Geocarto International 

About: Geocarto International is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Computer science & Environmental science. It has an ISSN identifier of 1010-6049. Over the lifetime, 2611 publications have been published receiving 43066 citations. The journal is also known as: Geocarto.

Introduction to remote sensing

Abstract: Preface. Part I: Foundations. History and Scope of Remote Sensing. Electromagentic Radiation. Part II: Image Acquisition. Photographic Sensors. Digital Data. Image Interpretation. Land Observation Satellites. Active Microwave and Lidar. Thermal Radiation. Image Resolution. Part III: Analysis. Preprocessing. Image Classification. Field Data. Accuracy Assessment. Hyperspectral Remote Sensing. Part IV: Applications. Geographic Information Systems. Plant Sciences. Earth Sciences. Hydrospheric Sciences. Land Use and Land Cover. Global Remote Sensing.

Computer Processing of Remotely-Sensed Images: An Introduction

Abstract: Preface to the First EditionPreface to the Second Edition Preface to the Third EditionList of Examples1 Remote Sensing: Basic Principles11 Introduction12 Electromagnetic radiation and its properties121 Terminology122 Nature of electromagnetic radiation123 The electromagnetic spectrum124 Sources of electromagnetic radiation125 Interactions with the Earth's atmosphere13 Interaction with Earth-surface materials131 Introduction132 Spectral reflectance of Earth surface materials1321 Vegetation1322 Geology1323 Water bodies1324 Soils14 Summary2 Remote Sensing Platforms and Sensors21 Introduction22 Characteristics of imaging remote sensing instruments221 Spatial resolution222 Spectral resolution223 Radiometric resolution23 Optical, near-infrared and thermal imaging sensors231 Along-Track Scanning Radiometer (ATSR)232 Advanced Very High Resolution Radiometer (AVHRR)233 MODIS (MODerate Resolution Imaging Spectrometer)234 Ocean observing instruments235 IRS-1 LISS236 Landsat Instruments2361 Landsat Multi-spectral Scanner (MSS)2362 Landsat Thematic Mapper (TM)2363 Enhanced Thematic Mapper Plus (ETM+)2364 Landsat follow-on programme237 SPOT sensors2371 SPOT High Resolution Visible (HRV)2372 Vegetation (VGT)2373 SPOT follow-on programme238 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)239 High-resolution commercial and micro-satellite systems2391 High-resolution commercial satellites - IKONOS2392 High-resolution commercial satellites - QuickBird24 Microwave imaging sensors241 ERS SAR242 RADARSAT25 Summary3 Hardware and Software Aspects of Digital Image Processing31 Introduction32 Properties of digital remote sensing data321 Digital data322 Data formats323 System processing33 MIPS software331 Installing MIPS332 Using MIPS333 Summary of MIPS functions34 Summary4 Pre-processing of Remotely Sensed Data41 Introduction42 Cosmetic operations421 Missing scan lines422 De-striping methods4221 Linear method4222 Histogram matching4223 Other destriping methods43 Geometric correction and registration431 Orbital geometry model432 Transformation based on ground control points433 Resampling procedures434 Image registration435 Other geometric correction methods44 Atmospheric correction441 Background442 Image-based methods443 Radiative transfer models444 Empirical line method45 Illumination and view angle effects46 Sensor calibration47 Terrain effects48 Summary5 Image Enhancement Techniques51 Introduction52 Human visual system53 Contrast enhancement531 Linear contrast stretch532 Histogram equalisation533 Gaussian Stretch54 Pseudocolour enghancement541 Density slicing542 Pseudocolour transform55 Summary6 Image Transforms61 Introduction62 Arithmetic operations621 Image addition622 Image subtraction623 Image multiplication624 Image division and vegetation ratios63 Empirically based image transforms631 Perpendicular Vegetation Index632 Tasselled Cap (Kauth-Thomas) transformation64 Principal Components Analysis641 Standard Principal Components Analysis642 Noise-adjusted Principal Components Analysis643 Decorrelation stretch65 Hue, Saturation and Intensity (HIS) transform66 The Discrete Fourier Transform661 Introduction662 Two-dimensional DFT663 Applications67 The Discrete Wavelet Transform671 Introduction672 The one-dimensional Discrete Wavelet Transform673 The two-dimensional Discrete Wavelet Transform68 Summary7 Filtering Techniques71 Introduction72 Spatial domain low-pass (smoothing) filters721 Moving average filter722 Median filter723 Adaptive filters73 Spatial domain high-pass (sharpening) filters731 Image subtraction method732 Derivative-based methods74 Spatial domain edge detectors75 Frequency domain filters76 Summary8 Classification81 Introduction82 Geometrical basis of classification83 Unsupervised classification831 The k-means algorithm832 ISODATA833 A modified k-means algorithm84 Supervised classification841 Training samples842 Statistical classifiers8421 Parallelepiped classifier8422 Centroid (k-means) classifier8423 Maximum likelihood method843 Neural classifiers85 Fuzzy classification and linear spectral unmixing851 The linear mixture model852 Fuzzy classifiers86 Other approaches to image classification87 Incorporation of non-spectral features871 Texture872 Use of external data88 Contextual information89 Feature selection810 Classification accuracy811 Summary9 Advanced Topics91 Introduction92 SAR Interferometry921 Basic principles923 Interferometric processing923 Problems in SAR interferometry924 Applications of SAR interferometry93 Imaging spectrometry931 Introduction932 Processing imaging spectrometer data9321 Derivative analysis9322 Smoothing and denoising the reflectance spectrum Savitzky-Golay polynomial smoothing Denoising using the Discrete Wavelet Transform9323 Determinationof 'red edge' characteristics of vegetation9324 Continuum removal94 Lidar941 Introduction942 Lidar details943 Lidar applicationsAppendix A: Description of Sample Image Data SetsReferencesIndex

Geographic information systems: A management perspective

Abstract: (1989). Geographic information systems: A management perspective. Geocarto International: Vol. 4, No. 4, pp. 58-58.

Remote sensing: Principles and interpretation

Abstract: (1987). Remote sensing: Principles and interpretation. Geocarto International: Vol. 2, Remote Sensing and Biomes, pp. 66-66.

Monitoring US agriculture: the US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program

Abstract: The National Agricultural Statistics Service (NASS) of the US Department of Agriculture (USDA) produces the Cropland Data Layer (CDL) product, which is a raster-formatted, geo-referenced, crop-specific, land cover map. CDL program inputs include medium resolution satellite imagery, USDA collected ground truth and other ancillary data, such as the National Land Cover Data set. A decision tree-supervised classification method is used to generate the freely available state-level crop cover classifications and provide crop acreage estimates based upon the CDL and NASS June Agricultural Survey ground truth to the NASS Agricultural Statistics Board. This paper provides an overview of the NASS CDL program. It describes various input data, processing procedures, classification and validation, accuracy assessment, CDL product specifications, dissemination venues and the crop acreage estimation methodology. In general, total crop mapping accuracies for the 2009 CDLs ranged from 85% to 95% for the major crop categories.