Rabies re-emergence after long-term disease freedom (Amur Oblast, Russia) by A. D. Botvinkin, I. D. Zarva, I. V. Meltsоv, S. A. Chupin, E. M. Poleshchuk, N. G. Zinyakov, S. V. Samokhvalov, I. V. Solovey, N. V. Yakovleva, G. N. Sidorov, I. A. Boyko, V. G. Yudin, E. I. Andaev, A. Ye. Metlin

“…GIS and open Earth remote sensing data were used to map the rabies cases. …”
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Fiber-tip photonic crystal for real-time referenced biosensing in serum by Mathias Dolci, Paco Dreverman, Mildred S. Cano-Velázquez, Arthur L. Hendriks, Emiel Veth, P.J. van Veldhoven, Andrea Fiore, Peter Zijlstra

“…Fiber optic sensors have become increasingly well-established due to the many advantages they provide such as immunity to electromagnetic interference, multiplexing capabilities, and remote sensing. The coupling of light with a transducer at the tip of the optical fiber enables the detection of physical and biological parameters. 2D photonic crystals (PhC) can be designed to feature guided-mode resonances (GMR) characterized by a strong electric field at the PhC surface, providing a suitable tool for the detection of local refractive index variations (e.g. biomolecule adsorption). …”
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Assessing national exposure to and impact of glacial lake outburst floods considering uncertainty under data sparsity by H. Chen, Q. Liang, J. Zhao, S. B. Maharjan

“…This study aims to exploit remote sensing techniques, well-established Bayesian regression models for estimating glacial lake conditions, cutting-edge flood modelling technology, and open data from various sources to innovate a framework for assessing the national exposure and impact of GLOFs. …”
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Improving wind and power predictions via four-dimensional data assimilation in the WRF model: case study of storms in February 2022 at Belgian offshore wind farms by T. Ivanova, T. Ivanova, S. Porchetta, S. Porchetta, S. Buckingham, G. Glabeke, G. Glabeke, J. van Beeck, W. Munters

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Phosphorus transitions driven by cyclone biparjoy linked middle east North Africa (MENA) and Indian Thar Desert dust storm pathways in Asia’s largest grassland by Rupak Dey, Seema B. Sharma, Mahesh G. Thakkar, Ranjit Kumar Sarangi, Abhiroop Chowdhury, Aliya Naz

“…Spatial and temporal variations in dust emissions were assessed using satellite remote sensing data, while ground truthing was performed for phosphorus content analysis using standard protocols. …”
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Modeling of historical and future changes in temperature and precipitation in the Panj River Basin in Central Asia under the CMIP5 RCP and CMIP6 SSP scenarios by Aminjon Gulakhmadov, Xi Chen, Nekruz Gulahmadov, Muhammmad Rizwan, Manuchekhr Gulakhmadov, Muhammad Umar Nadeem, Moldir Rakhimova, Tie Liu

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Time-series forest age estimation in Xinjiang based on forest disturbance and recovery detection by Lili Zhai, Mei Zan, Mao Ye, Jia Zhou, Cong Xue, Shunfa Yang, Yuntong Liu

“…In 1991, the age of forests in Xinjiang was estimated utilizing the Random Forest (RF) model, incorporating both forest inventory data and remote sensing data. Utilizing Landsat Time Series Stacked (LTSS) Data from 1991 to 2022, the LandTrendr(LT) algorithm was applied to identify forest disturbance and recovery events from 1992 to 2022 using the Google Earth Engine (GEE) platform. …”
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Impacts of meteorology and emission reductions on haze pollution during the lockdown in the North China Plain by L. Liu, L. Liu, X. Long, Y. Li, Y. Li, Z. Zang, Z. Zang, F. Wang, Y. Han, Z. Bao, Y. Chen, T. Feng, J. Yang

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Characteristics of Land Use Change and Evaluation of Ecological Sensitivity in Chongqing by XIE Xianjian, GOU Qiantao, WU Han

“…[Methods] A comprehensive assessment of the ecological sensitivity of Chongqing City was conducted by using remote sensing data from the years 2000, 2010 and 2020. …”
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Unleashing the potential of geostationary satellite observations in air quality forecasting through artificial intelligence techniques by C. Zhang, X. Niu, H. Wu, Z. Ding, K. L. Chan, J. Kim, T. Wagner, C. Liu, C. Liu, C. Liu

