Quantitative Assessment of Desertification in an Arid Oasis Using Remote Sensing Data and Spectral Index Techniques

被引:45
|
作者
Lamqadem, Atman Ait [1 ]
Saber, Hafid [1 ]
Pradhan, Biswajeet [2 ,3 ]
机构
[1] Chouaib Doukkali Univ, Dept Geol, Fac Sci, Lab Geodynam & Geomat, Ben Maachou St, El Jadida 24000, Morocco
[2] Univ Technol Sydney, Fac Engn & Informat Technol, CAMGIS, Ultimo, NSW 2007, Australia
[3] Sejong Univ, Dept Energy & Mineral Resources Engn, 209 Neungdong Ro, Seoul 05006, South Korea
关键词
Sentinel-2; GIS; tasselled cap transformation; NDVI; albedo; remote sensing; middle Draa valley; MONITORING DESERTIFICATION; LAND DEGRADATION; MIXTURE ANALYSIS; AREAS; TRANSFORMATION; ALBEDO; NDVI;
D O I
10.3390/rs10121862
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Desertification is an environmental problem worldwide. Remote sensing data and technique offer substantial information for mapping and assessment of desertification. Desertification is one of the most serious forms of environmental threat in Morocco, especially in the oases in the south-eastern part of the country. This study aims to map the degree of desertification in middle Draa Valley in 2017 using a Sentinel-2 MSI (multispectral instrument) image. Firstly, three indices, namely, tasselled cap brightness (TCB), greenness (TCG) and wetness (TCW) were extracted using the tasselled cap transformation method. Secondly, other indices, such as normalized difference vegetation index (NDVI) and albedo, were retrieved. Thirdly, a linear regression analysis was performed on NDVI-albedo, TCG-TCB and TCW-TCB combinations. Results showed a higher correlation between TCW and TCB (r = -0.812) than with that of the NDVI-albedo (r = -0.50). On the basis of this analysis, a desertification degree index was developed using the TCW-TCB feature space classification. A map of desertification grades was elaborated and divided into five classes, namely, nondesertification, low, moderate, severe and extreme levels. Results indicated that only 6.20% of the study area falls under the nondesertification grade, whereas 26.92% and 32.85% fall under the severe and extreme grades, respectively. The employed method was useful for the quantitative assessment of desertification with an overall accuracy of 93.07%. This method is simple, robust, powerful, and easy to use for the management and protection of the fragile arid and semiarid lands.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Assessment of Desertification Dynamics in Arid Coastal Areas by Integrating Remote Sensing Data and Statistical Techniques
    Hasan, Samia S.
    Alharbi, Omar A.
    Alqurashi, Abdullah F.
    Fahil, Amr S.
    SUSTAINABILITY, 2024, 16 (11)
  • [2] Development of topsoil grain size index for monitoring desertification in arid land using remote sensing
    Xiao, J.
    Shen, Y.
    Tateishi, R.
    Bayaer, W.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2006, 27 (12) : 2411 - 2422
  • [3] Monitoring and assessment of desertification using remote sensing
    Hernandez-Clemente, Rocio
    Hornero, Alberto
    ECOSISTEMAS, 2021, 30 (03):
  • [4] Mapping and assessment of evapotranspiration over an oasis in arid ecosystem using remote sensing and biophysical modelling
    Turk K.
    Zeineldin F.
    Aljughaiman A.S.
    Arabian Journal of Geosciences, 2021, 14 (19)
  • [5] Understanding the attributes of the dual oasis effect in an arid region using remote sensing and observational data
    Bie, Qiang
    Xie, Yaowen
    Wang, Xiaoyun
    Wei, Baocheng
    He, Lei
    Duan, Hanming
    Wang, Ju
    ECOSYSTEM HEALTH AND SUSTAINABILITY, 2020, 6 (01)
  • [6] Quantitative assessment of soil saline degradation using remote sensing indices in Siwa Oasis
    AbdelRahman, Mohamed A. E.
    Metwaly, Mohamed M.
    Shalaby, Adel
    REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2019, 13 : 53 - 60
  • [7] Mapping land degradation and desertification using remote sensing data
    Saha, S. K.
    Kumar, Munish
    Lal, Bhajan
    Barman, Alok Kumar
    Das, Satyendra Nath
    AGRICULTURE AND HYDROLOGY APPLICATIONS OF REMOTE SENSING, 2006, 6411
  • [8] Simple remote sensing data-based evapotranspiration model for oasis in arid zones
    Tsinghua University, Beijing 100084, China
    不详
    Shuili Xuebao, 2008, 4 (483-489):
  • [9] Monitoring sandy desertification of Minqin oasis, northwest China by remote sensing and GIS
    Ming, G
    Xin, L
    IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium, Vols 1-8, Proceedings, 2005, : 206 - 209
  • [10] Integration of remote sensing techniques for monitoring desertification in Mexico
    Becerril-Pina, Rocio
    Diaz-Delgado, Carlos
    Alberto Mastachi-Loza, Carlos
    Gonzalez-Sosa, Enrique
    HUMAN AND ECOLOGICAL RISK ASSESSMENT, 2016, 22 (06): : 1323 - 1340