Skip to main content

Investigation of the Vegetation Coverage Dynamics and its Relation to Atmospheric Patterns in Kabul River Basin in Afghanistan

Pure and Applied Geophysics volume 179, pages 3075–3094 (2022)Cite this article

Abstract

The variations in vegetation coverage (defined as the area with Normalised Difference Vegetation Index (NDVI) > 0.2) and atmospheric patterns occurring during various vegetation seasons in the Kabul River Basin (KRB) in Afghanistan during 2001–2019 were analyzed. The analysis was done based on the NDVI, land surface temperature (LST), precipitation images from the remote sensing data, and geopotential height and temperature at 500 hPa from the retrospective datasets. The results revealed that the vegetation dynamics in KRB are impacted by both precipitation and LST. In the winter season, the LST has a more substantial role in shaping the vegetation dynamics than precipitation, while it is on contrary during the summer season. Cluster analysis showed that the four atmospheric patterns (e.g., Sub-Tropical High Pressure (STHP), Western European ridge-the Eastern Mediterranean and the Black Sea trough, Caspian Sea ridge (CSR), and the Mediterranean Sea trough-Central to Eastern Iran trough) can be identified and connected with the periods with the highest and the lowest vegetation coverage (VC) anomalies in the study area. The CSR and the Mediterranean Sea trough-the Central to Eastern Iran trough are the patterns responsible for the most positive VC anomalies. At the same time, the STHP and Western Europe ridge-the Eastern Mediterranean and the Black Sea trough are responsible for the most negative VC anomalies. As the atmospheric patterns have a significant role in shaping the vegetation status, a quick alert system to prevent agricultural areas from water or temperature stresses can be developed based on observations of them.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  • Agrawal, S., Joshi, P. K., Shukla, Y., & Roy, P. S. (2003). SPOT vegetation multi temporal data for classifying vegetation in South Central Asia. Current Science, 84, 1440–1448.

    Google Scholar 

  • Ahmad, W., Khan, A. U., Khan, F. A., Farooq, M., Baig, A. A., Shah, L. A., & Khan, J. (2020). How vegetation spatially alters the response of precipitation and air temperature? Evidence from Pakistan. Asian Journal of Atmospheric Environment, 14, 133–145.

    Article  Google Scholar 

  • Akhtar, F. (2017). Water availability and demand analysis in the Kabul River Basin, Afghanistan. Universitäts- und Landesbibliothek Bonn. https://bonndoc.ulb.uni-bonn.de/xmlui/handle/20.500.11811/7031.

  • Akhtar, F., Awan, U. K., Tischbein, B., & Liaqat, U. W. (2018). Assessment of irrigation performance in large river basins under data scarce environment—A case of Kabul River Basin Afghanistan. Remote Sensing, 10, 972. https://doi.org/10.3390/rs10060972

    Article  Google Scholar 

  • Alijani, B., O’Brien, J., & Yarnal, B. (2008). Spatial analysis of precipitation intensity and concentration in Iran. Theoretical and Applied Climatology, 94, 107–124. https://doi.org/10.1007/s00704-007-0344-y

    Article  Google Scholar 

  • Banks, D., & Soldal, O. (2002). Towards a policy for sustainable use of groundwater by non-governmental organisations in Afghanistan. Hydrogeology Journal, 10, 377–392. https://doi.org/10.1007/s10040-002-0203-y

    Article  Google Scholar 

  • Barbosa, H. A., Huete, A. R., & Baethgen, W. E. (2006). A 20-year study of NDVI variability over the Northeast Region of Brazil. Journal of Arid Environments, 67, 288–307. https://doi.org/10.1016/j.jaridenv.2006.02.022

    Article  Google Scholar 

  • Barbosa, H. A., Lakshmi Kumar, T. V., & Silva, L. R. M. (2015). Recent trends in vegetation dynamics in the South America and their relationship to rainfall. Natural Hazards, 77, 883–899. https://doi.org/10.1007/s11069-015-1635-8

    Article  Google Scholar 

  • Bhuiyan, C., & Kogan, F. N. (2010). Monsoon variation and vegetative drought patterns in the Luni Basin in the rain-shadow zone. International Journal of Remote Sensing, 31, 3223–3242. https://doi.org/10.1080/01431160903159332

