Leaf chlorophyll, as a key factor for carbon circulation in the ecosystem, is significant for the photosynthetic productivity estimation and crop growth monitoring in agricultural management. Hyperspectral remote sensing (RS) provides feasible solutions for obtaining crop leaf chlorophyll content (LCC) by the advantages of its repeated and high throughput observations. However, the data redundancy

Marine heatwaves (MHWs) have significant ecological and economic impact at local and regional scales. Consequently, there is a pressing need to map the fine-scale temporal and spatial patterns of MHWs, for both historical and near real-time events. Satellite remote sensing of Sea Surface Temperature (SST) provides fundamental data for the mapping of MHWs. This study used high-resolution Himawari-8

Landscape fire is a widespread, somewhat unpredictable phenomena that plays an important part in Earth's biogeochemical cycling. In many biomes worldwide fire also provides multiple ecological benefits, but in certain circumstances can also pose a risk to life and infrastructure, lead to net increases in atmospheric greenhouse gas concentrations, and to degradation in air quality and consequently human

An algorithm for retrieving nighttime aerosol optical depth (AOD) from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) observations of reflected moonlight is presented for rural areas during the western U.S. fire seasons. The algorithm uses the UNified and Linearized Vector Radiative Transfer Model (UNL-VRTM) with newly developed capabilities for considering lunar illuminations

Over the past decade, western North America glaciers experienced strong mass loss. Regional mass loss during the ablation season is influenced by air temperature, but the importance of other factors such as changes in surface albedo remains uncertain. We examine changes in surface albedo for 17 glaciated regions of western North America as documented in a 20-year record (2000 to 2019) of MODIS daily

Precise information on tree species composition is critical for forest management and conservation, but mapping tree species with satellite data over large areas is still a challenge. Since 2017, Sentinel-2A/B provide multi-spectral time series with global coverage at an unprecedented spatial and temporal resolution. This is a new opportunity for mapping tree species over large areas that has not yet

Surface soil moisture and vegetation optical depth (VOD), as an indicator of vegetation wet biomass, from passive microwave remote sensing have been increasingly applied in global ecology and climate research. Both soil moisture and VOD are retrieved from satellite brightness temperature measurements assuming a zeroth order radiative transfer model, commonly known as the tau-omega model. In this model

Rivers are among the most dynamic components in Earth's terrestrial water cycle and provide critical ecosystem services. Yet, the spatiotemporal variability of river surface extents remains largely unquantified at the global scale. Satellite remote sensing provides a promising alternative to in-situ observations, which can enable a more comprehensive survey and systematic analysis of global rivers

Canopy radiative transfer (RT) modeling is critical for the quantitative retrieval of vegetation biophysical parameters and has been under intensive research over the decades. RT models of discontinuous canopies, such as three-dimensional (3D) RT models, posed challenges for the early one-dimensional (1D) hypothesis. Although 3D RT models have higher accuracy, theoretically, they suffer from two problems:

Satellite synthetic aperture radar (SAR) signals are affected by the Earth's ionosphere when the signals travel through the ionosphere. We first analyze the impact of ionospheric variation on the coseismic deformation results derived from interferometric SAR (InSAR) for the 2010 Maule, Chile, earthquake. We then jointly invert leveling, GPS and InSAR data for the coseismic slip distribution. The bias

In GPR profiles, ice is usually imaged as a mostly electromagnetic transparent facies. However, diffraction events, as well as internal layering, can be also observed. In some cases, the bedrock below glaciers is masked by dense diffractions usually interpreted as the effect of liquid water pockets inside the so-called warm ice. However, the actual physical meaning of such GPR facies is not always

Reindeer lichens (Cladonia spp.) are an essential food source for caribou especially during winter. They can also be a valuable indicator for ecosystem health and climate change. Inventory of lichen abundance at regional scales is required to assess availability within caribou ranges, and assess potential declines from natural and anthropogenic disturbances. Previous studies have mapped lichen cover

Water fulfils key roles in maintaining a plant's biological activity. Water shortage induces stomatal closure, causing a reduction in photosynthesis and transpiration rates. Sun-induced chlorophyll fluorescence (SIF) emission is sensitive to subtle, stress-induced variations in non-photochemical quenching and in photosynthetic electron transport, caused by e.g., a fluctuation in the water availability

