logo
calendar31 Avgust 2026
view12
Asosiy til:Ingliz

Markaziy Osiyoda shamol eroziyasi va chang emissiyasini masofadan zondlash va GIS yordamida monitoring qilish

Fan yo'nalishi:Ko'p tarmoqli
pdf

A-4_fc46aa54.pdf

PDF

MAQOLA ANNOTATSIYASI

quote
Ushbu sharh Markaziy Osiyoning qurg'oqchil va yarim qurg'oqchil hududlarida shamol eroziyasi va chang emissiyasini monitoring qilishda masofadan zondlash va GIS yondashuvlarini tanqidiy baholaydi. Optik sun'iy yo'ldosh kuzatuvlari, SAR/InSAR, UAV, RWEQ kabi eroziya modellari va aerozol mahsulotlari ko'rib chiqiladi. Natijalar optik ma'lumotlar o'simlik qoplami va ochiq tuproqni baholashda samarali ekanligini, SAR/InSAR strukturaviy o'zgarishlarni to'ldirishini va AOD/AAI chang hodisalarining atmosfera bosqichini tavsiflashini ko'rsatadi. Orol dengizi havzasi kabi mintaqaviy manbalarni kuzatish uchun masofadan zondlash, GIS, eroziya modellari va meteorologik kuzatuvlarni birlashtirgan integratsiyalashgan tizim eng istiqbolli yo'nalish sifatida ta'kidlanadi.

MUALLIFLAR

A.Mamatkulov

"TUPROQSHUNOSLIK VA AGROKIMYOVIY TADQIQOTLAR INSTITUTI" DAVLAT MUASSASASI

Z.Baxodirov

"TUPROQSHUNOSLIK VA AGROKIMYOVIY TADQIQOTLAR INSTITUTI" DAVLAT MUASSASASI

S.Eshmurodov

"TUPROQSHUNOSLIK VA AGROKIMYOVIY TADQIQOTLAR INSTITUTI" DAVLAT MUASSASASI

Teglar

# GIS# Markaziy Osiyo# masofadan zondlash# chang emissiyasi# shamol eroziyasi

O'XSHASH MAQOLALAR

SHU JURNALDAGI BOSHQA MAQOLALAR

Maqolani baholang

0
0 ta baho
5
4
3
2
1

Foydalanilgan adabiyotlar

Alfaro, S. C., & Gomes, L. (2001). Modeling mineral aerosol production by wind erosion: Emission intensities and aerosol size distributions in source areas. Journal of Geophysical Research: Atmospheres, 106(D16), 18075–18084. https://doi.org/10.1029/2000JD900339

Banks, J. R., Heinold, B., & Schepanski, K. (2022). Impacts of the desiccation of the Aral Sea on the Central Asian dust life-cycle. Journal of Geophysical Research: Atmospheres, 127, e2022JD036618. https://doi.org/10.1029/2022JD036618

Borrelli, P., Alewell, C., Alvarez, P., Ayach Anache, J. A., Baartman, J., Ballabio, C., et al. (2021). Soil erosion modelling: A global review and statistical analysis. Science of the Total Environment, 780, 146494. https://doi.org/10.1016/j.scitotenv.2021.146494

Chen, Z., Gao, X., & Lei, J. (2022). Dust emission and transport in the Aral Sea region. Geoderma, 428, 116177. https://doi.org/10.1016/j.geoderma.2022.116177

Chen, Z., Gao, X., & Lei, J. (2025). Monitoring of wind erosion in the southern Aral Sea using SBAS-InSAR technology. International Soil and Water Conservation Research, 13(3), 551–563. https://doi.org/10.1016/j.iswcr.2025.05.005

Chi, W., Zhao, Y., Kuang, W., & He, H. (2019). Impacts of anthropogenic land use/cover changes on soil wind erosion in China. Science of the Total Environment, 668, 204–215. https://doi.org/10.1016/j.scitotenv.2019.03.015

Fryrear, D. W., Chen, W., & Lester, C. (2001). Revised Wind Erosion Equation. Annals of Arid Zone, 40(3). https://doi.org/10.56093/aaz.v40i3.65816

Gao, G., Yin, X., Ding, G., Zhao, Y., Sun, G., & Wang, L. (2022). Soil erodibility for wind erosion: A critical review. Science of Soil and Water Conservation, 20(1), 143–150. https://doi.org/10.16843/j.sswc.2022.01.019

Hagen, L. J. (1991). A wind erosion prediction system to meet user needs. Journal of Soil and Water Conservation, 46(2), 106–111. https://doi.org/10.1080/00224561.1991.12456588

Hagen, L. J. (2004). Evaluation of the Wind Erosion Prediction System (WEPS) erosion submodel on cropland fields. Environmental Modelling & Software, 19(2), 171–176. https://doi.org/10.1016/S1364-8152(03)00119-1

Indoitu, R., Kozhoridze, G., Batyrbaeva, M., Vitkovskaya, I., Orlovsky, N., Blumberg, D., & Orlovsky, L. (2015). Dust emission and environmental changes in the dried bottom of the Aral Sea. Aeolian Research, 17, 101–115. https://doi.org/10.1016/j.aeolia.2015.02.004

