OPTIMA

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OPTIMA Optimization for Sustainable Water
Resources Management Kick-off Meeting, Malta
October 2004 Lebanon Partner 8 WP 5 Land use
change Remote Sensing GIS data National Center
for Remote Sensing M. Khawlie
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OPTIMA Kick-off Meeting/ Malta 2004

• The capacity for human organisms to alter their
  environment, including water resources, covers
  the potential for self destruction.
• Human existence depends on a multitude of
  natural resources which in turn can be negatively
  impacted by human actions.
• Since Land cover is related to land use thus,
  increasing the stresses due to human populations
  may lead, if not properly managed to an imbalance
  in water resources.

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OPTIMA Kick-off Meeting/ Malta 2004

• Thus, the spatial distribution of land use/ land
  cover information and its changes is desirable
  for any planning, management and monitoring
  programs for water resources.
• Planning means the assessment of future and
  making provisions for it.
• Therefore, to ensure sustainable development
  with availability of water there is a necessity
  to monitor ongoing changes in LUC pattern over a
  period of time.
• Remote sensing techniques along with GIS play a
  vital role in building the desired LUC change
  model and relevant water resources needs.

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OPTIMA Kick-off Meeting/ Malta 2004
Causes of Land use change/degradation
Anthropic
Natural (Climate)

• Increase in population rate
• (2 between 1963 and 1990 )
• Immigration towards civilized areas
• (about 80 of population in the coastal, urban
  region)
• Neglecting agricultural areas
• ( from1600km2 to 1030km2 between 1963 and 1990)
• Excess use of natural resources
• (e.g. water, soil, raw materials,
• forests decrease 305 km2 in 35 years)
• Excess of construction practices
• (e.g. new settlements, roads, dams, etc.)
• Use of new technologies
• (e.g. greenhouses in urban areas, drilling water
  wells in remote areas, etc.)

• Decline in precipitation rate
• (about 950 to 800 mm in 50 years
• This led to an increase in dry lands,
• decrease in irrigated areas, etc.)
• 2. Increase in temperature extremes
• (within 3Cº in 30 years Helps forest fire,
• droughts, desertification, torrents etc. )
• 3. Torrential rainfall
• (Enhances flooding and mass movements, modifying
  drainage systems, etc.)

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OPTIMA Kick-off Meeting/ Malta 2004
Both (Land use change anthropic natural) are
integrated with water resources
Example
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OPTIMA Kick-off Meeting/ Malta 2004
Data requirements

1. Time series data satellite imageries of the
   study area within a period of 15 years would be
   undertaken through the process of change
   detection
2. DEM to ensure the good overlay processing and
   referencing for different data sets
   Ortho-rectification, morphological
   distribution, drainage network extraction
   sub-catchments identifications
3. Ancillary data Topographic maps, water
   management issues, Hydrogeological data climatic
   data, socio-economical information, demographic
   developments, etc..
4. Software Remote sensing, GIS and their related
   extensions and modules

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OPTIMA Kick-off Meeting/ Malta 2004
To apply the LUC Model in water resources, data
must be compiled and standardized
Required data via Remote Sensing and GIS
Direct
Indirect
Through assessing the effect of LUC on water
resources modeling (WRM) and river run-off
modeling (RRM)
Through CORINE Land-Use classification- Level 3
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OPTIMA Kick-off Meeting/ Malta 2004
Direct
Beirut
Time series data ( available at NCRS)
Mediterranean Sea
- Multispectral Landsat (30m) TM image -Two time
series winter and spring (1988)
Qaroun Lake
Study Area
Saida
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OPTIMA Kick-off Meeting/ Malta 2004
Time series data ( available at NCRS)
Mediterranean Sea

• Multispectral SPOT imageries (20m)
• April September images 1994

Study Area
Saida
Tyr
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OPTIMA Kick-off Meeting/ Malta 2004
Time series data ( available at NCRS)

• Two images IRS (5m) and Landsat (30m)
• Pan-sharpened to have better interpretation

