[HTML][HTML] Object representations at multiple scales from digital elevation models
L Drăguţ, C Eisank - Geomorphology, 2011 - Elsevier
In the last decade landform classification and map** has developed as one of the most
active areas of geomorphometry. However, translation from continuous models of elevation …
active areas of geomorphometry. However, translation from continuous models of elevation …
Squeezing data from a rock: Machine learning for martian science
Data analysis methods have scarcely kept pace with the rapid increase in Earth
observations, spurring the development of novel algorithms, storage methods, and …
observations, spurring the development of novel algorithms, storage methods, and …
A stepwise domain adaptive segmentation network with covariate shift alleviation for remote sensing imagery
Semantic segmentation for remote sensing images (RSI) is critical for the Earth monitoring
system. However, the covariate shift between RSI datasets under different capture …
system. However, the covariate shift between RSI datasets under different capture …
Surface area and the seabed area, volume, depth, slope, and topographic variation for the world's seas, oceans, and countries
MJ Costello, A Cheung… - Environmental science & …, 2010 - ACS Publications
Depth and topography directly and indirectly influence most ocean environmental
conditions, including light penetration and photosynthesis, sedimentation, current …
conditions, including light penetration and photosynthesis, sedimentation, current …
Automatic landform recognition from the perspective of watershed spatial structure based on digital elevation models
S Lin, N Chen, Z He - Remote Sensing, 2021 - mdpi.com
Landform recognition is one of the most significant aspects of geomorphology research,
which is the essential tool for landform classification and understanding geomorphological …
which is the essential tool for landform classification and understanding geomorphological …
Machine learning in geography–Past, present, and future
A Lavallin, JA Downs - Geography Compass, 2021 - Wiley Online Library
This paper concentrates on the different meanings of machine learning (ML) from its origins
to the present and potential future, focusing on contributions within the discipline of …
to the present and potential future, focusing on contributions within the discipline of …
Automatic recognition of loess landforms using Random Forest method
The automatic recognition of landforms is regarded as one of the most important procedures
to classify landforms and deepen the understanding on the morphology of the earth …
to classify landforms and deepen the understanding on the morphology of the earth …
A review of landform classification methods
M Mokarram, D Sathyamoorthy - Spatial Information Research, 2018 - Springer
The study of landform can be used to predict specific solid rock and moisture conditions that
exist in that landform. Landforms are of significance in engineering because they influence …
exist in that landform. Landforms are of significance in engineering because they influence …
Object-based classification of landforms based on their local geometry and geomorphometric context
D Gerçek, V Toprak, J Strobl - International Journal of …, 2011 - Taylor & Francis
Terrain as a continuum can be categorized into landform units that exhibit common physical
and morphological characteristics of land surface which may serve as a boundary condition …
and morphological characteristics of land surface which may serve as a boundary condition …
Machine cataloging of impact craters on Mars
This study presents an automated system for cataloging impact craters using the MOLA
128pixels/degree digital elevation model of Mars. Craters are detected by a two-step …
128pixels/degree digital elevation model of Mars. Craters are detected by a two-step …