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Big Earth Data, Pp 1-20 (2026)
Scopus
ISSN 2574-5417 · Taylor & Francis Group · 349 artikel di indeks
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Artikel Jurnal
Incorporating remote sensing measurement error for forest inventory
Remotely sensed data are increasingly used with model-based inference to estimate forest population characteristics (e.g., areal means). However, at-sensor radiance affected by measurement errors has inherent variations over time, space and spectrum, violating the stationary data assumption in…
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The uncertainties and potential of locational-based social media for floodscape mapping
During a flood event, there has been an increasing number of observations recorded on Locational-based Social Media (LBSM) about the floodscape in near-real-time. Using the LBSM data harvested from X during Hurricane Harvey in 2017, this research adopted a computer vision (CV) approach that…
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Vector dataset of rivers, lakes/reservoirs and their spatial connectivity in High Mountain Asia
Significant changes in snow, glaciers, and the water system across High Mountain Asia (HMA) under global warming have intensified regional water system instabilities. Accurate mapping of the spatial distribution and connectivity of rivers and lakes is essential for understanding and managing the…
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TSDP: Automatic preprocessing and downloading of Landsat 1–9, Sentinel-2, and other remote sensing data for multi-resolution time-series image analysis
The Time-Series Data Downloader and Preprocessor (TSDP) is an open-source Python tool designed to streamline the acquisition and preprocessing of multispectral satellite imagery for time-series analysis. Built on Google Earth Engine (GEE), TSDP supports Landsat 1–9—from Landsat MSS to Landsat…
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A high-resolution Sentinel-2 dataset of Antarctic coastal snow algal dynamics (2018–2025) generated using cloud-scale parallel processing
Antarctic coastal snow algal blooms are ecologically important, but remain poorly documented at continental scales because of logistical constraints on field observations. Here, we present a high-resolution, multi-season Sentinel-2 dataset of Antarctic coastal snow algal blooms covering the western…
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A high-resolution, multi-decadal outgoing longwave radiation product from MODIS: algorithm and product
Current global Outgoing Longwave Radiation (OLR) products often face a trade-off between spatial resolution and temporal frequency, constraining their utility in monitoring rapid weather dynamics and fine-scale climate processes. To bridge this gap, this study presents a generation and…
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Global flood research patterns, disparities, and risk–attention mismatches revealed by large language models
Floods are among the most destructive natural hazards with growing social consequences. However, global flood research has exhibited pronounced regional disparities in thematic focus and scholarly attention, reinforcing unequal risk perceptions. This study analyzes 64,989 flood-related publications…
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Comparing Analog Ensemble and Corrective Diffusion for Western US precipitation downscaling from GraphCast
In the time of big geodata, uncertainty quantification and reliable forecasts are crucial for decision making, especially when the resolution is limited. This study investigates uncertainty quantification in precipitation forecasting by applying two downscaling methods, Analog Ensemble (AnEn) and…
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Uncertainty quantification in geospatial AI/ML applications: methods, metrics, and open-source support with an air quality use case
The adoption of AI/ML models in geospatial applications faces challenges related to trustworthiness and reliability due to uncertainties in model processing and datasets. Such uncertainties are exacerbated by the complexity of Earth’s systems and constraints, such as data quality and measurement…
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Quality assessment and control of urban environmental sensors using physical thresholding and machine learning-based probabilities
Reliable environmental sensor data are fundamental for accurate urban climate modeling and evidence-based planning. Conventional physics-based quality control (QC) methods apply fixed thresholds to flag physically implausible values, but they often fail to detect subtle, context-dependent…
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Evaluating the quality of VGI and authoritative data in red-crowned crane conservation: a comparative study
Volunteered Geographic Information (VGI) has emerged as a valuable resource in citizen science, yet concerns about its data quality remain. While prior studies have focused on specific data types or platforms, few have systematically evaluated heterogeneous VGI datasets within a unified application…
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An interactive toolkit based on Google Earth Engine for visual interpretation and analysis of land cover and land cover changes
Accuracy assessment is an indispensable part of land cover change monitoring, the core of which is obtaining high-quality validation datasets. This study proposes a novel and online interactive toolkit (Visual Interpretation Toolkit) for collecting validation datasets across space and time based on…
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Unveiling spatial heterogeneity and nonlinearity of OpenStreetMap building completeness in China: an assessment using authoritative benchmarks
While OpenStreetMap (OSM) serves as a critical infrastructure for urban management and emergency response, the completeness of its building data remains spatially uneven. The current research lacks nationwide empirical evaluations grounded in authoritative, high-precision reference data…
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Crop stubble retention categories recognition from multi-modal remote sensing imageries: a spatiotemporal cube approach
The degradation of croplands due to traditional tillage practices is a significant challenge for sustainable agriculture. Crop stubble retention (CSR), as a key conservation tillage method, is crucial for evaluating cropland sustainability, and the efficient acquisition of CSR category information…
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High-resolution (1 km) gridded dataset of premature deaths attributed to PM2.5 exposure in China (2000–2019)
Fine particulate matter (PM2.5) pollution is a major environmental risk factor contributing to multiple diseases and premature mortality. Although numerous studies have examined the health effects of PM2.5, a critical data gap remains in the availability of high-resolution, openly accessible…
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GeoAutoModuler: a knowledge–enhanced large language model for heterogeneous geospatial code understanding and knowledge extraction
In the era of geospatial big data, massive geospatial modeling scripts have accumulated across the Internet and have become essential carriers of modeling knowledge. However, these scripts are often unstructured and heterogeneous in terms of semantics and logic, making their embedded knowledge…
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Evaluation of ten satellite-based and reanalysis precipitation datasets on a daily basis for Czechia (2001–2021)
This study assesses the accuracy of ten satellite-based and reanalysis precipitation datasets available in Google Earth Engine (GEE) using in-situ rain gauge measurements across Czechia, Central Europe, from 2001 to 2021. The gauge-adjusted GSMaP dataset (GSMaPGA) was the most accurate dataset…
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An LLM-based multi-agent system for remote sensing analysis
Remote sensing analysis converts remotely sensed data into actionable insights across diverse fields. However, traditional data-driven approaches frequently overlook the technical challenges encountered by end-users lacking remote sensing expertise. To address this issue, we proposed a multi-agent…
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GeoJSON agents: a multi-agent LLM architecture for geospatial analysis—function calling vs. code generation
Large Language Models (LLMs) have demonstrated substantial progress in task automation and natural language understanding. However, without domain expertise in geographic information science (GIS), they continue to encounter limitations including reduced accuracy and unstable performance when…
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Geospatial data and workflows for environmental and sustainability compliance reporting: including the private sector
Geospatial data and workflows are rapidly becoming central to environmental and sustainability compliance reporting, but the relationship between evolving EU regulation and available Earth Observation (EO) and GIS technologies remains poorly systematized. Focusing on the European Union and…