Spatial Modeling - an overview | ScienceDirect Topics
Apr 15, 1999 · R-M-R, Remote sensing–spatial modeling–remote sensing. For the implementation of the proposed R-M-R approach, EUMETSAT rainfall data are used as inputs, HEC tools and models are …
Spatial Modeling in GIS and R for Earth and Environmental Sciences
The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and …
Multi-spatial urban function modeling: A multi-modal deep network ...
Feb 1, 2025 · This study introduces a multi-modal deep learning approach to modeling urban functions from a multi-spatial perspective. Based on ILUTM, the proposed framework leverages advanced …
Embryo-Net: A blastocyst image segmentation network based on …
Jul 14, 2025 · Embryo-Net is a multistage, multipath, multiloss embryo segmentation network that incorporates spatial modeling, specifically designed to improve the segmentation of the ICM and TE …
Integrating local climate zones and spatial modeling for carbon ...
Jun 1, 2025 · This research contributes to global climate action efforts by providing a replicable methodology for integrating spatial carbon emission modeling, urban morphology analysis, and …
Integrating spatial modeling-assisted InSAR phase unwrapping with ...
Sep 1, 2024 · The approach employs the iterative Modeling-Assisted Phase Unwrapping (MA-PU) algorithm for spatial phase unwrapping, and integrates it with temporal models to derive the …
Bayesian spatial modeling for speeding likelihood using floating car ...
Feb 1, 2025 · Albeit some studies have analyzed speeding likelihood, most of them are inadequate in considering spatial effects when analyzing speeding behaviors on urban road networks. This study …
Spatial prediction of flood-prone areas using ... - ScienceDirect
Dec 1, 2021 · This shows that by using GWR to consider local spatial variation in flood susceptibility analyses, the models fitted the observed data better than the non-spatial models (Mateo and …
Machine learning approach for spatial modeling of ridesourcing demand
Apr 1, 2022 · These models can capture the location-specific effects and estimate the parameters locally. Moreover, the modeling results offer us a deeper understanding of how spatial heterogeneity …
A two-stage spatial prediction modeling approach based on graph …
Dec 15, 2024 · Spatial prediction models hold significant application value in fields such as environmental science, economic development, and geological exploration. With advancements in …