Accurate habitat mapping methods are urgently required for the monitoring, conservation, and management of blue carbon ecosystems and their associated services. This study focuses on exposed intertidal seagrass meadows, which play a major role in the functioning of nearshore ecosystems. Using Sentinel-2 (S2) data, we demonstrate that satellite remote sensing can be used to map seagrass percent cover

Global lake evaporation is a critical component of the terrestrial water cycle. Accurate quantification of lake evaporation dynamics is of high importance for understanding lake energy budgets, land-atmosphere interactions, as well as regional water availability. However, the accurate quantification of lake evaporation has been hindered by the complexity involved with addressing the heat storage of

Timely and accurate knowledge about the geospatial distribution of crops at regional to continental scales is crucial for forecasting crop production and estimating crop water use. The United States (US) is one of the leading food-producing countries, but lacks a nationwide high resolution crop-specific land cover map available publicly during the current growing season. The goal of this study was

For the past two decades, quantitative retrievals of aerosol optical depth (AOD) have been made from both geostationary and polar-orbiting satellites, and the results have been widely used in numerous studies. Despite the progress made in improving the accuracy of AOD retrievals, there are still major challenges, especially over land. A notable one for the so-called Dark-Target (DT) algorithms is building

Information about forest stand species distribution is essential for biodiversity modelling, forest disturbances, fire hazard and drought monitoring, biomass and carbon estimation, detection of non-native and invasive species, as well as for planning forest management strategies. High temporal and spectral resolution remote sensing data from the Sentinel-2 mission enables the derivation of accurate

Airborne laser scanning (ALS) is a remote sensing technology known for its applicability in natural resources management. By quantifying the three-dimensional structure of vegetation and underlying terrain using laser technology, ALS has been used extensively for enhancing geospatial knowledge in the fields of forestry and ecology. Structural descriptions of vegetation provide a means of estimating

Changes in glacier facies (glacier zones), such as firn or superimposed ice (SI), are good indicators of glacier response to climate change. They are especially important for fast-warming Svalbard, where only a few glaciers are under glaciological mass balance monitoring. This paper presents a first study of changes of glacier facies extent for three tidewater glaciers located in southern Spitsbergen

This paper assessed the precision of 20-Hz sea level anomaly (SLA) estimates with different sea state bias (SSB) corrections from reprocessed Jason-1/2/3 and Sentinel-3A data over the period of 2002–2019 within 100 km from the entire Australian coast. The altimeter waveforms were retracked by the modified Brown-peaky (MBP) retracker for Jason missions and by the SAMOSA+ retracker for Sentinel-3A. We

Spectrally-based retrieval of bathymetry is challenging in inland/coastal waters due to variations in factors other than water depth across a water body, including bottom type, optically significant constituents, water surface roughness, and others. Optimal band ratio analysis (OBRA) is the most widely used method to deal with these confounding effects to retrieve water depth. OBRA identifies the pair

Land cover mapping in complex environments can be challenging due to their landscape heterogeneity. With the increasing availability of various open-access remotely sensed datasets, more images acquired by different sensors and on different dates tend to be used to improve land cover classification accuracy. Selecting an appropriate feature domain with the best landscape separability is therefore crucial

Land surface temperature (LST) is increasingly needed for studying the functioning of the Earth's surface at local to global scale. Radiative transfer (RT) models that simulate top of atmosphere (TOA) radiance are essential tools to derive accurate LST from thermal infrared (TIR) signals of Earth observation (EO) satellites. DART (Discrete Anisotropic Radiative Transfer) is one of the most accurate

Landsat imagery is an unparalleled freely available data source that allows reconstructing land-cover and land-use change, including urban form. This paper addresses the challenge of using Landsat data, particularly its 30 m spatial resolution, for monitoring three-dimensional urban densification. Unlike conventional convolutional neural networks (CNNs) for scene recognition resulting in resolution

The recent and projected investments across the world on radar satellite missions (e.g., Sentinel-1, SAOCOM, BIOMASS and NISAR) provide a great opportunity for operational radar soil moisture mapping with high spatial and temporal resolution. However, there is no retrieval algorithm that can make complementary use of the multi-frequency data from those missions, due to the large uncertainties in observations

This paper investigates the soil moisture retrievals over Tibetan Plateau using multi-temporal ALOS2-PALSAR2 data acquired in ScanSAR mode, in contrary to the commonly used StripMap SAR imaging mode. Considering the dual-polarimetry with limited observables, the surface roughness parameters such as the RMS height and auto-correlation length are first estimated by optimizing the semi-empirical Oh2004

