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Detection of Anthropogenic and Environmental Degradation in Mongolia Using Multi-Sources Remotely Sensed Time Series Data and Machine Learning Techniques

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Book cover Environmental Degradation in Asia

Part of the book series: Earth and Environmental Sciences Library ((EESL))

Abstract

The main objective of this study is to investigate land degradation and environmental change in Mongolia using time series of multi-sources remotely sensed data and advanced approaches. As the data analysis techniques, the Random Forest (RF) classifier, Ordinary Least Square (OLS), and Partial Least Square (PLS) regressions, Break for Additive Season and Trend (BFAST) algorithm, Sen’s slope and Restrend method were applied. For detecting land degradation and environmental change, we have investigated several factor impacts: (1) climate factor impact on land degradation and environmental change, (2) impact of land cover change on land degradation and environmental change, (3) impact of vegetation index on land degradation and environmental change, (4) impact of drought on land degradation and environmental change. The meteorological time series analysis showed that between 1990 and 2019, air temperature over Mongolian has increased by 1.8 °C, while annual total precipitation over Mongolia had decreased from 714 to 640 mm. The land cover analysis indicated that between 1990 and 2019, forest, steppe, dry steppe, and cropland were decreased. In contrast, the meadow steppe, wetland, sand land, broken area, urban land, and water were increased. The trend analysis result indicated that positive trends were observed in Mongolia's central, northern, and northeastern parts. In contrast, the negative trends were detected in all areas of the west, southern region, forested areas in the north and east, around the Ulaanbaatar city, and in the grassland area of eastern Mongolia. The drought detection analysis showed that the years 1993, 1994, 1997, 2000–2002, 2004–2007, 2009, and 2017 could very well detect the droughts during the growing season for the period 1990–2019. The trend analysis result showed that negative and positive trends of time series NDVI were strongly related to land cover change.

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Acknowledgements

The authors would like to thank many organizations that provided data for this study especially, Institute of Geography and Geoecology, Mongolian Academy of Sciences (IGG MAS), National University of Mongolia (NUM), and the Information and Research Institute of Meteorology, Hydrology, and Environment (IRIMHE). The authors also appreciate the provider’s time series of satellite and meteorological data to allow us to download and use these datasets. We thank the editors for their valuable comments and suggestions on the chapter who is Dr. Ayad M. Fadhil Al-Quraishi, Dr. Abdelazim M Negm and Dr. Yaseen T. Mustafa.

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Authors and Affiliations

  1. Institute of Geography and Geoecology, Mongolian Academy of Sciences (MAS), 15170, Ulaanbaatar, Mongolia

    Otgonbayar Munkhdulam, Damdinsuren Amarsaikhan & Dalantai Sainbayar

  2. Institute of Geomatics, University of Natural Resources and Life Sciences (BOKU), Peter-Jordan-Straße 82, 1190, Vienna, Austria

    Atzberger Clement

  3. Department of Geography, Graduate School of Environmental Studies, Nagoya University, Nagoya, 464-8601, Japan

    Otgonbayar Munkhdulam & Satoshi Yokoyama

  4. School of Arts and Sciences, National University of Mongolia (NUM), 14201, 46A, Ulaanbaatar, Mongolia

    Sumiya Erdenesukh

Authors
  1. Otgonbayar Munkhdulam
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  2. Atzberger Clement
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  3. Damdinsuren Amarsaikhan
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  4. Satoshi Yokoyama
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  5. Sumiya Erdenesukh
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  6. Dalantai Sainbayar
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Corresponding author

Correspondence to Otgonbayar Munkhdulam .

Editor information

Editors and Affiliations

  1. Petroleum and Mining Engineering Department, Tishk International University, Erbil, Iraq

    Ayad M. Fadhil Al-Quraishi

  2. University of Zakho, Zakho, Duhok, Iraq

    Yaseen T. Mustafa

  3. Zagazig University, Zagazig, Egypt

    Abdelazim M. Negm

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Munkhdulam, O., Clement, A., Amarsaikhan, D., Yokoyama, S., Erdenesukh, S., Sainbayar, D. (2022). Detection of Anthropogenic and Environmental Degradation in Mongolia Using Multi-Sources Remotely Sensed Time Series Data and Machine Learning Techniques. In: Al-Quraishi, A.M.F., Mustafa, Y.T., Negm, A.M. (eds) Environmental Degradation in Asia. Earth and Environmental Sciences Library. Springer, Cham. https://doi.org/10.1007/978-3-031-12112-8_2

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