Author
Listed:
- Munkhnasan Lamchin
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Woo-Kyun Lee
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Seong Woo Jeon
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Jong-Yeol Lee
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Cholho Song
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Dongfan Piao
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Chul Hee Lim
(Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea)
- Akhmadi Khaulenbek
(Institute of Geography and Geoecology (Desertification Research Center), Mongolian Academy of Sciences, Baruun Selbe-15, Chingeltei District, 4th Khoroo, Ulaanbaatar 15170, Mongolia)
- Itgelt Navaandorj
(Institute of Geography and Geoecology (Desertification Research Center), Mongolian Academy of Sciences, Baruun Selbe-15, Chingeltei District, 4th Khoroo, Ulaanbaatar 15170, Mongolia)
Abstract
In this paper, we used Landsat thematic mapper (TM) and enhanced thematic mapper (ETM) data from 1990, 2002, and 2011 to analyze the spatial and temporal patterns of desertification using seven factors; the normalized difference vegetation index (NDVI), the topsoil grain size index (TGSI), land surface albedo, the topographic wetness index (TWI), land surface temperature (LST), the perpendicular drought index (PDI), and the elevation of Hogno Khaan, which lies in a semiarid region of central Mongolia. We normalized the indicators, determined their weights, and defined five levels of desertification; none, low, medium, high, and severe. Sets of rules were constructed, and a multi-criteria evaluation (MCE) approach was used to assess desertification and test the correlations between the seven variables in comparison to the different levels of desertification, with field and reference data used for accuracy. We provide a review of the literature on MCE applied to desertification assessment issues based on satellite data. At the first step, major desertification factors were computed for satellite data. The next step was the construction of pairwise comparison matrix. Then, the weight of each factor was determined by the contribution of an analytical hierarchy process. Finally, the susceptible areas to desertification in the study area were identified using a multi-criteria evaluation method. We found that more than 15% of the total land area in Hogno Khaan suffered from severe desertification in 2011, increasing from 7% in 1990. Our analysis showed that the highest correlations were between TGSI and albedo, PDI and TGSI, and PDI and albedo at all levels of desertification. LST was less strongly correlated with TGSI, albedo, and PDI. The correlation of TWI with PDI and NDVI in the non- and low desertification areas produced R values of 0.15 and 0.58, respectively. The correlation analysis indicated a significant positive correlation between TWI and both NDVI and PDI for all years in non- and low desertification areas. Comparing elevation and NDVI, the highest correlation was found for severe desertification in 2002, although correlations for severe desertification were lower in 1990 and 2011.
Suggested Citation
Munkhnasan Lamchin & Woo-Kyun Lee & Seong Woo Jeon & Jong-Yeol Lee & Cholho Song & Dongfan Piao & Chul Hee Lim & Akhmadi Khaulenbek & Itgelt Navaandorj, 2017.
"Correlation between Desertification and Environmental Variables Using Remote Sensing Techniques in Hogno Khaan, Mongolia,"
Sustainability, MDPI, vol. 9(4), pages 1-17, April.
Handle:
RePEc:gam:jsusta:v:9:y:2017:i:4:p:581-:d:95472
Download full text from publisher
Citations
Citations are extracted by the
CitEc Project, subscribe to its
RSS feed for this item.
Cited by:
- Belay Manjur Gebru & Woo-Kyun Lee & Asia Khamzina & Sonam Wangyel Wang & Sungeun Cha & Cholho Song & Munkhansan Lamchin, 2021.
"Spatiotemporal multi-index analysis of desertification in dry Afromontane forests of northern Ethiopia,"
Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 423-450, January.
- Ludmila Floková & Tomáš Mikita, 2023.
"Landscape-Scale Long-Term Drought Prevalence Mapping for Small Municipalities Adaptation, the Czech Republic Case Study,"
Land, MDPI, vol. 12(10), pages 1-21, October.
- Eda Ustaoglu & Brendan Williams, 2022.
"Institutional Settings and Effects on Agricultural Land Conversion: A Global and Spatial Analysis of European Regions,"
Land, MDPI, vol. 12(1), pages 1-35, December.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:581-:d:95472. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.