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Association of temporal variation of land surface temperature and vegetation cover at the Mount Babor forest area, Algeria: a geospatial modeling approach

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Abstract

The current study aims to analyze the land surface temperature (LST), and the vegetation cover in the Mount Babor forest (North East of Algeria), and to examine the correlation between these two variables. Satellite imageries Landsat 5 (TM) and Landsat 8 (OLI/TIRS) for the years: 1990- 2000- 2010 -2021 (the summer season) were processed using ArcGIS 10.4 software. The LST data was retrieved from the thermal infrared (TIR) bands of satellite images; while the Normalized Difference Vegetation Index (NDVI) was determined by using the near infrared (NIR) and red (Red) bands. The regression technique was used to assess the correlation between the LST and NDVI. This study highlighted an increasing pattern in LST, where the mean LST increased from 25.08°C in 1990, to 29.33°C in 2021, thus an increase of 4.25 °C. Minimal LST also increased from 17.02°C in 1990, to 22.89°C in 2021, thus an increase of 5.87°C, over study period. Temporal variations of NDVI, showed dense and healthier vegetation in 1990, followed by the year 2000 (NDVI 0.756 and 0.749 respectively). However, a decline in NDVI is noted in 2010 and 2021 (NDVI 0.662 and 0.668 respectively). A strong linear negative correlation was observed between LST and NDVI over time, where the regression coefficient was of the order of:—0.73;—0.80;—0.83;—0.76 for the years: 1990, 2000,2010 and 2021 respectively, which present opposite spatial distribution patterns. The loss of vegetation is responsible for the rise in LST, and vice versa. This study will guide future studies on vegetation and temperature monitoring.

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Data availability

This research was based on the analysis and processing of satellite image data from the Earth Explorar platform available via the site https://earthexplorer.usgs.gov/

References

  • Abrams MD (2011) Adaptations of forest ecosystems to air pollution and climate change. Tree Physiol 31(3):258–261. https://doi.org/10.1093/treephys/tpr010

    Article  Google Scholar 

  • Akbar TA, Hassan QK, Ishaq S, Batool M, Butt HJ, Jabbar H (2019) Investigative spatial distribution and modelling of existing and future urban land changes and its impact on urbanization and economy. Remote Sensing 11(2):105. https://doi.org/10.3390/rs11020105

    Article  Google Scholar 

  • Alademomi AS, Okolie CJ, Daramola OE, Akinnusi SA, Adediran E, Olanrewaju HO ... Odumosu J (2022) The interrelationship between LST, NDVI, NDBI, and land cover change in a section of Lagos metropolis, Nigeria. Appl Geomatics, 14(2), 299–314

  • Alamm HM, Arafat MY, Ahmed KT, Uddin MN (2021) Temporal variation of land surface temperature in response to changes in vegetation index of Bhawal National Park, Bangladesh. In Sustainable Cities and Resilience: Select Proceedings of VCDRR (pp. 329–337). Singapore: Springer Singapore. https://doi.org/10.1007/978-981-16-5543-2_27

  • Anbazhagan S, Paramasivam CR (2016) Statistical correlation between land surface temperature (LST) and vegetation index (NDVI) using multi-temporal landsat TM data. Intl J Adv Earth Sci Eng 5(1):333–346. https://doi.org/10.23953/cloud.ijaese.204

    Article  Google Scholar 

  • Artis DA, Carnahan WH (1982) Survey of emissivity variability in thermography of urban areas. Remote Sens Environ, 12(4), 313–329.) https://doi.org/10.1016/0034-4257(82)90043-8

  • Assoul D, Touhami I, Moutahir H, Bellot J, Saidi S, Nasr Z (2020) Monitoring of the dynamics of vegetation and climate through the analysis of chronological series of modis images in the Sidi Zid forest, north-eastern Tunisia

  • Athick AMA, Shankar K, Naqvi HR (2019) Data on time series analysis of land surface temperature variation in response to vegetation indices in twelve Wereda of Ethiopia using mono window, split window algorithm and spectral radiance model. Data Brief 27:104773. https://doi.org/10.1016/j.dib.2019.104773

    Article  Google Scholar 

  • Bougaham AF, Rebbas K (2020) Nouvelle station de Cephalanthera rubra (Orchidaceae) au Babor (nord-est de l’Algérie). Bull Soc Roy Sci Liège 89:115–122

    Article  Google Scholar 

  • Burfield IJ, Butchart SH, Collar NJ (2017) BirdLife, conservation and taxonomy. Bird Conserv Intl 27(1):1–5

    Article  Google Scholar 

  • Carlson TN, Ripley A (1997) On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens Environ 62(3):241–252. https://doi.org/10.1016/S0034-4257(97)00104-1

    Article  Google Scholar 

  • Chan CK, Yao X (2008) Air pollution in mega cities in China. Atmos Environ 42(1):1–42

