Remote Sensing, Volume 11, Issue 7

Remotely sensed vegetation indices (RSVIs) can be used to efficiently estimate terrestrial primary productivity across space and time. Terrestrial productivity, however, has many facets (e.g., spatial and temporal variability, including seasonality,...

Pseudo invariant calibration sites (PICS) have been extensively used for the radiometric calibration and temporal stability monitoring of optical satellite sensors. Due to limited knowledge about the radiometric stability of North Africa, only a limi...

Pan-sharpening (PS) is a method of fusing the spatial details of a high-resolution panchromatic (PAN) image with the spectral information of a low-resolution multi-spectral (MS) image. Visual inspection is a crucial step in the evaluation of fused pr...

WorldView-3 satellite is providing images with an unprecedented combination of high spatial and spectral resolution. The stereo capabilities and the very high resolution of the panchromatic band (0.31 m) have been fostering new applications in urban...

The TanDEM-X (TDX) mission launched by the German Aerospace Center delivers unprecedented global coverage of a high-quality digital elevation model (DEM) with a pixel spacing of 12 m. To examine the relationships of terrain, vegetation, and building...

Recent flood events have demonstrated a demand for satellite-based inundation mapping in near real-time (NRT). Simulating and forecasting flood extent is essential for risk mitigation. While numerical models are designed to provide such information,...

One of the intrinsic properties of conventional terrestrial laser scanning technology is the unevenness of its point density over the scene where objects rendered closer to the scanner are more densely covered than the ones far away. This uneven dist...

Methane (${\mathrm{CH}}_4$) is a potent greenhouse gas with a large temporal variability. To increase the spatial coverage, methane observations are increasingly made from satellites that retrieve the column-averaged dry air mole fraction of methane (${\mathrm{XCH}}_4$). T...

Nowadays, 3-D convolutional neural networks (3-D CNN) have attracted lots of attention in the spectral-spatial classification of hyperspectral imageries (HSI). In this model, the feed-forward processing structure reduces the computational burden of 3...

Spaceborne radar altimeters record echo waveforms over all Earth surfaces, but their interpretation and quantitative exploitation over the Arctic Ocean is particularly challenging. Radar returns may be from all ocean, all sea ice, or a mixture of the...

Jointly using spectral and spatial information has become a mainstream strategy in the field of hyperspectral image (HSI) processing, especially for classification. However, due to the existence of noisy or correlated spectral bands in the spectral d...

Population growth, economic development and rural-urban migration have caused rapid expansion of urban areas and metropolitan regions in Turkey. The structure of urban administration and planning has faced different socio-economic and political chall...

This work presents a detailed analysis of building damage recognition, employing multi-source data fusion and ensemble learning algorithms for rapid damage mapping tasks. A damage classification framework is introduced and tested to categorize the bu...

This study proposes an effective method to map rice crops using the Sentinel-1 SAR (Synthetic Aperture Radar) time series over the Camargue region, Southern France. First, the temporal behavior of the SAR backscattering coefficient over 832 plots con...

The growing population in China has led to an increasing importance of crop area (CA) protection. A powerful tool for acquiring accurate and up-to-date CA maps is automatic mapping using information extracted from high spatial resolution remote sensi...

Applications of stereo imagery acquired by cameras onboard unmanned aerial vehicles (UAVs) as practical forest inventory tools are hindered by the unavailability of ground surface elevation. It is still a challenging issue to remove the elevation of...

Accurate estimation of above ground biomass (AGB) is very important for crop growth monitoring. The objective of this study was to estimate rice biomass by utilizing structural and meteorological features with widely used spectral features. Structura...

More than 90% of the sugar production in China comes from sugarcane, which is widely grown in South China. Optical image time series have proven to be efficient for sugarcane mapping. There are, however, two limitations associated with previous resea...

We apply deep convolutional neural networks (CNNs) to estimate wave breaking type (e.g., non-breaking, spilling, plunging) from close-range monochrome infrared imagery of the surf zone. Image features are extracted using six popular CNN architectures...

This article shows the interesting results of a pioneer effort by IAG/USP researchers to use ground-penetrating radar (GPR) for humanitarian purposes, guiding the rescue of victims in the tragedy of Brumadinho. The tailings Dam I at the Córreg...

With the warming of the global climate, the mass loss of the Greenland ice sheet is intensifying, having a profound impact on the rising of the global sea level. Here, we used Gravity Recovery and Climate Experiment (GRACE) RL06 data to retrieve the...

Underestimation of LiDAR heights is widely known but has never been evaluated for several sensors and for diverse types of ecological conditions. This underestimation is mainly linked to the probability of the pulse to reach the ground and the top of...

The general topic here is the application of very high-resolution satellite imagery to the study of ocean phenomena having horizontal spatial scales of the order of 1 kilometer, which is the realm of the ocean submesoscale. The focus of the present s...

This paper proposes novel autoencoders for unsupervised feature-learning from hyperspectral data. Hyperspectral data typically have many dimensions and a significant amount of variability such that many data points are required to represent the distr...

