integrated space technologies for natural hazards ... · - presentation of crts - desertification...

Integrated space technologies for natural hazards monitoring in for natural hazards monitoring in

Morocco

Istanbul, Turkish

15 September, 2010

Noureddine BIJABER

Natural Resources and Environment DepartmentRoyal Centre for Remote Sensing

Rabat, MOROCCO

CONTENTS

- Presentation of CRTS

- Desertification monitoring in Morocco

- Drought monitoring (RS & GIS)- Drought monitoring (RS & GIS)

- Forest fires monitoring

The Royal Center for Remote The Royal Center for Remote Sensing (CRTS)Sensing (CRTS)

Is the national institution responsible for :

- Development of capabilities at the national level

- Coordination and execution of the national program of RS

- Provision of technical advisory services and space information

- provision of training and education opportunities in Space technologies and carrying out reseach actions and programs

Operational applications to support strategic decisions

To support ministerial departments in various fields :

---- Agricultural statistics and production forecastingAgricultural statistics and production forecastingAgricultural statistics and production forecastingAgricultural statistics and production forecasting

---- Water resources managementWater resources managementWater resources managementWater resources management

---- Forest and pastoral resources assessmentForest and pastoral resources assessmentForest and pastoral resources assessmentForest and pastoral resources assessment

---- Urban and land managementUrban and land managementUrban and land managementUrban and land management

---- Space cartography and Space cartography and Space cartography and Space cartography and

geomaticsgeomaticsgeomaticsgeomatics

4

geomaticsgeomaticsgeomaticsgeomatics

---- Environment and hazardsEnvironment and hazardsEnvironment and hazardsEnvironment and hazards

---- Geological applicationsGeological applicationsGeological applicationsGeological applications

---- Oceanography, climate and Oceanography, climate and Oceanography, climate and Oceanography, climate and

marine resourcesmarine resourcesmarine resourcesmarine resources

CONTENTS





Desertification

in Morocco

Deforestation :31.000 ha/year

Degradation of rangelands: 8 M haDegradation of rangelands: 8 M ha

Overgrazing exceeding23% of the capacity of natural rangelands

Salinity :37.000 haof irrigated areas

Erosion by water :2/3of agricultural areas exposed

Contribution of Remote Sensing and GIS

Satellite data and GIS offer key tools for desertification monitoring at Satellite data and GIS offer key tools for desertification monitoring at

two levels :

- A local monitoring by using high resolution data allowing a specific

management and development of models to extrapolate results to

other sites

- A national monitoring (low resolution data) allowing to reply to national - A national monitoring (low resolution data) allowing to reply to national

plan objectives

Desertification monitoring at two levels

Macro geographic study Meso geographic study

Low resolution data

Macrogeographic indicators

Change maps

High resolution data

Mesogeographic indicators

Change mapsChange maps

NOAA/AVHRR imagery NDVI

Macrogeographic Indicators

Methodology

AlbedoST

θ

∆Ts

∆NDVI NDVI

Ts

March

July

March July

Since 1996

Slope : Arctangent (θ = ∆Ts/∆NDVI), and Module : (∆Ts & ∆NDVI)


NDVI

V

θ

∆NDVI

March

July

Vector

Land

Cover

Dynamic

22

100

1)T_CNT_CN()NDVI_CNNDVI_CN(Module max_NDVI

smax

smax_Tsmax −+−=

)NDVI_CNNDVI_CN

T_CNT_CNarctan(Pente

maxmax_Ts

max_NDVIs

maxs

−−

×π

= 180

∆ST ST

Ref. : Sobrino & Raissouni (2000 & 2001) on Morocco and on the Mediterranean basin

Le module


Slope map (1996) Module map

1997/1996

Change maps

2000/19962001/19962002/19962002/1996

Classes of land Classes of land use degradation

Stable

Classes of land use recovering

Synthetic map of sensible areas

Macro geographic study Meso geographic study

Desertification monitoring at two levels

Low resolution data

Macrogeographic indicators

Change maps

High resolution data

Mesogeographic indicators

Change maps

Studied zone

Series of satellite images (Landsat-TM, Spot-Series of satellite images (Landsat-TM, Spot-

XS, ASTER, 1986 - 2003)

Other data (field measurements, meteo data,

topographic maps,…)

Land cover Map

Land cover changes detection

1986

2003

Evolution of water areas19862003

Thematic data

Demographic evolution

Years

1996 1997 1998 1999 2000 2001 2002

CONTENTS





Objective

Elaboration of a drought early warning system based on environmental indicators

calculated from satellite data

Calculate of Indicators and drought early warning,

Methodology / Main steps

� Biophysical parameters extraction from satellite data (NOAA/AVHRR) since1999

� Calculate of drought monitoring indicators from satellite data:� Standardized Vegetation Index (SVI),� Vegetation Condition Index (VCI),� Temperature Condition Index (TCI)� Temperature Condition Index (TCI)� Vegetation Health (VH)