    Article  CAS  Google Scholar 

  • Chen XL, Zhao HM, Li PX, Yin ZY (2006) Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens Environ 104(2):133–146

    Article  Google Scholar 

  • Danodia A, Nikam RB, Kumar S, Patel NR (2017) Land surface temperature retrieval by radiative transfer equation and single channel algorithms using landsat-8 satellite data. Indian Inst Remote Sens-ISRO, 1–7

  • De Smet K, Bouanza F (1984) La structure forestière du mont Babor. Silva Gandavensis, 50

  • Demaze MT (2002) Caractérisation et suivi de la déforestation en milieu tropical par télédétection: application aux défrichements agricoles en Guyane française et au Brésil (Doctoral dissertation, Université d'Orléans)

  • Fathizad H, Tazeh M, Kalantari S, Shojaei S (2017) The investigation of spatiotemporal variations of land surface temperature based on land use changes using NDVI in southwest of Iran. J Afr Earth Sc 134:249–256. https://doi.org/10.1016/j.jafrearsci.2017.06.007

    Article  Google Scholar 

  • Fayech D, Tarhouni J (2021) Climate variability and its effect on normalized difference vegetation index (NDVI) using remote sensing in semi-arid area. Model Earth Syst Environ 7:1667–1682. https://doi.org/10.1007/s40808-020-00896-6

    Article  Google Scholar 

  • Fensholt R, Rasmussen K, Nielsen TT, Mbow C (2009) Evaluation of earth observation based long term vegetation trends—Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data. Remote Sens Environ 113(9):1886–1898. https://doi.org/10.1016/j.rse.2009.04.004

    Article  Google Scholar 

  • Gandhi GM, Parthiban S, Thummalu N, Christy A (2015) NDVI: Vegetation Change detection using Remote sensing and Gis – A case study of Vellore District. Procedia Comput Sci 57:1199–1210. https://doi.org/10.1016/j.procs.2015.07.415

    Article  Google Scholar 

  • Gharzouli R (2007) Flore et végétation de Kabylie des Babors. Etude floristique et phytosociologique des groupements forestiers et post-forestiers des djebels Takoucht, Adrar Ou-Mellal, Tababort et Babor. Sétif, Université Ferhat Abbas. Sétif

  • Gharzouli R, Djellouli Y (2005) Diversité floristique de la Kabylie des Babors (Algérie). Sci Et Changements Planétaires/Sécheresse 16(3):217–223

    Google Scholar 

  • Gorgani SA, Panahi M, Rezaie F (2013) The Relationship between NDVI and LST in the urban area of Mashhad, Iran. In International conference on civil engineering architecture & urban sustainable development (Vol. 27, p. 51)

  • Govil H, Guha S, Dey A, Gill N (2019) Seasonal evaluation of downscaled land surface temperature: A case study in a humid tropical city. Heliyon, 5(6). https://doi.org/10.1016/j.heliyon.2019.e01923

  • Goward SN, Xue Y, Czajkowski KP (2002) Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements: An exploration with the simplified simple biosphere model. Remote Sens Environ 79(2–3):225–242. https://doi.org/10.1016/S0034-4257(01)00275-9

    Article  Google Scholar 

  • Grover A, Singh RB (2015) Analysis of urban heat island (UHI) in relation to normalized difference vegetation index (NDVI): A comparative study of Delhi and Mumbai. Environments 2(2):125–138. https://doi.org/10.3390/environments2020125

    Article  Google Scholar 

  • Guha S, Govil H (2021) An assessment on the relationship between land surface temperature and normalized diference vegetation index. Environ Dev Sustain 23(2):1944–1963

    Article  Google Scholar 

  • Haichour S, Benabdeli Kh (2022 ) L'écosystème forestier algérien face aux pressions anthropiques et climatiquesAlgeria’s forest ecosystem in the face of anthropogenic and climatic pressuresRevue Geo-Eco-Trop N° 46 Tome 1, pp. 109–124

  • Haque M N, Khanam N R, Nanjiba M (2020) Geospatial Monitoring on Land Surface Temperature and Vegetation Dynamics: A Case of a City Area in Khulna, Bangladesh. Trends Undergrad Res, 3(2), a35–43. https://doi.org/10.33736/tur.2172.2020

  • Hesselbjerg-Christiansen, J. & Hewitson, B. (2007) Regional Climate Projection. In: IPCC Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon S., Qin D., Manning M., Chen Z., Marquis M., Averyt K.B., Tignor M., Miller H.L. eds., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 p.

