701 hasil
Menampilkan 1–20 · 0,58 detik · RSS
European Journal of Remote Sensing
Scopus
ISSN 2279-7254 · Taylor & Francis Group · 701 artikel di indeks
-
Artikel Jurnal
Joint use of multi-temporal satellite interferometric and geotechnical data for monitoring and investigating the kinematics of an urbanized relict landslide
The residual kinematics of relict landslides involving built areas can represent a severe source of risk. Such slope movements can be monitored through ground-based geotechnical and remote sensing techniques, like interferometric synthetic aperture radar (InSAR). In this study, to investigate the…
-
Artikel Jurnal
Assessment of building extraction and geometric corrections from UAV image using Mask R-CNN deep neural network algorithm
High-resolution spatial data acquired by unmanned aerial vehicles (UAVs) are increasingly used as a method of extracting buildings in urban areas, supporting planning, disaster management, and navigation-based applications. This research applies the Mask R-CNN deep learning algorithm to…
-
Artikel Jurnal
Spatiotemporal variations of PM2.5 concentrations in the Fen–Wei Plain of China between 2015 and 2020 based on MAIAC
This paper aims to study the spatiotemporal variations in PM2.5 concentrations between 2015 and 2020 in the Fen–Wei Plain. The AOD products of MCD19A2 based on MAIAC were utilized. Besides of AOD, some of its arithmetic values were also introduced to determine the best variable. AOD was determined…
-
Artikel Jurnal
Method for estimating dimensions and visualising changes in multi-epoch point clouds
The increasing amount of 3D data collected accumulates in datasets that can be used for change detection. In particular, multi-epoch datasets representing a single scene enable assessing rates of change. To track individual changes, points have to be identified. However, in unstructured point…
-
Artikel Jurnal
Spatio-temporal dynamics and future projections of carbon storage in Ziwuling, China, under rapid urbanization
The Ziwuling region, a critical ecological barrier on the Loess Plateau, was analyzed using land use and land cover (LULC) data from 1990, 2005, and 2020 to assess three decades of carbon storage dynamics via five methods: land use classification and transfer matrix, SHapley Additive exPlanations…
-
Artikel Jurnal
Riparian vegetation dynamics using satellite imagery and integrated spectral and spatial features: a case study of the Slovak Danube
Monitoring riparian vegetation with up-to-date technologies, such as remote sensing and machine learning, is emphasized by their extensive and dynamic nature. This study evaluates the spatiotemporal dynamics of vegetation in the Slovak Danube riparian zone from 2004 to 2022 using a multi-sensor…
-
Artikel Jurnal
Accounting for vertical leaf heterogeneity, sun-view geometry, and foliage traits to retrieve biophysical variables of Eucalyptus plantations using Sentinel 2 images
Estimating biophysical forest features from optical reflectance is a key approach for enhancing large-scale forest management. The present study estimates Leaf Area Index (LAI), leaf chlorophyll content (Cab), Leaf Mass per Area (LMA) and Equivalent Water Thickness (EWT) in different Eucalyptus sp…
-
Artikel Jurnal
Four decades of suspended particulate matter concentrations in the Po River revealed by landsat satellites
Suspended particulate matter (SPM) is a key indicator of both sediment transport and water quality in river environments. In this study, a comprehensive long-term analysis of SPM concentrations in the Po River, the longest in Italy, was carried out over the period 1984-2024 by applying a…
-
Artikel Jurnal
Cross-domain few-shot hyperspectral image classification with frequency-aware augmentation
Cross-domain few-shot hyperspectral image classification remains challenging due to limited labeled samples and domain shifts between source and target domains. This paper proposes a Frequency-Aware Augmentation Cross-Domain Few-Shot Learning framework (FAA-CDFSL) to enhance domain generalization…
-
Artikel Jurnal
Integrating image filters and confidence thresholds to improve cropland data layer for deep learning–based cropland segmentation
Accurate cropland segmentation is essential for agricultural monitoring, with deep learning (DL) models relying heavily on training data quality. The USDA’s Cropland Data Layer (CDL) is widely used for this purpose, but it includes classification errors and noise. Although a confidence layer is…
