Information technology of early crop identification by using satellite images

Vorobiova, N. S.; Sergeyev, V. V.; Чернов, А. В.

doi:10.18287/2412-6179-2016-40-6-929-938

Cited by 29 publications

(11 citation statements)

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“…For the future works it is interesting to investigate also the approaches based on the machine learning methods like publications [19]…”

Section: Resultsmentioning

confidence: 99%

“…In a series of papers published in 2009-2016 [16], [17], [18], [19] a method of hierarchical lossless compression for the purpose of storing HSI was constructed. The following requirements for the method were formulated: 1) the possibility of compression of multi-channel images; 2) quick access to fragments of compressed images at various scales; 3) low computational complexity of decompression; 4) strict error control; 5) high efficiency in "no-error" mode and with small errors; 6) use of interchannel dependencies; 7) quick access to the specified components of compressed images at various scales; 8) compression of 16-bit images.…”

Section: Introductionmentioning

confidence: 99%

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Investigation of hyperspectral image pixel signatures by the empirical mode decomposition method

Pahomov¹,

Borusyak²,

Турлапов

2018

Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology

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The signature of hyperspectral image (HSI) pixels and their decomposition into empirical modes (EM) and low-frequency residuals are investigated. On the basis of estimates related to the EM-decomposition method, the possibility of switching from a 2-byte representation of the values of the HIS-signature to a 1-byte one is examined using the example of the Moffett Field from the AVIRIS spectrometer. It is revealed that the localization of the minimum window sizes for the first EM is correlated with the localization of the significant influence of the atmosphere; the first low-frequency residues have a fairly high correlation coefficient with the signature and the first 2 of them and their EM are most interesting for use; 50 of the 224 HIS-channels are noisy and can be excluded from consideration; EM with practically no loss of accuracy can be reduced to a 1-byte representation. The management of the classification capabilities of signatures by changing the threshold value of the correlation coefficient with the sample, as well as the application of the 1st and 2nd low-frequency residues in place of the signature, was studied. Classification capabilities of signatures in a 1byte representation are almost equivalent to a 2-byte one, which makes it possible to put a signature with 1-byte representation as the object of compression. For the wavelet decomposition of the HSI data array, in combination with a 1-byte representation, a nearlossless compression ratio of 6.65 is obtained.

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“…For the future works it is interesting to investigate also the approaches based on the machine learning methods like publications [19]…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Investigation of hyperspectral image pixel signatures by the empirical mode decomposition method

Pahomov¹,

Borusyak²,

Турлапов

2018

Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology

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“…After a detailed analysis of European and Russian ratings and evaluation systems, a methodology was developed for assessing cities to introduce technologies of the "digital state", taking into account all the features of the Volga region [3][4][5][6].…”

Section: Analysis Of Existing Ratings In the Concept Of "Digital State"mentioning

confidence: 99%

Data Modelling to Analyze How the Cities in the Volga Region Correspondent to the Digital State Format

Khaimovich¹,

Рамзаев²,

Chumak³

2018

Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology

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The article suggests the methodology for assessing the readiness of Volga region municipal entities to introduce digital state. The authors worked out a model of statistic tests based on multiple probability theoretic and statistical modelling of parameter values of technological elements of digital economy. This model will allow the Volga region cities to define their possibility to participate in the State Program of Digital Economy, to choose cities most suitable for introduction of modern technologies, to identify the main shortcomings hindering their integration into the program. This research may be of interest to experts in the field of digital economy and Big Data management.

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“…Так, в работе [1] 2016 года реализована технология решения задачи раннего распознавания видов с/х культур по космическим снимкам полей в разные периоды вегетации в ситуации недостаточности исходных космических и наземных данных для формирования полноценной обучающей выборки. Метод основан на комбинации данных экспериментальных исследований на территории Самарской области.…”

Section: Introductionunclassified

Complex analysis and monitoring of the environment based on earth sensing data

et al. 2019

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We study a problem of complex analysis and monitoring of the environment based on Earth Sensing Data, with the emphasis on the use of hyperspectral images (HSI), and propose a solution based on developing algorithmic procedures for HSI processing and storage. HSI is considered as a two-dimensional field of pixel signatures. Methods are proposed for evaluating the similarity of a HSI pixel signature with a reference signature, via simple alignment transformations: identical; amplitude scaling; shift along y-axis; and a combination of the last two. A clustering / recognition method with self-learning is proposed, which determines values of the transformation parameters that ensure the alignment of the current pixel signature with the reference signature. Similarity with the reference is determined by a standard deviation value. A HSI compression method with controlled losses has been proposed. The method forms a basis via accumulating reference signatures and represents the rest of the signatures by parameters matching them with the already detected class-reference signature. In an experiment with the GSI f100520t01p00-12 data of the AVIRIS spectrometer, the method provided a 2 % loss and compression coefficients of the original HSI ranging from 43 to 165 for various types of alignment transformation, while not requiring archiving and thus maintaining active access to the HSI and using the list of references as an analogue of the HSI palette. An algorithm for the formation of dense groups of detectable objects (for example, oil spots) and their nonconvex contouring, controlled by 4 parameters, is proposed. A pilot version of the concept of geographic information system (GIS) and an appropriate database management system (DBMS) was built and implemented, which provides monitoring and is based on the prioritized processing and storage of the HSI, which serve as a data source for the system. A laboratory complex with new algorithms for processing and storing the GSE is introduced into the structure of the system.

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Information technology of early crop identification by using satellite images

Cited by 29 publications

References 0 publications

Investigation of hyperspectral image pixel signatures by the empirical mode decomposition method

Investigation of hyperspectral image pixel signatures by the empirical mode decomposition method

Data Modelling to Analyze How the Cities in the Volga Region Correspondent to the Digital State Format

Complex analysis and monitoring of the environment based on earth sensing data

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