Satellite Image Classification Method Using the Dempster–Shafer Approach

Popov, Mykhailo; Alpert, Sofiia; Podorvan, V.N.

doi:10.1134/s0001433817090250

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…A data combination method based on application of Jaccard coefficient and Dempster's rule combination was considered in this work. It was shown, that this new method can deal with conflicting sources of information (spectral bands) (Popov et al, 2017;Alpert, 2020).…”

Section: Discussionmentioning

confidence: 99%

Data combination method in Remote Sensing tasks in case of conflicting information sources

Alpert

2021

UJRS

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Nowadays technologies of UAV-based Remote Sensing are used in different areas, such as: ecological monitoring, agriculture tasks, exploring for minerals, oil and gas, forest monitoring and warfare. Drones provide information more rapidly than piloted aerial vehicles and give images of a very high resolution, sufficiently low cost and high precision.Let’s note, that processing of conflicting information is the most important task in remote sensing. Dempster’s rule of data combination is widely used in solution of different remote sensing tasks, because it can processes incomplete and vague information. However, Dempster’s rule has some disadvantage, it can not deal with highly conflicted data. This rule of data combination yields wrong results, when bodies of evidence highly conflict with each other. That’s why it was proposed a data combination method in UAV-based Remote Sensing. This method has several important advantages: simple calculation and high accuracy. In this paper data combination method based on application of Jaccard coefficient and Dempster’s rule of combination is proposed. The described method can deal with conflicting sources of information. This data combination method based on application of evidence theory and Jaccard coefficient takes into consideration the associative relationship of the evidences and can efficiently handle highly conflicting sources of data (spectral bands).The frequency approach to determine basic probability assignment and formula to determine Jaccard coefficient are described in this paper too. Jaccard coefficient is defined as the size of the intersection divided by the size of the union of the sample sets. Jaccard coefficient measures similarity between finite sets. Some numerical examples of calculation of Jaccard coefficient and basic probability assignments are considered in this work too.This data combination method based on application of Jaccard coefficient and Dempster’s rule of combination can be applied in exploring for minerals, different agricultural, practical and ecological tasks.

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Section: Discussionmentioning

confidence: 99%

Data combination method in Remote Sensing tasks in case of conflicting information sources

Alpert

2021

UJRS

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“…Нагадаємо, що навчальна вибіркаце набір пікселів із відомими в результаті наземних спостережень класами [8][9][10][11].…”

Section: процедура відбору інформативної підсистеми ознакunclassified

A new band selection method for multispectral data based on criterion function of information capability

Alpert¹

2023

MDCS

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Multispectral remote sensing is one of the most popular techniques in the earth observation, because this technique can provide information of ground objects on Earth’s surface using hundreds of narrow bands. However, multispectral images produces a very large volume of data. Processing the huge volume of information is one of most important and actual problems of remote sensing. The rapid development of the remote sensing demand to develop the data processing algorithms. But at present data processing techniques cannot give accurate results. If we use traditional methods to process multispectral images, the volume of the data increases. The main goal of the band selection is to choose the optimal combination of spectral bands for the solution of the particular remote sensing task. This process is important because different bands are sensitive to different objects. Selecting the right bands can help to optimize the detection of different ground objects. Some spectral bands are more sensitive to minerals, while others are more sensitive to vegetation or water bodies. Under a small number of training samples, the classification accuracy of multispectral images decreases when the volume of multispectral data increases. Usually adjacent bands are highly correlated, and some spectral bands may not carry unique information. That’s why it is necessarily to reduce the dimensionality of multispectral data. It helps to store, process, transmit information more efficiently and to reduce the computational costs while processing images. The different modern methods of multispectral band selection are also considered and analyzed in this work. It also is proposed a new method to select spectral bands, which is based on the concept of criterion function of information capability of spectral bands. In this article some examples using criterion function of information capability are considered too.

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“…Наголошувалося на тому, що дрони застосовуються для проведення моніторингу сільськогосподарських земель, прогнозу врожайності, у контролі снігового і льодового покриву, у воєнній справі, в екологічному контролі, у контролі морського судноплавства та у багатьох інших сферах. Супутниковий моніторинг у поєднанні з БПЛА дозволяє досить швидко та ефективно вирішувати задачі дистанційного зондування Землі (ДЗЗ) (Alpert et al, 2020;Popov et al, 2017;.…”

Section: висновкиunclassified

Satellite monitoring problems in the aerospace complex

Alpert

2020

UJRS

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Задачі підсуNowadays with the rapid development of information technologies, UAV-based Remote Sensing (drone remote sensing) gives a new opportunities for conducting scientific research in a much more detail way. UAVs (unmanned aerial vehicles) give the opportunity to acquire data at sufficiently low cost. They also provide remote data more rapidly than piloted aerial vehicles. Nowadays drones are often used, because application of piloted aerial vehicles can be dangerous, difficult and expensive for some territories. Application of low altitude UAVs give a possibility to achieve images with a very high resolution and sufficient precision. In this article structure and main details of drones were considered. It also was noted, that technologies of UAV-based Remote Sensing are used in different areas.Agricultural drones help to analyze crops, make decisions on how to use the crop information and take the necessary actions to correct the problems. These unmanned aerial vehicles let to see fields from the sky. Agricultural drones are used to help increase crop production and monitor crop growth. Drones and sensors give a detail picture of fields. They can survey the fields periodically. Agricultural drones can reveal many issues such as soil variation, pest infestations and changes in the crops over time. They also show differences between healthy and unhealthy plants. Drones are flied over the crops and help to make decisions on how to proceed given the crop information. Nowadays there is a large capacity for growth in the area of agricultural unmanned aerial vehicles. With technology constantly improving, imaging of the crops will need to improve as well.Drones are used for exploring for minerals and mapping deposit sites, they are used in the oil and gas industry for remote monitoring. Drones can provide information of nature disasters and give help to assess property damage. They help to conduct forest monitoring and to assess plant health. Unmanned aerial vehicles are also used in a military capacity and ecological monitoring. It also was noted, that there is a large capacity for development and improvement of unmanned aerial vehicles.путникового моніторингу в аерокосмічному комплексі

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Satellite Image Classification Method Using the Dempster–Shafer Approach

Cited by 5 publications

References 10 publications

Data combination method in Remote Sensing tasks in case of conflicting information sources

Data combination method in Remote Sensing tasks in case of conflicting information sources

A new band selection method for multispectral data based on criterion function of information capability

Satellite monitoring problems in the aerospace complex

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