Remote Sensing, Volume 13, Issue 21

We present an algorithm for computing ice drift in the marginal ice zone (MIZ), based on partial shape recognition. With the high spatial resolution of Sentinel-1 and Sentinel-2 images, and the low sensitivity to atmospheric influences of Sentinel-1,...

Understanding the spatio-temporal pattern of natural vegetation helps decoding the responses to climate change and interpretation on forest resilience. Satellite remote sensing based data products, by virtue of their synoptic and repetitive coverage,...

Ecological environment quality is a long-term continuous concept that is affected by various environmental factors. Its assessment has important implications for implementing the planning and protection of dynamic regional ecosystems. Therefore, this...

The equivalent water thickness (EWT) is an important biophysical indicator of water status in crops. The effective monitoring of EWT in wheat under different nitrogen and water treatments is important for irrigation management in precision agricultur...

Recent advances in autonomy of unmanned aerial vehicles (UAVs) have increased their use in remote sensing applications, such as precision agriculture, biosecurity, disaster monitoring, and surveillance. However, onboard UAV cognition capabilities for...

Peak ground displacement (PGD) and peak ground velocity (PGV) are critical parameters during earthquake early warning, as they can provide rapid magnitude estimation before rupture end. In this study, we used the high-rate Global Navigation Satellite...

The monitoring and maintenance of the Inner Mongolia section of the Yellow River Basin is of great significance to the safety and development of China’s Yellow River Economic Belt and to the protection of the Yellow River ecology. In this study, we c...

The conventional fuzzy c-spherical shells (FCSS) clustering model is extended to cluster shells involving non-crisp numbers, in this paper. This is achieved by a vectorized representation of distance, between two non-crisp numbers like the crisp numb...

Growing stock volume (GSV) is a fundamental parameter of forests, closely related to the above-ground biomass and hence to carbon storage. Estimation of GSV at regional to global scales depends on the use of satellite remote sensing data, although ac...

Widespread harmful cyanobacterial bloom is one of the most pressing concerns in lakes and reservoirs, resulting in a lot of negative ecological consequences and threatening public health. Ocean color instruments with low spatial resolution have been...

Long-term continuous monitoring of the mining activities in open-pit coal mines is conducive to planning and management of the mining operations. Additionally, this faciliatates assessment on their environmental impact and supervises illegal mining b...

Grassland ecosystems are a significant part of the global ecosystem and support the livelihoods of millions of people. The Inner Mongolia grassland is the largest temperate grassland in the world, and an important ecological barrier for China, but du...

Automation, including machine learning technologies, are becoming increasingly crucial in agriculture to increase productivity. Machine vision is one of the most popular parts of machine learning and has been widely used where advanced automation and...

Characterizing urban expansion patterns is of great significance to planning and decision-making for urban agglomeration development. This study examined the urban expansion in the entire Yangtze River Delta Region (YRDR) with its land-use data of si...

TH-2 is China’s first short-range satellite formation system used to realize interferometric synthetic aperture radar (InSAR) technology. In order to achieve the mission goal of InSAR processing, the relative orbit must be determined with high accura...

Aeolian transport affects beach and foredune pre-storm morphologies, which directly contribute to storm responses. However, significant spatiotemporal variation exists within beach-dune systems regarding how biotic and abiotic factors affect topograp...

This study aimed to identify the optimal sets of spectral bands for monitoring multiple grapevine nutrients in vineyards. We used spectral data spanning 400–2500 nm and leaf samples from 100 Concord grapevine canopies, lab-analyzed for six key nutrie...

Water vapor is one of the most important greenhouse gases in the world. There are many techniques that can measure water vapor directly or remotely. In this work, we first study the Global Positioning System (GPS)- and the Global Navigation Satellite...

The Northeast region of Brazil (NEB) has a high rate of deaths from lightning strikes (18% of the country’s total). The region has states, such as Piauí, with high mortality rates (1.8 deaths per million), much higher than the national rate (0.8) and...

The small baseline subset of spaceborne interferometric synthetic aperture radar (SBAS-InSAR) technology has become a classical method for monitoring slow deformations through time series analysis with an accuracy in the centimeter or even millimeter...

Mapping and monitoring the spatio-temporal variations of the Surface Urban Heat Island (SUHI) and thermal comfort of metropolitan areas are vital to obtaining the necessary information about the environmental conditions and promoting sustainable citi...

Coral reefs are an essential source of marine biodiversity, but they are declining at an alarming rate under the combined effects of global change and human pressure. A precise mapping of coral reef habitat with high spatial and time resolutions has...

The complex valley networks that cross the Martian surface offer geomorphologic evidence of the presence of liquid water at some point in its history. However, the derivation of both temporal and hydrological dimensions of this climate phase is far f...

