Improving H2RG Performance in SPHEREx Brassboard Model by Chi H. Nguyen, Phillip Korngut, C. Darren Dowell, James Bock, Jill Burnham, Samuel Condon, Walter Cook, Grigory Heaton, Howard Hui, Branislav Kecman, Hiromasa Miyasaka, Kenneth Manatt, Hien T. Nguyen, Stephen Padin, Marco Viero

“…Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer is an upcoming NASA satellite mission to study the physics of inflation, the history of galaxy formation, and the abundance of biogenic ices in the Milky Way, obtaining the first all-sky spectroscopic survey at infrared wavelengths 0.75–5.0 μ m. …”
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Synergistic mapping of urban tree canopy height using ICESat-2 data and GF-2 imagery by Xiaodi Xu, Ya Zhang, Peng Fu, Chaoya Dang, Bowen Cai, Qingwei Zhuang, Zhenfeng Shao, Deren Li, Qing Ding

“…As a result, the UTCH model created by fusing remote sensing spectral data with satellite-based lidar data can accurately estimate UTCH and offer a practical solution for predicting UTCH on a regional or even global scale.…”
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Climate change impacts on shoreline migration and community livelihood resilience: evidence from coastal Bangladesh by Md. Tariqul Islam, Md. Tariqul Islam, Md. Monabbir Hossain, Nur Mohammad Ha-Mim, Md. Zakir Hossain, Sujit Kumar Sikder

“…Historical data and more recent satellite remote sensing imagery analysis identified that the shrinking of the delta system has resulted from the migration of the shorelines at the mouth of the river system. …”
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Modeling the Dynamic Global Distribution of the Ring Current Oxygen Ions Using Artificial Neural Network Technique by Qiushuo Wang, Chao Yue, Jinxing Li, Jacob Bortnik, Donglai Ma, Chae‐Woo Jun

“…Abstract The ring current is an important component of the Earth's near‐space environment, as its variations are the direct driver of geomagnetic storms that can disrupt power grids, satellite communications, and navigation systems, thereby impacting a wide range of technological and human activities. …”
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Large-scale mapping of plastic-mulched land from Sentinel-2 using an index-feature-spatial-attention fused deep learning model by Lizhen Lu, Yunci Xu, Xinyu Huang, Hankui K. Zhang, Yuqi Du

“…Accurate and timely mapping of Plastic-Mulched Land (PML) on a large-scale using satellite data supports precision agriculture and enhances understanding the PML's impacts on regional climate and environment. …”
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Lake Iriqui’s Remarkable Revival: Field Observations and a Google Earth Engine Analysis of Its Recovery After over Half a Century of Desiccation by Adil Moumane, Tarik Bahouq, Ahmed Karmaoui, Dahmane Laghfiri, Mohamed Yassine, Jamal Al Karkouri, Mouhcine Batchi, Mustapha Faouzi, Mohamed Boulakhbar, Ali Ait Youssef

“…The revival was monitored using satellite imagery from Landsat 8 and 9 and Sentinel-2A, processed through Google Earth Engine (GEE), with the Normalized Difference Water Index (NDWI) applied to detect water presence. …”
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An approach for accurate identification and monitoring of species in mangrove forests based on multi-source spectral data and deep learning by Monterrubio-Martínez Erandi, Trujillo-Acatitla Rubicel, Tuxpan-Vargas José, Moreno-Casasola Patricia

“…Furthermore, the multispectral data obtained from the Sentinel-2 satellite was employed for the training of multilayer perceptron models (MLP) that are capable of accurately mapping mixed and monospecific mangrove forests. …”
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Normalized difference vegetation index prediction using reservoir computing and pretrained language models by John Olamofe, Ram Ray, Xishuang Dong, Lijun Qian

“…In this study, we examined plant health prediction through the Normalized Difference Vegetation Index (NDVI) calculated from satellite image derived reflectance values in the near-infrared and red spectra. …”
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Improvement in the Accuracy of the Postclassification of Land Use and Land Cover Using Landsat 8 Data Based on the Majority of Segment-Based Filtering Approach by Fajar Yulianto, Gatot Nugroho, Galdita Aruba Chulafak, Suwarsono Suwarsono

“…Three digital classification approaches, namely, maximum likelihood (ML), random forest (RF), and the support vector machine (SVM), were applied to test the improvement in the accuracy of LULC postclassification using the MaSegFil approach, based on annual cloud-free Landsat 8 satellite imagery data from 2019. The results of the accuracy assessment for the ML, RF, and SVM classifications before implementing the MaSegFil approach were 73.6%, 77.7%, and 77.5%, respectively. …”
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A comprehensive global mapping of offshore lighting by C. D. Elvidge, T. Ghosh, N. Chatterjee, N. Chatterjee, M. Zhizhin, M. Zhizhin, P. C. Sutton, M. Bazilian

“…<p>We present the first comprehensive multiyear global mapping of offshore lighting structures derived from low-light imaging satellite observations collected at night. The sensor is the day–night band (DNB) flown as part of the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS). …”
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Jitter Across 15 yr: Leveraging Precise Photometry from Kepler and TESS to Extract Exoplanets from Radial Velocity Time Series by Corey Beard, Paul Robertson, Jack Lubin, Te Han, Rae Holcomb, Pranav Premnath, R. Paul Butler, Paul A. Dalba, Brad Holden, Cullen H. Blake, Scott A. Diddams, Arvind F. Gupta, Samuel Halverson, Daniel M. Krolikowski, Dan Li, Andrea S.J. Lin, Sarah E. Logsdon, Emily Lubar, Suvrath Mahadevan, Michael W. McElwain, Joe P. Ninan, Leonardo A. Paredes, Arpita Roy, Christian Schwab, Gudmundur Stefansson, Ryan C. Terrien, Jason T. Wright