Jarrah, M., Mayel, S., Tatarko, J., Funk, R., & Kuka, K. (2020). A review of wind erosion models: Data requirements, processes, and validity. CATENA, 187, 104388. https://doi.org/10.1016/j.catena.2019.104388

Juliev, M., Kholmurodova, M., Abdikairov, B., & Abuduwaili, J. (2024). A comprehensive review of soil erosion research in Central Asian countries (1993–2022) based on the Scopus database. Soil and Water Research, 19(4), 244–256. https://doi.org/10.17221/82/2024-SWR

Lackoóvá, L., Lieskovský, J., Nikseresht, F., Halabuk, A., Hilbert, H., Halászová, K., & Bahreini, F. (2023). Unlocking the potential of remote sensing in wind erosion studies: A review and outlook for future directions. Remote Sensing, 15(13), 3316. https://doi.org/10.3390/rs15133316

Li, J., Ma, X., & Zhang, C. (2020). Predicting the spatiotemporal variation in soil wind erosion across Central Asia in response to climate change in the 21st century. Science of the Total Environment, 709, 136060. https://doi.org/10.1016/j.scitotenv.2019.136060

Baxodirov, Z. A., Mamatkulov, A. R., & Nurmatov, R. Sh. (2022). Noveyshie metody monitoringa vetrovoy erozii pochv [Latest methods for monitoring soil wind erosion]. Science and Innovation, 6, 38–46. https://doi.org/10.5281/zenodo.7086755; https://doi.org/10.5281/zenodo.13908141

Nishonov, B. E., Kholmatjanov, B. M., Labzovskii, L. D., Rakhmatova, N., Shardakova, L., Abdulakhatov, E. I., Yarashev, D. U., Toderich, K. N., Khujanazarov, T., & Belikov, D. A. (2023). Study of the strongest dust storm occurred in Uzbekistan in November 2021. Scientific Reports, 13, 20042. https://doi.org/10.1038/s41598-023-42256-1

Seo, I. W., Lim, C. S., Yang, J. E., Lee, S. P., Lee, D. S., Jung, H. G., Lee, K. S., & Chung, D. Y. (2020). An overview of applicability of WEQ, RWEQ, and WEPS models for prediction of wind erosion in lands. Korean Journal of Agricultural Science, 47(2), 381–394. https://doi.org/10.7744/kjoas.20200028

Tatarko, J., Sporcic, M. A., & Skidmore, E. L. (2013). A history of wind erosion prediction models in the United States Department of Agriculture prior to the Wind Erosion Prediction System. Aeolian Research, 10, 3–8. https://doi.org/10.1016/j.aeolia.2012.08.004

Van Pelt, R. S., Zobeck, T. M., Potter, K. N., Stout, J. E., & Popham, T. W. (2004). Validation of the wind erosion stochastic simulator (WESS) and the revised wind erosion equation (RWEQ) for single events. Environmental Modelling & Software, 19(2), 191–198. https://doi.org/10.1016/S1364-8152(03)00122-1

Voss, K. K., & Evan, A. T. (2020). A new satellite-based global climatology of dust aerosol optical depth. Journal of Applied Meteorology and Climatology, 59(1), 83–102. https://doi.org/10.1175/JAMC-D-19-0194.1

Wagner, L. E. (2013). A history of wind erosion prediction models in the United States Department of Agriculture: The Wind Erosion Prediction System (WEPS). Aeolian Research, 10, 9–24. https://doi.org/10.1016/j.aeolia.2012.10.001

Wang, W., Samat, A., Ge, Y., Ma, L., Tuheti, A., Zou, S., & Abuduwaili, J. (2020). Quantitative soil wind erosion potential mapping for Central Asia using the Google Earth Engine platform. Remote Sensing, 12(20), 3430. https://doi.org/10.3390/rs12203430

Webb, N. P., McGowan, H. A., Phinn, S. R., & McTainsh, G. H. (2006). AUSLEM (AUStralian Land Erodibility Model): A tool for identifying wind erosion hazard in Australia. Geomorphology, 78(3–4), 179–200. https://doi.org/10.1016/j.geomorph.2006.01.012

Webb, N. P., McGowan, H. A., Phinn, S. R., McTainsh, G. H., & Leys, J. F. (2009). Simulation of the spatiotemporal aspects of land erodibility in the northeast Lake Eyre Basin, Australia, 1980–2006. Journal of Geophysical Research: Earth Surface, 114, F01013. https://doi.org/10.1029/2008JF001097

Woodruff, N. P., & Siddoway, F. H. (1965). A wind erosion equation. Soil Science Society of America Journal, 29(5), 602–608. https://doi.org/10.2136/sssaj1965.03615995002900050035x

Xi, X., & Sokolik, I. N. (2016). Quantifying the anthropogenic dust emission from agricultural land use and desiccation of the Aral Sea in Central Asia. Journal of Geophysical Research: Atmospheres, 121, 12270–12281. https://doi.org/10.1002/2016JD025556

Yao, F., Ding, J., Bao, A., & Li, J. (2025). Attribution and risk assessment of wind erosion in the Aral Sea regions using multi-source remote sensing and RWEQ on GEE. Remote Sensing, 17(16), 2788. https://doi.org/10.3390/rs17162788