Remote Sensing, Volume 14, Issue 17

Atmospheric conditions vary significantly in terms of the temporal and spatial scales. Therefore, it is critical to obtain atmospheric parameters synchronized with an image for atmospheric correction based on radiative transfer calculation methods. O...

Prompt and precise acknowledgement of surface change around subways is of considerable significance in urban rail protection and local environmental management. Research has proven the considerable potential of synthetic aperture radar (SAR) images f...

Monitoring within-field crop variability at fine spatial and temporal resolution can assist farmers in making reliable decisions during their agricultural management; however, it traditionally involves a labor-intensive and time-consuming pointwise m...

The broadcast ionospheric model is one of the main methods for eliminating ionospheric delay errors for the Global Navigation Satellite Systems (GNSS) single-frequency users. GPS Klobuchar model (GPSK8) is the widely used broadcast ionospheric model...

Gaofen-3 is the first Chinese spaceborne C-band SAR satellite with multiple polarizations. The Gaofen-3 satellite’s data has few applications for monitoring landslides at present, and its potential for use requires further investigation. Conseq...

Artificial Neural Network (ANN) approaches are applied to detect and determine the object class using a special set of the UltraWideBand (UWB) pulse Ground Penetrating Radar (GPR) sounding results. It used the results of GPR sounding with the antenna...

A waterlogging assessment framework based on the stormwater management model (SWMM), considering the microtopography, is proposed (taking into account the complexity of the underlying surface, which contains various micro-surface features within the...

A better understanding of the relationship between land surface temperature (Ts) and near-surface air temperature (Ta) is crucial for improving the simulation accuracy of climate models, developing retrieval schemes for soil and vegetation moisture,...

The development of convolution neural networks (CNNs) has become a significant means to solve the problem of remote sensing scene image classification. However, well-performing CNNs generally have high complexity and are prone to overfitting. To hand...

The fall armyworm (FAW) (Spodoptera frugiperda) (J. E. Smith) is a migratory pest that lacks diapause and has raised widespread concern in recent years due to its global dispersal and infestation. Seasonal environmental changes lead to its large-scal...

Carbon dioxide (CO₂) is one of the main greenhouse gases leading to global warming, and the ocean is the largest carbon reservoir on the earth that plays an important role in regulating CO₂ concentration on a global scale. The column-averaged dry-air...

Plumas National Forest, located in the Butte and Plumas counties, has experienced devastating wildfires in recent years, resulting in substantial economic losses and threatening the safety of people. Mapping damaged areas and assessing wildfire susce...

Semi-supervised methods have made remarkable achievements via utilizing unlabeled samples for optical high-resolution remote sensing scene classification. However, the labeled data cannot be effectively combined with unlabeled data in the existing se...

In recent years, climate change and the intervention of anthropogenic activities have altered the seasonal features of Asian dust storms. This may also cause seasonal variations (including dust occurrence frequency and optical/microphysical propertie...

Sea ice loss and accelerated warming in the Barents Sea have recently been one of the main concerns of climate research. In this study, we investigated the trends and possible relationships between sea surface temperature (SST), sea ice concentration...

Offering real-time precise point positioning (PPP) services for global and large areas based on global navigation satellite systems (GNSS) has drawn more and more attention from institutions and companies. A precise and reliable satellite orbit is a...

Understanding the impact of climate change and human activities on the hydrological cycle of any watershed can provide a scientific basis for regional water resource planning, flood management, and disaster mitigation. An improved three-parameter hyd...

Coastal zones are considered to be highly vulnerable to the effects of climate change, such as erosion, flooding, and storms, including sea level rise (SLR). The effects of rising sea levels endanger several nations, including Indonesia, and it poten...

Traditional forest inventories are based on field surveys of established sample plots, which involve field measurements of individual trees within a sample plot and the selection of proper allometric equations for tree volume calculation. Thus, accur...

Extreme precipitation events can lead to severe mountain hazards, and they have therefore received widespread attention. The study of extreme precipitation can be hindered by the insufficient number and uneven distribution of rain gauge stations, esp...

In the original article [...]

Calibration and reconstruction of time series DMSP-OLS nighttime light images are critical for understanding urbanization processes and the evolution of urban spatial patterns from a unique perspective. In this study, we developed an improved stepwis...

The availability of the new generation Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06 products facilitates the utility of long-term higher spatial and temporal resolution precipitation data (0.1° × 0....

Ground moving targets (GMT), due to the existence of velocity in range and azimuth direction, will lead to the deviation from their true position and defocus in the azimuth direction during the synthetic aperture radar (SAR) imaging process. To addre...

Advancements in remote sensing have led to the development of Geographic Object-Based Image Analysis (GEOBIA). This method of information extraction focuses on segregating correlated pixels into groups for easier classification. This is of excellent...

