Model of optimum integration of diverse geodata for the benefit of management of forestry

Istomin, Eugene; Stepanov, S.; Petrov, Yaroslav; Kolbina, O.; Sidorenko, A.

doi:10.1088/1755-1315/316/1/012013

Cited by 10 publications

(3 citation statements)

References 6 publications

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“…Used to build software, using APIs, programmers can more easily "disassemble" software so that it can be developed or integrated with other software. API can connect an application with other applications that allow them to use system functions [10]. This process managed by the operating system, the advantage of this API is that it allows applications to associate and interact with other applications.…”

Section: Google Maps Apimentioning

confidence: 99%

Android Based Forest Fire Monitoring System

Andrea¹,

Wahyuni²,

Safitri³

et al. 2022

IJIEEB

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Forest fires are burning areas of forest or land in large or small areas. Forest fires are often uncontrollable and when this happens, the fire will burn anything nearby for two reasons, one of which is burning naturally or burning caused by humans. One of the man-made fires deliberate by humans is the burning used by the community around the forest to open or clear agricultural or plantation land. The community feels that clearing land with fire does not require a long time and is more economical, if the use of fire is not used properly it can cause the forest to burn. Forest fires in Riau area are still classified as minimal or fires rarely occur. However, the community is at least aware of the forest fires in Riau due to a lack of media information about where the fire hotspots occurred. With this application, it can help the public to better know where the hotspots have been burned. This application consists of 2 levels of access, namely: admin and user. For admins and users, the manufacturing process uses the Android Studio application with Java as the programming language, this application uses Firebase as its database to find out the location of fire hotspots using the Google Maps API. Testing on the application is created to test whether the application has run as desired. Test results using white box testing method.

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Section: Google Maps Apimentioning

confidence: 99%

Android Based Forest Fire Monitoring System

Andrea¹,

Wahyuni²,

Safitri³

et al. 2022

IJIEEB

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show abstract

“…However, this information, in its technical form, only provides broad forest information and features. The formation of new models for making management decisions has been described in various studies [2][3][4][5]. When a person completes a forest inventory task, the subjective aspect must be considered when evaluating taxation features.…”

Section: Introductionmentioning

confidence: 99%

Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

et al. 2021

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This article discusses the process of creating a digital forest model based on remote sensing data, three-dimensional modeling, and forest inventory data. Remote sensing data of the Earth provide a fundamental tool for integrating subsequent objects into a digital forest model, enabling the creation of an accurate digital model of a selected forest quarter by using forest inventory data in educational and experimental forestry, and providing a valuable and extensive database of forest characteristics. The formalization and compilation of technologies for connecting forest inventory databases and remote sensing data with the construction of three-dimensional tree models for a dynamic display of changes in forests provide an additional source of data for obtaining new knowledge. The quality of forest resource management can be improved by obtaining the most accurate details of the current state of forests. Using machine learning and regression analysis methods as part of a digital model, it is possible to visually assess the course of planting growth, changes in species composition, and other morphological characteristics of forests. The goal of digital, interactive forest modeling is to create virtual simulations of the future status of forests using a combination of predictive forest inventory models and machine learning technology. The research findings provide a basic idea and technique for developing local digital forest models based on remote sensing and data integration technologies.

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“…Density gradients in the ocean are quite small, therefore, to move particles vertically does not require large expenditures of energy and the amplitudes of internal waves can increase to large sizes (can reach tens of meters, but at the same time a slight increase in the level surface of the order of several centimeters) [4,13]. The cellular flows that accompany these oscillations are of the order of the phase velocities of the internal waves.…”

Section: Introductionmentioning

confidence: 99%

Determination of Internal Waves Off the Coast of Morocco According to Earth Remote Sensing Data

Tatarnikova

Martyn

Stepanov

et al. 2020

Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2

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This paper presents the results of a study of the internal wave isolation of the Northern coast of Morocco using synthetic aperture radar (SAR) images. A filter is applied to the remote sensing data to reduce the image grain, after which the direction of propagation of the wave is determined and its length is calculated. In most cases, internal waves appear on satellite images as quasi-periodic linear structures whose brightness is lower or higher than the background, which is well registered in the visible range and by synthetic aperture radar. When analyzing images off the coast of Morocco, internal waves were detected, the wave packet propagates in the direction from West to East. When comparing the obtained images with the bottom relief map, it can be assumed that the generation of internal waves is caused by the roughness of the bottom near the Northern coast of Morocco. The maximum wave length in the wave packet is almost 0.7 km, consists of at least 5 solitons, the prints of these solitons in the sea roughness area are visible in the images mainly in the Central part of a wave packet, the distance between a wave packet solitons is different. The wavelength decreases when moving to the back of a wave packet, which can be traced by changing the contrast on the site. As a result, internal waves were detected off the Northern coast of Morocco in rads images with a synthesized aperture, and the main characteristics of these waves were determined.

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Model of optimum integration of diverse geodata for the benefit of management of forestry

Cited by 10 publications

References 6 publications

Android Based Forest Fire Monitoring System

Android Based Forest Fire Monitoring System

Visual Digital Forest Model Based on a Remote Sensing Data and Forest Inventory Data

Determination of Internal Waves Off the Coast of Morocco According to Earth Remote Sensing Data

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