Methane is one of the most important anthropogenic greenhouse gases with a significant impact on the Earth's radiation budget and tropospheric background ozone. Despite a well-constrained global budget, quantification of local and regional methane emissions has proven challenging. Recent advancements in airborne remote sensing instruments such as from the next-generation Airborne Visible/Infrared Imaging

L-band passive microwave remote sensing is currently considered a robust technique for global monitoring of soil moisture. However, soil roughness complicates the relationship between brightness temperature and soil moisture, with current soil moisture retrieval algorithms typically assuming a constant roughness parameter globally, leading to a potential degradation in retrieval accuracy. This current

The increased variety and availability of remotely sensed data from satellite and airborne platforms are expected to enhance data fusion approaches aimed at characterizing wildlife habitat. We investigated multisensor machine learning (ML) models to estimate desert grassland habitat suitability for a critically endangered species, the mask bobwhite quail (Colinus virginianus ridgewayi). Contemporary

Digital elevation models (DEMs) contain some of the most important data for providing terrain information and supporting environmental analyses. However, the applications of DEMs are significantly limited by data voids, which are commonly found in regions with rugged terrain. We propose a novel deep learning-based strategy called a topographic knowledge-constrained conditional generative adversarial

Research of PM2.5 chronic health effects requires knowledge of large-scale and long-term exposure that is not supported by newly established monitoring networks due to their sparse spatial coverage and lack of historical measurements. Estimating PM2.5 using satellite-derived aerosol optical depth (AOD) can be used to fill the data gap left by the ground monitors and extend the PM2.5 data coverage to

Accurate estimation of leaf nitrogen concentration (LNC) is critical to characterize ecosystem and plant physiological processes for example in carbon fixation. Remote sensing can capture LNC, while interrelated traits and spectral diversity across plant species prevent development of transferable LNC assessment models based on leaf reflectance. Here, we developed a new transfer learning method by

The current study evaluates consistency among three Normalized Difference Vegetation Index (NDVI) datasets, namely GIMMS, MODIS and SPOT, to characterize alpine vegetation dynamics (greening and browning) across High Mountain Asia (HMA) in 2001–2015. The utility of these datasets is explored to evaluate the vegetation's variability at different spatial-temporal scales and, elevation, and to compare

In recent years, the growing availability of global satellite-derived burned area (BA) products has led to the development of methods and protocols to rigorously estimate their accuracy metrics. These protocols are based on design-based inference and provide unbiased estimators of various dimensions of accuracy. Current procedures consider the spatial and temporal dimension when obtaining the independent

We report a new version and an empirical evaluation of a forest reflectance model based on photon recollision probability (p). For the first time, a p-based approach to modeling forest reflectance was tested in a wide range of differently structured forests from different biomes. To parameterize the model, we measured forest canopy structure and spectral characteristics for 50 forest plots in four

Spatially explicit knowledge on grassland extent and management is critical to understand and monitor the impact of grassland use intensity on ecosystem services and biodiversity. While regional studies allow detailed insights into land use and ecosystem service interactions, information on a national scale can aid biodiversity assessments. However, for most European countries this information is not

Urbanization is the second largest mega-trend right after climate change. Accurate measurements of urban morphological and demographic figures are at the core of many international endeavors to address issues of urbanization, such as the United Nations’ call for “Sustainable Cities and Communities”. In many countries – particularly developing countries –, however, this database does not yet exist.

Satellite radar altimetry is widely used to measure glacier and ice sheet elevation changes, but can suffer from uncertainties related to geolocation and signal penetration. The unique capabilities of ESA's CryoSat-2 allow for accurate geolocation but impacts from signal penetration persist. This study uses surface elevations from Global Navigation Satellite System and airborne laser transects over

Area estimates of land cover and land cover change are often based on reference class labels determined by analysts interpreting satellite imagery and aerial photography. Different interpreters may assign different reference class labels to the same sample unit. This interpreter variability is typically not accounted for in variance estimators applied to area estimates of land cover. A simple measurement

Spartina alterniflora is an aggressive invasive plant spreading along the coastal China, spanning a latitudinal range of 20°N - 39°N, and its invasion resulted in dramatic decline in both native plant diversity and ecosystem functioning. Phenology of S. alterniflora saltmarshes is a critical feature to elucidate the invasion dynamics over geographical regions but has not been well understood yet. In