Over the past four decades, satellite systems and land surface models have been used to estimate global-scale surface soil moisture (SSM). However, in areas such as densely vegetated and irrigated regions, obtaining accurate SSM remains challenging. Before using satellite and model-based SSM estimates over these areas, we should understand the accuracy and error characteristics of various SSM products

Accurate estimation of cropping intensity (CI), an indicator of food production, is well aligned with the ongoing efforts to achieve sustainable development goals (SDGs) under diminishing natural resources. The advancement in satellite remote sensing provides unprecedented opportunities for capturing CI information in a spatially continuous manner. However, challenges remain due to the lack of generalizable

Evaluating the efficacy of air pollution control policies is an essential part of the decision-making process to develop new policies and improve existing measures. Since 2005, Fujian Province of Mainland China and Taiwan across the Taiwan Strait have both implemented aggressive air pollution control policies designed based on different principles, but a comprehensive evaluation of these control policies

The Central Valley in California is characterized by a semi-arid climate prone to droughts, a variable surface water supply, and immense agricultural areas dependent on groundwater irrigation. The groundwater is stored in a complex aquifer system composed of alternating layers of coarse sediments and fine-grained sediments acting as confining materials. Groundwater fluctuations are coupled with both

Tropical forests are characterized by large carbon stocks and high biodiversity, but they are increasingly threatened by human activities. Since structure strongly influences the functioning and resilience of forest communities and ecosystems, it is important to quantify it at fine spatial scales. Here, we propose a new simulation-based approach, the “Canopy Constructor”, with which we quantified forest

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and

Land surface temperature (LST) is a key diagnostic indicator of agricultural water use and crop stress. LST data retrieved from thermal infrared (TIR) band imagery, however, tend to have a coarser spatial resolution (e.g., 100 m for Landsat 8) than surface reflectance (SR) data collected from shortwave bands on the same instrument (e.g., 30 m for Landsat). Spatial sharpening of LST data using the higher

Soil salinity is one of the crucial factors which undermines agricultural production in the semi-arid region. The study was attempted for the Vellore district, one of the worst-hit semi-regions of Tamil Nadu by salinization. The Sentinel-1 data product of C-band frequency (5.36 GHz) was instrumental in the development of the model. In the present research, a semi-empirical dielectric model was proposed

This study provides the first report of reflectance spectra of coral-spawn slicks and their detection using optical satellite data. The reflectance spectra show that coral-spawn slicks can be discriminated from other sea-surface features such as wave foam and floating Sargassum. Analysis of Planet Dove and Sentinel-2B imagery allowed successful detection of coral-spawn slicks at Ishigaki Island, Okinawa

NASA's Orbiting Carbon Observatory-3 (OCO-3) was installed on the International Space Station (ISS) on 10 May 2019. OCO-3 combines the flight spare spectrometer from the Orbiting Carbon Observatory-2 (OCO-2) mission, which has been in operation since 2014, with a new Pointing Mirror Assembly (PMA) that facilitates observations of non-nadir targets from the nadir-oriented ISS platform. The PMA is a

We construct and present the first baseline, time series evolution of L-band SAR microwave backscatter (σ0HH) for landfast Arctic first-year (FYI) and multi-year (MYI) sea ice from ALOS PALSAR. We compare the winter to freeze-up seasonal L-band σ0HH signatures with C-band RADARSAT-2 SAR imagery and Ku-band QuikSCAT scatterometer data. We also explored the utility of L-band σ0HH to detect FYI and MYI

The point spread function (PSF) effect is ubiquitous in remote sensing images and imposes a fundamental uncertainty on subpixel mapping (SPM). The crucial PSF effect has been neglected in existing SPM methods. This paper proposes a general model to reduce the PSF effect in SPM. The model is applicable to any SPM methods treating spectral unmixing as pre-processing. To demonstrate the advantages of

Landslides represent one of the most damaging natural hazards and often lead to unexpected casualties and property damage. They also continually modify our natural environment and landscapes. Knowledge of landslide systems is largely restricted by the stochastic nature, subjective interpretation and infrequent or spatially sparse surveying of landslides. Characterized by persistent daily movements

We have analyzed the effect of aerosols on the retrieval of the dry air mixing ratio of carbon dioxide (XCO2) in the Earth's atmosphere from instruments like OCO-2 and GOSAT. High-fidelity simulations of multi-angle spectropolarimetric observations in the O2 A-band and the weak and strong CO2 bands are used to evaluate the information contained in different measurement subsets/synergies for the retrieval

