Spatio-temporal data mining: A survey of problems and methods
Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …
domains, including climate science, social sciences, neuroscience, epidemiology …
Spatio-temporal data mining for climate data: Advances, challenges, and opportunities
JH Faghmous, V Kumar - Data mining and knowledge discovery for big …, 2014 - Springer
Our planet is experiencing simultaneous changes in global population, urbanization, and
climate. These changes, along with the rapid growth of climate data and increasing …
climate. These changes, along with the rapid growth of climate data and increasing …
New directions in logistics
M Christopher - Global logistics and distribution planning, 2018 - taylorfrancis.com
Logistics management is essentially an integrative process that seeks to optimize the flow of
materials and supplies through the organization as well as its operations to the customer …
materials and supplies through the organization as well as its operations to the customer …
Contextual time series change detection
Time series data are common in a variety of fields ranging from economics to medicine and
manufacturing. As a result, time series analysis and modeling has become an active …
manufacturing. As a result, time series analysis and modeling has become an active …
Data mining algorithms for land cover change detection: a review
S Panigrahi, K Verma, P Tripathi - Sādhanā, 2017 - Springer
Land cover change detection has been a topic of active research in the remote sensing
community. Due to enormous amount of data available from satellites, it has attracted the …
community. Due to enormous amount of data available from satellites, it has attracted the …
Terrestrial ecosystem carbon fluxes predicted from MODIS satellite data and large-scale disturbance modeling
C Potter, S Klooster, V Genovese… - International …, 2012 - digitalcommons.csumb.edu
Abstract The CASA (Carnegie-Ames-Stanford) ecosystem model based on satellite
greenness observations has been used to estimate monthly carbon fluxes in terrestrial …
greenness observations has been used to estimate monthly carbon fluxes in terrestrial …
A new data mining framework for forest fire mapping
XC Chen, A Karpatne, Y Chamber… - 2012 Conference on …, 2012 - ieeexplore.ieee.org
Forests are an important natural resource that support economic activity and play a
significant role in regulating the climate and the carbon cycle, yet forest ecosystems are …
significant role in regulating the climate and the carbon cycle, yet forest ecosystems are …
An efficient approach to detect sudden changes in vegetation index time series for land change detection
S Panigrahi, K Verma, P Tripathi - IETE Technical Review, 2016 - Taylor & Francis
In this paper, we proposed a novel data mining approach Recursive Search Algorithm (RSA)
to detect sudden changes in time series data-set. In literature, Modified Lunetta, cumulative …
to detect sudden changes in time series data-set. In literature, Modified Lunetta, cumulative …
Clustering of Time Series for Land Change Detection: A Data Mining Approach
S Panigrahi - … on Machine Learning, Computer Systems and …, 2022 - ieeexplore.ieee.org
A significant field of study in the recent age is the detection of changes in land cover and
land use (LCLU), because any conversion of land cover its impacts on the local or the global …
land use (LCLU), because any conversion of land cover its impacts on the local or the global …
Earth science applications of sensor data
Advances in earth observation technologies have led to the acquisition of vast volumes of
accurate, timely and reliable environmental data which encompass a multitude of …
accurate, timely and reliable environmental data which encompass a multitude of …