Results 41 to 50 of about 1,147 (129)

Predicting Seismic Intensity Using Machine Learning With Ancillary Data: Evidence From Destructive Earthquakes in China

Engineering Reports, Volume 8, Issue 9, September 2026.
A machine learning framework integrating multisource seismic, social, and geographic data accurately predicts kilometer‐scale seismic intensity, enabling rapid postearthquake damage assessment during data‐scarce “black‐box” periods. ABSTRACT Accurate and rapid assessment of seismic intensity is crucial for postearthquake emergency response.
Ma Yuan, Yu Jianming, Zhao Hui, Gong Huiyuan, Zhang Jianying   +4 more
wiley   +1 more source

Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH₄ Product

Remote Sensing
The TROPOMI XCH4 data product requires rigorous cloud filtering to achieve a product accuracy of
Tobias Borsdorff, Mari C. Martinez-Velarte, Maarten Sneep, Mark ter Linden, Jochen Landgraf   +4 more
doaj   +1 more source

Inter-Comparison of S-NPP VIIRS and Aqua MODIS Thermal Emissive Bands Using Hyperspectral Infrared Sounder Measurements as a Transfer Reference

Remote Sensing, 2016
This paper compares the calibration consistency of the spectrally-matched thermal emissive bands (TEB) between the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and the Aqua Moderate Resolution ...
Yonghong Li, Aisheng Wu, Xiaoxiong Xiong
doaj   +1 more source

Post-Earthquake Night-Time Light Piecewise (PNLP) Pattern Based on NPP/VIIRS Night-Time Light Data: A Case Study of the 2015 Nepal Earthquake

Remote Sensing, 2020
Earthquakes are unpredictable and potentially destructive natural disasters that take a long time to recover from. Monitoring post-earthquake human activity (HA) is of great significance to recovery and reconstruction work.
Shengjun Gao, Yunhao Chen, Long Liang, Adu Gong   +3 more
doaj   +1 more source

U‐Net Based Machine Learning for Identification of Auroras in Space‐Based Images

Journal of Geophysical Research: Space Physics, Volume 131, Issue 9, September 2026.
Abstract We use a Semantic Segmentation based U‐Net model to predict the appearance of various classifications of aurora present in near‐infrared images from the Fast Auroral Imager (FAI) onboard the CASSIOPE satellite. We manually labeled pixels from a set of 4091 FAI near‐infrared images into 7 different classes: no aurora, contaminated, diffuse ...
Amit Kain, Matthew G. Finley, Andrew D. Howarth, Andrew W. Yau, David M. Miles   +4 more
wiley   +1 more source

Analysis of the heat sources detected by MODIS and VIIRS satellites in central western Amazonia

Biodiversidade Brasileira, 2020
Forest fires are characterized as environmental disasters and depending on its gravity they destroy the entire forests causing ecosystem losses. The quality of the detection of heat sources in the satellite is relevant to verify the sources of fires and
Vanusa de Souza Pacheco Hoki, Luciana Sanches, Pricila Juliana de Souza, Ana Carolina Freitas da Silva Taques, Jonathan Willian Zangeski Novais   +4 more
doaj   +3 more sources

A temporally consistent global 500 m-resolution monthly VIIRS-like nighttime light dataset (1992–2024) [PDF]

Earth System Science Data
Nighttime light (NTL) data serve as critical indicators of human activities and have been widely applied in urbanization monitoring and socioeconomic analyses.
H. Cheng, H. Cheng, M. Geng, X. Li, X. Li, S. Li, M. Zhao, C. Lin, C. Lin, J. Wang, P. Gong, P. Gong, Y. Zhou, Y. Zhou, Y. Zhou, Y. Zhou   +15 more
doaj   +1 more source

Carbon Emissions From Different Functional Zones of Construction Land in the Yellow River Basin Based on Nighttime Light Data and POI Data

Land Degradation &Development, Volume 37, Issue 14, Page 10387-10404, 30 August 2026.
ABSTRACT The Yellow River Basin is a critical region for ecological conservation and sustainable development in China. It also serves as a core area for carbon emissions across various functional zones of construction land. Accurately understanding carbon emissions from various types of construction land in the Yellow River Basin is crucial for China ...
Xi Chen, Wei Wei, Lei He, Xiaoxu Wei, Binbin Xie, Junju Zhou, Wei Shi, Yanli Pei   +7 more
wiley   +1 more source

THE CONSTRUCTION OF TIME SERIES SIMULTANEOUSLY USING SUOMI NPP VIIRS AND TERRA/AQUA MODIS REMOTE SENSING DATA

InterCarto. InterGIS, 2017
The new generation sensor VIIRS of Suomi NPP satellite has replaced MODIS sensors of TERRA & AQUA. VIIRS spectral channels are not full analogues of MODIS, and their spatial resolution differs slightly.
D. V. Pchel’nikov, N. N. Dobtretsov
doaj   +1 more source

Model Sensitivities of Biomass‐Burning Aerosol Chemical Aging, Sulfate Formation, and Cloud Droplet Activation in the Southeastern Atlantic Using CESM and E3SM

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 15, 16 August 2026.
Abstract Biomass‐burning smoke drives large uncertainty in climate projections of the Earth's radiative balance. This is due to the chemical and physical evolution of smoke and its impact on clouds and radiation. Here we focus on the southeastern Atlantic region and its inflow of African biomass‐burning smoke during August 2017.
Calvin Howes, Pablo Saide, Mary Barth, Yan Feng, Jens Redemann, Arthur J. Sedlacek III, Manish Shrivastava, Wenfu Tang, Rob Wood, Maria Zawadowicz, Paquita Zuidema   +10 more
wiley   +1 more source