Remote Sensing, Volume 11, Issue 19

Data saturation in optical sensor data has long been recognized as a major factor that causes underestimation of aboveground biomass (AGB) for forest sites having high AGB, but there is a lack of suitable approaches to solve this problem. The objecti...

Air temperatures in the Arctic have increased substantially over the last decades, which has extensively altered the properties of the land surface. Capturing the state and dynamics of Land Surface Temperatures (LSTs) at high spatial detail is of hig...

Emergency responders frequently request satellite-based crisis information for flood monitoring to target the often-limited resources and to prioritize response actions throughout a disaster situation. We present a generic processing chain that cover...

Remote sensing technology in recent years has been regarded the most important source to provide substantial information for delineating the flooding extent to the disaster management authority. There have been numerous studies proposing mathematical...

Developments in the capabilities and affordability of unmanned aerial vehicles (UAVs) have led to an explosion in their use for a range of ecological and agricultural remote sensing applications. However, the ubiquity of visible light cameras aboard...

Global Navigation Satellite System (GNSS) reflected signals can be used to remotely sense the Earth’s surface, known as GNSS reflectometry (GNSS-R). The GNSS-R technique has been applied to numerous areas, such as the retrieval of wind speed, a...

Cloud masking is of central importance to the Earth Observation community. This paper deals with the problem of detecting clouds in visible and multispectral imagery from high-resolution satellite cameras. Recently, Machine Learning has offered promi...

Forests have potential economic value and play a significant role in maintaining ecological balance. Considering its outdated and incomplete forest statistics, the Kyrgyzstan Republic urgently needs a forest cover map for assessing its current forest...

In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN). We tested our methods by identifying seve...

This paper describes a non-contact methodology for computing river discharge based on data collected from small Unmanned Aerial Systems (sUAS). The approach is complete in that both surface velocity and channel geometry are measured directly under fi...

The ASTER Volcanic Ash Library (AVAL) is presented, developed using quantitative laboratory thermal infrared (TIR) emission spectroscopic methods, spanning the 2000–400 cm⁻¹ (5–25 μm wavelength) range, including the Earth’s...

The echo waveforms received by conventional radar altimeters are interpreted by retracking algorithms to give estimates of range, wave height, and backscatter strength. However, in response to fading noise on the waveform leading edge, common retrack...

Synthetic aperture radar (SAR) images have been used to map flooded areas with great success. Flooded areas are often identified by detecting changes between a pair of images recorded before and after a certain flood. During the 2018 Western Japan Fl...

We present new results for ocean surface current signatures in dual co- and cross-polarized synthetic aperture radar (SAR) images. C-band RADARSAT-2 quad-polarized SAR ocean scenes are decomposed into resonant Bragg scattering from regular (non-break...

Surface urban heat islands (SUHIs) are influenced by the spatial distribution of green space, which in turn can be influenced by urban planning. When studying the relationship between structure and function it is critical that the scale of observatio...

Snow depth on sea ice is a major constituent of the marine cryosphere. It is a key parameter for the derivation of sea-ice thickness from satellite altimetry. One way to retrieve the basin-scale snow depth on sea ice is by satellite microwave radiome...

As an important indicator to characterize the surface vegetation, fractional vegetation cover (FVC) with high spatio-temporal resolution is essential for earth surface process simulation. However, due to technical limitations and the influence of wea...

This Special Issue was announced in March 2018 [...]

Recently, terrestrial laser scanning (TLS) has shown potential in measuring vegetation biochemical traits in three dimensions (3D) by using reflectance derived from backscattered intensity data. The 3D estimates can provide information about the vert...

This study presents an assessment of the version-6 (V06) of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product from June 2014 to December 2017 over different hydro-climatic regimes in the Tianshan Mountains...

Pansharpening is the process of merging the spectral resolution of a multi-band remote-sensing image with the spatial resolution of a co-registered single-band panchromatic observation of the same scene. Conceived and contextualized over 30 years ago...

The expected amplitude of fixed-point sea surface temperature (SST) fluctuations induced by barotropic and baroclinic tidal flows is estimated from tidal current atlases and SST observations. The fluctuations considered are the result of the advectio...

The Normalized Difference Vegetation Index (NDVI) is widely used to monitor vegetation phenology and productivity around the world. Over the last few decades, phenology monitoring at large scales has been possible due to the information and metrics d...

A spatially distributed land surface temperature is important for many studies. The recent launch of the Sentinel satellite programs paves the way for an abundance of opportunities for both large area and long-term investigations. However, the spatia...

The utility of land cover maps for natural resources management relies on knowing the uncertainty associated with each map. The continuous advances typical of remote sensing, including the increasing availability of higher spatial and temporal resolu...

Red and near-infrared line-height algorithms such as the maximum chlorophyll index (MCI) are often considered optimal for remote sensing of chlorophyll-a (Chl-a) in turbid eutrophic waters, under the assumption of minimal influence from mineral sedim...

