In this study, the mechanism of channel-floodplain seasonal connectivity along the Amazon River is analyzed over a full hydrological year through the use of satellite radar altimetry data (Jason-2). This is done via a novel observation-based approach which employs the concurrent measurement of water levels (WLs) over river and floodplain, analyzing seasonal changes in water surface height differences

Quantification of snow cover changes and related phenology in global mountain areas has not been consistently addressed, despite the well-known importance of the snow in this environment. By using MODIS products from 2000 to 2018, this study reveals that around 78% of the global mountain areas are undergoing a snow decline characterized by snow cover duration decrease up to 43 days, and a snow cover

Historically, change detection reviews have examined and categorized algorithms based on their techniques for the remote sensing community. Here, we synthesize urban land change algorithms by the types of information they provide to a diverse and growing set of user communities. Two goals of the paper are first to synthesize past and current change detection studies to examine urban land change to

Satellite remote sensing data are critical for assessing ecosystem state and evaluating long-term trends and shifts in ecosystem components. Many operational tools rely on continuous streams of remote sensing data, and when a satellite sensor reaches the end of its designed lifespan, these tools must be transferred to a more reliable data stream. Transferring between data streams can produce discontinuities

Measurements of reflected solar radiation by imaging spectrometers can quantify water in different states (solid, liquid, gas) thanks to the discriminative absorption shapes. We developed a retrieval method to quantify the amount of water in each of the three states from spaceborne imaging spectroscopy data, such as those from the German EnMAP mission. The retrieval couples atmospheric radiative transfer

Water in oil (WO) and oil in water (OW) emulsions from marine oil spills have different physical properties, volume concentrations, and spectral characteristics. Identification and quantification of these different types of oil emulsions are important for oil spill response and post-spill assessment. While the spectral characteristics of WO and OW emulsions have been presented in previous studies including

Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on a triple-source surface energy balance (triple-SEB)

Landfast sea ice (fast ice) is an important feature prevalent around the Antarctic coast, which is affected by climate change and energy exchanges with the atmosphere and ocean. This study proposed a method for detection of the West Antarctic fast ice using the Advanced Land Observing Satellite Phased Array L-band SAR (ALOS PALSAR) images. The algorithm has combined image segmentation, image correlation

Operated since the end of 2009, the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite mission is the first orbiting radiometer that collects regular and global observations from space of two Essential Climate Variables of the Global Climate Observing System: Sea Surface Salinity (SSS) and Soil Moisture. The National Aeronautics and Space Administration (NASA) Aquarius mission

This paper presents the temporal evolution of Global Navigation Satellite System Reflectometry (GNSS-R) ocean wind speed retrieval performance during three years of the UK TechDemoSat-1 (TDS-1) mission. TDS-1 was launched in July 2014 and provides globally distributed spaceborne GNSS-R data over a lifespan of over three years, including several months of 24/7 operations. TDS-1 wind speeds are computed

Passive microwave (PMW) remote sensing has proven to be a useful approach to characterize the volume of seasonal snowpack in remote northern regions at the synoptic scale. Modeling emitted microwave brightness temperatures (TB) is made possible using a physical radiative transfer model that takes into account microstructural and stratigraphic structure of the snowpack. However, prescribing the microstructure

Climatology (mean seasonal cycle) errors often cause large differences between soil moisture products. However, relatively little work has been done to objectively evaluate soil moisture mean seasonal cycle (SMC) information acquired from different sources. This study evaluates surface (0–10 cm) SMCs obtained from four land surface models (LSMs), two C/X-band and two L-band remote-sensing (RS) products

Mangrove ecosystems are targeted for many conservation and rehabilitation efforts due to their ability to store large amounts of carbon in their living biomass and soil. Traditional methods to monitor above-ground biomass (AGB) rely on on-ground measurements, which are expensive, labour intensive and cover small spatial scales. Structure from Motion and Multi-View Stereo reconstructions from Unmanned

Region-wide investigation of glacier change in High Mountain Asia marked the strongest recession in southeastern Tibetan Plateau (SETP) in recent decades. However, evident differences of quantitative glacier mass balance (MB) estimations on fine scales exist in the prior reports. The large uncertainties in current geodetic observations over this region highlight the need for more independent validations

The area, distribution, and temporal dynamics of anthropogenic impervious surface (AIS) at large scale are significant for environmental, ecological and socio-economic studies. Remote sensing has become an important tool for monitoring large scale AIS, while it remains challenging for accurate extraction of AIS using optical datasets alone due to the high diversity of land covers over large scale.