GNSS Reflectometry (GNSS-R) is a novel remote sensing technique for the monitoring of geophysical parameters using reflected GNSS signals from the Earth's surface. Ocean wind speed monitoring is the main objective of the recently launched Cyclone GNSS (CyGNSS), a GNSS-R constellation of eight microsatellites, launched in late 2016. In this study, the capability of deep learning, especially, for an

Tidal wetlands, the global hotspots of biodiversity and carbon stocks, are currently experiencing widespread modifications in their composition due to human disturbances and changing climate. Accurate mapping of tidal wetland composition is crucial and urgently required for the conservation and management of coastal ecosystem, as well as for maximizing their associated services. However, remote sensing

Deriving burn severity from multispectral satellite data is a widely adopted approach to infer the degree of environmental change caused by fire. Burn severity maps obtained by thresholding bi-temporal indices based on pre- and post-fire Normalized Burn Ratio (NBR) can vary substantially depending on temporal constraints such as matched acquisition and optimal seasonal timing. Satisfying temporal requirements

Soil moisture controls the land surface water and energy budget and plays a crucial role in land surface processes. Based on certain mathematical rules, data assimilation can merge satellite observations and land surface models, and produce spatiotemporally continuous profile soil moisture. The two mainstream assimilation algorithms (variational-based and sequential-based) both need model error and

Soybean is among the most important crops for food and feed production worldwide. Sustainable and local production in regions with marginal climates requires cold-adapted varieties that create high yield and protein content in a short vegetation period. Drone-based high-throughput field phenotyping methods allow monitoring the success and the developmental speed of genotypes in such target environments

Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Assessments of surface urban heat island (UHI) usually focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain period. However, the mechanisms and complex interactions in landscape dynamics and land

Water-leaving albedo (αw), defined as the ratio of water-leaving irradiance to downwelling irradiance just above the surface, is a major component of ocean surface albedo (α) but has long been ignored or underrepresented. A semi-analytical scheme based on inherent optical properties (IOPs), termed IOPs-αw, is proposed in this study to estimate spectral αw(λ) from ocean color measurements. Evaluations

Fresh water stored by on-farm reservoirs (OFRs) is an important component of surface hydrology and is critical for meeting global irrigation needs. Farmers use OFRs to store water during the wet season and for crop irrigation during the dry season, yet their seasonal and inter-annual variability and downstream impacts are not quantified. Therefore, OFRs' sub-weekly surface area changes are critical

Sinkhole activity in Florida is a major hazard for people and property. Its increasing frequency is often related to an accelerated use of ground-water and land resources in the region. In this work, we use a combined approach of radar interferometry and spatial clustering analysis over three selected sites in West-Central Florida to identify localized deformation that may be caused by sinkhole activity

The freshwater scarcity and sustainability of overexploited aquifers have been recognized as a big threat to global water security for human development. Consequently, much research has focused in the past on negative consequences of groundwater abstraction, but somewhat less has been documented about the impacts of adequate management practices to address water shortages. Here, using an integrated

Field spectroscopy is a powerful tool for monitoring leaf functional traits in situ, but it remains unclear whether universal statistical models can be developed to predict traits from spectral information, or whether re-calibration is necessary as conditions vary. In particular, multiple leaf traits vary simultaneously across growing seasons, and it is an open question whether these temporal changes

It is important to understand temporal and spatial variations in the structure and photosynthetic capacity of tropical rainforests in a world of changing climate, increased disturbances and human appropriation. The equatorial rainforests of Central Africa are the second largest and least disturbed of the biodiversly-rich and highly productive rainforests on Earth. Currently, there is a dearth of knowledge

Topographic laser scanning is a remote sensing method to create detailed 3D point cloud representations of the Earth's surface. Since data acquisition is expensive, simulations can complement real data given certain premises are met: (i) models of 3D scene and scanner are available and (ii) modelling of the beam-scene interaction is simplified to a computationally feasible while physically realistic

Ozone (O3) is an important trace and greenhouse gas in the atmosphere, posing a threat to the ecological environment and human health at the ground level. Large-scale and long-term studies of O3 pollution in China are few due to highly limited direct ground and satellite measurements. This study offers a new perspective to estimate ground-level O3 from solar radiation intensity and surface temperature