  • Hou GL, Zhang HY, Wang YQ, Qiao ZH, Zhang ZX (2010) Retrieval and spatial distribution of land surface temperature in the middle part of Jilin province based on MODIS data. Scientia Geographica Sinica 30(3):421–427

    Google Scholar 

  • Ikermoud M (2000) Évaluation des ressources forestières nationales. DGF. Alger

  • Isaya NM, Avdan U (2016) Application of open source coding technologies in the production of land surface temperature (LST) maps from Landsat: a PyQGIS plugin. Remote Sens 8(5):413

    Article  Google Scholar 

  • Jayaraman R, Chokkalingam L (2021) Correlation between land surface temperature and vegetation cover of Nagapattinam Coastal Zone, Tamil Nadu, using geospatial techniques. In Groundwater Resources Development and Planning in the Semi-Arid Region (pp. 221–238). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-68124-1_12

  • Karnieli A, Agam N, Pinker RT, Anderson M, Imhoff ML, Gutman GG, Goldberg A (2010) Use of NDVI and land surface temperature for drought assessment: Merits and limitations. J Clim 23(3):618–633. https://doi.org/10.1175/2009JCLI2900.1

    Article  Google Scholar 

  • Kolai L (1992) La sapinière à Abies numidica dans le mont Babor: phytosociologie et production. Ann. Rech. for. Algérie, 2e semestre, 85–99

  • Ledant JP (1981) Conservation et fragilité de la forêt de Babor, habitat de la Sittelle kabyle. Aves 18(1–2):1–9

    Google Scholar 

  • Li ZL, Tang BH, Wu H, Ren H, Yan G, Wan Z, Sobrino JA (2013) Satellite-derived land surface temperature: Current status and perspectives. Remote Sens Environ 131:14–37. https://doi.org/10.1016/j.rse.2012.12.008

    Article  Google Scholar 

  • Madoui A (2003). Un site à préserver: la forêt des Babors, Algérie. XIIe Congrès forestier mondial

  • Madoui A (2020). La forêt de Babor (Sétif, Algérie) : Richesse et fragilité. Al Yasmina 1 : 03/1–16

  • Madoui A, Véla E (2020) Les Orchidées de la région de Sétif et de sa partie septentrionale (nord-est de l’Algérie). Bull Mens Soc Linn Lyon 89(5–6):88–122

    Google Scholar 

  • Mehta A, Shukla S, & Rakholia S (2021). Vegetation change analysis using normalized difference vegetation index and land surface temperature in greater Gir landscape. Journal of Scientific Research, 65(3), 1–6. :https://doi.org/10.37398/JSR.2021.650301

  • Missaui K (2019) Dynamique des écosystéme dusétifois face aux changements globaux. Thése de Doctorat.université Ferhat Abbas Sétif 1, Algeria.126p

  • Morgan JA (1998) The definition of surface emissivity in thermal remote sensing. In 1998 IEEE Aerospace Conference Proceedings (Cat. No. 98TH8339) (Vol. 5, pp. 159–169). IEEE

  • Naughton-Treves L, Holland MB, Brandon K (2005) The role of protected areas in conserving biodiversity and sustaining local livelihoods. Annu Rev Environ Resour, 30, 219–252. :https://doi.org/10.1146/annurev.energy.30.050504.164507

  • Omran ESE (2012) Detection of land-use and surface temperature change at different resolutions

  • Panda A, Sahu N (2019) Trend analysis of seasonal rainfall and temperature pattern in Kalahandi, Bolangir and Koraput districts of Odisha. India Atmos Sci Lett 20(10):e932. https://doi.org/10.1002/asl.932

    Article  Google Scholar 

  • Rehman Z, Kazmi SJ, Khanum F, Samoon ZA (2015) Analysis of land surface temperature and NDVI using geo-spatial technique : A case study of Keti Bunder, Sindh, Pakistan. J Basic Appl Sci 11:514–527. https://doi.org/10.6000/1927-5129.2015.11.69

    Article  Google Scholar 

  • Rekis A, Belhamra M (2015) Etude diachronique de la végétation par télédetection. Cas De La Région De Tolga En Algérie Intl J Environ Global Clim Chang 3(5):49–61

    Google Scholar 

  • Richard JU, Abah IA (2019) Derivation of Land Surface Temperature (LST) from LANDSAT 7 & 8 Imageries and its Relationship with two Vegetation Indices (NDVI and GNDVI). Intl J Res-Granthaalayah 7(2):108–120. https://doi.org/10.29121/granthaalayah.v7.i2.2019.1013

    Article  Google Scholar 

  • Rouse JW, Haas RH, Schell JA, Deering DW (1974) Monitoring vegetation systems in the Great Plains with ERTS. NASA Spec Publ 351(1):309. https://doi.org/10.4236/jwarp.2016.82023

    Article  CAS  Google Scholar 

  • Sahana M, Ahmed R, Sajjad H (2016) Analyzing land surface temperature distribution in response to land use/land cover change using split window algorithm and spectral radiance model in Sundarban Biosphere Reserve, India. Model Earth Syst Environ 2:1–11

