However, there are no similar studies on the complex of nongregarious locusts, and due to the polyphagous nature of these pests, their study is very relevant for the agricultural regions of North Kazakhstan. In addition, the proposed approaches and methods can be used by other researchers in solving similar problems. In terms of the prevalence of nongregarious locust pests, the regions of North Kazakhstan belong to a region with a high pest population degree. They damage grains, legumes, forage crops, and pasture lands. According to the conducted observations in recent years there has been an increase in the number of these phytophages and pest infestation exceeding the economicharmfulness threshold (above 10 individuals per 1 sq. m) has been observed in many grain crops of North Kazakhstan.
Author(s) Details:
Kurmet Baibussenov
S. Seifullin Kazakh Agro Technical University, 62 Zhenis Ave., 010011, Nur-Sultan, Republic of Kazakhstan.
Aigul Bekbayeva
S. Seifullin Kazakh Agro Technical University, 62 Zhenis Ave., 010011, Nur-Sultan, Republic of
Kazakhstan
Valery Azhbenov
Zh. Zhyembaev Kazakh Scientific Research Institute of Plant Protection and Quarantine, 1 Kultobe
Str., 050000, Almaty, Republic of Kazakhstan.
Also See : Biodiversity Hotspot : A Part from the Book Chapter : Pteridophyte Flora of Western Ghats- A Review
Recent Global Research Developments in GIS-Based Modeling for Locust Management in Northern Kazakhstan
GIS-based Potential Distribution Modeling for Harmful Non-Gregarious Locusts in Agricultural Areas of Northern Kazakhstan:
- Researchers used MaxEnt software based on GIS and remote sensing data to predict the potential distribution of harmful non-gregarious locusts.
- The study considered environmental, climatic conditions, agricultural land management, and pesticide application [1].
- The goal was to prioritize areas for risk assessment, monitoring, and early prevention measures.
Design and Implementation of Geographic Information Systems (GIS) and Remote Sensing (RS) for Locust Control:
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- An information platform was developed using GPS, RS, and GIS to monitor and control locusts effectively [2].
- This platform provides accurate information about locust occurrence and control strategies for specific geographic locations.
Application of Remote Sensing Data for Locust Research and Management:
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- A comprehensive review paper summarized remote sensing-based studies for locust management over the past four decades [3].
- It quantified locust species, regions of interest, sensor data, and thematic foci.
Locust Habitat Monitoring and Risk Assessment Using Remote Sensing and GIS:
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- This chapter provides insights into using geospatial tools for locust habitat monitoring and risk assessment [4].
- It covers concepts, data collected by remote sensing satellites, and applications in locust management.
References
- Baibussenov, K., Bekbayeva, A., & Azhbenov, V. GIS-based Potential Distribution Modeling for Harmful Non-Gregarious Locusts in Agricultural Areas of Northern Kazakhstan to Improve Preventive Pest Management.
- Li, L., Zhu, D., Ye, S., Yao, X., Li, J., Zhang, N., … & Zhang, L. (2014). Design and implementation of geographic information systems, remote sensing, and global positioning system–based information platform for locust control. Journal of Applied Remote Sensing, 8(1), 084899-084899.
- Klein I, Oppelt N, Kuenzer C. Application of Remote Sensing Data for Locust Research and Management—A Review. Insects. 2021; 12(3):233. https://doi.org/10.3390/insects12030233
- Latchininsky, A.V., Sivanpillai, R. (2010). Locust Habitat Monitoring and Risk Assessment Using Remote Sensing and GIS Technologies. In: Ciancio, A., Mukerji, K. (eds) Integrated Management of Arthropod Pests and Insect Borne Diseases. Integrated Management of Plant Pests and Diseases, vol 5. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8606-8_7