home icon user icon
Welcome to International Network for Natural Sciences | INNS Pub.
Home My Account
Submit Manuscript
double_slash
breadcumb_bg

Vegetation and land cover change in the National park of EL Kala: Application of NDVI differencing and classification analysis

Paper Details

Research Paper 01/07/2015
Views (332) Download (9)
current_issue_feature_image
publication_file

Vegetation and land cover change in the National park of EL Kala: Application of NDVI differencing and classification analysis

Mouna Khaznadar, Mohammed Fenni
J. Bio. Env. Sci.7( 1), 231-244, July 2015.
Certificate: JBES 2015 [Generate Certificate]
Key: Change detectionLand coverNational Park of El KalaNDVI DifferencingVegetation

Abstract

In this study, vegetation and land cover change were investigated in order to understand the nature and dynamic of changes occurred in the National Park of El-Kala (Algeria) between years 2002 and 2013. Landsat images, remote sensing techniques and GIS tools were the key elements to achieve this study. The 2013 NDVI image was subtracted from the 2002 one, and the resulting NDVI differencing image was classified into three categories: positive, negative and no change. Assessment was satisfactory with an overall accuracy of 98.14% and Kappa coefficient of 0.97. Areas affected by vegetation loss are mainly found in the east and south part of the park, whereas areas with vegetation gain are located around water bodies. Regarding land cover change, two unsupervised classifications were applied and seven land cover classes were defined in both images. Based on field knowledge and statistics’ comparison, land cover classes affected by areas’ decrease are Dense forest (-0.96 %), Uncultivated land (-3.99 %) and Barren land (-6.56 %). In contrast, land cover classes with positive change are: Water body (+2.01 %); Open forest (+4.93 %), Cultivated land (+4.45 %) and Urban (+3.66 %). The main causes for these changes are: Expansion of urban tissue and new infrastructures, degradation of dense forests due to human pressures mainly grazing and clearing, intensification of agriculture activities with uncontrolled irrigation and last but not least, forest fires in summers due to long droughts periods and holiday rush.

VIEWS 19
Cover PDF

Allen HD. 2001. Mediterranean Ecogeography. Pearson Education Limited. 263 P.

Alphan H, Derse MA. 2013. Change detection in Southern Turkey using normalized difference vegetation index (NDVI). Journal of Environmental Engineering and Landscape Management21(1), 12-18.

Anderson JR, Hardy EE, Roach JT, WitmerRE. 1976. A land use and land cover classification system for use with remote sensor data. U.S. Geological Survey. Professional Paper, No. 964, USGS, Washington, D.C.

ANTB: National Agency of Dams.2014. L’Agence Nationale des Barrages et Transferts http://www.soudoudzair.com/index.php?action=es map_vect&table=chahidgis_barrage&id=84

Benderradji MEH, Alatou D, Arfa AMT. 2004. Bilan des incendies de forêt dans l’extrême nord-est algérien : le cas de Skikda, Annaba et El-Tarf. New Medit2, 35-41

Chavez PS Jr. 1996.  Image-based  atmospheric corrections-revisited and improved-Photogrammetric Engineering and Remote Sensing. 62, 1025-1036.

Directorate of Environment and Urban Management.2014. Annuaire statistique de la wilaya d’El Tarf.

Directorate of Tourism of El Tarf. 2014. Rapport sur le tourisme dans la Wilaya d’El Tarf.

Feoli E, Giacomich P, Mignozzi K. 2003. Monitoring desertification risk with an index integrating climatic and remotely sensed data. An example from the coastal area of Turkey. Management of Environmental Quality14(1), 10-21.

Fichera CR, Modica G, Pollino M. 2012. Land Cover classification and change-detection analysis using multi-temporal remote sensed imagery and landscape metrics. European Journal of Remote Sensing45, 1-18.

Foody GM. 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment 80, 185-201. Professional Paper, 964, 28.

Fung T, Le Drew E. 1988. The Determination of Optimal Threshold Levels for Change Detection Using Various Accuracy Indices. Photogrammetric Engineering and Remote Sensing54(10), 1449-1454.

Griffiths GH. 1988.Monitoring Urban Change From Landsat TM and Spot Satellite Imagery by Image Differencing. Proceedings of IGRASS 88 Symposium, Edinburgh, Scotland, 13-16 Sept, 1988. Published by ESA Publications Division.