    Article  Google Scholar 

  • Chen, Z., Wang, W., & Fu, J. (2020). Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China. Science and Reports, 10, 830. https://doi.org/10.1038/s41598-020-57910-1

    Article  Google Scholar 

  • Coops, N. C., Wulder, M. A., & Iwanicka, D. (2009). Large area monitoring with a MODIS-based Disturbance Index (DI) sensitive to annual and seasonal variations. Remote Sensing of Environment, 113, 1250–1261. https://doi.org/10.1016/j.rse.2009.02.015

    Article  Google Scholar 

  • Davenport, M. L., & Nicholson, S. E. (1993). On the relation between rainfall and the Normalized Difference Vegetation Index for diverse vegetation types in East Africa. International Journal of Remote Sensing, 14, 2369–2389. https://doi.org/10.1080/01431169308954042

    Article  Google Scholar 

  • Dinku, T., Ceccato, P., Grover-Kopec, E., Lemma, M., Connor, S. J., & Ropelewski, C. F. (2007). Validation of satellite rainfall products over East Africa’s complex topography. International Journal of Remote Sensing, 28, 1503–1526. https://doi.org/10.1080/01431160600954688

    Article  Google Scholar 

  • Duan, Z., & Bastiaanssen, W. G. M. (2013). First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling–calibration procedure. Remote Sensing of Environment, 131, 1–13. https://doi.org/10.1016/j.rse.2012.12.002

    Article  Google Scholar 

  • Fang, J., Du, J., Xu, W., Shi, P., Li, M., & Ming, X. (2013). Spatial downscaling of TRMM precipitation data based on the orographical effect and meteorological conditions in a mountainous area. Advances in Water Resources, 61, 42–50. https://doi.org/10.1016/j.advwatres.2013.08.011

    Article  Google Scholar 

  • Ghafarian Malamiri, H. R., Rousta, I., Olafsson, H., Zare, H., & Zhang, H. (2018). Gap-filling of MODIS time series Land Surface Temperature (LST) products using Singular Spectrum Analysis (SSA). Atmosphere, 9, 334. https://doi.org/10.3390/atmos9090334

    Article  Google Scholar 

  • GlobLand30 (2016). http://glc30.tianditu.com/.

  • Houben, G., Niard, N., Tünnermeier, T., & Himmelsbach, T. (2009). Hydrogeology of the Kabul Basin (Afghanistan), part I: Aquifers and hydrology. Hydrogeology Journal, 17, 665–677. https://doi.org/10.1007/s10040-008-0377-z

    Article  Google Scholar 

  • Huffman, G. J., Bolvin, D. T., Nelkin, E. J., Wolff, D. B., Adler, R. F., Gu, G., Hong, Y., Bowman, K. P., & Stocker, E. F. (2007). The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8, 38–55. https://doi.org/10.1175/JHM560.1

    Article  Google Scholar 

  • Imhoff, M. L., Zhang, P., Wolfe, R. E., & Bounoua, L. (2010). Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sensing of Environment, 114, 504–513. https://doi.org/10.1016/j.rse.2009.10.008

    Article  Google Scholar 

  • Julien, Y., & Sobrino, J. A. (2009). The Yearly Land Cover Dynamics (YLCD) method: An analysis of global vegetation from NDVI and LST parameters. Remote Sensing of Environment, 113, 329–334. https://doi.org/10.1016/j.rse.2008.09.016

    Article  Google Scholar 

  • Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, B., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., … Dennis, J. (1996). The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77, 437–472.

    Article  Google Scholar 

  • Kumar, D., & Shekhar, S. (2015). Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing. Ecotoxicology and Environmental Safety, 121, 39–44. https://doi.org/10.1016/j.ecoenv.2015.07.004

    Article  Google Scholar 

  • Kummerow, C., Barnes, W., Kozu, T., Shiue, J., & Simpson, J. (1998). The Tropical Rainfall Measuring Mission (TRMM) sensor package. The Journal of Atmospheric and Oceanic Technology, 15, 809–817. https://doi.org/10.1175/1520-0426(1998)015%3c0809:TTRMMT%3e2.0.CO;2

    Article  Google Scholar 

  • Lakshmi Kumar, T. V., Koteswara Rao, K., Barbosa, H., & Prabha Jothi, E. (2013). Studies on spatial pattern of NDVI over Indiaand its relationship with rainfall, air temperature, soil moisture adequacy and ENSO. Geofizika, 30, 1–18.