    Article  Google Scholar 

  • Salahi B, Behrouzi M (2023) Modeling of land surface temperature (LST) in Ardabil plain using NDVI index and Bayesian neural network approach. Model Earth Syst Environ 9(4):3897–3906. https://doi.org/10.1007/s40808-023-01709-2

    Article  Google Scholar 

  • Schultz NM, Lawrence PJ, Lee X (2017) Global satellite data highlights the diurnal asymmetry of the surface temperature response to deforestation. J Geophys Res Biogeosci 122(4):903–917. https://doi.org/10.1002/2016JG003653

    Article  Google Scholar 

  • Shah SA, Kiranb M, Nazirc A, Darsd R (2021) Evaluation of Land Surface Temperature and Normalized Difference Vegetation Index Relationship Using Landsat 8 Satellite Images in Mehar Taluka, Dadu. Pakistan J Geol. https://doi.org/10.2478/pjg-2021-0008

  • Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013) Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J Geophys Res: Atmos, 118(6), 2473–2493

  • Sobrino JA, Jiménez-Muñoz JC, Paolini L (2004) Land surface temperature retrieval from LANDSAT TM 5. Remote Sens Environ 90(4):434–440. https://doi.org/10.1016/j.rse.2004.02.003

    Article  Google Scholar 

  • Solanky V, Singh S, Katiyar SK (2018) Land surface temperature estimation using remote sensing data. In Hydrologic Modeling: Select Proceedings of ICWEES-2016 (pp. 343–351). Springer Singapore. https://doi.org/10.1007/978-981-10-5801-1_24

  • Vennetier M, Ripert C (2010). Impact du changement climatique sur la flore méditerranéenne: théorie et pratique. In book: Changement climatique et biodiversité (pp.75–87) Edition: VUIBERT – AFAS Chapter: 6 Publisher: AFAS

  • Vennetier M (2020) Forêts et changement climatique. Le constat en région méditerranéenne. Sci Eaux Territoires, 33(3), 18–25. https://doi.org/10.3917/set.033.0018

  • Voogt JA, Oke TR (2003) Thermal remote sensing of urban climates. Remote Sens Environ 86(3):370–384. https://doi.org/10.1016/S0034-4257(03)00079-8

    Article  Google Scholar 

  • Weng Q, Lu D, Schubring J (2004) Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens Environ 89(4):467–483. https://doi.org/10.1016/j.rse.2003.11.005

    Article  Google Scholar 

  • Xue J, Su B (2017). Significant remote sensing vegetation indices: A review of developments and applications. J Sens. https://doi.org/10.1155/2017/1353691

  • Yuan X, Wang W, Cui J, Meng F, Kurban A, De Maeyer P (2017) Vegetation changes and land surface feedbacks drive shifts in local temperatures over Central Asia. Sci Rep 7(1):3287. https://doi.org/10.1038/s41598-017-03432-2

    Article  CAS  Google Scholar 

  • Yue W, Xu J, Tan W, Xu L (2007) The relationship between land surface temperature and NDVI with remote sensing: application to Shanghai Landsat 7 ETM+ data. Int J Remote Sens 28(15):3205–3226. https://doi.org/10.1080/01431160500306906

    Article  Google Scholar 

  • Zanter K (2019) Landsat 8 (L8) Data users handbook; EROS: Sioux Falls, SD, USA

  • Zareie S, Khosravi H, Nasiri A (2016) Derivation of land surface temperature from Landsat Thematic Mapper (TM) sensor data and analysing relation between land use changes and surface temperature. Solid Earth. Discuss, 1-15. https://doi.org/10.5194/se-2016-22

  • Zerroug K (2012) Elaboration d’un système d’information géographique (flore) dans la wilaya de Sétif. Doctoral dissertation, University of Sétif 1

  • Zhang XX, Wu PF, Chen B (2010) Relationship between vegetation greenness and urban heat island effect in Beijing City of China. Procedia Environ Sci 2:1438–1450. https://doi.org/10.1016/j.proenv.2010.10.157

    Article  Google Scholar 

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Acknowledgements

We are grateful to the online platform USGS Earth Explorer for the Landsat datasets used in our analysis. We are also grateful to the conservation of the forests of the province of Setif, Algeria, and associated staff, for assistance in the realization of the field outings.

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  1. Department of Biology and Plant Ecology, Faculty of Natural and Life Sciences, Ferhat Abbas University, Setif 1, 19000, Setif, Algeria

    Asma Bouchelouche

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Bouchelouche, A. Association of temporal variation of land surface temperature and vegetation cover at the Mount Babor forest area, Algeria: a geospatial modeling approach. Model. Earth Syst. Environ. (2024). https://doi.org/10.1007/s40808-024-02027-x

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