The Pan-Third Pole (PTP) region, one of the areas with the most intense global warming, has seen substantial changes in vegetation cover. Based on the GIMMS NDVI3g and meteorological dataset from 1982 to 2015, this study evaluated the spatio-temporal...

Along with the development of remote sensing technology, the spatial–temporal variability of vegetation productivity has been well observed. However, the drivers controlling the variation in vegetation under various climate gradients remain poo...

Combining remote sensing images with deep learning algorithms plays an important role in wide applications. However, it is difficult to have large-scale labeled datasets for remote sensing images because of acquisition conditions and costs. How to us...

It is very useful for adaptive optics (AO) systems to have appropriate knowledge of optical turbulence. However, due to the limitations of space and time, it is difficult to obtain turbulence parameters, especially in the far sea area. In this paper,...

Monitoring and early warning systems for landslides are urgently needed worldwide to effectively reduce the losses of life and property caused by these natural disasters. Detecting the precursors of giant landslides constitutes the premise of landsli...

After recovering from the Rwanda Genocide in the last century, Rwanda is experiencing rapid economic growth and urban expansion. With increasing demand for electricity and a strong desire to achieve the Sustainable Development Goals (SDGs), it is sig...

Digital/true orthoimage maps (D/TOMs) are one of the most important forms of national spatial data infrastructure (NSDI). The traditional generation of D/TOM is to orthorectify an aerial image into its upright and correct position by deleting displac...

Sentinel-2 NDVI and surface reflectance time series have been widely used in various geoscience research, but the data is deteriorated or missing due to the cloud contamination, so it is necessary to reconstruct the Sentinel-2 NDVI and surface reflec...

Target localization is a fundamental problem in array signal processing. The problem of locating near-field targets with multiple-input multiple-output (MIMO) radar has been studied extensively; however, most of the conventional matrix-based approach...

Clustering of multi-source geospatial big data provides opportunities to comprehensively describe urban structures. Most existing studies focus only on the clustering of a single type of geospatial big data, which leads to biased results. Although mu...

Light Detection and Ranging (LiDAR) data collected by mobile mapping systems (MMS) have been utilized to detect lane markings through intensity-based approaches. As LiDAR data continue to be used for lane marking extraction, greater emphasis is being...

There were significant differences in the dominant driving factors of the change process of different types of wetlands in the Yellow River delta. In addition, to our knowledge, the optimal classification feature sets with the Random Forest algorithm...

Forest fires destroy the ecological environment and cause large property loss. There is much research in the field of geographic information that revolves around forest fires. The traditional forest fire prediction methods hardly consider multi-sourc...

Hyperspectral sharpening has been considered an important topic in many earth observation applications. Many studies have been performed to solve the Visible-Near-Infrared (Vis-NIR) hyperpectral sharpening problem, but there is little research relate...

We present a novel optomechanical inertial sensor for low-frequency applications and corresponding acceleration measurements. This sensor has a resonant frequency of 4.715 (1) Hz, a mechanical quality factor of 4.76(3) × 10⁵, a test mass of 2.6...

The U.S. Forest Service, Forest Inventory and Analysis (FIA) program is tasked with making and reporting estimates of various forest attributes using a design-based network of permanent sampling plots. To make its estimates more precise, FIA uses a t...

The gas plume is a direct manifestation of sea cold seep and one of the most significant symbol indicators of the presence of gas hydrate reservoirs. The multibeam water column (MWC) data can be used to extract and identify the gas plume efficiently...

A surface-based duct (SBD) is an abnormal atmospheric structure with a low probability of occurrence buta strong ability to trap electromagnetic waves. However, the existing research is based on the assumption that the range direction of the surface...

Due to the cost of acquiring and labeling remote sensing images, only a limited number of images with the target objects are obtained and labeled in some practical applications, which severely limits the generalization capability of typical deep lear...

Open-pit mining and reclamation damage the land, resulting in unknown and significant changes to the regional ecology and ecosystem services. Surface mining restoration procedures necessitate a significant amount of money, typically at an unclear cos...

In this work, statistical analysis of the main ionospheric trough was performed using K-band ranging system (KBR) measurements from the GRACE satellite constellation from 2002 to 2015. The investigated period covers high- and low-solar-activity condi...

Conservation easements (CEs) play an important role in the provision of ecological services. This paper aims to use the open-access Sentinel-2 satellites to advance existing conservation management capacity to a new level of near-real-time monitoring...

With the rapid development of the remote sensing monitoring and computer vision technology, the deep learning method has made a great progress to achieve applications such as earth observation, climate change and even space exploration. However, the...

Unsupervised band selection has gained increasing attention recently since massive unlabeled high-dimensional data often need to be processed in the domains of machine learning and data mining. This paper presents a novel unsupervised HSI band select...

Unmanned aerial vehicles (UAVs) are widely used in Internet-of-Things (IoT) networks, especially in remote areas where communication infrastructure is unavailable, due to flexibility and low cost. However, the joint optimization of locations of UAVs...