DIS4ME DIS4ME βασική σελίδα | DESERTLINKS βασική σελίδα | © DESERTLINKS 2004
English-EN | Español-ES | Italiano-I | Ελληνικά-GR | Portuguese-PT
Σύστημα Δεικτών Ερημοποίησης για την Μεσογειακή Ευρώπη
leftmenu_gr


Indicators that are relevant at national and Mediterranean-wide spatial scales
DIS4ME editor: Jane Brandt <desertlinks@medalus.demon.co.uk>


Not all indicators are appropriate at all scales. Some are more suitable for local or landscape scales, others for regional, national and Mediterranean scales. Two of the major determinants of the scale at which an indicator is appropriate are the availability of widespread, long term data sets and the possibility of using remote sensing to obtain the data.
g Indicators used at the national scale
g Portugal
g Spain
g Italy
g Greece
g Desertification indicators obtained from remote sensing

g Indicators used at the national scale

When assessing desertification threatened areas and the extent for their National Action Programmes, the Annex IV sub-region Focal Points each used 3 or 4 indexes which they mapped nationally. Most of them also mapped a further set of indicators at the regional scale. Most of the indexes or indicators in these lists are described in DIS4ME (as shown by links to the indicator database), sometimes under a slightly different name.

g Portugal

Mapped at national scale

Climatic Quality Index (= Aridity index (2))

Using the Penman definition where Aridity index = mean annual precipitation /mean annual potential evapotranspiration.
Soil Quality Index/ Index of Soil Susceptibility to Desertification Soil depth, Soil permeability, Soil structural stability Stoniness (instead of Rock fragments for which data is not available), Drainage, Slope gradient.
Vegetation Quality Index Fire risk, Erosion protection, Drought resistance, Vegetation cover, Structural cover, Proximity to climax
These are combined in an Index of Susceptibility to Desertification
Complementary indicators (that have also been mapped at national scale) Economic and social indicators

Population density, Decrease in population (variation on Population growth rate, but assuming linear rate of change), Vitality index (population>= 65 years old / population less than 14 years old) (variation on Old age index), Old age dependants (population>= 65 years / population 15-64 years), Literacy level, Second homes (%), Purchasing power.

Source: Lúcio do Rosário (2004) Indicadores de Desertificação para Portgal Continental. Direcção-Geral dos Recursos Florestais. http://www.dgrf.min-agricultura.pt

5 top

g Spain

National scale

 

 

 

 

Aridity index (2)

Penman definition. Mean annual precipitation /mean annual potential evapotranspiration

Soil loss index
(=Soil erosion (USLE))

Soil erosion as calculated by the USLE T/haˇyears

Drought

% of the normal mean annual precipitation values

Forest and wild fires

% of surface affected by fires in the last 10 years

Aquifer over exploitation

Comparision of pumping to recharge rates

The above indices are combined into a Desertification Index.

5 top

g Italy

Scale 1:1,250,000

Aridity index (2)

Penman definition. Mean annual precipitation /mean annual potential evapotranspiration

Soil characteristics index

Related to the peco-climatic classification of Italy (dependant on soil and its biotic cover)

Land use index

Obtained from CORINE land cover classes

Demographic variation index

% of population variation between 1981 and 1991 at the municipal scale

These are combined in an index of susceptibility to desertification

Scale 1:250,000

Soil texture, Parent material, Soil depth, Slope gradient, Aridity , Fire risk, Erosion protection, Drought resistance, Vegetation cover, Land use intensity, Protection policy

5 top

g Greece

Scale 1:1,000,000

 

 

Soil mapping units

Soil map of Europe. Indicative of the extent of erosion that has taken place, the erosion risk, soil depth and soil drought risk.

Slope gradient

Using the CORINE definition

Bio-climatic index
(=Aridity index (1))

Bagnouls-Gaussen definition, derived from the Bioclimatic Map of Greece. The aridity of each unit was used to estimate soil drought, soil salinity and potential resilience of damaged vegetation cover.

Irrigation intensity and salt water intrusion

Derived from irrigation work and sea water intrusion map and used to estimate secondary salinisation risk of irrigated soils.

Scale 1:50,000

 

Soil texture, Rock fragments, Soil depth , Drainage, Slope gradient, Rainfall, Aridity index, Slope aspect, Fire risk, Erosion protection, Drought resistance, Vegetation cover, Land use type, Land use intensity, Land use policy

5 top

g Desertification indicators obtained from remote sensing

A broad range of potential remote sensing based desertification indicators has been discussed and reviewed, but especially those that refer to the issues and themes identified by stakeholders. Most remote sensing indicators relate to vegetation cover and its changes, but remote sensing can also address issues such as urban sprawl and organic matter content of the top-soil. Preference has been given to those indicators that can be obtained quasi-operationally by remote sensing alone, where the remote sensing component is central in indicator modelling or where we expect an increasing importance of remote sensing in the near future. A further criterion was knowledge of existing major European initiatives addressing an issue, such as in the case of urban sprawl or forest fire.

