TY - JOUR
T1 - Identifying potential vegetation establishment areas on the dried Aral Sea floor using satellite images
AU - Kim, Jiwon
AU - Song, Cholho
AU - Lee, Sujong
AU - Jo, Hyun Woo
AU - Park, Eunbeen
AU - Yu, Hangnan
AU - Cha, Sungeun
AU - An, Jiae
AU - Son, Yowhan
AU - Khamzina, Asia
AU - Lee, Woo Kyun
N1 - Funding Information:
Biodiversity Conservation Fund of Kazakhstan; National Research Foundation of Korea, Grant/Award Number: 2018K1A3A7A03089842 Funding information
Funding Information:
This research was supported by the International Research & Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (Grant number: 2018K1A3A7A03089842) and Biodiversity Conservation Fund of Kazakhstan.
Publisher Copyright:
© 2020 John Wiley & Sons, Ltd.
PY - 2020/12
Y1 - 2020/12
N2 - The Aral Sea was one of the largest lakes in the world, but almost 60,000 km2 of the waterbody has dried up due to water withdrawal for irrigation. Afforestation on the desiccated seafloor could be important in preventing soil flation, dust storms, and negative impact on human health. In this study, we aimed to delineate potential vegetation establishment areas on the dried Aral Sea bed using remote-sensed data in support of the decision-making related to afforestation. Various indices such as normalized difference vegetation index (NDVI), topsoil grain size index (TGSI), soil salinity index (SSI), and normalized multiband drought index (NMDI) were calculated from the LANDSAT-8 OLI satellite imagery. As an indicator of vegetation existence, NDVI was classified into three groups and set as a base for classifying other indices by performing statistical analyses. Based on the decision tree method, indices were combined and the potential vegetation establishment area was detected. Higher NDVI was identified in the southeast than the west of the study area. The results of statistical analyses showed that TGSI had a positive correlation with NDVI, while SSI and NMDI had a negative correlation. Overall, the potential vegetation area comprised 7,295.21 km2 (61.34%) of the 'unsuitable' area, 2,818.64 km2 (23.7%) of the 'intermediate' area, 1,612.15 km2 (13.56%) of the 'suitable' area, and 166.42 km2 (1.4%) of the 'very suitable' area. The developed map enables to identify dried seafloor area suitable for vegetation establishment thus contributing to planning the land rehabilitation efforts and preventing further land degradation.
AB - The Aral Sea was one of the largest lakes in the world, but almost 60,000 km2 of the waterbody has dried up due to water withdrawal for irrigation. Afforestation on the desiccated seafloor could be important in preventing soil flation, dust storms, and negative impact on human health. In this study, we aimed to delineate potential vegetation establishment areas on the dried Aral Sea bed using remote-sensed data in support of the decision-making related to afforestation. Various indices such as normalized difference vegetation index (NDVI), topsoil grain size index (TGSI), soil salinity index (SSI), and normalized multiband drought index (NMDI) were calculated from the LANDSAT-8 OLI satellite imagery. As an indicator of vegetation existence, NDVI was classified into three groups and set as a base for classifying other indices by performing statistical analyses. Based on the decision tree method, indices were combined and the potential vegetation establishment area was detected. Higher NDVI was identified in the southeast than the west of the study area. The results of statistical analyses showed that TGSI had a positive correlation with NDVI, while SSI and NMDI had a negative correlation. Overall, the potential vegetation area comprised 7,295.21 km2 (61.34%) of the 'unsuitable' area, 2,818.64 km2 (23.7%) of the 'intermediate' area, 1,612.15 km2 (13.56%) of the 'suitable' area, and 166.42 km2 (1.4%) of the 'very suitable' area. The developed map enables to identify dried seafloor area suitable for vegetation establishment thus contributing to planning the land rehabilitation efforts and preventing further land degradation.
KW - Afforestation plan
KW - LANDSAT
KW - Land degradation
KW - Remote sensing
UR - http://www.scopus.com/inward/record.url?scp=85091650716&partnerID=8YFLogxK
U2 - 10.1002/ldr.3642
DO - 10.1002/ldr.3642
M3 - Article
AN - SCOPUS:85091650716
SN - 1085-3278
VL - 31
SP - 2749
EP - 2762
JO - Land Degradation and Development
JF - Land Degradation and Development
IS - 18
ER -