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Snow depth estimation on leadless landfast ice using Cryo2Ice satellite observations by M. Saha, J. Stroeve, J. Stroeve, D. Isleifson, J. Yackel, V. Nandan, V. Nandan, J. C. Landy, H. M. Lam

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Using satellite-based Sun-induced chlorophyll fluorescence and spectral reflectance for improving terrestrial CO2 flux estimates of India by Aparnna Ravi, Dhanyalekshmi Pillai, Christoph Gerbig, Stephen Sitch, Sönke Zaehle, Vishnu Thilakan, Chandra Sekhar Jha, Thara Anna Mathew

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Unraveling the interplay between NDVI, soil moisture, and snowmelt: A comprehensive analysis of the Tibetan Plateau agroecosystem by Di Wei, Lin Yan, Ziqi Zhang, Jia Yu, Xue’er Luo, Yun Zhang, Bo Wang

“…This study integrates MODIS remote sensing images and ERA5-Land meteorological reanalysis datasets to establish a ternary system encompassing NDVI, soil moisture, and snowmelt. …”
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Use of supervised and unsupervised approaches to make zonal application maps for variable-rate application of crop growth regulators in commercial cotton fields by Maria C. da S. Andrea, Cristiano F. de Oliveira, Fabrícia C. M. Mota, Rafael C. dos Santos, Edilson F. Rodrigues Junior, Lucas M. Bianchi, Rodrigo S. de Oliveira, Caio M. de Gouveia, Victor G. S. Barbosa, Marco A. Bispo E Silva

“…Subsequently, a SUF (based on historical data between 2020–2021 to 2022–2023 agricultural seasons) was developed to predict plant height using remote sensing and phenology data, aiming to replicate same zonal maps but without relying on direct field measurements of plant height. …”
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Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4) by J. Feng, C. Zhao, C. Zhao, C. Zhao, C. Zhao, C. Zhao, C. Zhao, Q. Du, Z. Yang, C. Jin

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Lidar estimates of birch pollen number, mass, and CCN-related concentrations by M. Filioglou, P. Tiitta, P. Tiitta, X. Shang, A. Leskinen, P. Ahola, S. Pätsi, A. Saarto, V. Vakkari, V. Vakkari, U. Isopahkala, M. Komppula

“…Recently, lidars have been employed to identify and monitor pollen particles in the atmosphere, an understudied aerosol particle with health and possibly climate implications. Lidar remote sensing of pollen is an emerging research field, and in this study, we present for the first time retrievals of particle number, mass, CCN, giant CCN (GCCN), and ultragiant CCN (UGCCN) concentration estimations of birch pollen derived from polarization lidar observations and specifically from a PollyXT lidar and a Vaisala CL61 ceilometer at 532 and 910 nm, respectively.…”
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An urban land surface temperature and emissivity separation algorithm from ASTER TIR data and its application by Jinglun Li, Kun Li, Yonggang Qian, Xianhui Dou, Qijin Han, Jian Zeng, Hang Zhao, Qiongqiong Lan, Zhaopeng Xu, Jiayi Bai, Baoan Wei, Xining Liu, Feng Wang, Juntao Yang, Yueming Wang

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Comprehensive Evaluation and Error-Component Analysis of Four Satellite-Based Precipitation Estimates against Gauged Rainfall over Mainland China by Guanghua Wei, Haishen Lü, Wade T. Crow, Yonghua Zhu, Jianbin Su, Li Ren

“…Moreover, V06C and V06UC rainfall estimates are compared against the Precipitation Estimation from Remotely Sensed Imagery using Artificial Neural Networks (PERSIANN)-Climate Data Record (CDR) and the Climate Prediction Center morphing technique (CMORPH) gauge-satellite blended (BLD) products. …”
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Fine-scale satellite-based monitoring of temperature and vegetation cover in microclimates, distribution ranges, and landscape connectivity for Neurergus kaiseri (Kaiser’s mountain... by Peyman Karami, Sajad Tavakoli, Mina Esmaeili

“…However, a gap remains in monitoring time-specific environmental indicators using fine-scale satellite remote sensing (SRS). This study integrates spatiotemporal indicators with fine-scale SDMs to provide insights into Neurergus kaiseri’s response to vegetation cover and temperature changes during the breeding season, informing conservation and management strategies.Data on localities, habitat suitability, and population cores connectivity from Karami et al. (2024) were divided into five sub-basins in Iran. …”
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