“…We use NEID RVs acquired simultaneously with Transiting Exoplanet Survey Satellite (TESS) photometry, and we perform injection-recovery tests to quantify the efficacy of recent TESS photometry versus archival Kepler/K2 photometry for removing stellar variability from RVs. …”
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Fine-scale forest classification with multi-temporal sentinel-1/2 imagery using a temporal convolutional neural network by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang, Juan Gu

“…However, spectral similarity between different vegetation types and the issue of mixed pixels in medium-resolution satellite imagery remain significant challenges for fine-scale forest classification. …”
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Mapping hierarchical wetland characteristics by optical-SAR integration with collaborative spatial-spectral-temporal learning by Linwei Yue, Meiyue Wang, Chengpeng Huang, Qing Cheng, Qiangqiang Yuan, Huanfeng Shen

“…The learning-based integration of optical and synthetic aperture radar (SAR) satellite imagery is known to be effective in promoting the accuracy of wetland land-cover classification. …”
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Spatio-temporal analysis of litterfall load in the lower reaches of Qarqan and Tarim rivers using BP neural networks by Junyu Xu, Anwar Eziz, Alishir Kurban, Ümüt Halik, Zhiwen Shi, Saif Ullah, Gift Donu Fidelis, Yingdong Ma, Ziwargul Kibir, Toqeer Ahmed, Tim Van de Voorde, Adil Hujashim, Hossein Azadi

“…This study aims to estimate Litterfall load using a BP neural network based on vegetation indices from Landsat 5 and 8 satellite images, litterfall inventory data, slope, and distance to major river tributaries. …”
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Modeling of Ultraviolet Aurora Intensity Associated With Interplanetary and Geomagnetic Parameters Based on Neural Networks by Ze‐Jun Hu, Bing Han, Yisheng Zhang, Huifang Lian, Ping Wang, Guojun Li, Bin Li, Xiang‐Cai Chen, Jian‐Jun Liu

“…Based on Ultraviolet Imager (UVI) data of Polar satellite, we constructed two auroral models by using two different neural networks, that is, the generalized regression neural network (GRNN), and the conditional generation adversarial network (CGAN). …”
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HARNESSING ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AGRICULTURE: A COMPREHENSIVE REVIEW OF AFRICAN APPLICATIONS IN SPATIAL ANALYSIS AND PRECISION AGRICULTURE by Obasi S.N, Tenebe V. A, Obasi C.C, Jokthan G.E, Adjei E.A, Keyagha E.R

“…The project explores adapting precision farming to enhance crop yields, soil health, and mitigate climate change concerns using AI technologies such as sensor-based monitoring and satellite imaging analysis. Examining the socio-economic effects of AI adoption in agriculture in the African context, light is cast on how this technology may promote both economic growth and sustainable development. …”
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The Analysis of Spatiotemporal Changes in Vegetation Coverage and Driving Factors in the Historically Affected Manganese Mining Areas of Yongzhou City, Hunan Province by Jinbin Liu, Zexin He, Huading Shi, Yun Zhao, Junke Wang, Anfu Liu, Li Li, Ruifeng Zhu

“…This paper takes the manganese mining area in Yongzhou City, Hunan Province as a case study and selects multiple periods of Landsat satellite images from 2000 to 2023. By calculating the Normalized Difference Vegetation Index (NDVI) and the Fractional Vegetation Coverage (FVC), the spatiotemporal changes and driving factors of vegetation coverage in the Yongzhou manganese mining area from 2000 to 2023 were analyzed. …”
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Mechanisms for upstream migration of firn aquifer drainage: preliminary observations from Helheim Glacier, Greenland by Jessica Z. Mejia, Kristin Poinar, Colin R. Meyer, Aleah N. Sommers, Winnie Chu

“…We infer inland expansion of crevasses over the firn aquifer from crevasse-nucleated whaleback dune formation and Global Navigation Satellite System-station detected crevasse opening extending 14 and 4 km, respectively, inland from the current, farthest-upstream drainage point. …”
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Review of Sensor Network-Based Irrigation Systems Using IoT and Remote Sensing by Wei Li, Muhammad Awais, Weimin Ru, Weidong Shi, Muhammad Ajmal, Saad Uddin, Chenchen Liu

“…This review paper highlights the development of an automated irrigation system with portable wireless sensor networks and decision support methods to remotely measure the environmental parameters in an agriculture field. Radio satellite, mobile phones, sensors, internet-based communication, and microcontroller capture the ecological parameters such as soil moisture, temperature, humidity, and light intensity. …”
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Drought and flood risk mapping using a GIS-based multi-criteria decision method: A case of the Olifants Basin, South Africa by Luxon Nhamo, James Magidi, Sylvester Mpandeli, Onisimo Mutanga, Stanley Liphadzi, Tafadzwanashe Mabhaudhi

“…The mapped drought and flood risk areas agree with historical and topographic data, and satellite-derived indices related to drought and floods. …”
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