. However, the relationship between the ground-level

Tropospheric delays (TDs) limit the accurate detection of slow slope motion using interferometric synthetic aperture radar (InSAR), especially in subtropical coastal regions prone to frequent changes in humidity. Although TDs can be estimated through external weather data, their spatiotemporal resolution and data availability are greatly limited, which is not applicable for individual slopes. This

L-band passive microwave remote sensing has evolved over the past decade to estimate soil moisture (SM) and Vegetation Optical Depth (VOD). Novel Radiative Transfer Model (RTM) schemes and model parameterizations are proposed to achieve this goal. In this work, we attempt to characterize errors and uncertainties that propagate from RTMs and their parameters while retrieving SM and VOD from Soil Moisture

Accurate classification of individual tree species is essential for inventorying, managing, and protecting forest resources. Individual tree species classification in subtropical forests remains challenging as existing individual tree segmentation algorithms typically result in over-segmentation in subtropical broadleaf forests, in which tree crowns often have multiple peaks. In this study, we proposed

Ecological resilience is the capacity of a system to maintain function following disturbance. With the frequency and severity of wildfire activity increasing due to warmer and drier global climate conditions, there are increasing reports of declines in ecological resilience and ecosystems at risk of collapse due to post-fire recovery failure. Observational monitoring of post-fire recovery at the landscape

The Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China–France Oceanography Satellite (CFOSAT) can provide wave spectra using its off-nadir beams. Although SWIM shows a reasonable performance for capturing spectral peak, the accuracy of mean wave periods (MWPs) computed directly from the SWIM spectra is not satisfying due to the high noise level of the spectra. SWIM can also

Persistent Scatterer Interferometry (PSI) is a multi-epoch InSAR method for measuring displacements of Earth's surface over time by exploring the interferometric phase of constantly coherent points, named Persistent Scatterer (PS). PSI has shown its superior capability to monitor linear features with long-distance and large-span characteristics. Nevertheless, the interpretation of estimated displacements

PlanetScope CubeSats data with a 3-m resolution, frequent revisits, and global coverage have provided an unprecedented opportunity to advance land surface monitoring over the recent years. Similar to other optical satellites, cloud-induced data missing in PlanetScope satellites substantially hinders its use for broad applications. However, effective gap-filling in PlanetScope image time series remains

Accurate, spatially extensive, and frequent assessments of plant nitrogen (N) enabled by remote sensing allow growers to optimize fertilizer applications and reduce environmental impacts. Standard remote sensing methods for N assessment typically involve the use of chlorophyll-sensitive vegetation indices calculated from multispectral or hyperspectral reflectance data. However, the chlorophyll a + b

Identifying sea ice types in the early stages of development from L-band SAR imagery remains an active research area during the Arctic freeze-up period. We used ScanSAR C- and L-band imagery from RADARSAT-2, ALOS PALSAR and ALOS-2 PALSAR-2, to identify ice types in the North Water Polynya (NOW) and Victoria Strait (VS) region of the Canadian Arctic. We investigated the HH-polarized microwave backscatter

The Visible Infrared Imaging Radiometer Suite (VIIRS) has observed the Earth since 2011 and will continue for several decades. Unfortunately, few high-level land surface products have been produced and publicly released. The numerical inversion of radiative transfer model (RTM) has long been used for the retrieval of land surface and atmospheric variables from satellite data; however, it is computationally

Solar-induced chlorophyll fluorescence (SIF) has been shown to be a novel proxy for terrestrial gross primary production (GPP). A growing number of ground-based automatic SIF observation systems equipped with hemispherical-conical and bi-hemispherical observation configurations have been developed in synergy with EC flux measurements across different ecosystems. However, the difference in the canopy

Knowledge about the forest canopy stratification is of essential importance for forest management and planning. Collecting structural information (e.g. natural regeneration) still depends on cost and labour intensive forest inventories with a coarse spatio-temporal resolution. Remote sensing partly overcomes these limitations and particularly active sensors of type light detection and ranging (LiDAR)