Understanding the causes of inter-satellite biases in climate data records from observations of the Earth is crucial for constructing a consistent time series of the essential climate variables. In this article, we analyse the strong scan- and time-d...

An in situ soil moisture observation network at pixel scale is constructed in cropland in the northeast of China for accurate regional soil moisture evaluations of satellite products. The soil moisture products are based on the Japan Aerospace Explor...

Measurement campaigns in wind energy research are becoming increasingly complex, which has exacerbated the difficulty of taking optimal measurements using light detection and ranging (LiDAR) systems. Compromises between spatial and temporal resolutio...

Remote sensing archaeology in recent years has emphasized the use of high-precision and high-accuracy tools to achieve the detailed documentation of archaeological elements (drones, LIDAR, etc.). Satellite remote sensing has also benefited from an in...

Remote sensing techniques provide data on the spatial–temporal distribution of environmental parameters over regions with sparse ground observations. However, the resolution of satellite precipitation data is too coarse to be applied to hydrolo...

Surface albedo is an important physical attribute of the climate system and satellite retrievals are useful for understanding how it varies in time and space. Surface albedo is sensitive to land cover and structure, which can vary considerably within...

Knowledge of the aboveground biomass (AGB) of large pasture fields is invaluable as it assists graziers to set stocking rate. In this preliminary evaluation, we investigated the response of Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data to bioph...

The main objective of this work was to study the feasibility of using the green red vegetation index (GRVI) and the red edge ratio (RE/R) obtained from UAS imagery for monitoring the effects of soil water deficit and for predicting fibre quality in a...

NASA’s carbon dioxide mission, Orbiting Carbon Observatory-2, began operating in September 2014. In this paper, we analyze four years (2015–2018) of global (60°S–60°N) XCO₂ anomalies and their annual variations and seasonal patterns. We show that the...

Most vegetation indices (VIs) of remote sensing were designed based on the concept of soil-line, which represents a linear correlation between bare soil reflectance at the red and near-infrared (NIR) bands. Unfortunately, the soil-line can only suppr...

In order to provide a constant and complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) at over the horizon (OTH) distances, a network of high frequency surface-wave-radars (HFSWR) slowly becomes a necessity. Si...

This study builds upon a framework to develop a climate data record of temperature and humidity profiles from high-resolution infrared radiation sounder (HIRS) clear-sky measurements. The resultant time series is a unique, long-term dataset (1978&nda...

NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilitie...

Unmanned aerial vehicles have become a popular remote sensing platform for agricultural applications, with an emphasis on crop monitoring. Although there are several methods to detect vegetation through aerial imagery, these remain dependent of manua...

ICESat-2 is the new generation of NASA’s ICESat (Ice, Cloud and land Elevation Satellite) mission launched in September 2018. We investigate the potential of forest parameter estimation using metrics from photon counting LiDAR data, using an in...

In synthetic aperture radar (SAR) images, azimuth ambiguity is one of the important factors that affect image quality. Generally, the azimuth ambiguity-to-signal ratio (AASR) is a measure of the azimuth ambiguity of SAR images. For the low signal-to-...

From the recent developments of data-driven methods as a means to better exploit large-scale observation, simulation and reanalysis datasets for solving inverse problems, this study addresses the improvement of the reconstruction of higher-resolution...

This Special Issue hosts papers related to ocean radars including the high-frequency (HF) surface wave and sky wave radars, X-, L-, K-band marine radars, airborne scatterometers, and altimeter. The topics covered by these papers include sea surface w...

Mobile laser scanning (MLS, or mobile lidar) is a 3-D data acquisition technique that has been widely used in a variety of applications in recent years due to its high accuracy and efficiency. However, given the large data volume and complexity of th...

A portable unmanned Mie-scattering Scheimpflug lidar system has been designed and implemented for atmospheric remote sensing. The Scheimpflug lidar system employs a continuous-wave high-power 808 nm laser diode as the light source and the emitted las...

Velocity updates have been proven to be important for constraining motion-sensor-based dead-reckoning (DR) solutions in indoor unmanned aerial vehicle (UAV) applications. The forward velocity from a mass flow sensor and the lateral and vertical non-h...

The Global Flood Detection Systems (GFDS) currently operated at the European Commission’s Joint Research Centre (JRC) is a satellite-based observation system that provides daily stream flow measurements of global rivers. The system was initiall...

Multi-year field measurements of sea surface Ka-band dual-co-polarized (vertical transmit–receive polarization (VV) and horizontal transmit–receive polarization (HH)) radar Doppler characteristics from an oceanographic platform in the Bla...

It is known that films on the sea surface can appear due to ship pollution, river and collector drains, as well as natural biological processes. Marine film slicks can indicate various geophysical processes in the upper layer of the ocean and in the...

Satellite-retrieved aerosol optical depth (AOD) data have been widely used to predict PM_2.5 concentrations. Most of their spatial resolutions (~1 km or greater), however, are too coarse to support PM_2.5-related studies at fine scales (e.g., urban-sca...

Although wetlands provide valuable services to humans and the environment and cover a large portion of Canada, there is currently no Canada-wide wetland inventory based on the specifications defined by the Canadian Wetland Classification System (CWCS...