Interannual variability (IAV) in ecosystem productivity may reveal vulnerabilities of vegetation to climate stressors. We analyzed IAV of northern hemisphere ecosystems using several remote sensing datasets, including longstanding observations of the normalized difference vegetation index (NDVI) and more novel metrics for productivity including solar-induced chlorophyll fluorescence (SIF) and the near-infrared

Crop emergence date is a critical input to models of crop development and biomass accumulation. The ability to robustly detect and map emergence date using remote sensing would greatly benefit operational yield estimation and crop monitoring efforts; however, this has proven to be challenging. Previous remote-sensing phenology algorithms showed that crop stages can typically be detected starting only

The angle-dependent scattering effect of aerosols in the atmosphere not only influences climate through radiative forcing effects but also impacts trace gas remote sensing by modifying the path of radiation through the atmosphere. The aerosol phase function, which characterizes the angular signature of scattering, has been continuously monitored from ground-based and space-borne observations. However

Nitrogen (N) is considered as one of the most important plant macronutrients and proper management of N therefore is a pre-requisite for modern agriculture. Continuous satellite-based monitoring of this key plant trait would help to understand individual crop N use efficiency and thus would enable site-specific N management. Since hyperspectral imaging sensors could provide detailed measurements of

Invasive Spartina alterniflora (S. alterniflora), a native riparian species in the U.S. Gulf of Mexico, has led to serious degradation to the ecosystem and biodiversity as well as economic losses since it was introduced to China in 1979. Although multi-temporal remote sensing offers unique capability to monitor S. alterniflora over large areas and long time periods, three major hurdle exist: (1) in

Accurate and detailed soil moisture information is essential for, among other things, irrigation, drought and flood prediction, water resources management, and field-scale (i.e., tens of m) decision making. Recent satellite missions measuring soil moisture from space continue to improve the availability of soil moisture information. However, the utility of these satellite products is limited by the

Underground coal mining with high groundwater levels causes many environmental problems, one of the main ones being subsidence waterlogging. After the subsidence waterlogging, the land faces many problems, such as insufficient land development and difficult and costly land restoration. Therefore, it is necessary to monitor the spatial range and temporal trajectory pattern of surface subsidence in a

Landfast ice is an important component of the Antarctic sea ice regime. It affects the Antarctic climate and ecological system. In this study, the first high-resolution, long time series of the landfast ice edge from 2006 to 2011 and 2016 to 2017 is presented. The dataset was produced based on the improved net gradient difference algorithm using 2470 SAR scenes from ENVISAT and Sentinel-1A/B as well

Commonly applied water indices such as the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) were originally conceived for medium spatial resolution remote sensing images. In recent decades, high spatial resolution imagery has shown considerable potential for deriving accurate land cover maps of urban environments. Applying traditional water indices

Change detection between images is a procedure used in many applications of remote sensing data. Among these applications, the identification of damaged infrastructures in urban areas due to a large-scale disaster is a task that is crucial for distributing relief, quantifying losses, and rescue purposes. A crucial consideration for change detection is that the images must be co-registered precisely

The surface seasonal freeze/thaw (F/T) signal detected by passive microwave remote sensing is very important for the water cycle, carbon cycle and climate change research. In this study, we evaluated and analyzed the Soil Moisture Active Passive (SMAP) L3 F/T product, Advanced Microwave Scanning Radiometer 2 (AMSR2) F/T product and Making Earth System Data Records for Use in Research Environments (MEaSUREs)

The modeling of Near-Surface Temperature Lapse Rate (NSTLR) is of great importance in various environmental applications. This study proposed a new approach for modeling the NSTLR based on the Normalized Land Surface Temperature (NLST). A set of remote sensing imagery including Landsat images, MODIS products, and ASTER Digital Elevation Model (DEM), land cover maps, and climatic data recorded in meteorological

There is limited research focusing on Interferometric Synthetic Aperture Radar (InSAR) applications in the Great Lakes coastal wetlands with large water level fluctuations. In this study, we investigated the potential of using C-band SAR data to characterize marsh wetland and monitor water level changes along the coast of the Great Lakes. InSAR analysis was conducted using Radarsat-2 and Sentinel-1

Accurate representations of canopy cover are essential for directing natural resource management efforts targeted at issues such as carbon storage, habitat modeling, fire spread, water resources, and ecosystem services. A two-phase classification approach utilizing an iterative classification of high-resolution aerial imagery to develop training data for a regional-scale classification of percentage

Many derived Earth Observation products share surface reflectance as a common step in their processing chains. This makes the maintenance and improvement of surface reflectance product quality of fundamental importance to ensure information derived from these downstream products can be trusted. Despite this, the literature is relatively light on the implementation of validation methodologies designed

