ISBN: 9798193465744 - remote sensing mathematics (6 risultati)

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  • Lingua: Inglese

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

    9798193465744

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Condizione: Nuovo

    EUR 243,09

    EUR 35,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 2 disponibili

    Taschenbuch. Condizione: 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. …

  • Lingua: Inglese

    Editore: Amazon Digital Services LLC - Kdp, 2026

    9798193465744

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    • Print on Demand

    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    Condizione: Nuovo

    EUR 169,13

    EUR 6,97 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: Più di 20 disponibili

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

  • Lingua: Inglese

    Editore: Amazon Digital Services LLC - Kdp, 2026

    9798193465744

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    • Print on Demand

    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    Condizione: Nuovo

    EUR 178,75

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

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798193465744

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    • Print on Demand

    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    Condizione: Nuovo

    EUR 191,99

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    Spedito in U.S.A.

    Quantità: 1 disponibile

    Paperback. Condizione: 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. …

  • Lingua: Inglese

    Editore: Independently published, 2026

    9798193465744

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    • Print on Demand

    Da: California Books, Miami, FL, U.S.A.California Books

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    Condizione: Nuovo

    EUR 192,89

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    Quantità: Più di 20 disponibili

    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798193465744

    • Brossura
    • Print on Demand

    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Condizione: Nuovo

    EUR 178,47

    EUR 43,92 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibile

    Paperback. Condizione: 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. …