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Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition
20 Mar 2019-
TL;DR: In this article, images, arrays, and vectors are used for image registration and classification, and transformations are used to represent the transformation of images, images, and arrays of vectors.
Abstract: Images, Arrays, and Vectors. Image Statistics. Transformations. Radiometric Enhancement. Topographic Modeling. Image Registration. Image Sharpening. Change Detection. Unsupervised Classification. Supervised Classification. Hyperspectral Analysis.
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TL;DR: In this paper, the authors developed methods for assessing crown base height for individual trees using airborne lidar data in forest settings typical for the southeastern United States, and evaluated the accuracy of estimating crown base heights of individual trees.
348 citations
TL;DR: A context-sensitive technique for unsupervised change detection in multitemporal remote sensing images based on fuzzy clustering approach and takes care of spatial correlation between neighboring pixels of the difference image produced by comparing two images acquired on the same geographical area at different times.
307 citations
Cites background or methods from "Image Analysis, Classification and ..."
...In supervised techniques, a set of training patterns is required for learning the ....
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...…Remote sensing Change detection Multi-temporal images Fuzzy clustering Fuzzy c-means clustering Gustafson–Kessel clustering Genetic algorithms Simulated annealing Xie–Beni validity measure 0020-0255/$ - see front matter 2010 Elsevier Inc doi:10.1016/j.ins.2010.10.016 ⇑ Corresponding author....
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TL;DR: A recently proposed method for automatic radiometric normalization of multi- and hyperspectral imagery based on the invariance property of the Multivariate Alteration Detection (MAD) transformation and orthogonal linear regression is extended by using an iterative re-weighting scheme involving no-change probabilities.
292 citations
Additional excerpts
...Extensions to ENVI for image registration, wavelet fusion, the IR-MAD transformation and radiometric normalization were written in the IDL language, see Canty (2007) for software availability....
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TL;DR: Overall, increased temperature and enhanced precipitation favored vegetation growth, however, their combined effects exhibited strong spatial heterogeneity, and precipitation was the limiting factor in Tibet during dry periods.
Abstract: Grasslands occupy nearly three quarters of the land surface of the Qinghai-Tibet plateau (QTP) and play a critical role in regulating the ecological functions of the QTP. Ongoing climate change and human interference have greatly affected grasslands on the QTP. Differentiating human-induced and climate-driven vegetation changes is vital for both ecological understanding and the management of husbandry. In this study, we employed statistical analysis of annual records, various sources of remote sensing data, and an ecosystem process model to calculate the relative contribution of climate and human activities to vegetation vigor on the QTP. The temperature, precipitation and the intensity and spatial pattern of livestock grazing differed between the periods prior to and after the year 2000, which led to different vegetation dynamics. Overall, increased temperature and enhanced precipitation favored vegetation growth. However, their combined effects exhibited strong spatial heterogeneity. Specifically, increased temperature restrained vegetation growth in dry steppe regions during a period of slightly increasing precipitation from 1986 to 2000 and in meadow regions during a period of precipitation decline during 2000–2011, thereby making precipitation a dominant factor. An increase in precipitation tended to enhance vegetation growth in wet meadow regions during warm periods, and temperature was the limiting factor in Tibet during dry periods. The dominant role played by climate and human activities differed with location and targeted time period. Areas dominated by human activities are much smaller than those dominated by climate. The effects of grazing on grassland pasture were more obvious under unfavorable climate conditions than under suitable ones.
194 citations
TL;DR: An optimal atmospheric correction model is described, as well as an improved algorithm for sunglint removal based on combined physical and image processing techniques, and results of atmospheric correction, remote bathymetry, and benthic habitat mapping of shallow-water environments have been validated.
Abstract: Coastlines, shoals, and reefs are some of the most dynamic and constantly changing regions of the globe. The emergence of high-resolution satellites with new spectral channels, such as the WorldView-2, increases the amount of data available, thereby improving the determination of coastal management parameters. Water-leaving radiance is very difficult to determine accurately, since it is often small compared to the reflected radiance from other sources such as atmospheric and water surface scattering. Hence, the atmospheric correction has proven to be a very important step in the processing of high-resolution images for coastal applications. On the other hand, specular reflection of solar radiation on nonflat water surfaces is a serious confounding factor for bathymetry and for obtaining the seafloor albedo with high precision in shallow-water environments. This paper describes, at first, an optimal atmospheric correction model, as well as an improved algorithm for sunglint removal based on combined physical and image processing techniques. Then, using the corrected multispectral data, an efficient multichannel physics-based algorithm has been implemented, which is capable of solving through optimization the radiative transfer model of seawater for bathymetry retrieval, unmixing the water intrinsic optical properties, depth, and seafloor albedo contributions. Finally, for the mapping of benthic features, a supervised classification methodology has been implemented, combining seafloor-type normalized indexes and support vector machine techniques. Results of atmospheric correction, remote bathymetry, and benthic habitat mapping of shallow-water environments have been validated with in situ data and available bionomic profiles providing excellent accuracy.
179 citations