    Google Scholar 

  • Lambin, E. F., & Ehrlich, D. (1995). Combining vegetation indices and surface temperature for land-cover mapping at broad spatial scales. International Journal of Remote Sensing, 16, 573–579. https://doi.org/10.1080/01431169508954423

    Article  Google Scholar 

  • Lashkaripour, G. R., & Hussaini, S. A. (2008). Water resource management in Kabul River Basin, eastern Afghanistan. The Environmentalist, 28, 253–260. https://doi.org/10.1007/s10669-007-9136-2

    Article  Google Scholar 

  • Liou, Y.-A., & Mulualem, G. M. (2019). Spatio–temporal assessment of drought in Ethiopia and the impact of Rrecent intense droughts. Remote Sensing, 11, 1828. https://doi.org/10.3390/rs11151828

    Article  Google Scholar 

  • Liu, S., Yan, D., Shi, X., Wang, G., Yuan, Z., & Yin, J. (2013). Grassland NDVI response to climate factors in different vegetation regionalizations in China. in Geo-Informatics in Resource Management and Sustainable Ecosystem Communications in Computer and Information Science., eds. F. Bian, Y. Xie, X. Cui, & Y. Zeng (Berlin, Heidelberg: Springer), 370–380. https://doi.org/10.1007/978-3-642-41908-9_38.

  • Mack, T. J., Chornack, M. P., & Taher, M. R. (2013). Groundwater-level trends and implications for sustainable water use in the Kabul Basin, Afghanistan. Environment System and Decisions, 33, 457–467. https://doi.org/10.1007/s10669-013-9455-4

    Article  Google Scholar 

  • Mainuddin, M., Peña-Arancibia, J. L., Karim, F., Hasan, M. M., Mojid, M. A., & Kirby, J. M. (2022). Long-term spatio-temporal variability and trends in rainfall and temperature extremes and their potential risk to rice production in Bangladesh. PLOS Climate, 1, e0000009.

    Article  Google Scholar 

  • Malo, A. R., & Nicholson, S. E. (1990). A study of rainfall and vegetation dynamics in the African Sahel using normalized difference vegetation index. Journal of Arid Environments, 19, 1–24. https://doi.org/10.1016/S0140-1963(18)30825-5

    Article  Google Scholar 

  • Mandal, G., & Joshi, S. P. (2014). Analysis of vegetation dynamics and phytodiversity from three dry deciduous forests of Doon Valley, Western Himalaya, India. Journal Asia-Pacific Biodiversity, 7, 292–304. https://doi.org/10.1016/j.japb.2014.07.006

    Article  Google Scholar 

  • Marzban, F., Sodoudi, S., & Preusker, R. (2018). The influence of land-cover type on the relationship between NDVI–LST and LST-Tair. International Journal of Remote Sensing, 39, 1377–1398. https://doi.org/10.1080/01431161.2017.1402386

    Article  Google Scholar 

  • Mildrexler, D. J., Zhao, M., Heinsch, F. A., & Running, S. W. (2007). A new satellite-based methodology for continental-scale disturbance detection. Ecological Applications, 17, 235–250. https://doi.org/10.1890/1051-0761(2007)017[0235:ANSMFC]2.0.CO;2

    Article  Google Scholar 

  • Mushore, T. D., Dube, T., Manjowe, M., Gumindoga, W., Chemura, A., Rousta, I., Odindi, J., & Mutanga, O. (2019). Remotely sensed retrieval of Local Climate Zones and their linkages to land surface temperature in Harare metropolitan city, Zimbabwe. Urban Climate, 27, 259–271. https://doi.org/10.1016/j.uclim.2018.12.006

    Article  Google Scholar 

  • Najmuddin, O., Qamer, F. M., Gul, H., Zhuang, W., & Zhang, F. (2021). Cropland use preferences under land, water and labour constraints—implications for wheat self-sufficiency in the Kabul River basin, Afghanistan. Food Security, 1–25.

