Alternative, or non-traditional, data sources can be used to generate datasets which can in turn be analyzed for temporal, spatial and climatological patterns. Events and case studies inferred from the analysis of these patterns can be used by the remote sensing community to more effectively search for Earth observation data. In this paper, we present a new alternative Earth science dataset created from the National Weather Services Area Forecast Discussion (AFD) documents. We then present an exploratory methodology for identifying interesting climatological patterns within the AFD data and a corresponding motivating example as to how these data and patterns can be used to search for relevant events or case studies
Extreme weather and climate events, such as heavy rainfall, heatwave, floods and droughts, and stron...
Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes h...
As the number of Earth pointing satellites has increased over the last several decades, the data vol...
In this paper, a unique approach to the problem of spatio-temporal pattern detection is discussed in...
Knowledge graphs link key entities within a specific domain to other entities via relationships. Res...
There is need in the research community for weather-related case studies to improve prediction of an...
Climate and weather modeling generate enormous volumes that make iterative analysis challenging, spu...
AbstractFrom field-scale measurements to global climate simulations and remote sensing, the growing ...
The thesis focuses on machine learning methods for Earth Observation (EO) data, more specifically, r...
One of the largest continuing challenges in any Earth science investigation is the discovery and acc...
From field-scale measurements to global climate simulations and remote sensing, the growing body of ...
Contents 1 Discovery of Patterns in Earth Science Data Using Data Mining 1 P. Zhang, M. Steinbach, ...
Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based mi...
AbstractDetecting and tracking extreme events in gridded climatological data is a challenging proble...
Abnormal events in earth science have great influence on both the natural environment and the human ...
Extreme weather and climate events, such as heavy rainfall, heatwave, floods and droughts, and stron...
Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes h...
As the number of Earth pointing satellites has increased over the last several decades, the data vol...
In this paper, a unique approach to the problem of spatio-temporal pattern detection is discussed in...
Knowledge graphs link key entities within a specific domain to other entities via relationships. Res...
There is need in the research community for weather-related case studies to improve prediction of an...
Climate and weather modeling generate enormous volumes that make iterative analysis challenging, spu...
AbstractFrom field-scale measurements to global climate simulations and remote sensing, the growing ...
The thesis focuses on machine learning methods for Earth Observation (EO) data, more specifically, r...
One of the largest continuing challenges in any Earth science investigation is the discovery and acc...
From field-scale measurements to global climate simulations and remote sensing, the growing body of ...
Contents 1 Discovery of Patterns in Earth Science Data Using Data Mining 1 P. Zhang, M. Steinbach, ...
Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based mi...
AbstractDetecting and tracking extreme events in gridded climatological data is a challenging proble...
Abnormal events in earth science have great influence on both the natural environment and the human ...
Extreme weather and climate events, such as heavy rainfall, heatwave, floods and droughts, and stron...
Extreme events such as heat waves, cold spells, floods, droughts, tropical cyclones, and tornadoes h...
As the number of Earth pointing satellites has increased over the last several decades, the data vol...