[HTML][HTML] Geomorphometry and terrain analysis: Data, methods, platforms and applications
Terrain is considered one of the most essential natural geographic features and is a key
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …
factor in physical processes. Geomorphometry and terrain analyses have provided a wealth …
GeoAI for large-scale image analysis and machine vision: recent progress of artificial intelligence in geography
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for
spatial analytics in Geography. Although much progress has been made in exploring the …
spatial analytics in Geography. Although much progress has been made in exploring the …
Explainable GeoAI: can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection
Improving the interpretability of geospatial artificial intelligence (GeoAI) models has become
critically important to open the 'black box'of complex AI models, such as deep learning. This …
critically important to open the 'black box'of complex AI models, such as deep learning. This …
Terrain feature-aware deep learning network for digital elevation model superresolution
Neural networks (NNs) have demonstrated the potential to recover finer textural details from
lower-resolution images by superresolution (SR). Given similar grid-based data structures …
lower-resolution images by superresolution (SR). Given similar grid-based data structures …
Geospatial foundation models for image analysis: Evaluating and enhancing NASA-IBM Prithvi's domain adaptability
Research on geospatial foundation models (GFMs) has become a trending topic in
geospatial artificial intelligence (AI) research due to their potential for achieving high …
geospatial artificial intelligence (AI) research due to their potential for achieving high …
GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning
The field of GeoAI or Geospatial Artificial Intelligence has undergone rapid development
since 2017. It has been widely applied to address environmental and social science …
since 2017. It has been widely applied to address environmental and social science …
[HTML][HTML] Smart hotspot detection using geospatial artificial intelligence: A machine learning approach to reduce flood risk
Abstract This study employs Geospatial Artificial Intelligence (GeoAI) and the Random
Forest Machine Learning (ML) algorithm to enhance flood hazard assessments in Portugal …
Forest Machine Learning (ML) algorithm to enhance flood hazard assessments in Portugal …
Developing an integrated approach based on geographic object-based image analysis and convolutional neural network for volcanic and glacial landforms mapping
M Kazemi Garajeh, Z Li, S Hasanlu… - Scientific reports, 2022 - nature.com
Rapid detection and mapping of landforms are crucially important to improve our
understanding of past and presently active processes across the earth, especially, in …
understanding of past and presently active processes across the earth, especially, in …
Desert landform detection and mapping using a semi-automated object-based image analysis approach
Traditional landform modeling approaches are labor-intensive and time-consuming. We
proposed and developed a semi-automated object-based image analysis (OBIA) rule set …
proposed and developed a semi-automated object-based image analysis (OBIA) rule set …
Assessment of a new GeoAI foundation model for flood inundation mapping
Vision foundation models are a new frontier in Geospatial Artificial Intelligence (GeoAI), an
interdisciplinary research area that applies and extends AI for geospatial problem solving …
interdisciplinary research area that applies and extends AI for geospatial problem solving …