  • Najmuddin, O., Deng, X., & Siqi, J. (2017). Scenario analysis of land use change in Kabul River Basin—A river basin with rapid socio-economic changes in Afghanistan. Physics and Chemistry of the Earth Parts ABC, 101, 121–136. https://doi.org/10.1016/j.pce.2017.06.002

    Article  Google Scholar 

  • Nemani, R., & Running, S. (1997). Land cover characterization using multitemporal red, near-IR, and thermal-IR data from NOAA/AVHRR. Ecological Applications, 7, 79–90. https://doi.org/10.1890/1051-0761(1997)007[0079:LCCUMR]2.0.CO;2

    Article  Google Scholar 

  • NRVA (2009). National Risk and Vulnerability Assessment 2007/2008: A profile of Afghanistan. Kabul, Afghanistan: ICON-INSTITUTE.

  • Olafsson, H., & Rousta, I. (2021). Influence of atmospheric patterns and North Atlantic Oscillation (NAO) on vegetation dynamics in Iceland using Remote Sensing. European Journal of Remote Sensing, 54, 351–363.

    Article  Google Scholar 

  • Patel, N. R., Chopra, P., & Dadhwal, V. K. (2007). Analyzing spatial patterns of meteorological drought using standardized precipitation index. Meteorological Applications, 14, 329–336. https://doi.org/10.1002/met.33

    Article  Google Scholar 

  • Peña-Arancibia, J. L., Mahboob, M. G., Islam, A. T., Mainuddin, M., Yu, Y., Ahmad, M. D., Murad, K. F. I., Saha, K. K., Hossain, A., & Moniruzzaman, M. (2021). The Green Revolution from space: Mapping the historic dynamics of main rice types in one of the world’s food bowls. Remote Sensing Applications: Society and Environment, 21, 100460.

    Article  Google Scholar 

  • Pervez, M. S., Budde, M., & Rowland, J. (2014). Mapping irrigated areas in Afghanistan over the past decade using MODIS NDVI. Remote Sensing of Environment, 149, 11. https://doi.org/10.1016/j.rse.2014.04.008

    Article  Google Scholar 

  • Propastin, P., Kappas, M., Erasmi, S., & Muratova, N. R. (2007). Remote sensing based study on intra-annual dynamics of vegetation and climate in drylands of Kazakhastan. Basic and Applied Dryland Research. https://doi.org/10.1127/badr/1/2007/138

    Article  Google Scholar 

  • Raja, R., Nayak, A. K., Panda, B. B., Lal, B., Tripathi, R., Shahid, M., Kumar, A., Mohanty, S., Samal, P., Gautam, P., & Rao, K. S. (2014). Monitoring of meteorological drought and its impact on rice (Oryza sativa L.) productivity in Odisha using standardized precipitation index. Archives of Agronomy and Soil Science, 60, 1701–1715.

    Article  Google Scholar 

  • Reboita, M. S., Ambrizzi, T., Silva, B. A., Pinheiro, R. F., & da Rocha, R. P. (2019). The South Atlantic Subtropical Anticyclone: Present and future climate. Frontiers in Earth Science, 7, 8. https://doi.org/10.3389/feart.2019.00008

    Article  Google Scholar 

  • Regmi, R., Ma, Y., Ma, W., Baniya, B., & Bashir, B. (2020). Interannual variation of NDVI, precipitation and temperature during the Growing Season in Langtang National Park, Central Himalaya, Nepal. Applied Ecology and Environmental Sciences, 8, 218–228. https://doi.org/10.12691/aees-8-5-5

    Article  Google Scholar 

  • Rousta, I., Javadizadeh, F., Dargahian, F., Ólafsson, H., Shiri-Karimvandi, A., Vahedinejad, S. H., Doostkamian, M., Vargas, E. R. M., & Asadolahi, A. (2018). Investigation of vorticity during prevalent winter precipitation in Iran. Advances in Meteorology, 2018, e6941501. https://doi.org/10.1155/2018/6941501

    Article  Google Scholar 

  • Rousta, I., Olafsson, H., Moniruzzaman, M., Ardö, J., Zhang, H., Mushore, T. D., Shahin, S., & Azim, S. (2020a). The 2000–2017 drought risk assessment of the western and southwestern basins in Iran. Model Earth Systems and Environment, 6, 1201–1221.

    Article  Google Scholar 

  • Rousta, I., Olafsson, H., Moniruzzaman, M., Zhang, H., Liou, Y.-A., Mushore, T. D., & Gupta, A. (2020b). Impacts of drought on vegetation assessed by vegetation indices and meteorological factors in Afghanistan. Journal of Remote Sensing, 12, 2433.