Although satellite-based light use efficiency (LUE) model is widely used to estimate gross primary production (GPP) of terrestrial ecosystems, microwave observations have not been integrated into LUE models. This study developed a new LUE model coupled with a passive microwave vegetation index (Emissivity Difference Vegetation Index, EDVI) for daily GPP estimation. Normalized EDVI (nEDVI), an indicator

The fine spatial resolution of the ICESat-2 (IS2) satellite altimeter allows monitoring the evolution of sea ice thickness with detailed dynamic information (e.g. ridges and leads). In this study, we first assess the ability of IS2 to estimate thermodynamic ice growth and dynamic thickening during the ice-growing season in the central Arctic Ocean. As an indicator of the thermodynamic ice growth, we

We propose a signal deconvolution procedure for imaging spectrometer data, where a measured point spread function (PSF) is deconvolved itself before being used for deconvolution of the signal. We evaluate the effectiveness of our procedure for improvement of the spatio-spectral signal, as well as our target application, i.e. estimation of sun-induced fluorescence (SIF). Imaging spectrometers are well

Carbon dioxide (CO2) emitted from thermal power plants accounts for approximately 40% of energy-related CO2 emissions in the world. CO2 emission datasets for thermal power plants have large uncertainties, especially those from developing countries. We performed CO2 column measurements with solar-viewing portable Fourier transform spectrometers and wind measurements with a Doppler lidar at sites approximately

There are several long-term statistical researches using the Molchan diagram (MD) to prove the relation between thermal infrared (TIR) anomalies and earthquakes in different regions, however, these studies are flawed: 1) the original MD is based on the spatially uniform Poisson model, but it will offer wrong evaluations for inhomogenous systems with uneven spatial-temporal distribution of earthquakes;

One great advantage of optical hyperspectral remote sensing from unmanned aerial systems (UAS) compared to satellite missions is the possibility to fly and collect data below clouds. The most typical scenario is flying below intermittent clouds and under turbulent conditions, which causes tilting of the platform. This study aims to advance hyperspectral imaging from UAS in most weather conditions by

Satellite product uncertainty estimates are critical for the further development and evaluation of remote sensing algorithms, as well as for the user community (e.g., modelers, climate scientists, and decision-makers). Optical remote sensing of water quality is affected by significant uncertainties stemming from correction for atmospheric effects as well as a lack of algorithms that can be universally

Detailed parcel-level crop type mapping for the whole European Union (EU) is necessary for the evaluation of agricultural policies. The Copernicus program, and Sentinel-1 (S1) in particular, offers the opportunity to monitor agricultural land at a continental scale and in a timely manner. However, so far the potential of S1 has not been explored at such a scale. Capitalizing on the unique LUCAS 2018

As the spatial and temporal resolution of remotely sensed imagery has improved over the last four decades, algorithms for monitoring and mapping seasonal changes in surface properties have evolved rapidly. Most recently, the availability of daily PlanetScope imagery has created new opportunities for monitoring the land surface phenology (LSP) of terrestrial ecosystems at high spatial resolution. However

Surface soil moisture is estimated by inverting physical scattering models for low- crops using L-band airborne SAR data over the incidence angle range from 30 to 50°. The forward simulation is accurate with 1.7, 1.8, and 2.3 dB rmse for grass, wheat (including oat and forage), and soybean respectively assessed over 38 fields and during the full growth period for soybean. Dominant scattering mechanisms

Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state

Global change analyses are facilitated by the growing number of remote-sensing datasets that have both broad spatial extent and repeated observations over decades. These datasets provide unprecedented power to detect patterns of time trends involving information from all pixels on a map. However, rigorously testing for time trends requires a solid statistical foundation to identify underlying patterns

Land surface temperature (LST) is a crucial parameter for hydrology, climate monitoring, and ecological and environmental research. LST products from thermal infrared (TIR) satellite data have been widely used for that. However, TIR information cannot provide LST data under cloudy-sky conditions. All-sky LST can be estimated from microwave measurements, but their coarse spatial resolution, narrow swaths

Despite its critical importance to carbon storage modeling, forest vertical structure remains poorly characterized over large areas. Canopy height estimates from current satellite missions such as ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) offer promise to close this knowledge gap, but their validation is critically important to inform their measurement uncertainties and scientific utility

