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Geographic Mapping

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Monitoring of Technology Adoption Using Web Content Mining of Location Information and Geographic Information Systems: A Case Study of Digital Breast Tomosynthesis.

JCO clinical cancer informatics
PURPOSE: To our knowledge, integration of Web content mining of publicly available addresses with a geographic information system (GIS) has not been applied to the timely monitoring of medical technology adoption. Here, we explore the diffusion of a ...

Why Mathematical Computer Simulations Are the New Laboratory for Scientists.

Substance use & misuse
In this paper, we introduce a new powerful scientific paradigm to understand natural and cultural processes. This new paradigm is based on two fundamental keywords: Data, as representative sample of the process we need to analyze, and Artificial Adap...

Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran.

Anais da Academia Brasileira de Ciencias
During the recent decades, deciduous forests have been molested by human intervention. Easy access, abundance and diversity of valuable forest products have led to increased population density, creating new residential areas and deforestation activit...

Support Vector Machine Optimized by Genetic Algorithm for Data Analysis of Near-Infrared Spectroscopy Sensors.

Sensors (Basel, Switzerland)
Near-infrared (NIR) spectral sensors deliver the spectral response of the light absorbed by materials for quantification, qualification or identification. Spectral analysis technology based on the NIR sensor has been a useful tool for complex informa...

Deep learning and process understanding for data-driven Earth system science.

Nature
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...

Testing the ability of unmanned aerial systems and machine learning to map weeds at subfield scales: a test with the weed Alopecurus myosuroides (Huds).

Pest management science
BACKGROUND: It is important to map agricultural weed populations to improve management and maintain future food security. Advances in data collection and statistical methodology have created new opportunities to aid in the mapping of weed populations...

Emulation of wildland fire spread simulation using deep learning.

Neural networks : the official journal of the International Neural Network Society
Numerical simulation of wildland fire spread is useful to predict the locations that are likely to burn and to support decision in an operational context, notably for crisis situations and long-term planning. For short-term, the computational time of...

Mapping, intensities and future prediction of land use/land cover dynamics using google earth engine and CA- artificial neural network model.

PloS one
Mapping of land use/ land cover (LULC) dynamics has gained significant attention in the past decades. This is due to the role played by LULC change in assessing climate, various ecosystem functions, natural resource activities and livelihoods in gene...

Using spatial video and deep learning for automated mapping of ground-level context in relief camps.

International journal of health geographics
BACKGROUND: The creation of relief camps following a disaster, conflict or other form of externality often generates additional health problems. The density of people in a highly stressed environment with questionable safe food and water access prese...