Vegetation state is usually assessed by calculating vegetation indices (VIs) derived from remote sensing systems where the near infrared (NIR) band is used to enhance the vegetation signal. However VIs are pixel-based and require both visible and NIR...

Our study explores the relationship between land surface albedo (LSA) changes and burn severity, checking whether the LSA is an indicator of burn severity, in a large forest fire (117.75 km², Spain). The LSA was obtained from Landsat data. In particu...

A new satellite-based technique for rainfall retrieval in high spatio-temporal resolution (3 km, 15 min) for Iran is presented. The algorithm is based on the infrared bands of the Meteosat Second Generation Spinning Enhanced Visible and Infrared Imag...

During the last few decades, a large number of people have migrated to Kathmandu city from all parts of Nepal, resulting in rapid expansion of the city. The unplanned and accelerated growth is causing many environmental and population management issu...

The European Space Agency’s Copernicus satellites Sentinel-2 and Sentinel-3 provide observations with high spectral, spatial, and temporal resolution which can be used to monitor inland and coastal waters. Such waters are optically complex, and...

Multi-temporal interferometric synthetic aperture radar (MT-InSAR) can be applied to monitor the structural health of infrastructure such as railways, bridges, and highways. However, for the successful interpretation of the observed deformation withi...

This work proposes a novel Ground Penetrating Radar (GPR) system to detect landmines and Improvised Explosive Devices (IEDs). The system, which was numerically evaluated, is composed of a transmitter placed on a vehicle and looking forward and a rece...

Despite increasing efforts in the mapping of landslides using Sentinel-1 and -2, research on their combination for discerning historical landslides in forest areas is still lacking, particularly using object-oriented machine learning approaches. This...

The water cycle is the most essential supporting physical mechanism ensuring the existence of life on Earth. Its components encompass the atmosphere, land, and oceans. The cycle is composed of evaporation, evapotranspiration, sublimation, water vapor...

This article presents an investigation into the problem of 3D radar echo extrapolation in precipitation nowcasting, using recent AI advances, together with a viewpoint from Computer Vision. While Deep Learning methods, especially convolutional recurr...

The lack of long term and well distributed precipitation observations on the Tibetan Plateau (TiP) with its complex terrain raises the need for other sources of precipitation data for this area. Satellite-based precipitation retrievals can fill those...

A series of earthquakes hit Kumamoto Prefecture, Japan, continuously over a period of two days in April 2016. The earthquakes caused many landslides and numerous surface ruptures. In this study, two sets of the pre- and post-event airborne Lidar data...

In recent years, there has been a preliminary research on monitoring rainfall information based on polarimetric Global Navigation Satellite System (GNSS) signals, which is a quite novel concept. After previous theoretical research on monitoring rain...

Ocean surface heat fluxes play a significant role in the genesis and evolution of various marine-based atmospheric phenomena, from the synoptic scale down to the microscale. While in-situ measurements from buoys and flux towers will continue to be th...

This paper analyses the critical phase unwrapping step in a differential interferometric phase (D-InSAR) stack where both the solving of conventional methods and alternative approaches are discussed. It can be shown that including the temporal relati...

Sentinel-3A/3B (S3A/B) satellites are equipped with a number of precise instruments dedicated to the measurement of surface topography, sea and land surface temperatures and ocean and land surface color. The high-precision orbit is guaranteed by thre...

Suspended particulate matter (SPM) directly affects the underwater light field and, as a consequence, changes the water clarity and can reduce the primary production. Remote sensing-based bio-optical modeling can provide efficient monitoring of the s...

The Karnali highway is a vital transport link and the only primary roadway that connects the remote Karnali region to the lowlands in Mid-Western Nepal. Every year there are reports of landslides blocking the road, making this area largely inaccessib...

This study analyzed the Groundwater Productivity Potential (GPP) of Okcheon city, Korea, using three different models. Two of these three models are data mining models: Boosted Regression Tree (BRT) model and Random Forest (RF) model. The other model...

Global land cover information is required to initialize land surface and Earth system models. In recent years, new land cover (LC) datasets at finer spatial resolutions have become available while those currently implemented in most models are outdat...

Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR res...

Dimensionality Reduction (DR) models are highly useful for tackling Hyperspectral Images (HSIs) classification tasks. They mainly address two issues: the curse of dimensionality with respect to spectral features, and the limited number of labeled tra...

The use of Convolutional Neural Networks (CNNs) to solve Domain Adaptation (DA) image classification problems in the context of remote sensing has proven to provide good results but at high computational cost. To avoid this problem, a deep learning n...

Hyperspectral images are depictions of scenes represented across many bands of the electromagnetic spectrum. The large size of these images as well as their unique structure requires the need for specialized data compression algorithms. The redundanc...