The lack of proper understanding of multi-layer soil moisture (SM) profile (signals) remains a persistent challenge in sustainable agricultural water management and food security, especially during drought conditions. We develop a machine-learning algorithm using the concept of learning from patterns to estimate the multi-layer SM information in ungauged locations firmly based on local knowledge of

Exposure to fine particulate matter (PM2.5) has been linked to a substantial disease burden globally, yet little has been done to estimate the population health risks of PM2.5 in South Africa due to the lack of high-resolution PM2.5 exposure estimates. We developed a random forest model to estimate daily PM2.5 concentrations at 1 km2 resolution in and around industrialized Gauteng Province, South Africa

Vitality loss of trees caused by extreme weather conditions, drought stress or insect infestations, are expected to increase with ongoing climate change. The detection of vitality loss at an early stage is thus of vital importance for forestry and forest management to minimize ecological and economical damage. Remote sensing instruments are able to detect changes over large areas down to the level

Estimating methane (CH4) emission rates using quantitative CH4 retrievals from the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) requires the use of wind speeds. Model wind speeds have limited temporal and spatial resolution, meteorological station wind data are of variable quality and are often not available near observed plumes, and the use of ultrasonic anemometers co-located

Retrieval of the phycocyanin concentration (PC), a characteristic pigment of, and proxy for, cyanobacteria biomass, from hyperspectral satellite remote sensing measurements is challenging due to uncertainties in the remote sensing reflectance (∆Rrs) resulting from atmospheric correction and instrument radiometric noise. Although several individual algorithms have been proven to capture local variations

Over the past decades, solar panels have been widely used to harvest solar energy owing to the decreased cost of silicon-based photovoltaic (PV) modules, and therefore it is essential to remotely map and monitor the presence of solar PV modules. Many studies have explored on PV module detection based on color aerial photography and manual photo interpretation. Imaging spectroscopy data are capable

The Monitoring Nitrous Oxide Sources (MIN2OS) satellite project aims at monitoring global-scale nitrous oxide (N2O) sources by retrieving N2O surface fluxes from the inversion of space-borne N2O measurements that are sensitive to the lowermost atmospheric layers under favorable conditions. MIN2OS will provide emission estimates of N2O at a horizontal resolution of 1° × 1° on the global scale and 10 × 10 km2

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) is unique in its ability to perform profiling measurements of aerosol and cloud layers globally. Detecting the layer boundaries of aerosols and clouds is a crucial step in CALIPSO data retrieval. The CALIPSO team uses the selective iterated boundary location (SIBYL) algorithm based on threshold arrays to find aerosol and

The accuracy of earthquake catalogs limits the reliability of earthquake hazard assessment and the comprehensive understanding of earthquake mechanisms. Current seismic catalogs are based on the inversion of seismic wave data. The accuracy of their source parameters, which reflect the quantity and layout of seismic stations, and the crustal velocity model used, are often highly uncertain. The open

A method for rectifying thermograms in perspective captured at human height is proposed. It applies to the image pixel-by-pixel corrections that account for the surface emissivity, the reflected longwave infrared radiation flux, and the radiation emitted and attenuated by the atmosphere. The results are validated in two steps: first by comparison with contact temperature devices and then by comparison

Annual global land cover maps (GLC) are being provided by several operational monitoring efforts. However, map validation is lagging, in the sense that the annual land cover maps are often not validated. Concurrently, users such as the climate and land management community require information on the temporal consistency of multi-date GLC maps and stability in their accuracy. In this study, we propose

Research has demonstrated the utility of digital aerial photogrammetry (DAP) for area-based predictions of forest inventory attributes. To date, studies have used DAP data acquired with a range of spatial resolutions and image overlaps. The systematic benchmarking of DAP acquisition parameters remains an outstanding research and operational gap for forest applications. While the impact of along-track

In light of the ongoing global biodiversity crisis, the urge to monitor and map terrestrial plant biodiversity at large spatial extents has spurred research on adequate quantitative methods. The use of spectral diversity metrics from different remote sensing platforms has emerged as a promising tool for such biodiversity assessments. Satellite remote sensing presents the next frontier for implementation

The wind direction dependence of the fully polarimetric ocean emissivity at L-band is studied using a semi-theoretical approach. The model, which is tuned and validated against Aquarius and Soil Moisture Active-Passive (SMAP) mission observations, incorporates the two-scale polarimetric ocean emission model, an improved directional wave spectrum, the Anguelova and Gaiser, 2013 (AG13) foam emissivity

