386
M. Ahmed and V. Barale
purposes. Land reclamation rates range from less than 1 km
2 /year, in Lake Bardawil,
to 2–3 km
2 /year, in Lake Edku and Lake Burullus, and up to 7–8 km
2 /year, in certain parts of Lake Manzala (Flower et al. 2009). Untreated domestic, industrial and
agricultural wastes are dumped into the Nile delta drainage system, which in turn
discharges locally into the lagoons (Oczkowski et al. 2011). The degree of pollution
varies from high in the eastern part of Lake Maryut and in the southern eastern part of
Lake Manzala, to minor in Lake Burullus (Saad et al. 1981; Siegel et al. 1994). The
high concentrations of nutrients in organic waste, together with the accumulation
of pesticides and heavy metals in the water and sediments, have already altered the
lagoons’ ecosystem profoundly. The increase of nutrients load, in particular, has lead
to overgrowth of macrophytes, plants that have adapted to aquatic environments in
either freshwater or saltwater, and to widespread eutrophication.
19.3 RS and GIS Applications
Satellite data from several different sources have been used, by a number of studies
to be reviewed here, for repeated observations of the coastal lagoons of northern
Egypt. These include data originated by the Landsat Multi Spectral Scanner (MSS),
Thematic Mapper
TM and Enhanced Thematic Mapper Plus (ETM+ ); the Système
Pour l’Observation de la Terre (SPOT); and EgyptSat −1. The Landsat sensors—i.e.
the MSS, TM and ETM+ (see e.g. Markham et al. 2004 and reference therein)—
have been the workhorse of land-oriented RS for 4 decades, offering observations in
a wide visible and infrared spectral range, with a relatively high spatial resolution
(from about 80 m to 30 m and 15 m, in the visible and panchromatic bands, for the
successive versions of the instruments) that allows precision mapping in space, and
with a temporal resolution (16 days) that allows systematic monitoring over time,
when the local climate is good enough to ensure repeated cloud-free conditions.
The series of SPOT sensors—i.e. the High-Resolution Visible (HRV), on SPOT-2/3,
High-Resolution Visible-Infrared (HRV-IR), on SPOT-4, and the High Resolution
Geometry (HRG), on SPOT-5 (see e.g. Clark et al. 2010, and references therein)—
has also privileged visible and near-infrared observations, in both panchromatic
and spectral modes, with high spatial resolution (20 m, and 10 m in panchromatic
mode, originally, and then 10 m, and 5 m in panchromatic mode) and specific tasking
capabilities. Finally, EgyptSat-1 was the first in a series of orbital sensors planned
in Egypt, jointly built by Egypt’s National Authority for Remote Sensing and Space
Sciences together with the Yuzhnoye Design Bureau of Ukraine (see e.g. Elshehaby
and Taha 2010, and references therein). The sensor provided data in the visible (green
and red bands) and near infrared, with 7.8 m spatial resolution and a 50 days revisit
cycle.An additional band was also available in the mid-infrared, but at a coarser
spatial resolution (∼40 m).
In general, the processing of RS data includes image registration and referencing to a common coordinate system, nearest-neighbor resampling and compositing
(when required), as well as image classification, based on a supervised or unsupervised approach (see e.g. Ahmed et al. 2009). When the observations address
M. Ahmed and V. Barale
purposes. Land reclamation rates range from less than 1 km
2 /year, in Lake Bardawil,
to 2–3 km
2 /year, in Lake Edku and Lake Burullus, and up to 7–8 km
2 /year, in certain parts of Lake Manzala (Flower et al. 2009). Untreated domestic, industrial and
agricultural wastes are dumped into the Nile delta drainage system, which in turn
discharges locally into the lagoons (Oczkowski et al. 2011). The degree of pollution
varies from high in the eastern part of Lake Maryut and in the southern eastern part of
Lake Manzala, to minor in Lake Burullus (Saad et al. 1981; Siegel et al. 1994). The
high concentrations of nutrients in organic waste, together with the accumulation
of pesticides and heavy metals in the water and sediments, have already altered the
lagoons’ ecosystem profoundly. The increase of nutrients load, in particular, has lead
to overgrowth of macrophytes, plants that have adapted to aquatic environments in
either freshwater or saltwater, and to widespread eutrophication.
19.3 RS and GIS Applications
Satellite data from several different sources have been used, by a number of studies
to be reviewed here, for repeated observations of the coastal lagoons of northern
Egypt. These include data originated by the Landsat Multi Spectral Scanner (MSS),
Thematic Mapper
TM and Enhanced Thematic Mapper Plus (ETM+ ); the Système
Pour l’Observation de la Terre (SPOT); and EgyptSat −1. The Landsat sensors—i.e.
the MSS, TM and ETM+ (see e.g. Markham et al. 2004 and reference therein)—
have been the workhorse of land-oriented RS for 4 decades, offering observations in
a wide visible and infrared spectral range, with a relatively high spatial resolution
(from about 80 m to 30 m and 15 m, in the visible and panchromatic bands, for the
successive versions of the instruments) that allows precision mapping in space, and
with a temporal resolution (16 days) that allows systematic monitoring over time,
when the local climate is good enough to ensure repeated cloud-free conditions.
The series of SPOT sensors—i.e. the High-Resolution Visible (HRV), on SPOT-2/3,
High-Resolution Visible-Infrared (HRV-IR), on SPOT-4, and the High Resolution
Geometry (HRG), on SPOT-5 (see e.g. Clark et al. 2010, and references therein)—
has also privileged visible and near-infrared observations, in both panchromatic
and spectral modes, with high spatial resolution (20 m, and 10 m in panchromatic
mode, originally, and then 10 m, and 5 m in panchromatic mode) and specific tasking
capabilities. Finally, EgyptSat-1 was the first in a series of orbital sensors planned
in Egypt, jointly built by Egypt’s National Authority for Remote Sensing and Space
Sciences together with the Yuzhnoye Design Bureau of Ukraine (see e.g. Elshehaby
and Taha 2010, and references therein). The sensor provided data in the visible (green
and red bands) and near infrared, with 7.8 m spatial resolution and a 50 days revisit
cycle.An additional band was also available in the mid-infrared, but at a coarser
spatial resolution (∼40 m).
In general, the processing of RS data includes image registration and referencing to a common coordinate system, nearest-neighbor resampling and compositing
(when required), as well as image classification, based on a supervised or unsupervised approach (see e.g. Ahmed et al. 2009). When the observations address