    Article  Google Scholar 

  • Roy, D. P., Jin, Y., Lewis, P. E., & Justice, C. O. (2005). Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sensing of Environment, 97, 137–162. https://doi.org/10.1016/j.rse.2005.04.007

    Article  Google Scholar 

  • Sarma, A. A. L. N., & Kumar, T. V. L. (2006). Studies on crop growing period and NDVI in relation to water balance components. Indian Journal of Radio & Space Physics, 35, 424–434.

    Google Scholar 

  • Schmugge, T. J., Kustas, W. P., Ritchie, J. C., Jackson, T. J., & Rango, A. (2002). Remote sensing in hydrology. Advances in Water Resources, 25, 1367–1385. https://doi.org/10.1016/S0309-1708(02)00065-9

    Article  Google Scholar 

  • Shilong, P., Jingyun, F., Wei, J., Qinghua, G., Jinhu, K., & Shu, T. (2004). Variation in a satellite-based Vegetation Index in relation to climate in China. Journal of Vegetation Science, 15, 219–226.

    Article  Google Scholar 

  • Simpson, J., Kummerow, C., Tao, W.-K., & Adler, R. F. (1996). On the Tropical Rainfall Measuring Mission (TRMM). Meteorology and Atmospheric Physics, 60, 19–36. https://doi.org/10.1007/BF01029783

    Article  Google Scholar 

  • Sobrino, J., Jiménez-Muñoz, J., & Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90(4), 434–440. https://doi.org/10.1016/j.rse.2004.02.003

    Article  Google Scholar 

  • Soltani, M., Laux, P., Kunstmann, H., Stan, K., Sohrabi, M. M., Molanejad, M., Sabziparvar, A. A., Ranjbar SaadatAbadi, A., Ranjbar, F., Rousta, I., Zawar-Reza, P., Khoshakhlagh, F., Soltanzadeh, I., Babu, C. A., Azizi, G. H., & Martin, M. V. (2016). Assessment of climate variations in temperature and precipitation extreme events over Iran. Theoretical and Applied Climatology, 126, 775–795. https://doi.org/10.1007/s00704-015-1609-5

    Article  Google Scholar 

  • Sun, D., & Kafatos, M. (2007). Note on the NDVI-LST relationship and the use of temperature-related drought indices over North America. Geophysical Research Letters. https://doi.org/10.1029/2007GL031485

    Article  Google Scholar 

  • Tayyebi, A., & Jenerette, G. D. (2016). Increases in the climate change adaption effectiveness and availability of vegetation across a coastal to desert climate gradient in metropolitan Los Angeles, CA, USA. Science of the Total Environment, 548, 60–71.

    Article  Google Scholar 

  • USDA, F. (2011). Unites States Department of Agriculture Foreign Agricultural Service, Global Agricultural Trade System (GATS), Forest products trade statistics. J Acces.

  • Viola, M., Najimi, F. K., & Bacon, B. (2007). Afghanistan Food Security Conditions and Causes. United States Agency for International Development Famine Early Warning Systems Network (FEWS NET).

  • Wan, Z., & Dozier, J. (1996). A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Transactions on Geoscience and Remote Sensing, 34, 892–905. https://doi.org/10.1109/36.508406

    Article  Google Scholar 

  • Wan, Z., Zhang, Y., Zhang, Q., & Li, Z.-L. (2004). Quality assessment and validation of the MODIS global Land Surface Temperature. International Journal of Remote Sensing, 25, 261–274. https://doi.org/10.1080/0143116031000116417

    Article  Google Scholar 

  • WB (2010). Afghanistan - Scoping strategic options for development of the Kabul River Basin: a multisectoral decision support system approach. World Bank. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/319391468185978566/Afghanistan-Scoping-strategic-options-for-development-of-the-Kabul-River-Basin-a-multisectoral-decision-support-system-approach.

  • WHO (2009). Country profile: Afghanistan. World Health Organization.

