Rock glaciers (RG) are landforms that occur in high latitudes or elevations and — in their active state — consist of a mixture of rock debris and ice. Despite serving as a form of groundwater s…
In this study we compared various machine learning techniques that used soil geochemistry to aid in geologic mapping. We tested six different sampling methods (undersample, oversample, Synthetic Mi…
Using Python-based geospatial analytics, open-source web mapping technologies, geophysical data models, and subsurface stratigraphy models from the Regional Geology Geologic Framework Model databas…
In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake…
Crop type and crop extent are critical information that helps policymakers make informed decisions on food security. As the economic growth of Bhutan has increased at an annual rate of 7.5% over th…
Thermal mapping of buildings can be one approach to assess the insulation, which is important in regard to upgrade buildings to increase energy efficiency and for climate change adaptation. Persona…
Among photogrammetric products, orthophotos are probably the most versatile and widely used in many fields of application. In the last years, coupled with the spread of semi-automated survey and pr…
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote sensing are becoming standard analytical tools in the geosciences. A series of studies has presented the se…
Satellite remote sensing plays an important role in mapping the location and extent of surface water. A variety of approaches are available for mapping surface water, but deep learning approaches a…
Spherical robots are a format that has not been thoroughly explored for the application of mobile mapping. In contrast to other designs, it provides some unique advantages. Among those is a spheric…