The table below lists indicators that have the strongest potential to be derived with major contributions from remote sensing. Although the list is short, it should be noted that there are a number of other issues and indicators where remote sensing information may play a role (e.g. grazing, land abandonment etc) in particular applied in combination with geomatics, ecological and socio-economic modelling (as shown in the GeoRange and LADAMER projects). The three final indicators have been added because they have been identified by national Focal Points as being relevant for important target areas in Annex IV countries.

DESERTLINKS indicators with the strongest potential for remote sensing applications

Indicator Measurement / Unit Mediterranean-wide Regional
Vegetation cover rs % green vegetation X (example available) X (example available)
Ecosystem resilience Trends of change of rain use efficiency X (example available) X

Burned area

Ha/spatial unit

X

X (example available)

Fire frequency

No of fires/spatial unit

X

X (example available)

Forest fragmentation

Fragmentation index

X

X

Soil organic matter in surface soil rs

% SOC, experimental

X

Urban sprawl

Ha/year

e.g. coastal zones

X (example available)

Area of cultivated and semi-natural vegetation

Ratio/raster cell
Ratio/spatial unit

X (experimental)

X

Land cover type change

% transition between vegetation/LC classes

X (example available)

Mining waste hazard

% surface abundance of critical waste material per catchment

X (example available)

Grazing pressure

Combined indicator

X

Remote sensing has been used to investigate in what way and to what extent changing energy and water fluxes at the land surface – atmosphere interface are related to the assumed changes in climatic forcing of desertification processes. Advanced techniques have been developed to accurately derive standardised “primary” radiometric variables (e.g. spectral reflectance, albedo, surface temperature, emissivity etc.) and to analyse the temporal behaviour of these variables in terms of changing energy, momentum and mass exchange between land and atmosphere [1] [2]. Instead of the “climatic” approach, DESERTLINKS is aiming more at the identification of changes of physical land surface conditions in terms of vegetation cover and soil status. This approach also requires the correct conversion of radiance registered by the remote sensing sensor into primary physical variables (e.g. reflectance, land surface temperature). Then the information on physical land surface status may be derived both from remote sensing directly and through integration of remotely sensed information with data from other sources. In particular this may be achieved within a complex modelling framework such as the Regional Degradation Index models for Mediterranean wide risk of water erosion and salinisation.

The requirement for Regional Indicators is that they should be applied to the entire Mediterranean basin at full coverage, giving a general overview at coarse scale in order to identify areas where more detailed studies should be performed. They should also have the potential to be regularly up-dated for monitoring purposes. This implies that at this scale only the use of a coarse resolution/high revisit rate (1 to 3 days) remote sensing system such as NOAA-AVHRR (1 to 8 km resolution), SPOT VEGETATION (1 km), TERRA-MODIS (0.25 to 1 km) or MERIS (0.3 to 1 km) are realistic options. Although, compared to the other systems, NOAA-AVHRR has a number of shortcomings in radiometric and geometric accuracy, it is still a central element in the indicator development and understanding of desertification processes. This because it is the only system having 20 years history of operation and thus it is crucial to building the backbone of the necessary long term, multi-temporal analyses and base-lines. Newer systems, nevertheless, assure continuity with the NOAA satellite data, and will allow definite improvements to geo-referencing in relation to ground information, and extended possibilities for deriving information on vegetation and soil status.

As regards validation and calibration of regional scale indicators remote sensing offers a strong potential for down-scaling from regional scale to target areas by disaggregation of vegetation cover related information with the help of higher resolution remote sensing data such as Landsat-TM and/or higher resolution thematic data e.g. CORINE land cover. In particular, the approach to derive fractional vegetation cover at different scales on the basis of spectral mixture analysis (SMA) has shown that vegetation cover has a fractal dimension which allows its comparison at different scales. Although the dominant factors (controlling e.g. patterns of vegetation) change at the different scales, the scientific rationale for comparison could be given by applying concepts of ecosystem resilience during given time periods, which are covered both by available coarse resolution and high resolution satellite data over the DESERTLINKS target areas.

References

[1] Bolle, H.J., 1996: The Role of Remote Sensing in Understanding and Controlling Land Degradation and Desertification Processes: The EFEDA Research Strategy. In: The use of remote sensing for land degradation and desertification monitoring in the Mediterranean basin. EUR 16732 EN, Eds. J. Hill and D. Peter, pp45-78.
[2]
RESMEDES 1998: Remote Sensing of Mediterranean desertification and environmental changes (Resmedes). Final report ENV4-CT95-0094, EUR 18352 EN, Luxembourg. Office for Official Publications of the European Communities ISBN 92-827-4040-4, 39 p.

5 top