Geo-Spatial Information Science’s Post

Elated to share that my research paper titled "Visual saliency-based landslide identification using super-resolution remote sensing data" has been published by Results in Engineering, Elsevier (IF: 5, SJR: 0.79, Q1). This paper proposes an innovative deep-learning framework utilizing visual saliency for automatic landslide identification, employing super-resolution remote sensing image datasets. Unlike conventional models relying on raw images, our method leverages saliency-generated feature maps, achieving a remarkable 94% accuracy, surpassing existing models by 5%. This novel approach introduces a valuable dimension to landslide detection, particularly in complex terrains, offering a promising tool for advancing risk assessment and management in landslide-prone areas. The paper can be accessed from: https://lnkd.in/gbdiiTCY #researchpublication #elsevier #q1 #scopus #webofscience #landslideanalysis #visualsaliency #remotesensing #keralauniversity

Welcome to submit your paper to this #specialissue "Geometric Algorithms and Applications"   Edited by Dr. Antoine Vigneron Explore more details via the link:  https://lnkd.in/efhbgKt7 MDPI Ulsan National Institute of Science and Technology #algorithms #callforpapers #geometricalgorithms

Dynamic land cover evapotranspiration model algorithm: DyLEMa Science Direct https://lnkd.in/grMVH5T3

DUG Multi-parameter FWI Imaging delivers superior pre-stack reflectivity outputs for both AVA analysis, and, elastic rock property and fluid prediction — directly from field data. Learn more in this feature on GEO EXPRO! https://lnkd.in/di4NDxZK

I am proud to share that our latest (and my first!) contribution entitled "A nonparametric penalized likelihood approach to density estimation of space-time point patterns" has been published in "Spatial Statistics". 💡 We propose a novel nonparametric method to estimate the unknown spatio-temporal probability density function associated with point patterns spatially observed on complex domains of various kinds. ✏ We establish some important theoretical properties of the considered estimator and develop a flexible and efficient estimation procedure. 📊 We thoroughly validate the proposed method, by means of several simulation studies and applications to real-world data. Authors: Blerta Begu, Simone Panzeri, Eleonora Arnone, Michelle Carey, Laura M. Sangalli Code available at: https://lnkd.in/eX9KsgqQ Paper available at: https://lnkd.in/eqKQ_mzz #nonparametric #densityestimation #spatiotemporal #pointpatterns

#mdpisymmetry Check this published article "Moment of Inertia and Dynamical Symmetry" at https://lnkd.in/gSngucWh Authors: József Cseh and Gábor Riczu #momentofinertia

Don't miss this Technical Article by Alireza Roodaki et al in the May issue of First Break to find out how CGG resolved a persistent imaging challenge on Central North Sea shallow water OBS data by applying its FWI technology to generate high-resolution P-wave and S-wave velocity models. Read the article here: https://lnkd.in/eXNd_FMW Thanks to EAGE (European Association of Geoscientists and Engineers) for publishing this article in May’s First Break. #geoscience #velocity #imaging #data #seismic

You've blown your compute budget calculating a Bayesian solution, and now you want to change the prior information - Help! Don't worry: this paper by Xuebin Zhao explains how prior information can be updated to provide a new solution, almost for free, using 'variational prior replacement'. This allows the effects of different hypotheses to be tested, or different regularisations to be applied, and is an approximate but computationally efficient version of the theory originally developed by Matthew Walker. Xuebin's paper:  https://lnkd.in/ejm8tktk Matt's paper:  https://lnkd.in/e-tGKwWy #geophysics #geoscience #inversion #uncertainty #imaging #geosciences #Edinburgh #EdinburghUniversity #Bayesian #variational #British_Geophysical_Association #britgeophysics

🔥 Read our Paper 📚 Spatial and Temporal Distribution Characteristics of Landslide Surge Based on Large-Scale Physical Modeling Experiment 🔗 https://lnkd.in/gdf5j6GY 👨🔬 by Yangyang Zhang et al. 🏫 Hohai University #landslidesurge

It seems that there will be only 30 papers (the numbers are too low compared to other remote sensing fields with several hundreds of papers) on the use of Polarimetric Synthetic Aperture Radar (PolSAR) in the upcoming 2024 IEEE International Geoscience and Remote Sensing Symposium. Two papers will be presented by us. These two papers use relatively simple and straightforward techniques with excellent capabilities. I will share the codes soon. 1. A Mixing Convolutional and Involution Algorithm for PolSAR data Classification Authors: Ali Jamali, Swalpa Kumar Roy, Bing Lu, Avik Bhattacharya, Pedram Ghamisi, and Jocelyn Chanussot 2. PolSARConvMixer: A Channel and Spatial Mixing Convolutional Algorithm for PolSAR data Classification Authors: Ali Jamali, Swalpa Kumar Roy, Bing Lu, Avik Bhattacharya, and Pedram Ghamisi #deeplearning #machinelearning #computervision #SAR #PolSAR #remotesensing