Haines-Young R. 2009. Land Use and Biodiversity Relationships. Land Use Policy. 26(1), 178-186.

Halder A, Ghosh A, Ghosh S.2011. Supervised and unsupervised landuse map generation from remotely sensed images using ant based system. Applied Soft Computing11, 5770-5781.

Homewood KM. 1993. Livestock Economy and Ecology in El Kala, Algeria: Evaluating Ecological and Economic Costs and Benefits in Pastoralist Systems. Network paper. Volume 35, Partie 1 de Paper (Overseas Development Institute (London, England). Pastoral Development Network). ODI Pastoral Development Network. 19 p.

Jensen JR. 1996. Introductory Digital Image Processing. A Remote Sensing Perspective. Second edition. Prentice Hall. Upper saddle River, New Jersey, 318 p.

Kosmas C, Danalatos NG, Lopez-Bermudez F, Roereo Diaz MA. 2002.The effect of land Use on soil Erosion and Land Degradation under Mediterranean Conditions. InMediterranean Desertification: A mosaic of Processes and responses. Edited by N.A. Geeson, C.J. Brant and J.B. Thornes. John Wiley& Sons, Ltd.440 P.

Lasanta T, Vicente-Serrano SM. 2012.Complex land cover change processes in semiarid Mediterranean regions: An approach using Landsat images in northeast Spain. Remote Sensing of Environment124, 1-14. http://dx.doi.org/10.1016/j.rse.2012.04.023

Li P, Jiang L, Feng Z. 2014. Cross-Comparison of Vegetation Indices Derived from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) Sensors. Remote Sens. 6, 310-329. http://dx.doi.org/10.3390/rs6010310

Lillesand T, Kiefer RW, Chipman J. 2008. Remote Sensing and Image Interpretation. John Wiley & Sons; 6th Edition. ISBN-10: 0470052457. ISBN-13: 978-0470052457. 768p

Mas JF. 1999. Monitoring land cover change: a comparison of change detection techniques. Int. J. Remote Sensing. 20, 139-152

Medail F, Quézel P. 1999. Biodiversity Hotspot in the MediterraneanBasin: Setting global conservation Priorities. Conservation Biology13(6), 1510-1513.

Oulmouhoub S. 2005. Gestion multi usage et conservation du patrimoine forestier : Cas des subéraies du parc d’El Kala. Institut agronomique méditerranéen de Montpellier ; CIHEAM-IAMM 2005.

Peijun D, Xingli L, Wen C, Yan L, Huanpeng Z. 2010. Monitoring urban land cover and vegetation change by multi-temporal remote sensing information. Mining Science and Technology20, 922-932.

Peng J, Wu J, Yin H, Chang Q, Mu T. 2008. Rural land use change during 1986–2002 in Lijiang, China, based on remote sensing and GIS data. Sensors8, 8201–8223. http://dx.doi.org/10.3390/s8128201

Rozenstein O, Karnieli A. 2011. Comparison of methods for land-use classification incorporating remote sensing and GIS inputs. Applied Geography. 31, 533-544

Singh A. 1989. Review Article: Digital change detection techniques using remotely sensed data. Int. J. Remote Sensing10, 989-1003.

Sinha P, Kumar L. 2013. Independent two-step thresholding of binary images in inter-annual landcover change/no-change identification. ISPRS Journal of Photogrammetry and Remote Sensing81, 31-43.

Skinner J, Smart M. 1984. The EI Kala wetlands of Algeria and their use by waterfowl. Wildfowl35, 106-118.

Stevenson AC, Skinner J, Hollis GE, Smart M. 1988.  The  El  Kala  National  Park  and  Environs, Algeria:  An  Ecological  Evaluation.  Environmental Conservation15(04), 335- 348.

Véla E, Benhouhou S. 2007. Évaluation d’un nouveau point chaud de biodiversité végétale dans le Bassin méditerranéen (Afrique du Nord) C.R. Biologies330, 589- 605.

Xu D, Guo X. 2014. Compare NDVI Extracted from Landsat 8 Imagery with that from Landsat 7 Imagery. American Journal of Remote Sensing2(2), 10-14. http://dx.doi.org/10.11648/j.ajrs.20140202.11

Yahi N, Vela E, Benhouhou S, De Belair G, Gharzouli R. 2012. Identifying Important Plants Areas (Key Biodiversity Areas for Plants) in northern Algeria. Journal of Threatened Taxa.4(8), 2753-2765.

Submit Manuscript