Abstract
The Al-Asfar wetland, locally known as Lake Al-Asfar, is the largest inland wetland in the Arabian Peninsula. It is situated to the east of the Al-Ahsa Oasis. It was formed at the expense of the Umm Hishah sabkha via the discharge of increasing quantities of drainage water to the oasis. This research was conducted to assess changes in land cover using four satellite images collected from 1990 to 2020. The study used a Landsat 5 TM image (1990), a Landsat 7 ETM+ image (2000), a Landsat 8 OLI-TIRS image (2010), and a Landsat Sentinel-2 L2A image to examine land cover in the Al-Asfar wetland. The normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to evaluate the tendency of ecosystem evolution. The results indicate that for the past three decades, the wetland area has increased significantly. Approximately 15.46 km2 (24.69%) of the body of water was added during this time frame, and the vegetation areas expanded to approximately 10.74 km2 (17.15%). The changes detected in the study area can be explained by the discharge of agricultural drainage water and semi-treated water from sewage treatment plants and the spread of reed mites (Phragmites australis) which covered approximately 23.81% of the area of the Al-Asfar wetland in 2020. For these reasons, the study recommends the necessity of imperative consideration for the protection of the resources of other wetlands in Saudi Arabia to ensure their sustainable use for future generations.
Similar content being viewed by others
References
Abdel-Moneim A (2014) Histopathological and ultrastructural perturbations in tilapia liver as potential indicators of pollution in Lake Al-Asfar, Saudi Arabia. Environ Sci Pollut Res 21:4387–4396
Acharya TD, Yang IT, Anoj Subedi A, Lee DH (2017) Change detection of lakes in Pokhara, Nepal Using Landsat Data. Proceedings 1:17. https://doi.org/10.3390/ecsa-3-E005
Ahangarha M, Seydi ST, Reza Shahhoseini R (2019) Hyperspectral change detection in wetland and water-body areas based on machine learning, the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, GeoSpatial Conference 2019 – Joint Conferences of SMPR and GI Research, Volume XLII-4/W18: 19-24
Al-Dakheel YY, Hussein AHA, El-Mahmoudi AS, Massoud MA (2009) Soil, water chemistry and sedimentological studies of Al Asfar evaporation lake and its Inland sabkha, Al-Hassa area, Saudi Arabia. Asian J Earth Sci 2:1–21
Al-Obaid S, Samraoui B, Thomas J, El-Serehy HA, Alfarhan AH, Schneider W, O’Connell M (2017) An overview of wetlands of Saudi Arabia: Values, threats, and perspectives. Ambio 46:98–108. https://doi.org/10.1007/s13280-016-0807-4
Al-Sheikh H, Fathi AA (2010) Ecological studies on Al-Asfar Lake. Al-Hassa, Saudi Arabia, with special references to the sediment. Res J Environ Sci 4:13–22
Bhandari A, Kumar A, Singh GK (2012) Feature extracting using normalized difference vegetation index (NDVI): a case study of Jabalpur city. Proc Technol 6:612–621
Buma WG, Lee S, Seo JY (2018) Recent surface water extent of lake chad from multispectral sensors and GRACE. Sensors 18:2082. https://doi.org/10.3390/s18072082
Chen L, Jin Z, Michishita R, Cai J, Yue T, Chen B, Xu B (2014) Dynamic monitoring of wetland cover changes using time-series remote sensing imagery. Ecol Inform 24:17–26
Das K (2017) NDVI and NDWI based change detection analysis of Borfoibam Beelmukh Wetlandscape, Assam using IRS LISS III data. ADBU-J Eng Technol 6(2)
Dong Z, Wang Z, Liu D, Song K, Li L, Jia M, Ding Z (2014) Mapping wetland areas using Landsat-derived NDVI and LSWI: a case study of West Songnen plain, Northeast China. J Indian Soc Remote Sens 42:1–8
Eid A, Olatubara CO, Ewemoje TA, Farouk H, El-Hennawy MT (2020) Coastal wetland vegetation features and digital change detection mapping based on remotely sensed imagery: El-Burullus Lake, Egypt. Int Soil Water Conserv Res 8:66–79
El Mahmoudi AS, Massoud MA, Al-Dakheel YY, Hussein AHA (2011) Studies of Al Asfar and Al Uyoun evaporation lakes water quality and the potential of its reuse in agriculture activities, Al Hassa Area, KSA; JKAU: Met., Env. and Arid Land Agric Sci 22, 3: 67-85 (2011 A.D. /1432 A.H.). 10.4197/ Met. 22-3.4
Fathi AA, Al-Fredan MA, Youssef AM (2009) Water quality and phytoplankton communities in Lake Al-Asfar, AL-Hassa, Saudi Arabia. Res J Environ Sci 3:504–513
Fontinovo G, Allegrini A, Atturo C, Salvatori R (2012) Speedy methodology for geometric correction of MIVIS data. Eur J Remote Sens 45:19–25. https://doi.org/10.5721/EuJRS20124502
Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80(1):185–201. https://doi.org/10.1016/S0034-4257(01)00295-4
Gandhi GM, Parthiban S, Thummalu N, Christy A (2015) NDVI: Vegetation change detection using remote sensing and GIS-a case study of Vellore District. Proc Comput Sci 57:1199–1210
Gianinetto M (2012) Automatic co-registration of satellite time series, the. Photogramm Rec 27(140):462–470. https://doi.org/10.1111/j.1477-9730.2012.00689.x
Huang C, Peng Y, Lang M, Yeo IY, Mccarty G (2014) Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data. Remote Sens Environ 141:231–242
