pluvial Sensing has made substantial contribution in

pluvial
flood and coastal flood.

 Due to
anthropogenic activities and climatic variability, floods have been raised
lately in several regions worldwide. The resulting impact of floods on
environment is often harmful. This is particularly applicable to under
developed countries like Pakistan, the country which is known for dry climatic
conditions, and it became known region for such natural hazards and calamities (A  shakeel et al 2014)

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 Remote Sensing has made substantial
contribution in flood monitoring and damage assessment that leads the disaster
management authorities to contribute significantly High temporal resolution
played a major role in Remote Sensing data for flood monitoring to encounter
the cloud cover.(M Haq et all 2012).

The
causes of these floods are related to a number of factors which play as a major
contribution to the worsening of the flood disaster. These factors were
classified into the following: geomorphological features, anthropogenic
activities (urban changes), network and catchment factors, and rainfall and
climatic changes factors. The climatic changes have a major impact on the
rainfall intensity and will appear more in the future (A Youssef et all 2015).

Accurate
and current floodplain maps can be the most valuable tools for avoiding severe
social and economic losses from floods. Accurately updated floodplain maps also
improve public safety. Early identification of flood-prone properties during
emergencies allows public safety organizations to establish warning and
evacuation priorities. Armed with definitive information, government agencies
can initiate corrective and remedial efforts before disaster strikes (Chapman
and Canaan, 2001).

 Flash flood in the cities led to high levels
of water in the streets and roads, causing many

problems
such as bridge collapse, building damage and traffic problems. It is impossible
to avoid

risks
of floods or prevent their occurrence, however it is plausible to work on the
reduction of their

effects
and to reduce the losses which they may cause. Flash flood mapping to identify
sites in high risk flood zones is one of the powerful tools for this purpose.
Mapping flash flood will be beneficial to urban and infrastructure planners,
risk managers and disaster response or emergency services during extreme and
intense rainfall events (Ismail Elkhrachy 2015).

River
valley human settlements will be most effected by floods due to dependence of
water source and physical and social works. One effected floods will distribute
life fabric for five to ten years. This in turn changes migration pattern and
relocation. Advances in remote sensing technology and new satellite platforms
such as ALOS (Advanced Land Observation Satellite) sensors widened the
application of satellite data. One of the many fields that these technologies
can be applied is to validate flood inundation models. For a long time flood
extent from flood inundation models were validated using the ground truth
surveys which was not very much reliable (M Sathish et all 2012).

 

The
floods are affecting the Pakistan from time to time since 1928 especially
during the monsoon period between July and September. In 2014, the heavy
rainfall in the first week of September caused flooding in Pakistan provinces
of Azad Kashmir, Punjab, Gilgit- Baltistan, Khyber Pakhtunkhwa and later on
Sindh province. About 367 people died in the catastrophe. Over 2.5 million
people were affected by the flood event (Davir R 2014).

Using
GIS and remote sensing technique, it is made possible to accurately delineate
flooded areas, flood-hazard areas and suitable areas for flood shelter in order
to minimize impacts (Uddin k et all 2013).

Bad
weather conditions during and after flood events can represent a strong
constraint to the utilization of optical remotely sensed data. For this reason,
optical sensors are generally used to assess inundated fields only some days
after the event, either by recognition of fluvial sediments left on the land
(Rosso 1995) or by the detection of vegetation stress (Michener and Houhoulis
1997).

If
radar images are acquired some days after the event, when only a few areas are
still submerged by water, it is advisable to use a multi-sensor approach. In
this case flooded areas as derived from radar data are complemented with
information extracted from optical images, such as the areal extent of material
left during the flood (ImhoV et al. 1987).

In the age of modern technology, the integration of information
extracted through Geographical Information System (GIS) and Remote Sensing (RS)
with other datasets provides tremendous potential for identification,
monitoring and assessment of flood disaster (Pradhan et al., 2009; Pradhan and Shafie.2009