� Calculate of thematic indicators (meteorological, agronomic and forests)

� Bulletin edition

Vegetation Condition Index (results)

VCIOct. 2009

VCINov. 2009

VCIDec. 2009

VCI = (NDVIi – NDVImin) / (NDVImax – NDVImin) * 100Ref. : Felix N. Kogan, 2000

VCIJanv. 2010

VCIFeb. 2010

VCIApr. 2010Janv. 2010 Feb. 2010 Apr. 2010

Between 40 & 60%

Legend

Near to minimal (< 20%)

Between 20 & 40%

Between 60 & 80%

Near to maximal

Clouds (or snow)

TCIOct. 2009

TCINov. 2009

TCIDec. 2009

Temperature Condition Index (results)TCI = (BTmax – BTi) / (Btmax–BTmin) * 100

Ref. : Felix N. Kogan, 2000

TCIJanv. 2010

TCIFeb. 2010

TCIMar. 2010Janv. 2010 Feb. 2010 Mar. 2010

Between 40 & 60%

Legend


Between 20 & 40%

Between 60 & 80%

Near to maximal

Clouds (or snow)

Indicators (results)

VCI TCI

Legend


VH < 40% stress(Kogan)

VH = 0,5 VCI + 0,5 TCIDecade3, April 2010

Between 40 & 60%

Between 20 & 40%

Between 60 & 80%

Near to maximal

Clouds (or snow)

SVI

April 2010

Standardized Vegetation Index (results)

April 2010

Decade3

Legend

SVI = (NDVIi – NDVIm) / σσσσ

Ref. : Felix N. Kogan, 2000

Très favorable (0.975 – 1)

LegendTrès défavorable (< 0.025)

Défavorable (0.025 – 0.25)

Normale (0.25 – 0.75)

Favorable (0.75 – 0.975)

Nuages (ou neige)

Integration of thematic dataMaps of meteorological indicator

Standardized Precipitation Index (SPI) “Percent of Normal”

Ref. : DMN Morocco

Map of ploughed fields situation

(December 08) compared to the last ten years mean

Integration of thematic dataMaps of agronomic indicator

Map of cereal seedling situation (wheat and

barley) compared to the last ten years meanto the last ten years mean last ten years mean

Ref. : MADRPM Morocco

Drought warning bulletin

Period : from November to April every year

CONTENTS





Moroccan forest

9 M ha, 12 % NTDiversity / bioclimat

- Aridity of Moroccan climate

- Degradation >30.000 ha/y

� exploitation� overgrazing

Constraints :

� overgrazing� feeling� forest fires� urbanization� drought� forest health

Forest fires in Morocco

�� > 75% of burned areas is located in the Rif Region (North)

�� July-August : is the risky period

�� > 90% of forest fires are caused by human activities

Remote Sensing to monitor forest fires

�� Forest fires risk mapping at national scale

�� Hot Spot localization

�� Burned areas mapping

Risk index module

ct·bt·a(t)NDVI 2 ++=

NDVI

Vegetation regression index

NDVITS

Vegetation drought index

NDVI estimé

NDVI réel

Temps

LST

nNDVIm += ·T s

LST

NDVI

Forest fires risk : k1*VRI + k2*VDI

Very high risk

High riskModerate risk

Low risk

No risk

Deux feux, de 200 et de 60 ha, survenus le Deux feux, de 200 et de 60 ha, survenus le Deux feux, de 200 et de 60 ha, survenus le Deux feux, de 200 et de 60 ha, survenus le 18/08 18/08 18/08 18/08 dans la dans la dans la dans la zone de Chefchaoun.zone de Chefchaoun.zone de Chefchaoun.zone de Chefchaoun.

Hot Spot

Feu de 1130 ha, survenu dans la zone de Sefrou, le 01/08/2003.

Espèces Area (ha)

Chêne liége 761,404

Chêne Vert 6,624

Feuillés 118,869

Matorral 142,127Matorral 142,127

Reboisements

feuillus 6,999

Reboisements

Résineux 2717,074

Terrains non

Boisés 67,36

Total 3820,457

CONCLUSION

- The presented projects were realized in the objective to develop amethodology to monitor changes in arid ecosystems and productionof documents to help end users.

- Natural hazards (desertification, CC, diseases, ..) are a complexphenomenon (large extend) and result from interaction between

of documents to help end users.

- However,The maps & indicators produced can’t stop natural resourcesdegradation if there is no goodwill to strengthen collaborationbetween institutions at different levels.

phenomenon (large extend) and result from interaction betweenseveral parameters. And it is very difficult to study & monitor thisphenomenon without a global observation of the affected areas.

- Remote sensing and GIS combined to ground data are operational fornatural hazards monitoring at different levels.

Noureddine BIJABER

Natural Resources and Environment DepartmentRoyal Centre for Remote Sensing

Rabat, [email protected]

www.crts.gov.ma

integrated space technologies for natural hazards ... · - presentation of crts - desertification...

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