Kadhim MM (2018) Monitoring land cover change using remote sensing and GIS techniques: a case study of Al-Dalmaj Marsh, Iraq. J Eng 9(24):96–108
Kaptué AT, Hanan NP, Prihodko L (2013) Characterization of the spatial and temporal variability of surface water in the Soudan-Sahel region of Africa. J Geophys Res 118:1–12
Ke Y, Im J, Lee J, Gong H, Ryu Y (2015) Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations. Remote Sens Environ 164:298–313
McFeeters SK (1996) The use of the normalized difference water index (NDWI) in the delineation of open water features. Int J Remote Sens 17:1425–1432
Mousazadeh R, Ghaffarzadeh H, Nouri J, Gharagozlou A, Farahpour M (2015) Land use change detection and impact assessment in Anzali international coastal wetland using multi-temporal satellite images. Environ Monit Assess 187:776. https://doi.org/10.1007/s10661-015-4900-0
Nguyen TH (2015) Optimal ground control points for geometric correction using genetic algorithm with global accuracy. Eur J Remote Sens 48(1):101–120. https://doi.org/10.5721/EuJRS20154807
Nhu VH, Mohammadi A, Shahabi H, Shirzadi A, Al-Ansari N, Bin Ahmad B, Chen W, Khodadadi M, Ahmadi M, Khosravi K, Jaafari A, Nguyen H (2020) Monitoring and assessment of water level fluctuations of the Lake Urmia and its environmental consequences using multitemporal Landsat 7 ETM+ Images. Int J Environ Res Public Health 17:4210. https://doi.org/10.3390/ijerph17124210
Ojaghi S, Ahmadi FF, Ebadi H, Bianchetti R (2017) Wetland cover change detection using multi-temporal remotely sensed data; a case study: Ghara Gheshlagh wetland in the southern part of the Urmia Lake. Arab J Geosci 10:470. https://doi.org/10.1007/s12517-017-3239-y
Othman AA, Al-Saady YI, Al-Khafagi AK, Gloaguen R (2013) Environmental change detection in the central part of Iraq using remote sensing data and GIS. Arab J Geosci 7(3):1017–1028
Peters AJ, Walter-shea EA, Ji L, Vina A, Hayes M, Svoboda MD (2002) Drought monitoring with NDVI-based standardized vegetation index. Photogramm Eng Remote Sens 68(1):71–75
Petropoulos GP, Kalivas DP, Griffiths HM, Dimou PP (2015) Remote sensing and GIS analysis for mapping spatio-temporal changes of erosion and deposition of two Mediterranean river deltas: the case of the Axios and Aliakmonas rivers, Greece. Int J Appl Earth Obs 35:217–228
Prasad G, Ramesh MV (2019) Spatio-temporal analysis of land use/land cover changes in an ecologically fragile area—Alappuzha District, Southern Kerala, India; Natural Resources Research, 28, S1. https://doi.org/10.1007/s11053-018-9419-y
Rapinel S, Bouzillé JB, Oszwald J, Bonis A (2015) Use of bi-seasonal Landsat-8 imagery for mapping marshland plant community combinations at the regional scale. Wetlands 35:1–12
Rokni K, Ahmad A, Selamat A, Hazini S (2014) Water feature extraction and change detection using multitemporal Landsat imagery. Remote Sens 6:4173–4189. https://doi.org/10.3390/rs6054173
Shao Y, Lunetta RS, Wheeler B, Liames JS, Campbell JB (2016) An evaluation of time-series smoothing algorithms for land-cover classifications using MODIS-NDVI multi-temporal data. Remote Sens Environ 174:258–265
Sheng Y, Song CH, Wang J, Lyons EA, Knox BR, Cox JS, Gao F (2016) Representative lake water extent mapping at continental scales using multi-temporal Landsat-8 imagery. Remote Sens Environ V 185:129–141. https://doi.org/10.1016/j.rse.2015.12.041
Tuxen K, Schile L, Stralberg D, Siegel S, Parker T, Vasey M, Callaway J, Kelly M (2011) Mapping changes in tidal wetland vegetation composition and pattern across a salinity gradient using high spatial resolution imagery. Wetl Ecol Manag 19:141–157
Wang J, Yong Gea Y, Heuvelinkc G, Zhoua C, Brusd D (2012) Effect of the sampling design of ground control points on the geometric correction of remotely sensed imagery. Int J Appl Earth Obs Geoinf 18:91–100
Xu H (2006) Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. Int J Remote Sens 27(14):3025–3033. https://doi.org/10.1080/01431160600589179
Youssef AM, Al-Fredan MA, Adel A, Fathi AA (2009) Floristic composition of Lake Al-Asfar, Alahsa, Saudi Arabia. Int J Bot 5:116–125. https://doi.org/10.3923/ijb.2009.116.125
Zhang L, Wang MH, Hu J, Ho YS (2010) A review of published wetland research, 1991–2008: Ecological engineering and ecosystem restoration. Ecol Eng 36:973–980
Zoffoli ML, Kandus P, Madanes N, Calvo DH (2008) Seasonal and interannual analysis of wetlands in South America using NOAA-AVHRR NDVI time series: the case of the Parana Delta region. Landsc Ecol 23:833–848
Acknowledgements
The author acknowledges the Deanship of Scientific Research at the King Faisal University for the financial support under Nasher Track (Grant No. 206033).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares that he has no competing interests.
Additional information
Responsible Editor: Stefan Grab
Rights and permissions
About this article
Cite this article
Chouari, W. Wetland land cover change detection using multitemporal Landsat data: a case study of the Al-Asfar wetland, Kingdom of Saudi Arabia. Arab J Geosci 14, 523 (2021). https://doi.org/10.1007/s12517-021-06815-y
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-021-06815-y