Wetland is a very fragile ecosystem that provides important services to a large variety of flora and fauna species, as well as for humans. As wetland depends on water availability, protecting this important ecosystem requires careful hydrological monitoring. The Sentinel-1 mission, featuring a wide swath coverage, high temporal observations and open data policy, provides unprecedented opportunity for

Radar data at C-band has shown great potential for the monitoring of soil and canopy hydric conditions of wheat crops. In this study, the C-band Sentinel-1 time series including the backscattering coefficients σ0 at VV and VH polarization, the polarization ratio (PR) and the interferometric coherence ρ are first analyzed with the support of experimental data gathered on three plots of irrigated winter

Passive microwave datasets have been used to quantify the extent and duration of surface melt in Greenland and Antarctica from 1978 on with daily and near-daily intervals. These results have important implications for climate analysis and may help evaluate ice shelf stability. However, the accuracy of passive microwave methods used to detect melt is difficult to quantify, especially on the Antarctic

Aquatic land cover represents the land cover type that is significantly influenced by the presence of water over an extensive part of a year. Monitoring global aquatic land cover types plays an essential role in preserving aquatic ecosystems and maintaining the ecosystem service they provide for humans, while at the same time their accurate and consistent monitoring for multiple purposes (e.g. climate

Satellite remote sensing provides unprecedented information on near-surface soil moisture at a global scale, enabling a wide range of studies such as drought monitoring and forecasting. Data Assimilation (DA) has been recognized as an effective means to incorporate such observations into hydrologic models to better predict and forecast hydroclimatic variables. In this study, we use a recently developed

Cloud cover is a common and inevitable phenomenon that often hinders the usability of optical remote sensing (RS) image data and further interferes with continuous cartography based on RS image interpretation. In the literature, the off-the-shelf cloud detection methods either require various hand-crafted features or utilize data-driven features using deep networks. Overall, deep networks achieve much

Satellite remote sensing offers an effective remedy to challenges in ground-based and aerial mapping that have previously impeded quantitative assessments of global seagrass extent. Commercial satellite platforms offer fine spatial resolution, an important consideration in patchy seagrass ecosystems. Currently, no consistent protocol exists for image processing of commercial data, limiting reproducibility

Rock glaciers are an important component of the cryosphere and are one of the most visible manifestations of permafrost. While the significance of rock glacier contribution to streamflow remains uncertain, the contribution is likely to be important for certain parts of the world. High-resolution remote sensing data has permitted the creation of rock glacier inventories for large regions. However, due

Over the last decade, an increase of gastrointestinal illness due to Vibrio parahaemolyticus in the consumption of raw shellfish has been reported in multiple regions around the United States. Studies mainly attribute this increase to rising sea surface temperatures and prolonged warm seasons in the mid-latitudes. Historically, temperature has been the main environmental determinant used to predict

Monitoring invasive species distribution and prevalence is important, but direct field-based assessment is often impractical. In this paper, we introduce and validate a cost-effective method for mapping understory invasive plant species. We utilized Landsat imagery, spectral mixture analysis (SMA) and a maximum entropy (Maxent) modeling framework to map the spatial extent of Mikania micrantha in Chitwan

The ability of high-resolution synthetic aperture radar (SAR) to detect marine atmospheric boundary layer (MABL) roll-induced roughness modulation of the sea surface wave field is well known. This study presents SAR measurements of MABL rolls using global coverage data collected by the European Space Agency's C-band Sentinel-1A satellite in 2016–2017. An automated classifier is used to identify likely

Unmanned aerial vehicle (UAV)-borne hyperspectral systems can acquire hyperspectral imagery with a high spatial resolution (which we refer to here as H2 imagery). As a result of the low operating cost, high flexibility, and the ability to achieve real-time data acquisition, UAV-borne hyperspectral systems have become an important data source for remote sensing based agricultural monitoring. However

Polar-orbiting ocean color satellites such as Landsat-8, Suomi National Polar-orbiting Partnership (SNPP), and Sentinel-3 offer valuable image data for the derivation of water bathymetry in optically shallow environments. Because of the multi-spectral limitation, however, it is challenging to derive bathymetry over global shallow waters without reliable mechanistic algorithms. In this contribution

Accurate bathymetric data is essential for marine, coastal ecosystems, and related studies. In the past decades, a lot of studies were investigated to obtain bathymetric data in shallow waters using satellite remotely sensed data. Satellite multispectral imagery has been widely used to estimate shallow water depths based on empirical models and physics-based models. However, the in-situ water depth