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity

Accurate estimation of global evapotranspiration (ET) is critical to understand the water and energy cycles in the Earth system. Satellite-driven ET algorithms serve as an effective way to estimate the global ET. However, many algorithms have been designed independently of water balance constraints, which potentially limit their ability to estimate ET in water-limited and high interception regions

Submarine groundwater discharge (SGD) represents an important component of the global water cycle. Improved assessment of SGD occurrences provides information to constrain current estimates of total freshwater discharges, which are crucial for evaluation of changes in the global water cycle. This study leverages SGD linkages to patterns in sea surface temperature (SST) and color. Typically, groundwater

Plant area density (PAD in m2·m−3) defines the total one-sided total plant surface area within a given volume. It is a key variable in characterizing exchange processes between the atmosphere and land surface. Terrestrial laser scanning (TLS) provides unprecedented detail of the 3D structure of forest canopies. Yet, signal occlusion and uneven sampling density of the TLS point clouds limit our capacity

This study presented an integrated SVM classification method that investigated the relationship between intrinsic scattering attributes of the surface features and the conductivity characteristics of the soil in the newly proposed two- and three-dimensional classification (2D and 3D) schema to classify the saline landscape. The study was conducted in the Vellore district, Tamil Nadu, which is composed

The feasibility of soil moisture retrieval from C-band Sentinel-1 data has been widely acknowledged, with pre-operational 1-km products currently available at regional and/or continental scale using the long-term (LTCD) or short-term change detection (STCD) methods. Both algorithms share the same assumptions of time-invariant roughness and vegetation, which can be questionable even for a short period

For sustainable food production in the Mekong Delta, local information on irrigation status is essential for allocating water resources efficiently at the community level. ALOS-2 PALSAR-2 L-band SAR can be used to detect submerged and nonsubmerged soil covered by rice plants at a spatial resolution compatible with field observation but a low temporal resolution. In this study, a new multiscale data

Statistically rigorous inferences in the form of confidence intervals for map-based estimates require model-based inferential methods. Model-based mean square errors (MSE) incorporate estimates of both residual variability and sampling variability, of which the latter includes population unit variance estimates and pairwise population unit covariance estimates. Bootstrapping, which can be used with

Monitoring oceanographic parameters is essential for marine engineering construction, coastal safety, marine analysis, and climatic analysis. Traditionally, oceanographic parameters have been monitored using different sensors. With the development of global navigation satellite systems (GNSS), signal-to-noise ratio (SNR) observations have been found to oscillate due to the interference between direct

We propose to derive local sea level variations by using the Signal-to-Noise Ratio (SNR) of the GNSS reflected signals at four GNSS single antenna sites (ILDG, TAR0, FFT2, LYTT) located at different latitudes. For these sites representing various ocean conditions (waves, tides, storm surges, etc…), tides estimates by SNR are highly consistent to tide gauges records as highlighted by tidal harmonic

To better understand the dynamics of human settlements, thorough knowledge of the uncertainty in geospatial built-up surface datasets is critical. While frameworks for localized accuracy assessments of categorical gridded data have been proposed to account for the spatial non-stationarity of classification accuracy, such approaches have not been applied to (binary) built-up land data. Such data differs

L-band brightness temperature (TB) has been shown to provide the best sensitivity to soil moisture (SM) although C- and X-band based products offer a longer time-series from satellite-based measurements. Currently, global coverage SM is routinely produced from spaceborne measurements using all three frequency bands, but despite continued validation efforts of the products, the relative characteristics

Photochemical reflectance index (PRI) is an intriguing avenue for monitoring photosynthetic light use efficiency (LUE), which is a crucial physiological variable and the primary source of uncertainty in gross primary production (GPP) prediction. The correlations between PRI and LUE induced by the energy-dependent xanthophyll cycle are overall convincing at the leaf scale. However, their relationship