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This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.

Environmental science, engineering & technology --- groundwater potential --- specific capacity --- machine learning --- boosted tree --- ensemble models --- prototype selection --- river pollution --- supervised classification --- WSN --- probabilistic method --- Monte Carlo simulation --- physical slope model --- Mt. Umyeon landslides --- Seoul --- synthetic aperture radar --- land subsidence --- GIS --- time-series --- Jakarta --- land subsidence susceptibility mapping --- time-series InSAR --- StaMPS processing --- seismic vulnerability map --- DPM method --- Sentinel-1 --- seismic literacy --- neural networks --- urban vegetation --- urban open spaces --- Monterrey Metropolitan Area --- sustainable development --- deep learning --- transfer learning --- artificial intelligence --- remote sensing --- earth observation --- DInSAR --- change detection --- space data science

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.

Environmental science, engineering & technology --- groundwater potential --- specific capacity --- machine learning --- boosted tree --- ensemble models --- prototype selection --- river pollution --- supervised classification --- WSN --- probabilistic method --- Monte Carlo simulation --- physical slope model --- Mt. Umyeon landslides --- Seoul --- synthetic aperture radar --- land subsidence --- GIS --- time-series --- Jakarta --- land subsidence susceptibility mapping --- time-series InSAR --- StaMPS processing --- seismic vulnerability map --- DPM method --- Sentinel-1 --- seismic literacy --- neural networks --- urban vegetation --- urban open spaces --- Monterrey Metropolitan Area --- sustainable development --- deep learning --- transfer learning --- artificial intelligence --- remote sensing --- earth observation --- DInSAR --- change detection --- space data science --- groundwater potential --- specific capacity --- machine learning --- boosted tree --- ensemble models --- prototype selection --- river pollution --- supervised classification --- WSN --- probabilistic method --- Monte Carlo simulation --- physical slope model --- Mt. Umyeon landslides --- Seoul --- synthetic aperture radar --- land subsidence --- GIS --- time-series --- Jakarta --- land subsidence susceptibility mapping --- time-series InSAR --- StaMPS processing --- seismic vulnerability map --- DPM method --- Sentinel-1 --- seismic literacy --- neural networks --- urban vegetation --- urban open spaces --- Monterrey Metropolitan Area --- sustainable development --- deep learning --- transfer learning --- artificial intelligence --- remote sensing --- earth observation --- DInSAR --- change detection --- space data science

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• Reference Manager
• EndNote
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This book presents the analytic foundations to the theory of the hypoelliptic Laplacian. The hypoelliptic Laplacian, a second-order operator acting on the cotangent bundle of a compact manifold, is supposed to interpolate between the classical Laplacian and the geodesic flow. Jean-Michel Bismut and Gilles Lebeau establish the basic functional analytic properties of this operator, which is also studied from the perspective of local index theory and analytic torsion. The book shows that the hypoelliptic Laplacian provides a geometric version of the Fokker-Planck equations. The authors give the proper functional analytic setting in order to study this operator and develop a pseudodifferential calculus, which provides estimates on the hypoelliptic Laplacian's resolvent. When the deformation parameter tends to zero, the hypoelliptic Laplacian converges to the standard Hodge Laplacian of the base by a collapsing argument in which the fibers of the cotangent bundle collapse to a point. For the local index theory, small time asymptotics for the supertrace of the associated heat kernel are obtained. The Ray-Singer analytic torsion of the hypoelliptic Laplacian as well as the associated Ray-Singer metrics on the determinant of the cohomology are studied in an equivariant setting, resulting in a key comparison formula between the elliptic and hypoelliptic analytic torsions.

Differential equations, Hypoelliptic. --- Laplacian operator. --- Metric spaces. --- Spaces, Metric --- Operator, Laplacian --- Hypoelliptic differential equations --- Generalized spaces --- Set theory --- Topology --- Differential equations, Partial --- Alexander Grothendieck. --- Analytic function. --- Asymptote. --- Asymptotic expansion. --- Berezin integral. --- Bijection. --- Brownian dynamics. --- Brownian motion. --- Chaos theory. --- Chern class. --- Classical Wiener space. --- Clifford algebra. --- Cohomology. --- Combination. --- Commutator. --- Computation. --- Connection form. --- Coordinate system. --- Cotangent bundle. --- Covariance matrix. --- Curvature tensor. --- Curvature. --- De Rham cohomology. --- Derivative. --- Determinant. --- Differentiable manifold. --- Differential operator. --- Dirac operator. --- Direct proof. --- Eigenform. --- Eigenvalues and eigenvectors. --- Ellipse. --- Embedding. --- Equation. --- Estimation. --- Euclidean space. --- Explicit formula. --- Explicit formulae (L-function). --- Feynman–Kac formula. --- Fiber bundle. --- Fokker–Planck equation. --- Formal power series. --- Fourier series. --- Fourier transform. --- Fredholm determinant. --- Function space. --- Girsanov theorem. --- Ground state. --- Heat kernel. --- Hilbert space. --- Hodge theory. --- Holomorphic function. --- Holomorphic vector bundle. --- Hypoelliptic operator. --- Integration by parts. --- Invertible matrix. --- Logarithm. --- Malliavin calculus. --- Martingale (probability theory). --- Matrix calculus. --- Mellin transform. --- Morse theory. --- Notation. --- Parameter. --- Parametrix. --- Parity (mathematics). --- Polynomial. --- Principal bundle. --- Probabilistic method. --- Projection (linear algebra). --- Rectangle. --- Resolvent set. --- Ricci curvature. --- Riemann–Roch theorem. --- Scientific notation. --- Self-adjoint operator. --- Self-adjoint. --- Sign convention. --- Smoothness. --- Sobolev space. --- Spectral theory. --- Square root. --- Stochastic calculus. --- Stochastic process. --- Summation. --- Supertrace. --- Symmetric space. --- Tangent space. --- Taylor series. --- Theorem. --- Theory. --- Torus. --- Trace class. --- Translational symmetry. --- Transversality (mathematics). --- Uniform convergence. --- Variable (mathematics). --- Vector bundle. --- Vector space. --- Wave equation.