Efficient, socially acceptable and rapid methods of exploration are required to discover new deposits and enable the green energy transition. Sustainable exploration requires a combination of innovative thinking and new technologies. Hyperspectral imaging (HSI) is a rapidly developing technology and allows for fast and systematic mineral mapping, facilitating exploration of the Earth's surface at various

Forests play a significant role in mitigating the effects of climate change and regulating the biogeochemical cycles. Water use efficiency (WUE) is an important indicator that links the carbon and water cycles in terrestrial ecosystems. In the present study, WUE of major forest formations of India was calculated from 2003 to 2018 as the ratio of Moderate Resolution Spectroradiometer (MODIS) Gross Primary

Despite the ecological and socioeconomic impacts of wildfires, little attention has been paid to the spatiotemporal patterns of nighttime fire activity across the conterminous United States (CONUS). Daytime fire radiative power (FRP) detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) was nearly evenly split (54% vs. 46%) between inside and outside wildfires from 2003 to 2020. In

The presence of surface water on the canopy affects radar backscatter. However, its influence on the relationship between radar backscatter and crop biophysical parameters has not been investigated. The aim of this study was to quantify the influence of surface canopy water (SCW) on the relationship between L-band radar backscatter and biophysical variables of interest in agricultural monitoring. In

Severe droughts caused unprecedented impacts on grasslands in Central Europe in 2018 and 2019. Yet, spatially varying drought impacts on grasslands remain poorly understood as they are driven by complex interactions of environmental conditions and land management. Sentinel-2 time series offer untapped potential for improving grassland monitoring during droughts with the required spatial and temporal

Deriving land cover from remotely sensed data is fundamental to many operational mapping and reporting programs as well as providing core information to support science activities. The ability to generate land cover maps has benefited from free and open access to imagery, as well as increased storage and computational power. The accuracy of the land cover maps is directly linked to the calibration

High-throughput mapping of latent heat flux (λET) is critical to efforts to optimize water resources management and to accelerate forest tree breeding for improved drought tolerance. Ideally, investigation of the energy response at the tree level may promote tailored irrigation strategies and, thus, maximize crop biomass productivity. However, data availability is limited and planning experimental

Spatiotemporal image fusion is a potential way to resolve the constraint between the spatial and temporal resolutions of satellite images and has been developed rapidly in recent years. However, two key challenges related to fusion accuracy remain: a) reducing the uncertainty of image fusion caused by sensor differences and b) addressing strong temporal changes. To solve the above two issues, this

Knowledge of forest change type and timing is required for forest management, reporting, and science. Time series of historic satellite data (e.g. Landsat) have resulted in an invaluable record of changes in forest conditions. Natural resource management and reporting typically operate at an annual time step, yet the recent addition of data streams from compatible satellites (e.g., Sentinel-2) offer

Many countries and regions build underground gas storages (UGSs) to regulate the energy demand and supply in different seasons. The Hutubi underground gas storage (HUGS) in Xinjiang province is the largest UGS in China, so it is of great significance to monitor its operation. At present, the researches on the HUGS mainly rely on traditional geodetic monitoring (e.g., in-situ leveling and global navigation

Solar-induced chlorophyll fluorescence (SIF) observed by satellites has advanced the monitoring of terrestrial photosynthesis regionally and globally. The relationship between SIF and gross primary production (GPP) at leaf, canopy, and ecosystem scales has received tremendous attention in recent years. It remains controversial whether the SIF-GPP relationship at the ecosystem scale is universal or

Permafrost on the Qinghai-Tibet Plateau (QTP) undergoes significant thawing and degradation, which affects the hydrological processes, ecosystems and infrastructure stability. The ground deformation, a key indicator of permafrost degradation, can be quantified via geodetic observations, especially using multi-temporal InSAR techniques. The previous InSAR studies, however, either rely on data-driven

The Tibetan Plateau (TP) hosts numerous glaciers and lakes which are critical natural water reserves but highly vulnerable to changing climate. In contrast to general drying trends in global endorheic basins in recent decades, the widespread lake expansions across the endorheic TP stand out as a puzzling “anomaly”. To quantify the contribution of glacier mass changes to lake expansion at fine basin-scale