  • Wilkinson, C. R. (1996). Global change and coral reefs: Impacts on reefs, economies and human cultures. Global Change Biology, 2, 547–558. https://doi.org/10.1111/j.1365-2486.1996.tb00066.x

    Article  Google Scholar 

  • Zarrin, A., Ghaemi, H., Azadi, M., & Farajzadeh, M. (2010). The spatial pattern of summertime subtropical anticyclones over Asia and Africa: A climatological review. International Journal of Climatology, 30, 159–173. https://doi.org/10.1002/joc.1879

    Article  Google Scholar 

  • Zhang, Q., Shi, P., Singh, V. P., Fan, K., & Huang, J. (2017). Spatial downscaling of TRMM-based precipitation data using vegetative response in Xinjiang, China. International Journal of Climatology, 37, 3895–3909. https://doi.org/10.1002/joc.4964

    Article  Google Scholar 

  • Zhang, X., Friedl, M. A., Schaaf, C. B., Strahler, A. H., Hodges, J. C. F., Gao, F., Reed, B. C., & Huete, A. (2003). Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84, 471–475. https://doi.org/10.1016/S0034-4257(02)00135-9

    Article  Google Scholar 

  • Zhang, X., Friedl, M. A., Schaaf, C. B., Strahler, A. H., & Liu, Z. (2005). Monitoring the response of vegetation phenology to precipitation in Africa by coupling MODIS and TRMM instruments. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2004JD005263

    Article  Google Scholar 

Download references

Acknowledgements

Iman Rousta is deeply grateful to his supervisor, Haraldur Olafsson (Professor of Atmospheric Sciences, Institute for Atmospheric Sciences-Weather and Climate, and Department of Physics, University of Iceland, and Icelandic Meteorological Office (IMO)), for his great support, kind guidance, and encouragement.

Funding

This work was supported by Vedurfelagid, Rannis and Rannsoknastofa i vedurfraedi. J.K. and P.B. have been partly financed by the Polish National Centre for Research and Development within the framework of the MSINiN project (contract number: BIOSTRATEG3/343547/8/NCBR/2017).

Author information

Authors and Affiliations

  1. Department of Geography, Yazd University, Yazd, 8915818411, Iran

    Iman Rousta

  2. Institute for Atmospheric Sciences-Weather and Climate, University of Iceland and Icelandic Meteorological Office (IMO), Bustadavegur 7, IS-108, Reykjavik, Iceland

    Iman Rousta

  3. ASICT Division, Bangladesh Agricultural Research Institute, Gazipur, 1701, Bangladesh

    Md Moniruzzaman

  4. Spatial Business Integration GmbH (SBI), Marienburgstraße 27, 64297, Darmstadt, Germany

    Md Moniruzzaman

  5. Institute for Atmospheric Sciences-Weather and Climate and Department of Physics, University of Iceland and Icelandic Meteorological Office (IMO), Bustadavegur 7, IS-108, Reykjavik, Iceland

    Haraldur Olafsson

  6. Department of Environmental Science and Engineering Jiangwan Campus, Fudan University, 2005 Songhu Road, Yangpu District, Shanghai, 200438, China

    Hao Zhang

  7. Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290, Lublin, Poland

    Piotr Baranowski & Jaromir Krzyszczak

  8. Department of Agricultural and Environmental Chemistry, University of Life Sciences in Lublin, Akademicka 15, 20-950, Lublin, Poland

    Przemysław Tkaczyk

  9. Department of Grassland and Landscape Forming, University of Life Sciences, Akademicka 13, 20-950, Lublin, Poland

    Halina Lipińska & Agnieszka Kępkowicz

Authors
  1. Iman Rousta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Md Moniruzzaman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Haraldur Olafsson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hao Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Piotr Baranowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Przemysław Tkaczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Halina Lipińska
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Agnieszka Kępkowicz
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jaromir Krzyszczak
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization, IR; methodology, software, data curation, validation, formal analysis, IR, MM, HO, and HZ; writing—original draft preparation IR, MM, HO, and HZ; enhancing the research design and analysis IR, PB, PT, HL, AK, and JK; writing—review and editing JK and PB All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Jaromir Krzyszczak.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rousta, I., Moniruzzaman, M., Olafsson, H. et al. Investigation of the Vegetation Coverage Dynamics and its Relation to Atmospheric Patterns in Kabul River Basin in Afghanistan. Pure Appl. Geophys. 179, 3075–3094 (2022). https://doi.org/10.1007/s00024-022-03044-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-022-03044-6

Keywords

  • Vegetation coverage
  • remote sensing
  • atmospheric patterns
  • agricultural areas
  • cluster analysis
  • MODerate resolution imaging spectroradiometer