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OPTIMA Kick-off Meeting/ Malta 2004
DEM ( available at NCRS)
-Elevation Contour lines (10m)
Altimetric accuracy 3m

• Utilization
• Ortho-rectification
• Drainage network extractions
• Sub-catchments delineation
• Elevation distribution

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CORINE classification
Image classification would be based on the
European CORINE ( CoORdination des INformation
sur lEnvironnement) classification (level 3).
Adapted to the Lebanese standards
The CORINE Land cover nomenclature is a physical
and physiognomic land cover hierarchical
nomenclature, which is strongly related to the
process of image interpretation

• Deductive analysis is required for some classes
  especially classes of level 3
• The aggregation of primitive objects required in
  some cases of spatial organization of landscape
  elements is a subjective process

The spatial unit in CORINE corresponds both
to 1- an area of homogeneous cover ( water,
forest,) 2- an aggregation of small homogeneous
areas representing a land cover structure
Highly related to the extraction level, level
2, level 3, or even level 4
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OPTIMA Kick-off Meeting/ Malta 2004
A spatial unit is attributed to a class not only
on the basis of the satellite imagery, but also
through the use of additional data available for
image-interpreter
Ancillary data essentially comprise -standard
topo maps -old thematic maps (where
available) -statistical information -aerial
photographs
A set of pre-processed images (for example, using
PCA, contrast stretching, filtering, color
composition and NDVI) might be produced and
integrated for LUC mapping and change detection
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OPTIMA Kick-off Meeting/ Malta 2004
Indirect data
Deals with changes of land features and their
effect on water resources. This is to be used in
modeling (WRM) and (RRM)
Important notes in compiling and standardizing
data
1. The study area should be classified into a
number of zones, such as sub-catchments,
clusters, typological zones, etc.
2. Data required will be compiled for each zone
separately
3. Data must be presented on time series for
future scenarios
4. Emphasis should be concentrated on
indicators and scenarios
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OPTIMA Kick-off Meeting/ Malta 2004
Data required
To be integrated in a uniform framework. This is
for easy access to advanced tools of data
analysis, simulation modeling and multi-criteria
decision support system DSS
Treats
1. River basin objects
2. Meteorological data
3. Hydrological data
4. Water quality and economic data
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OPTIMA Kick-off Meeting/ Malta 2004
1. River basin objects
RS GIS
GIS
1. Supply Objects
River nodes
Gauging station, major confluences, major
diversions, dams, lakes
Springs nodes
Location of major springs
Man-made nodes
Water wells, tanks, reservoirs
Aquifers and Sub-catchment
Areal extent of aquifers and sub-basins
2. Demand Objects
Cities/villages
Areal extent of urban settlements
Agricultural areas
Areal extent of irrigated lands
Industrial areas
Areal extent of industrial areas
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Water Nodes and Areas in Abou Ali River Basin,
Lebanon
OPTIMA Kick-off Meeting/ Malta 2004
Example
Node Definition Abbreviation Local name Description
Gauging stations Control nodes along the river network, used for calibration G1 Abou Samra Liminographs with weekly measures. Rehabilitated in 1998
Gauging stations Control nodes along the river network, used for calibration G2 Rachaeen Liminographs with weekly measures. Rehabilitated in 1998
Gauging stations Control nodes along the river network, used for calibration G3 Daraya-Kafer Zeghab Non-operational station (Liminograph)
Gauging stations Control nodes along the river network, used for calibration G4 Kousba Liminographs with weekly measures. Rehabilitated in 1998
Gauging stations Control nodes along the river network, used for calibration G5 Houeit-Marh Liminographs with weekly measures. Rehabilitated in 1998
Major confluences Conjunction between a tributary and the primary water course C1 Tahoun Ed-Deir Permanent water courses
Major confluences Conjunction between a tributary and the primary water course C2 El-Mikhada Permanent water courses
Major confluences Conjunction between a tributary and the primary water course C3 Ain Stanboul Intermittent streams
Major confluences Conjunction between a tributary and the primary water course C4 Mazraat En-Naher Permanent water course
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OPTIMA Kick-off Meeting/ Malta 2004
Example from Abou-Ali River basin, Lebanon
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OPTIMA Kick-off Meeting/ Malta 2004
2. Meteorological and 3. Hydrological Data
Must be on a time-series

