Results 201 to 210 of about 159,878 (310)
Abstract Accurate retrieval of satellite‐derived aerosol optical depth (AOD) is critical for air quality forecasting, especially when AOD is assimilated into models. However, if retrieval errors in the satellite‐derived AOD are not corrected or characterized, they can lead to false analysis increments and ultimately degrade the quality of data ...
Joonhee Kim +6 more
wiley +1 more source
Global urban vegetation exhibits divergent thermal effects: From cooling to warming as aridity increases. [PDF]
Guo Z +14 more
europepmc +1 more source
Abstract Biomass burning aerosols influence atmospheric temperatures by absorbing solar radiation, thereby altering the contrast between day and night temperatures. This study investigates the correlation between these aerosols and day‐night (D‐N) temperature changes over India by applying principal component analysis (PCA) in long‐term (2003–2021 ...
Lakhima Chutia +5 more
wiley +1 more source
Predictive Modelling of Tick Distribution: A Machine Learning Approach to Ixodes ricinus Abundance
ABSTRACT The resurgence of tick‐borne diseases necessitates predictive frameworks that integrate both high accuracy and ecological relevance. This study develops a comprehensive machine learning pipeline to forecast the occurrence of Ixodes ricinus, a principal tick vector in Europe, leveraging high‐dimensional climatic, environmental, and land‐use ...
Kruttika Jamalpuram +6 more
wiley +1 more source
Spatiotemporal Variation of Burnt Area Detected from High-Resolution Sentinel-2 Observation During the Post-Monsoon Fire Seasons of 2022-2024 in Punjab, India. [PDF]
Arbain AA, Imasu R.
europepmc +1 more source
A 25-year assessment of aerosol dynamics and environmental drivers in Iran's Lakes and wetlands. [PDF]
Ebrahimi-Khusfi Z +3 more
europepmc +1 more source
Exploring the Use of MODIS NDVI-Based Phenology Indicators for Classifying Forest General Habitat Categories [PDF]
Nicola Clerici +2 more
openalex +1 more source
Mangrove Phenology From Scale, Data and Species Perspectives
This study investigates mangrove phenology in the northern subtropical zone of Zhanjiang, China, using satellite‐derived Enhanced Vegetation Index (EVI) time series. Our results reveal clear annual phenological patterns with significant variation across species and datasets, highlighting the superior sensitivity of Sentinel‐2 over Landsat 8.
Yuhang Wang +5 more
wiley +1 more source

