Bouajila ESSIFI

Environmental Remote Sensing, Ph.D. Candidate

INSTITUT DES REGIONS ARIDES (IRA)

TUNISIA

« Desertification and Drought Monitoring

in Arid Tunisia based on Remote Sensing Imagery »

Research Undertaken & Case-Studies

EU COST Action September 2015, Antalya – Turkey

Bouajila ESSIFI

INSTITUT DES REGIONS ARIDES (IRA),

TUNISIA

TUNISIA…Arid and Semiarid regions:

The dry prone areas cover almost more than 4/5 the total area where

desertification related problems are of major importance.

R EMAD A SMA RD H IBA TAT AOU I N E SU DTAT OU I N E NO R DG HO MR ASSE NBI R L AH MAR T U N I S I A i n N O R T H AF R I C A

Longitude: 7° and 12° E

Latitude: 32° and 38° N

Area: 164 000 km²

Climate Heterogeneity:

2 opposite climate domains:

Mediterranean (temperate humid),

Sahara (arid tropical)

Coastline spans: 1300 km,

75% suffers from aridity and

drought,

Annual rainfall:

Northwest: 500-1500 mm.

South:150 mm.

A strong variability:

After 1900: 20 Droughts and 14

Floods,

G E O G R AP H I C & C L I M AT I C C H AR A C T E R I S T I C S

The INSTITUT DES RÉGIONS ARIDES (IRA), created in 1976, has been assigned

the main mandates of:

G E O - I N F O R M AT I C R E L AT E D AC T I V I T I E S O F I R A

Conducting research on natural resources management and

combating desertification

Contributing to capacity building in drylands

related topics

Providing expertise and assistance for

development agencies operating in

the dry areas.

G E O - I N F O R M AT I C R E L AT E D AC T I V I T I E S O F I R A

A specific program on desertification surveillance by combining RS

tools to field investigation.

Natural resources and desertification surveillance at

different spatial and resolution

scales

Socio-economic

interactions between local

population and their

environmental landscapes

Monitoring of wildlife and endangered

animal species

Geomatic-based tools for decision making in drylands

assessment and

development

I R A – I N T E R N AT I O N A L C O O P E R AT I O N P R O J E C T S

• 2003-2006: “Desertification Observatories” funded by the Swiss Cooperation in

collaboration with OSS and ROSELT

• 2005-2010: “A Surveillance System for Assessing and Monitoring of Desertification

(DeSURVEY)” funded by the EU

I R A – I N T E R N AT I O N A L C O O P E R AT I O N P R O J E C T S

• 2007-2010: LADA “Land Degradation in Drylands” funded by FAO

I R A – I N T E R N AT I O N A L C O O P E R AT I O N P R O J E C T S

• 2007-2011: “Desertification Mitigation and Remediation of Land” (DESIRE) funded by the

EU

I R A – I N T E R N AT I O N A L C O O P E R AT I O N P R O J E C T S

N AT I O N A L C E N T E R S F O R S PAC E T E C H N O L O G Y

1988: CNCT, The National Remote Sensing Center

Develeop capacities at national level,

Coordinate and execute national programs on space technology,

Provide technical advisory services related to space infromation, training and education

opportunities in Space technology,

Enhance the regional and internatinal cooperation.

1990: CRTEAN, The North African States Regional Center for Remote

Sensing

Promote RS, GIS, mapping and their applied activities,

Ensure a useful and efficient complementarity in the above fields for the

benfit of its member statesand associated members.

Drought is a complex natural phenomenon of climate (Wilhite, 2005):

A period of lower than average rainfall,

Linked to a deficit of water resources availability covering a large geographic

area and which extends over a relatively significant period (Rossi, 2000).

Droughts impacts depend on meteorological conditions, land surface and ecosystem

type, and social and economic circumstances.

D R O U G H T M O N I T O R I N G : A H I G H P R I O R I T Y F O R T U N I S I A

Preparedness for drought forms an important part of national environmental policies.

TUNISIA, has limited institutional and technical capacity to prepare for a drought and

to mitigate its impacts.

Insufficient readily available information on drought onset and development for

agencies and for the general public.

P R O B L E M AT I C R AT I O N A L E

ARID & SEMIARID TUNISIA

Quantitative Degradation Qualitative Degradation

Reduction of Area Biodiversity Loss

Droughts / Erosion Croplands / Overgrazing

Edaphic / Climatic Contrainsts Anthropogenic Impact

Precarious climate tightly linked to aridity.

Degraded soil resources and water resources.

ARID TUNISIA: B I O P H Y S I C AL AS P E C T S

Steppic rangelands with sparse vegetation

ARID TUNISIA: B I O P H Y S I C AL AS P E C T S

Overexploitation Favorising Desertification Processes

Extensive Livestock

Dry Farming

Overgrazing

Desertification

E AR T H O B S E R VAT I O N S : AN AS S E T

Environmental Change is defined by its landscape consequences, and it is these

consequences that have to be detected and quantified using space data.

