ISBN: 9798193465744 - remote sensing mathematics (6 resultados)

ISBN: 
Refinar con la Búsqueda avanzada

Filtrar la búsqueda

  • Libros (6)

  • Nuevo (6)

a

Intervalo de precios personalizado (EUR)

a

  • Idioma: Inglés

    Editorial: Amazon Digital Services LLC - Kdp Aug 2026, 2026

    9798193465744

    • Tapa blanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 243,09

    Envío por EUR 35,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. Neuware - Stop treating remote sensing algorithms like black boxes. Understand the mathematics that makes them work.Remote Sensing Mathematics gives you a practical mathematical foundation for interpreting, selecting, troubleshooting, and applying the transformations, filters, and classification algorithms used throughout modern geospatial analysis.Instead of separating theory from real-world remote sensing, this book connects equations directly to satellite imagery, spectral data, image correction, feature extraction, and classification.Inside, you'll learn how to: - Build confidence with linear algebra, matrices, probability, statistics, covariance, and signal theory as they apply to imagery- Understand geometric correction, coordinate transformations, radiometric calibration, atmospheric effects, and resampling mathematically- Work through convolution, spatial filtering, Fourier analysis, wavelets, PCA, spectral transformations, and dimensionality reduction- Understand statistical classifiers, K-means, support vector machines, random forests, neural networks, and other machine-learning methods- Evaluate confusion matrices, classification accuracy, uncertainty, cross-validation, and classifier performance- Explore change detection, CNNs, semantic segmentation, transfer learning, transformers, and other emerging computational methods- Quickly revisit notation, formulas, terminology, and computational tools through dedicated reference appendices and a glossaryStructured across fifteen chapters, this vendor-neutral reference is designed for GIS professionals, remote sensing analysts, engineers, graduate students, researchers, and data scientists who want to move beyond simply running an algorithm toward understanding why it produces the result it does.If you want to strengthen the mathematical reasoning behind your remote sensing work, add Remote Sensing Mathematics to your professional library today. …

  • Idioma: Inglés

    Editorial: Amazon Digital Services LLC - Kdp, 2026

    9798193465744

    • Tapa blanda
    • Impresión bajo demanda

    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 169,75

    Envío por EUR 6,99 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Amazon Digital Services LLC - Kdp, 2026

    9798193465744

    • Tapa blanda
    • Impresión bajo demanda

    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 178,56

     Gastos de envío gratis 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798193465744

    • Tapa blanda
    • Impresión bajo demanda

    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 191,78

     Gastos de envío gratis 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. Stop treating remote sensing algorithms like black boxes. Understand the mathematics that makes them work.Remote Sensing Mathematics gives you a practical mathematical foundation for interpreting, selecting, troubleshooting, and applying the transformations, filters, and classification algorithms used throughout modern geospatial analysis.Instead of separating theory from real-world remote sensing, this book connects equations directly to satellite imagery, spectral data, image correction, feature extraction, and classification.Inside, you'll learn how to: Build confidence with linear algebra, matrices, probability, statistics, covariance, and signal theory as they apply to imageryUnderstand geometric correction, coordinate transformations, radiometric calibration, atmospheric effects, and resampling mathematicallyWork through convolution, spatial filtering, Fourier analysis, wavelets, PCA, spectral transformations, and dimensionality reductionUnderstand statistical classifiers, K-means, support vector machines, random forests, neural networks, and other machine-learning methodsEvaluate confusion matrices, classification accuracy, uncertainty, cross-validation, and classifier performanceExplore change detection, CNNs, semantic segmentation, transfer learning, transformers, and other emerging computational methodsQuickly revisit notation, formulas, terminology, and computational tools through dedicated reference appendices and a glossaryStructured across fifteen chapters, this vendor-neutral reference is designed for GIS professionals, remote sensing analysts, engineers, graduate students, researchers, and data scientists who want to move beyond simply running an algorithm toward understanding why it produces the result it does.If you want to strengthen the mathematical reasoning behind your remote sensing work, add Remote Sensing Mathematics to your professional library today. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

  • Idioma: Inglés

    Editorial: Independently published, 2026

    9798193465744

    • Tapa blanda
    • Impresión bajo demanda

    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 192,68

     Gastos de envío gratis 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798193465744

    • Tapa blanda
    • Impresión bajo demanda

    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 179,12

    Envío por EUR 44,07 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. Stop treating remote sensing algorithms like black boxes. Understand the mathematics that makes them work.Remote Sensing Mathematics gives you a practical mathematical foundation for interpreting, selecting, troubleshooting, and applying the transformations, filters, and classification algorithms used throughout modern geospatial analysis.Instead of separating theory from real-world remote sensing, this book connects equations directly to satellite imagery, spectral data, image correction, feature extraction, and classification.Inside, you'll learn how to: Build confidence with linear algebra, matrices, probability, statistics, covariance, and signal theory as they apply to imageryUnderstand geometric correction, coordinate transformations, radiometric calibration, atmospheric effects, and resampling mathematicallyWork through convolution, spatial filtering, Fourier analysis, wavelets, PCA, spectral transformations, and dimensionality reductionUnderstand statistical classifiers, K-means, support vector machines, random forests, neural networks, and other machine-learning methodsEvaluate confusion matrices, classification accuracy, uncertainty, cross-validation, and classifier performanceExplore change detection, CNNs, semantic segmentation, transfer learning, transformers, and other emerging computational methodsQuickly revisit notation, formulas, terminology, and computational tools through dedicated reference appendices and a glossaryStructured across fifteen chapters, this vendor-neutral reference is designed for GIS professionals, remote sensing analysts, engineers, graduate students, researchers, and data scientists who want to move beyond simply running an algorithm toward understanding why it produces the result it does.If you want to strengthen the mathematical reasoning behind your remote sensing work, add Remote Sensing Mathematics to your professional library today. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …