Simulation of Favorable Habitats for Non-Gregarious Locust Pests in North Kazakhstan Based on Satellite Data for Preventive Measures

Baibussenov, Kurmet; Bekbayeva, Aigul; Azhbenov, Valery

doi:10.12911/22998993/150043

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Efforts to predict forest fire behaviors have been ongoing for some time, with RS and GIS playing pivotal roles globally in studying forest fires and associated risk zones [3][4][5]. The advantages of these methods include their rapid, noninvasive nature and their ability to offer expansive coverage, thereby surpassing traditional field observations [6][7][8].…”

Section: Current Techniques and Limitationsmentioning

confidence: 99%

Assessing Pine Forest Restoration Post-Fire Using NDVI and GIS Technologies

Sagynbayeva,

Mambetov,

Kalachev

et al. 2023

IJDNE

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This study addresses the pressing and pertinent issue of establishing a space-based monitoring system to track forest condition changes. Utilizing geographic information system technologies and the Normalized Difference Vegetation Index (NDVI), it examines the evolution and dynamics of pine forest regeneration in the Semey Ormany State Forest Natural Reserve (Zhanasemey branch), Kazakhstan. Landsat-5 satellite data were employed to map and identify terrestrial vegetation changes within the Zhanasemey branch. Satellite imagery for June 2007 and September 2008 were specifically utilized for this investigation. Post-acquisition, the satellite images were subjected to corrections, followed by radiometric adjustments to minimize atmospheric interference. Subsequently, NDVI classifications, an established method for plant classification, were applied to each image. The study focused on a 15-year timespan (2008 to 2022) to monitor changes in vegetation intensity, classified according to NDVI, and to track the reforestation process in areas affected by fire. Analysis of the regeneration of the pine forest post the 2008 fire, conducted at five-year intervals, revealed an increase in the restored forest area from 6,773.49 ha in 2013 to 10,721.07 ha in 2018, and finally to 14,742.54 ha in 2022. In 2008, the fire-impacted area with reduced vegetation spanned 7,015.41 ha, while by 2022, the restored area encompassed 14,742.54 ha, indicating a significant enhancement in the pine forest restoration process. The findings underscore the critical role of remote sensing in forest fire modelling and identifying areas at risk, suggesting its potential utility in large-scale monitoring and management efforts. The study demonstrates the feasibility and efficiency of using space-based technologies to monitor long-term changes in forest conditions and to track reforestation dynamics in fire-affected regions.

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Section: Current Techniques and Limitationsmentioning

confidence: 99%

Assessing Pine Forest Restoration Post-Fire Using NDVI and GIS Technologies

Sagynbayeva,

Mambetov,

Kalachev

et al. 2023

IJDNE

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“…2) Natural disasters. Such phenomena as floods, droughts, and pest invasions [26] can lead to significant losses of crops, livestock, and fish stocks, thereby affecting the availability of food [38].…”

Section: Factor Analysismentioning

confidence: 99%

Data-Driven Management of Regional Food Security for Sustainable Development: A Case Study of Kazakhstan

Dulambayeva,

Jumabayev,

Bedelbayeva

et al. 2023

IJSDP

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The purpose of the paper is to evaluate the possibility of implementing a food security management system in the Republic of Kazakhstan using the concept of data-driven decisionmaking in terms of achieving the principles of sustainable development. To achieve the goal set in the study, the authors use qualitative and statistical methods for processing the results obtained. Based on the analysis of internal and external factors, the authors determine indicators of food security in Kazakhstan for basic types of agricultural products/food in 2021, factors of influence on regional food security, and indicators of regional food security, which should be considered when making data-driven management decisions. A special external factor for Kazakhstan is the current geopolitical situation caused by the invasion of Russian troops in Ukraine. The study finds that in the process of managing regional food security, the use of the data-driven decision-making concept makes it possible to adequately assess the initial state of the problem and determine the optimal methods for its solution. The study identifies key internal and external factors influencing food security in the region and proposes a data-driven decision-making algorithm for managing food security. The results highlight the potential of this approach for improving food security management in the context of sustainable development.

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Effect of fertilizers and growth stimulants on the content of coumarin and its derivatives in the vegetative mass of melilot

Suraganov,

Seilkhanov,

Sagalbekov

et al. 2024

Braz. J. Biol.

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The paper presents the results of determining the content of coumarin and its derivatives in the melilot using nuclear magnetic resonance spectroscopy, including the study of the effect of fertilizers on the quantitative content of coumarin and its derivatives in the composition of the melilot treated by phases using the method of 1H and 13C nuclear magnetic resonance spectroscopy. Based on the results of the nuclear magnetic resonance spectroscopy, the possibility of qualitative and quantitative determination of the content of coumarin and its derivatives isolated from extracts of fertilized melilot was evaluated. The effect of eight preparations on the plant and its concentration in solution on the content of coumarin substances in the Altynbas yellow melilot variety was studied. It was shown that the preparations have a slight effect on the coumarin content in the melilot and, accordingly, on the quality of feed based on it. In the control variant (variant 9), the coumarin proton content was 9.85%, and the maximum coumarin proton content was observed in the variant where BioEnergy was used as fertilizer and amounted to 22.44%.

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Simulation of Favorable Habitats for Non-Gregarious Locust Pests in North Kazakhstan Based on Satellite Data for Preventive Measures

Cited by 3 publications

References 18 publications

Assessing Pine Forest Restoration Post-Fire Using NDVI and GIS Technologies

Assessing Pine Forest Restoration Post-Fire Using NDVI and GIS Technologies

Data-Driven Management of Regional Food Security for Sustainable Development: A Case Study of Kazakhstan

Effect of fertilizers and growth stimulants on the content of coumarin and its derivatives in the vegetative mass of melilot

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