Environmental Change can only be inferred from remote measurements of the spatial

and temporal dynamics of landscape attributes. -R.D. Graetz (1996)

Detection and Monitoring must be based on

Landscape Functions that are Associated with Land

Degradation Status

Biological Productivity, Soil Resources, Efficiency of Water & Energy

Use

Consistency with Desertification Process

Sufficiently large time window for observation steps (i.e. 5 year

integration periods) to avoid impact of exceptional situations

Sufficiently long time intervals between assessment steps (i.e., 10

years) to allow for recordable changes in landscape functions

applicable to both natural and agricultural landscapes (annual

averages vs. seasonal peaks of landscape functions)

Forecasting Capacities

S AT E L L I T E O B S E R VAT I O N S

S AT E L L I T E O B S E R VAT I O N S

A S P E C T S O F T H E A D O P T E D A P P R A O C H

GIS Socioeconomic Data Fieldwork

Synoptic - Repetitive - Selective

RS Times-Series

Inventory Assessment Surveillance

Knowledge – Modelling – Management

LU/LC Classification

STABILITY

Synthesis in terms of Tendencies

AMELIORATION DEGRADATION

Discriminate Hotspots of Change

O V E R AL L O B J E C T I V E S

To assess land degradation in Southern Tunisia natural regions (1984 to 2010) using RS times-

series (Landsat, AVHRR, MODIS…) and higher resolution for hotspots (SPOT, GEOEYE, IKONOS...),

To develop a surveillance system that can de used to monitor and diagnose desertification,

vulnerability of eco-agricultural systems relative to desertification (‘vulnerability’ is land

degradation).

To contribute to strengthen the necessary scientific knowledge for the future orientation of the

sustainable Development Strategy at national level.

To establish the relationships between degradation processes, natural dynamics ecosystem,

and human activities.

M E T H O D O L O G Y & S T U D Y F L O W C H AR T

Decadal Image

Classification:

LANDSAT

Data Preprocessing: Radiometric & Atmospheric Calibrations of LANDSAT

- MODIS - AVHRR

Image Enhancement:

Photo-interpretation

Geostatistics:

TimeStats

Accuracy Assessment Ancillary Data

Ground Truth

GIS Integration:

Change Detection

Land Cover / Land Use Maps

Analysis & Discussion of Results – Conclusion

Bibliographical Review

Geostatistics

Landcover Classification

LANDSAT TIME-SERIES

Assessment / SPACE Modelling / TIME

Change-maps

of

Land Processes

Map of MONITORING

CHARACTERIZATION OF DEGRADATION/DESERTIFICATION HOTSPOTS

DESERTIFICATION SYNDROME:

DESCRIPTION OF ARCHETYPICAL, CO-EVOLUTIONNARY PATTERNS OF

HUMAN–NATURE INTERACTIONS

Map of ASSESSMENT

M E T H O D O L O G Y & S T U D Y F L O W C H AR T ( C o n t i n u e d … )

L AN D C O N D I T I O N I N T H E M AG H R E B ( 1 9 9 8 - 2 0 0 8 )

DEL BARRIO et al. (2010) 2dRUE APPLICATION, (DeSurvey Project)

Input Data: NDVI

monthly images (1998-

2008)

Source: SPOT

VEGETATION NDVI data,

(VITO, 2005):

http://free.vgt.vito.be

Dekadal NDVI data is

obtained in a geographic

projection with spatial

resolution of 0.00892857

degrees

L AN D C O N D I T I O N I N T H E M AG H R E B ( 1 9 9 8 - 2 0 0 8 )

DEL BARRIO et al. (2010) 2dRUE APPLICATION, (DeSurvey Project)

Hypothesis:

Active degradation took

place before the analysis

period, and a reason for so

much static land is that it is

already very degraded,

Land actively degrading along the last 10 years is very scarce: 7000 sq.km.

Land static with no trend in long or short term is very abundant: 1000000 sq.km.

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

Typology of hydrological years from 1969 to

2012 (Beni-Khedache Station):

Pourcentage of normality (mm):

PN = (Pi/Pm)*100

With Pi (mm): annual rainfall et Pm: average

rainfall of years (1969 à 2012),

Based on year classification:

Humid: PN [ 110;+∞ ],

Normal: PN [ 80;110],

Moderately Dry: PN [ 55;80],

Very Dry: PN [0;55]

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

L C L U I N S O U T H E R N T U N I S I A ( 1 9 8 4 - 2 0 11 )

MOURTALA et al. (2013) - AFROMAISON PROJECT

D R O U G H T M O N I T O R I N G : O N G O I N G Q U E S T

Perspectives:

Data acquisition and processing,

Statistical modelling,

LC-LU mapping.

Bring out results that may explain:

Desertification syndrome concept: Exploitation - Regional/Local

Analysis,

Retrospective evaluation of the effects of changing socio-

economic boundary conditions on development and current state

of natural resources in Southern Tunisia.

Bouajila Essifi

Eremology & Combating Desertification Lab.

Institut des Regions Arides (IRA)

Medenine 4119 – Tunisia

Email: essifib@gmail.com

THANK YOU