The urban heat island (UHI) is a major topic in the study of urban climates. However, comprehensive research on the atmospheric UHI (UHIAtm), surface UHI (UHISurf), and subsurface UHI (UHISub) simultaneously has yet not been reported. Using the MODIS land surface temperature and atmospheric profile data during the 2010–2016 period, we investigated the diurnal, seasonal, and vertical variations of UHIAtm

Biochemical traits in forest vegetation are key indicators of leaf physiological processes, specifically photosynthetic and other photochemical light pathways, and are critical to the quantification of the terrestrial carbon cycle. Advances in remote sensing sensors and platforms are allowing multi-dimensional and continuous-spatial information to be acquired in a fast and non-destructive way to quantify

The satellite remote sensing reflectance (Rrs(λ)) at two short blue bands (410 or 412 nm and 443 nm) are prone to large uncertainties in coastal and inland waters, prohibiting algorithms from generating reliable ocean color products associated with these bands. In this study, we developed an algorithm to estimate Rrs(41×) and Rrs(443) when the satellite Rrs(λ) in blue bands suffer from large uncertainties

We analysed 7188 Sentinel-1A Synthetic Aperture Radar (SAR) images acquired in a 3-year period, between October 2014 and September 2017, in the Western Mediterranean Sea and found imprints of about 14,300 oceanic eddies with diameters ranging from 0.4 km to 160.1 km. Those eddies manifest on the SAR imagery either through the accumulation of surfactants or through wave-current interaction, and considering

Forest canopies act as intermediaries in radiation energy exchange between the atmosphere and the snow surface. The size, location and distribution of forest discontinuities are important controls on forest shortwave radiation transmission and subsequent snow surface shading and radiation energy exchange between the atmosphere and the canopy, but challenges arise when accounting for these vegetation

Numerous algorithms are used in remote sensing to detect changes in vegetation. Majority of them require several tunable parameters or can only detect abrupt forest disturbances. The aim of this study was to develop a new threshold- and trend-based vegetation change monitoring algorithm (TVCMA) that can detect abrupt and gradual changes in vegetation within forested and non-forested areas. To test

Advances in differential interferometric synthetic aperture radar (DInSAR) processing algorithms, such as the Intermittent Small Baseline Subset (ISBAS), and increased data availability from SAR systems, such as Sentinel-1, provide the opportunity to increase the spatial and temporal density of ground deformation measurements. Such measurements, when combined with modelling, have the potential to make

In open forest canopies, such as in boreal forests, forest floor can contribute significantly to the observed top of canopy reflectance. In order to retrieve the biophysical properties of the tree layer, correcting for forest floor is essential. Traditionally, the algorithms for retrieval of forest floor reflectance depend on tree layer information such as leaf area index, canopy cover, and site fertility

Near real-time monitoring of forest disturbance is a critical tool for combating illegal logging. The only feasible data sources for near real-time monitoring over large area are remote sensing data, and historically the only sensors with repeat times sufficient for near-real time monitoring are from coarse-resolution sensors such as MODIS. The MODIS sensors onboard the Terra and Aqua satellites have

Deriving inherent optical properties (IOPs) from multispectral imagery of shallow water environments using physics-based inversion models require prior knowledge of the spectral reflectance of the bottom substrate. The use of an incorrect bottom reflectance adversely affects the IOPs and, in part, the depth derived from inversion models. To date, an operational approach that determines the bottom reflectance

Imbalance of residential environments in cities (e.g., slums and wealthy districts) causes serious social inequality, negatively impacting livable city development and attracting worldwide attentions. Previous studies on residential environmental quality (REQ) mainly focused on general evaluations at city level, while ignored the spatial heterogeneity of REQ inside cities and failed to survey REQ at

Mapping and monitoring landslides in remote areas with steep and mountainous terrain is logistically challenging, expensive, and time consuming. Yet, in order to mitigate hazards and prevent loss of life in these areas, and to better understand landslide processes, high-resolution measurements of landslide activity are necessary. Satellite-based synthetic aperture radar interferometry (InSAR) provides

With a revisit time of 1 h, spatial resolution of 500 m, and high radiometric sensitivity, the Geostationary Ocean Color Imager (GOCI) is widely used to monitor diurnal dynamics of oceanic phenomena. However, atmospheric correction (AC) of GOCI data with high solar zenith angle (>70°) is still a challenge for traditional algorithms. Here, we propose a novel neural network (NN) AC algorithm for GOCI