• Hydrological properties of running water in
  rivers
• Hydrological properties of issuing water from
  springs
• Volume of precipitated and evapotranspirated water

• Precipitation
• Evapotranspiration
• Supplementary climatic data (e.g. temperature,
  humidity, wind velocity, etc. )

Can be done by RS
Partially achieved by RS
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OPTIMA Kick-off Meeting/ Malta 2004
Calculating the volume of water in the form of
snow
Example

Mediterranean Sea
Beirut

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OPTIMA Kick-off Meeting/ Malta 2004
Example
Delineating catchment areas
Mediterranean Sea
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OPTIMA Kick-off Meeting/ Malta 2004
No RS involvement
4. Water Quality and Economic data
  It deals with water prices LUC impact, which
reflects services, distribution costs and
environmental costs.
It deals with water quality, with special
emphasis on rivers, springs, aquifers as well as
drinking water
Water quality Cl, SO4--, CO3--, HCO3-, F,
Cu, SiO2, TDS, etc..
Economic data Water price for domestic,
agricultural, industrial, tourism, etc
Water consumption for
domestic, agricultural, industrial, etc
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OPTIMA Kick-off Meeting/ Malta 2004
The Land use change model
Land use change model is a dynamic model that
afford to space, time and system attributes.

• LUC change model would be based on
• A set of space organized into discrete areal
  units ( land use classes based on CORINE
  classification)
• Transition rules which are the real driving
  forces behind the model dynamics
• Functions which serve as the algorithms that
  code real-world behavior into the artificial
  raster world
• Time or temporal resolution that maintain the
  uniform application for the transitional rules

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OPTIMA Kick-off Meeting/ Malta 2004
Variables/ Driving forces
Variables would be introduced in a GIS format to
implement the LUC change model

• Urban growth rate
• Climatic data
• Estimates dynamic water budget, supply/demand,
  reliability of supply
• Integrated master land use planning
• National environmental policies, programs
  regulations

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OPTIMA Kick-off Meeting/ Malta 2004
Model Examples
- Transition probability where the rows of the
matrix sum up to one and the diagonal cells
represent the probability of no change - Map
Algebra ( Rules, Conditions, operator and
functions) If condition AND/OR condition Then
P(n,m) Change-Operator Value Condition
TRUE/FALSE, FRACTION, FREQUENCY
LAST Operators REL-DECREASE, REL-INCREASE,
ABS.etc Functions FRACTION (N,i), FREQUENCY
(N,i), LAST (i) Example If FRACTION (1.1,2)
gt 500 p(1.1) RE-INCREASE 500 If more than half
the immediate neighbors in a 5x5 area around a
cell are city (1.1), then the probability of
transition increase by 50
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OPTIMA Kick-off Meeting/ Malta 2004
Documentation / Meta-data
A documentation catalogues that include
information about the content, representation,
extent ( both geometric and temporal ), spatial
reference system, quality and administration of
the datasets
Example Identification Title, area covered,
themes, restrictions Data quality Accuracy,
completeness, logical consistency,
lineage Spatial data organization Vector, raster,
type of elements, number Spatial
reference Projection, grid system, datum,
coordinate system Entity and attribute
information Features, attributes, attribute
values Meta-data reference Author, date
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OPTIMA Kick-off Meeting/ Malta 2004
Publication, implementation and user interface
(web access)
A- GIS data
1- LUC map for different time series 2- Drainage
networks 3- DEM / TIN 4- Anthropic map (showing
urban settlements, road network, etc..)
B- RS data
1- Different imageries utilized in the LUC 2-
Derived data (NDVI, PCA, etc)
C- Model implementation
scenario selector that access available cases,
compromising the following parts 1- the region
(initially, start time initial conditions, time
horizon) 2- the development scenario ( transition
probabilities and rules) 3- initial conditions
and time frame
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Thank you