A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …
environment has become essential for many countries' sustainable development. As various …
[HTML][HTML] Rock glaciers and mountain hydrology: A review
In mountainous regions, climate change threatens cryospheric water resources, and
understanding all components of the hydrological cycle is necessary for effective water …
understanding all components of the hydrological cycle is necessary for effective water …
System for automated geoscientific analyses (SAGA) v. 2.1. 4
O Conrad, B Bechtel, M Bock, H Dietrich… - Geoscientific model …, 2015 - gmd.copernicus.org
The System for Automated Geoscientific Analyses (SAGA) is an open source geographic
information system (GIS), mainly licensed under the GNU General Public License. Since its …
information system (GIS), mainly licensed under the GNU General Public License. Since its …
Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling
JN Goetz, A Brenning, H Petschko, P Leopold - Computers & geosciences, 2015 - Elsevier
Statistical and now machine learning prediction methods have been gaining popularity in
the field of landslide susceptibility modeling. Particularly, these data driven approaches …
the field of landslide susceptibility modeling. Particularly, these data driven approaches …
Support vector machines in remote sensing: A review
A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …
be proposed and assessed. In this paper, we review remote sensing implementations of …
A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT …
Pixel-based and object-based image analysis approaches for classifying broad land cover
classes over agricultural landscapes are compared using three supervised machine …
classes over agricultural landscapes are compared using three supervised machine …
A comparison of resampling methods for remote sensing classification and accuracy assessment
Maps that categorise the landscape into discrete units are a cornerstone of many scientific,
management and conservation activities. The accuracy of these maps is often the primary …
management and conservation activities. The accuracy of these maps is often the primary …
[HTML][HTML] Automated detection of rock glaciers using deep learning and object-based image analysis
Rock glaciers are an important component of the cryosphere and are one of the most visible
manifestations of permafrost. While the significance of rock glacier contribution to streamflow …
manifestations of permafrost. While the significance of rock glacier contribution to streamflow …
Mining data with random forests: A survey and results of new tests
A Verikas, A Gelzinis, M Bacauskiene - Pattern recognition, 2011 - Elsevier
Random forests (RF) has become a popular technique for classification, prediction, studying
variable importance, variable selection, and outlier detection. There are numerous …
variable importance, variable selection, and outlier detection. There are numerous …
Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using support vector machines
Crop mapping is one major component of agricultural resource monitoring using remote
sensing. Yield or water demand modeling requires that both, the total surface that is …
sensing. Yield or water demand modeling requires that both, the total surface that is …