Solar-induced chlorophyll fluorescence (SIF) measured from space has been increasingly used to quantify plant photosynthesis at regional and global scales. Apparent canopy SIF yield (SIFyield apparent), determined by fluorescence yield (ΦF) and escaping ratio (fesc), together with absorbed photosynthetically active radiation (APAR), is crucial in driving spatio-temporal variability of SIF. While strong

The past two decades have been prolific in production of global or near-global Digital Elevation Models (DEMs) derived from satellite data. The most recent addition to the family of global DEMs is the TanDEM-X DEM with resolution of 0.4 arc sec. DEMs are essential for a wide range of environmental applications, many of which are related to mountains including studies on natural hazards, forestry or

A new method, combining empirical modeling with time series Interferometric Synthetic Aperture Radar (InSAR) data, is proposed to provide an assessment of potential landslide volume and area. The method was developed to evaluate potential landslides in the Heitai river terrace of the Yellow River in central Gansu Province, China. The elevated terrace has a substantial loess cover and along the terrace

Various forms of machine learning (ML) methods have historically played a valuable role in environmental remote sensing research. With an increasing amount of “big data” from earth observation and rapid advances in ML, increasing opportunities for novel methods have emerged to aid in earth environmental monitoring. Over the last decade, a typical and state-of-the-art ML framework named deep learning

Scarcity of water temperature data in rivers may limit a diversity of studies considering this property, which regulates many physical, chemical, and biological processes. We present a robust method to generate a consistent, continuous daily river water temperature (RWT) data series for medium and large rivers using the combined techniques of remote sensing and water temperature modelling. In order

Tree mortality from major disturbances can greatly increase dead wood in forested areas, affecting fire intensity and behavior, wildlife habitat, and carbon dynamics. Accurately quantifying regional standing dead tree (SDT) pools, as conducted by the U.S. Forest Service Forest Inventory and Analysis (FIA) program, remains a prominent challenge. Little empirical work has been done accounting for structural

This work presents a new methodology to simultaneously account for both the mean and variance of 17 years of Carbon Monoxide [CO] measurements from the MOPITT satellite (from 2000 to 2016) over Southeast and East Asia. We demonstrate that the new technique is stable and produces a set of results which are both consistent with the understood geographical and temporal distribution of CO sources, as well

Characterisation of the ecosystem functioning of mudflats requires insight on the morphology and facies of these coastal features, but also on biological processes that influence mudflat geomorphology, such as crab bioturbation and the formation of benthic biofilms, as well as their heterogeneity at cm or less scales. Insight into this fine scale of ecosystem functioning is also important as far as

The lack of aerosol information over the cryosphere introduces large uncertainties to our understanding of phenomenon, known as the Arctic Amplification (AA) and its feedback mechanisms. The aerosol optical depth (AOD) describes the optical characteristics of aerosol loading. This paper describes a novel algorithm, which retrieves AOD above snow-covered regions from the measurements of the up-welling

Statistical time series models are increasingly being used to fit medium resolution time series provided by satellite sensors, such as Landsat, for terrestrial monitoring. Cloud and shadows, combined with low satellite repeat cycles, reduce surface observation availability. In addition, only a single year of data can be used where there is high inter-annual variation, for example, over many croplands

Climate change is a threat to many high-latitude regions. Changing patterns in precipitation intensity and increasing glacial ablation during spring and summer have major influence on river dynamics and the risk of widespread flooding. To monitor these rapid events, more frequent discharge observations are necessary. Having access to near-daily satellite based discharge observations is therefore highly

Vegetation growth and physiological functioning, including carbon uptake and transpiration, can be strongly affected by drought. During water-limited conditions, urban vegetation may be limited in its ability to provide ecosystem services, such as shading and evaporative cooling. While there has been extensive research on drought response in natural vegetation and agricultural systems using remote

Knowledge of snow water equivalent (SWE) magnitude and spatial distribution are keys to improving snowmelt flood predictions. Since the 1980s, the operational National Oceanic and Atmospheric Administration's (NOAA) airborne gamma radiation soil moisture (SM) and SWE survey has provided over 20,000 SWE observations to regional National Weather Service (NWS) River Forecast Centers (RFCs). Because the

The paper discusses the possibilities and limitations of using satellite data to determine the radiation budget NET and its components at the Baltic Sea surface in near real time using a newly established SBRB system (SatBałtyk Radiation Budget). The system enables determination of daily radiation fluxes over the entire Baltic Sea employing data from satellites in combination with data from numerical