Convolutional neural networks (CNNs) have been widely used in hyperspectral image classification in recent years. The training of CNNs relies on a large amount of labeled sample data. However, the number of labeled samples of hyperspectral data is re...

Three-dimensional reconstruction technology has demonstrated broad application potential in the industrial, construction, medical, forestry, agricultural, and pastural sectors in the last few years. High-quality digital point cloud information exists...

This study investigates the potential of observations with improved frequency and latency time of upcoming altimetry missions on the accuracy of flood forecasting and early warnings. To achieve this, we assessed the skill of the forecasts of a distri...

The influence of climate change and anthropogenic activities (e.g., water withdrawals) on groundwater basins has gained attention recently across the globe. However, the understanding of hydrological stores (e.g., groundwater storage) in one of the l...

A reliable framework for SINS/SAR/GPS integrated positioning systems is proposed for the case that sensors are in critical environments. Credibility is used to describe the difference between the true error and the initial setting standard deviation....

Accurate and timely land surface phenology (LSP) provides essential information for investigating the responses of terrestrial ecosystems to climate changes and quantifying carbon and surface energy cycles on the Earth. LSP has been widely investigat...

Regional or continental-scale land cover mapping requires various amounts of months of multi-temporal satellite data to pick phenological variation in vegetation, enhancing differentiability among surface cover types and improving accuracy. However,...

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a...

Terrestrial evapotranspiration (ET) is a critical component of water and energy cycles, and improving global land evapotranspiration is one of the challenging works in the development of land surface models (LSMs). In this study, we apply a bias corr...

The documentation of underwater cultural heritage (UCH) is the basis for sustainable maritime development including its protection, preservation, and incorporation in coastal zone management plans. In this study, we present a multidisciplinary, non-i...

Accurate knowledge of photosynthetic capacity is critical for understanding the carbon cycle under climate change. Despite the fact that deep neural network (DNN) models are increasingly applied across a wide range of fields, there are very few attem...

The Arctic is under great pressure due to climate change. Drones are increasingly used as a tool in ecology and may be especially valuable in rapidly changing and remote landscapes, as can be found in the Arctic. For effective applications of drones,...

Deep learning methods have achieved considerable progress in remote sensing image building extraction. Most building extraction methods are based on Convolutional Neural Networks (CNN). Recently, vision transformers have provided a better perspective...

Accurate estimation of spatiotemporal precipitation dynamics is crucial for flash flood forecasting; however, it is still a challenge in Andean-Amazon sub-basins due to the lack of suitable rain gauge networks. This study proposes a framework to impr...

Under the circumstance of global climate change, the evolution of thermal environments has attracted more attention, for which the surface urban heat island (SUHI) is one of the major concerns. In this research, we focused on the spatiotemporal patte...

The knowledge of glacier zones’ extent and their temporal variations is fundamental for the retrieval of surface mass balance of glaciers and ice sheets. In this context, a key parameter is the firn line (FL), the lower boundary of the percolation zo...

Numerous studies have confirmed that climate change leads to a decrease in the net ecosystem productivity (NEP) of terrestrial ecosystems and alters regional carbon source/sink patterns. However, the response mechanism of NEP to climate change in the...

Satellite-based long-term observations of vegetation cover development in combination with recent in-situ observations provide a basis to better understand the spatio-temporal changes of vegetation patterns, their sensitivity to climate drivers and t...

In view of the difficulty of wind direction retrieval in the case of the large space and time span of the global sea surface, a method of sea surface wind direction retrieval using a support vector machine (SVM) is proposed. This paper uses the space...

Spatial information on benthic habitats in Wangiwangi island waters, Wakatobi District, Indonesia was very limited in recent years. However, this area is one of the marine tourism destinations and one of the Indonesia’s triangle coral reef regions wi...

Emissivity information derived from thermal infrared (TIR) hyperspectral imagery has the advantages of both high spatial and spectral resolutions, which facilitate the detection and identification of the subtle spectral features of ground targets. De...

In recent years, the deep neural network has shown a strong presence in classification tasks and its effectiveness has been well proved. However, the framework of DNN usually requires a large number of samples. Compared to the training sets in classi...

The important variable of horizontal visibility within forest stands is gaining increasing attention in studies and applications involving terrestrial laser scanning (TLS), photographic measurements of forest structure, and autonomous mobility. We in...

Information about water level is essential for hydrological monitoring and flood/drought risk assessment. In a large part of Italian river network, in situ instruments for measuring water level are rare or lacking. Here we consider the satellite meas...

This paper introduces a genetic algorithm (GA) and a beam tracing algorithm incorporated within a dual parallel computing framework to optimize urban aerial laser scanning (ALS) missions to maximize vertical façade data capture, as needed for many th...

We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully...

We conducted a systematic review and inventory of recent research achievements related to spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil-related strategic goals for a three-year period (2019–2021). Scaling, res...