Monitoring vegetation dynamics in southern Tunisia using SPOT-5 (Take5) data: a case study of the Tozeur oases

Abstract. Spatial data on vegetation dynamics are sparse for the Djerid oases of Tunisia, but such data are urgently needed by policy makers for natural resource management purposes. These data can be collected by remote sensing and analyzed using Geographic Information System software. We analyzed the changing dynamics of the Tozeur oases in southwestern Tunisia using normalized difference vegetation index (NDVI) index data that were generated from SPOT-5 (Take5) satellite imagery taken from April to September, 2015. We used agglomerative hierarchical clustering (AHC) to produce a dendrogram that segmented the area into similar NDVI classes, then analyzed these clusters with reference to ground-truth data collected by field surveys. The unsupervised classification map produced by AHC represents a spatial model of the NDVI distribution in the oases. The results revealed seven different clusters with very high spatial heterogeneity that were linked to biophysical parameters in the field.

[1]  Ali Ferchichi,et al.  Change of oases farming systems and their effects on vegetable species diversity: Case of oasian agro-systems of Nefzaoua (South of Tunisia) , 2014 .

[2]  T. Carlson,et al.  On the relation between NDVI, fractional vegetation cover, and leaf area index , 1997 .

[3]  Haoyu Wang,et al.  The application of threshold methods for image segmentation in oasis vegetation extraction , 2010, 2010 18th International Conference on Geoinformatics.

[4]  Xin Li,et al.  Landscape evolution in the middle Heihe River Basin of north-west China during the last decade , 2003 .

[5]  Lisheng Song,et al.  Estimations of Regional Surface Energy Fluxes Over Heterogeneous Oasis–Desert Surfaces in the Middle Reaches of the Heihe River During HiWATER-MUSOEXE , 2015, IEEE Geoscience and Remote Sensing Letters.

[6]  Rosa Lasaponara,et al.  Fisher-Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbance , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[7]  Ana Teodoro,et al.  Criterion definition for the identification of physical-geographical boundaries of Khorezm oasis through remotely sensed data , 2015, Environmental Monitoring and Assessment.

[8]  Zhang Hong,et al.  A preliminary study of oasis evolution in the Tarim Basin, Xinjiang, China , 2003 .

[9]  Mohammad Firuz Ramli,et al.  Measuring Land Cover Change in Seremban, Malaysia Using NDVI Index , 2015 .

[10]  C. Tucker,et al.  Satellite remote sensing of rangelands in Botswana II. NOAA AVHRR and herbaceous vegetation , 1986 .

[11]  Thomas Corpetti,et al.  Identification of grassland management practices from leaf area index time series , 2014 .

[12]  Salah,et al.  Food Value of Soft Dates Cultivated in Tunisian Coastal Oases , 2015 .

[13]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .

[14]  Ranga B. Myneni,et al.  Potential gross primary productivity of terrestrial vegetation from 1982 - 1990 , 1995 .

[15]  Xiangzheng Deng,et al.  Analysis and Projection of the Relationship between Industrial Structure and Land Use Structure in China , 2014 .

[16]  Zhiqiang Zhang,et al.  Oasis land-use dynamics and its influence on the oasis environment in Xinjiang, China , 2004 .

[17]  José Perrin,et al.  Classifying airborne radiometry data with Agglomerative Hierarchical Clustering: A tool for geological mapping in context of rainforest (French Guiana) , 2006 .

[18]  José M. Paruelo,et al.  Annual and seasonal variation of NDVI explained by current and previous precipitation across Northern Patagonia , 2009 .

[19]  Baihua Fu,et al.  Riparian vegetation NDVI dynamics and its relationship with climate, surface water and groundwater , 2015 .

[20]  Compton J. Tucker,et al.  Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel - 1980-1984 , 1985 .

[21]  José A. Sobrino,et al.  A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data , 2001 .

[22]  C. Jeganathan,et al.  Extracting seasonal cropping patterns using multi-temporal vegetation indices from IRS LISS-III data in Muzaffarpur District of Bihar, India , 2014 .

[23]  Martin Kappas,et al.  Modeling Net Ecosystem Exchange for Grassland in Central Kazakhstan by Combining Remote Sensing and Field Data , 2009, Remote. Sens..

[24]  Chenghu Zhou,et al.  The oasis expansion and eco-environment change over the last 50 years in Manas River Valley, Xinjiang , 2006 .

[25]  Manchun Li,et al.  Impacts of LUCC on soil properties in the riparian zones of desert oasis with remote sensing data: a case study of the middle Heihe River basin, China. , 2015, The Science of the total environment.

[26]  J. Cihlar,et al.  A multiyear analysis of the relationship between surface environmental variables and NDVI over the Canadian landmass , 1993 .

[27]  Geping Luo,et al.  Quantifying the contributions of agricultural oasis expansion, management practices and climate change to net primary production and evapotranspiration in croplands in arid northwest China , 2014 .

[28]  Benoît Duchemin,et al.  Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region , 2010, Remote. Sens..

[29]  Sylvie Le Hégarat-Mascle,et al.  Determination of vegetation cover fraction by inversion of a four-parameter model based on isoline parametrization , 2007 .

[30]  A. Plasència,et al.  Normalized difference vegetation index (NDVI) as a marker of surrounding greenness in epidemiological studies: The case of Barcelona city , 2016 .

[31]  D. Dutta,et al.  Assessment of agricultural drought in Rajasthan (India) using remote sensing derived Vegetation Condition Index (VCI) and Standardized Precipitation Index (SPI) , 2015 .

[32]  G. Meera Gandhi,et al.  Ndvi: Vegetation Change Detection Using Remote Sensing and Gis – A Case Study of Vellore District☆ , 2015 .

[33]  Jonas Ardö,et al.  Automated mapping of vegetation trends with polynomials using NDVI imagery over the Sahel , 2014 .

[34]  Caroline King,et al.  Monitoring environmental change and degradation in the irrigated oases of the Northern Sahara , 2014 .

[35]  B. de Barros Neto,et al.  Statistical design--chemometrics , 2006 .

[36]  J. H. Ward Hierarchical Grouping to Optimize an Objective Function , 1963 .

[37]  M. AboelGhar,et al.  Retrieving leaf area index from SPOT4 satellite data , 2010 .

[38]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[39]  Xiao Du-ning,et al.  Dynamics of Typical Agricultural Landscape and its Relationship With Water Resource in Inland Shiyang River Watershed, Gansu Province, Northwest China , 2006, Environmental monitoring and assessment.

[40]  A. Huete,et al.  Development of a two-band enhanced vegetation index without a blue band , 2008 .

[41]  Johanna Smeyers-Verbeke,et al.  Visual presentation of data by means of box plots , 2005 .

[42]  Juha Hyyppä,et al.  Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing , 2010, Remote. Sens..

[43]  Mehrez Zribi,et al.  Analysis of Vegetation Behavior in a North African Semi-Arid Region, Using SPOT-VEGETATION NDVI Data , 2011, Remote. Sens..

[44]  Ying Zhang,et al.  Expansion of agricultural oasis in the Heihe River Basin of China: Patterns, reasons and policy implications , 2015 .

[45]  P. Su,et al.  Ecological effects of desertification control and desertified land reclamation in an oasis–desert ecotone in an arid region: A case study in Hexi Corridor, northwest China , 2007 .

[46]  David Western,et al.  Spatial cluster analysis for large herbivore distributions: Amboseli ecosystem, Kenya , 2015, Ecol. Informatics.

[47]  Luft und Raumfahrttechnik NASA Earth Observatory , 2010 .