-
Artikel Jurnal
Characterising the ill-posedness of PROSAIL inversion for biophysical parameter retrieval
The inversion of PROSAIL, a radiative transfer model widely used for vegetation parameter retrieval, is often considered to be an ill-posed problem. However, beyond this general label, the ill-posedness and its characteristics are not well understood. This study aims to theoretically characterise…
-
Artikel Jurnal
Advancing spatio-temporal fusion with spectral super-resolution for enhancing remote sensing of marine debris and landfills
Monitoring environmental challenges such as landfill expansion and marine debris accumulation requires high-resolution satellite imagery with enhanced spectral, spatial, and temporal details. However, remote sensing systems often face trade-offs between these resolutions, limiting their…
-
Artikel Jurnal
Satellite-based vessel detection under turbulence and jitter: a degradation-aware comparison
Maritime domain awareness increasingly relies on satellite-based Earth observation (EO) for wide-area vessel monitoring. Low Earth orbit (LEO) platforms enable flexible acquisition, but optical imagery can be degraded by atmospheric turbulence and platform jitter. This paper presents a…
-
Artikel Jurnal
Comparison of shallow and deep learning methods for LiDAR-based aboveground biomass estimation of eucalyptus plantations in Ibu Kota Nusantara, East Kalimantan Province, Indonesia
Forests store substantial carbon in aboveground biomass (AGB), making accurate estimation essential for carbon accounting and climate change mitigation. This study integrates LiDAR-derived metrics, including canopy height metrics (CHM), statistical height metrics (SHM), intensity metrics (IM) and…
-
Artikel Jurnal
Synthetic generation of hyperspectral data from multispectral data through generative adversarial network model
Remote sensing applications utilizing hyperspectral imaging technology have demonstrated their capability to deliver detailed and comprehensive analytical results in earth observation studies, significantly outperforming traditional multispectral data approaches. One constraint of these methods…
-
Artikel Jurnal
Automatic evergreen forest mapping based on Harmonised Landsat Sentinel-2 and existing broad-category land cover product within Google Earth Engine
Evergreen forests retain green foliage throughout the year and exhibit distinct phenological and biophysical characteristics. However, although many regional and global land cover products are available at 30 m resolution, most adopt coarse classification schemes and do not explicitly distinguish…
-
Artikel Jurnal
Evaluating the maximum cross-correlation method for near-real-time ocean currents estimation using multi-platform AVHRR thermal imagery
The study evaluates the performance of the MCC algorithm for near-real-time (NRT) ocean surface current estimation using TIR imagery acquired from the AVHRR sensor onboard EUMETSAT and NOAA satellites. We focused on image pairs with short time-lags (
-
Artikel Jurnal
Implementation of machine learning for wind speed retrieval from HY-2B altimeter
This study presents a novel machine learning algorithm for wind speed retrieval using the Haiyang-2B (HY-2B) altimeter. To construct a high-fidelity reference dataset, a wind field over the Northwest Pacific Ocean with a spatial resolution of 0.05° and an hourly temporal resolution was hindcast by…
-
Artikel Jurnal
Geometric accuracy analysis of Jilin-1 satellite images using different mathematical models
Chinese high-resolution Earth observation satellites have developed rapidly over the last two decades and have made continuous progress in terms of their mapping capabilities. In this study, we analyzed the geometric accuracy potential of Jilin-1 satellite imagery covering the area around the…
-
Artikel Jurnal
A google earth engine app to map ground-mounted photovoltaic system and track land use change in Italy
Ground-mounted photovoltaic systems are expanding rapidly to meet decarbonisation targets, but their growth raises concerns about land take, farmland conversion, and biodiversity impacts. Addressing the lack of tools to monitor local land-use change across Italian municipalities, this study…