The quantification of leaf area index (LAI) is essential for modeling the interaction between atmosphere and biosphere. The airborne LiDAR has emerged as an effective tool for mapping plant area index (PAI) in a landscape consisting of both woody and leaf materials. However, the discrimination between woody and leaf materials and the estimation of effective LAI (eLAI) have, to date, rarely been studied

Landslides and resultant barrier lakes are significant threats to human lives and infrastructures. Three-dimensional (3D) surface displacements can give vital clues to the exploration of internal structure of landslides, but they are difficult to be retrieved from spaceborne Synthetic Aperture Radar (SAR) observations due to the intrinsic limitation of SAR imaging geometry. Meanwhile, studies on predicting

Sediment budgets are a critical metric to assess coastal marsh vulnerability to sea level rise and declining riverine sediment inputs. However, calculating accurate sediment budgets is challenging in tidal marsh-influenced estuaries where suspended sediment concentrations (SSC) typically vary on scales of hours and hundreds of meters, and where SSC dynamics are driven by a complex and often site-specific

The development of fractional vegetation cover products for Australia that resolve cover into photosynthetic vegetation (FPV), non-photosynthetic vegetation (FNPV) and bare soil/rock (FBS) provides a new basis for examination of responses of vegetation cover to long term precipitation cycles, and to explore the interaction between these responses and land cover type, land use and other land surface

To better eliminate the adverse effects of the ground surface on winter wheat Leaf area index (LAI) inversions and to further improve the accuracy of regional winter wheat LAI inversion using SAR remote sensing data, considering the morphological characteristics at different wheat growth stages, a winter wheat LAI inversion model coupled with the microwave scattering model (MSM) for winter wheat at

Dense time series of Landsat 8 and Sentinel-2 imagery are creating exciting new opportunities to monitor, map, and characterize temporal dynamics in land surface properties with unprecedented spatial detail and quality. By combining imagery from the Landsat 8 Operational Land Imager and the MultiSpectral Instrument on-board Sentinel-2A and -2B, the remote sensing community now has access to moderate

Dramatic phenological shifts and ecosystem responses of deciduous forests to global climate change have been reported around the world. Land Surface Phenology (LSP) derived from satellite imagery is useful to estimate the phenological responses of vegetation to climate variability and inform terrestrial ecosystem models at landscape to global scales. However, there is a large (and unquantified) uncertainty

The Landsat archive offers great potential for monitoring forest cover change, and new approaches moving from categorical towards continuous change products emerge rapidly. Most approaches, however, require vast amounts of high-quality reference data, limiting their applicability across space and time. We here propose the use of a generalized regression-based unmixing approach to overcome this limitation

Terricolous macrolichens are an important food source for caribou (Rangifer tarandus) and can greatly influence their movement, distribution and demography over time. Mapping the spatial distribution and cover of macrolichens with remote sensing can serve as an important approach for assessing the impact of disturbances (e.g. fire, grazing, trampling) on lichen cover at the landscape scale and for

Environmental conditions are important drivers in regulating the distribution pattern of phytoplankton composition in the world's oceans. We constructed models that predict pico-, nano- and micro-phytoplankton size classes and assessed the impact of separately including sea surface temperature (SST) and estimates of light level in the surface mixed-layer on model skill. The empirical models were trained

Human-mediated climate change over the past century has resulted in significant impacts to global ecosystems and biodiversity including accelerating redistribution of the geographic ranges of species. In mountainous regions, the transition zone from continuous closed-canopy montane forests to treeless alpine tundra areas at higher elevations is commonly referred to as the “alpine treeline ecotone”

Land cover mixture at moderate- to coarse-resolution is an important cause for the uncertainty of global leaf area index (LAI) products. The accuracy of LAI retrievals over land-water mixed pixels is adversely impacted because water absorbs considerable solar radiation and thus can greatly lower pixel-level reflectance especially in the near-infrared wavelength. Here we proposed an approach named Reduced

Accurate and consistent broad-scale mapping of fire severity is an important resource for fire management as well as fire-related ecological and climate change research. Remote sensing and machine learning approaches present an opportunity to enhance accuracy and efficiency of current practices. Quantitative biophysical models of photosynthetic, non-photosynthetic and bare cover fractions have not

The Ocean and Sea-Ice Satellite Application Facility (OSI-SAF) of the EUropean Organisation for the Exploitation of METeorological Satellites (EUMETSAT) has performed a reprocessing of Sea Surface Temperature (SST) from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) archive (2004–2012). The retrieval method consists of a non-linear split-window algorithm