Plant water use is difficult to monitor and predict in complex terrain. NASA's ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides new data for understanding hydrologic cycling in these forested mountain areas. Evaluation of ECOSTRESS evapotranspiration (ET) has relied primarily on eddy flux towers, but most flux towers are located in flat terrain, sampling relatively

The prescription of surface emissivity (ε) strongly controls satellite-derived estimates of land surface temperature (LST). This is particularly important for studying surface urban heat islands (SUHI) since built-up and natural landscapes are known to have distinct ε values. Given the small signal associated with the SUHI compared to LST, accurately prescribing urban and rural ε would improve our

Wildfires have become one of the biggest natural hazards for environments worldwide. The effects of wildfires are heterogeneous, meaning that the magnitude of their effects depends on many factors such as geographical region, climate and land cover/vegetation type. Yet, which areas are more affected by these events remains unclear. Here we present a novel application of the Generalized Synthetic Control

Monitoring the spatiotemporal dynamics of surface water from remote sensing imagery is essential for understanding water's impact on the global ecosystem and climate change. There is often a tradeoff between the spatial and temporal resolutions of imagery acquired from current satellite sensors and as such various spatiotemporal image fusion methods have been explored to circumvent the challenges this

Soil moisture (SM) retrieval in agricultural regions during the growing seasons is particularly challenging due to high spatial variability and dynamic vegetation conditions. The retrievals have been problematic even when the passive signatures at different spatial scales match well since they depend upon the accuracy of vegetation information such as the vegetation water content (VWC). The VWC used

Landslides are common geohazards associated with natural drivers such as precipitation, land degradation, toe erosion by rivers and wave attack, and ground shaking. On the other hand, human alterations such as inundation by water impoundment or rapid drawdown may also destabilize the surrounding slopes. The Guobu slope is an ancient rockslide on the banks of the Laxiwa hydropower station reservoir

Indonesia recently implemented a novel, technology-driven approach for conducting agricultural production surveys, which involves monthly observations at many thousands of strategic locations and automated data logging via a cellular phone application. Data from these comprehensive field surveys offer immense value for advancing remote sensing technology to map crop production across Indonesia, particularly

The detection and repairment of methane leaks from fossil fuel production activities have been identified as a key climate change mitigation strategy. Several types of optical satellite sensors have recently shown potential to support this task. Spaceborne imaging spectrometers measuring in the 400–2500 nm spectral range belong to this group. These instruments measure the solar radiation reflected

A reliable accuracy is essential for the application of land surface temperature (LST) products. Current satellite retrieved LSTs are mainly validated over a few homogeneous sites. However, most of the existing ground sites are located in inhomogeneous areas: thus, their spatial representativeness on satellite pixel scales is unknown. In this situation, how to evaluate the spatial representativeness

Sun-induced chlorophyll fluorescence (SIF) from spaceborne sensors is a promising tool for global carbon cycle monitoring, but its application is constrained by insufficient understanding of the drivers underlying diurnal SIF dynamics. SIF measurements from ground-based towers can reveal diurnal SIF dynamics across biomes and environmental conditions; however, meaningful interpretation of diurnal variations

Full waveform (FW) LiDAR systems have proven their effectiveness to map forest biophysical variables in the last two decades, owing to their ability of measuring, with high accuracy, forest vertical structures. The Global Ecosystem Dynamics Investigation (GEDI) system on board the International Space Station (ISS) is the latest FW spaceborne LiDAR instrument for the continuous observation of Earth's

Medium resolution satellite-derived fractional cover estimates of bare soil (fBS), photosynthetic vegetation (fPV), and non-photosynthetic vegetation (fNPV) provide a powerful means to study arid ecosystem dynamics. This paper employed remote sensing estimates of fPV and fNPV from five case study sites from Australia's vegetated dunefields to observe (a) vegetation growth response to rainfall ‘pulses’

Current estimates of forest degradation are associated with large uncertainties. However, recent advancements in the availability of remote sensing data (e.g., the free data policies of the Landsat and Sentinel Programs) and cloud computing platforms (e.g., Google Earth Engine (GEE)) provide new opportunities for monitoring forest degradation. Several recent studies focus on monitoring forest degradation