Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping
نویسندگان
چکیده
منابع مشابه
Mapping Continuous Distributions of Land Cover: A Comparison of Maximum-Likelihood Estimation and Artificial Neural Networks
Both maximum-likelihood and neural network classifiers can be used to characterize land cover as continuous fields that represent either class proportions or classification certainty. We compared these two approaches by examining the correspondence between their output values and photointerpreted class proportions of 39 test regions within a heterogeneous study area in southern California. The ...
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soil texture is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. detailed information on soil texture variability is crucial for proper crop and land management and environmental studies. therefore, at present research, 103 soil profiles were dogged and then sampled in order to prepare digital map of soil texture in bijar...
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Proper flood discharge forecasting is significant for the design of hydraulic structures, reducing the risk of failure, and minimizing downstream environmental damage. The objective of this study was to investigate the application of machine learning methods in Regional Flood Frequency Analysis (RFFA). To achieve this goal, 18 physiographic, climatic, lithological, and land use parameters were ...
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ژورنال
عنوان ژورنال: Revista Brasileira de Ciência do Solo
سال: 2013
ISSN: 0100-0683
DOI: 10.1590/s0100-06832013000200005