Land surface temperature (LST) is an essential input for modeling the processes of energy exchange and balance of the earth's surface. Thermal infrared (TIR) remote sensing is considered to be the most efficient way to obtain accurate LST, both regionally and globally. Currently, many LST retrieval algorithms have been developed, including the up-to-date SW-TES (SW: split window; TES: temperature-emissivity

Accurate, reliable, and high spatio-temporal resolution precipitation data are vital for many applications, including the study of extreme events, hydrological modeling, water resource management, and hydroclimatic research in general. In this study, we performed a systematic review of the available literature to assess the performance of the Integrated Multi-Satellite Retrievals for GPM (IMERG) products

Quantifying fuel load over large areas is essential to support integrated fire management initiatives in fire-prone regions to preserve carbon stock, biodiversity and ecosystem functioning. It also allows a better understanding of global climate regulation as a potential carbon sink or source. Large area assessments usually require data from spaceborne remote sensors, but most of them cannot measure

Rapid shrub expansion has been observed across the Arctic, driving a need for regional-scale estimates of shrub biomass and shrub-mediated ecosystem processes such as rainfall interception. Synthetic-Aperture Radar (SAR) data have been shown sensitive to vegetation canopy characteristics across many ecosystems, thereby potentially providing an accurate and cost-effective tool to quantify shrub canopy

Diameter frequency distributions provide essential information for estimating timber assortment, monitoring carbon stocks, and formulating forest management measures. In this study, we estimated diameter distribution utilizing unmanned aerial vehicle laser scanning (ULS) data by applying three Weibull distribution modeling methods: (1) parameter prediction method (PPM); (2) moment-based parameter recovery

Direct sensing of total ocean surface currents with microwave Doppler signals is a growing topic of interest for oceanography, with relevance to several new ocean mission concepts proposed in recent years. Since 2014, the spaceborne C-band SAR instruments of the Copernicus Sentinel-1 (S1) mission routinely acquire microwave Doppler data, distributed to users through operational S1 Level-2 ocean radial

Pronounced climate warming has resulted in a significant reduction of snow cover extent, as well as poleward and upslope shifts of shrubs in Arctic and alpine ecosystems. However, it is difficult to establish links between changes in snow cover and shrub distribution changes due to a lack of in situ and long-term snow records in relation to abundance shifts of shrubs at their leading (i.e., cold) and

The decline of the number of newly discovered mineral deposits and increase in demand for different minerals in recent years has led exploration geologists to look for more efficient and innovative methods for processing different data types at each stage of mineral exploration. As a primary step, various features, such as lithological units, alteration types, structures, and indicator minerals, are

Glaciers in polar regions are sensitive to climate and ocean changes and can thin rapidly as a consequence of global warming. Digital Elevation Models (DEMs) from remote sensing observations have been widely used to detect changes in polar glaciers. DEMs from Terrestrial Radar Interferometer (TRI) have recently been used for high frequency glacier change and glacier-ocean interaction studies. However

Land surface temperature (LST) is listed as an essential climate variable (ECV) and supports quantitative estimates of the energy budget while serving as a proxy for measuring the effects of climate change and extreme events. Forested areas are considered a major land unit impacted by temperature rise; therefore, thorough monitoring is mandatory. An accuracy assessment of the LST of forests must consider

Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculation. Here, we use over 350 optical and synthetic aperture radar (SAR) images from the summer months to

Traditional optical remote sensing data have been widely used for snow cover detection and monitoring. However, they are limited to daytime detection and often suffer from large data gaps due to frequent cloud obscuration. This is in particular a serious challenge for high-latitude and polar regions where long nights prevail during the winter. Nighttime light sensors have a strong capability of sensing

Anthropogenic methane emissions from urban centers are important and addressable, yet remain poorly characterized, and the representativeness of studies from individual cities is unknown. A satellite-based approach provides a pathway to tackle this challenge on a national or global scale. Here we present a space-based method that uses the simultaneous, daily observation of methane and carbon monoxide

Disentangling the individual contributions from vegetation and soil in measured canopy reflectance is a grand challenge to the remote sensing and ecophysiology communities. Since Solar Induced chlorophyll Fluorescence (SIF) is uniquely emitted from vegetation, it can be used to evaluate how well reflectance-based vegetation indices (VIs) can separate the vegetation and soil components. Due to the residual