- The student critiques their group project which aimed to plan wetland habitat complexes in Sandwich Bay, UK. - They fulfilled project objectives but could have done more fieldwork and GIS/CAD work by splitting into smaller groups. - The student proposes an improved methodology including using updated habitat data to refine their site suitability model, focusing fieldwork on priority areas, and splitting tasks between groups to increase outputs.

1. Student: Vincenzo Iannuzziello ID : 000815098
GEOG1029 Individual Project Report
STUDY AREA: SANDWICH AND PEGWELL BAY, KENT

2. A critique of the group project, including a consideration of alternative approaches
The aim of the project is to plan the creation of complexes of ponds providing additional
wetland habitat in order to support wildlife’s and flora’s natural colonisation and habitat
adaptation within Sandwich Bay Special Area of Conservation (SAC) and neighbouring
areas, including the Pegwell Bay Country Park.
Looking at the objectives listed in our proposal I suppose that we have fulfilled (even though
not entirely in the content) all of them:
1. To select potential locations following recommended criteria – by building a model with
ModelBuilder in ArcMap for the identification of potential suitable areas according to our
purpose.
2. To investigate the accessibility and visibility of the short-listed areas – by ground
validation and adopting, to the area chosen as suitable location, two methodologies of
visibility analysis (Line of Sight and Viewshed). However the visibility analysis was carried
out on one single final location chosen only.
3. To model the ponds’ structure following recommended criteria – by designing the structure
of our ponds (3D modeling with AutoCAD 2015).
4. To compile the pond creation action plan and habitat development regulations – by
providing specifications about criteria of pond location/creation and management/monitoring.
We also followed the initially proposed methodology according to the criteria defined in our
proposal. In general, the result of our work approximately met the initial expectations. After
running the model we had our study area significantly restricted in terms of square meters,
facilitating our mission on the field by reducing the areas to visit for ground validation and
points recording. However, the greatest limitation was the Land Cover 2007 which we added
into the model to identify improved and rough grassland and exclude all other areas. In fact,
in some of the identified areas the land use has changed since 2007 as we found agricultural
fields rather than grassland during the field survey.
Overall, the activity at Sandwich Bay was intense and, even if not well coordinated actions
were taken from the beginning by our group, the result was quite satisfactory. However, in
my opinion we could have produced more work (both GIS and CAD) and do more field
activity. To save time and use it to develop more results I would have split our group into two
smaller groups of two people each and organized the activities as follow in the timetable
(next page).

3. PRESUMED TIME TABLE
09:00 – 12:00 14:00 – 18:00 19:00 – 23:00
Field
survey
GIS/CAD
work
Field
survey
GIS/CAD
work
GIS achieved
result
CAD
achieved
result
Monday
(day 1)
Group 1
(points
recording
Pegwell)
Group 2
(Building
Model)
Group 2
(points
recording
Sandwich)
Group 1
(Building
Model)
Potential
areas
identified
X
Tuesday
(day 2)
Group 1&2
(ground
validation)
X
Group 1&2
(ground
validation)
X
Locations
chosen
X
Wednesday
(day 3)
Group 1&2
(tracking
ponds'
boundary)
X
Group 1&2
(tracking
ponds'
boundary)
X
Working on
visibility
analysis
Working on
3D
Modeling
Thursday
(day 4)
X
Group 1&2
(visibility
analysis)
X
Group 1&2
(3D
modelling)
Line of Sight
and Viewshed
analysis
3D Model of
the ponds
Friday
(day 5)
X
Working on
Presentation
X Presentation X X
On day 1, Group 1 would have been doing some field survey in Pegwell Bay, where the
ground is hillier. The points recorded in Pegwell Bay were useful to compare, with those
recorded in Sandwich Bay, the Lidar's elevation accuracy with the GPS elevation, as we
showed during our presentation, even though there was a mistake in the Sandwich field graph
image (the correct graphs in figures below).
LIDAR VS GPS ELEVATION

4. In my opinion, on day 1 we should have prioritised our work on the identification of
potential areas by concentrating majority of our efforts building the model (possibly using
more recent sources), as soon as possible, in order to reduce the study area and start our field
activity. To obtain a more recent and reliable result, I would have georeferenced the Habitat
Map 2012 (we received it from Kent & Medway Biological Records Centre) and digitized the
improved grassland areas only (figure below).

5. The new model would look like (figure below)
At that point, after converted to raster and reclassified, I would have added that layer to the
Weighted Overlay function rather than the reclassified Land Cover 2007 layer. The result
would have been quite different, as the model would have excluded all those areas in the
North-West of the map and in the Centre (Figures below).
REPLACED LAYER`
FLOW DIAGRAM: IDENTIFICATION OF POTENTIAL AREAS

6. Thus, as the new model indicates that the identified areas are mostly located in the South
(figure above), we could have focused our efforts there and spent more time on the field,
surveying those areas. I would keep the slope layer and the rest of the layers added into the
model with the same parameters, applying the same buffer as we did during the fieldcourse:
• Proximity_to_Populated_Areas - 350m buffer to buildings.shp, in order to consider
only those areas at least 350m from buildings. In India, facultative ponds are situated
no less than 450 meters away from vast populated areas, and in USA 0.5-1Km of
minimum distance is recommended (Shrivastava 2004).
We chose 350m because there are not large residential areas within our study area, but
still we wanted to keep our presumed pond/s far from buildings (even small
complexes of houses).
• Proximity_to_Railway - 50m buffer to railway.shp, in order to consider only those
areas at least 50m away from railways. Proximity to railways should not be injurious
to our presumed pond/s, however we decided to include a safe distance at least to
keep lower the annoying noise of transiting trains.
• Proximity_to_Main_Roads - 650m buffer to main_roads.shp, in order to consider only
those areas at least 650m away from main roads. According to an article published on
internet (Nature et Progrès), ponds should be situated at a minimum distance of 500m
from main roads and must be free from air pollution, industrial fumes, chemical
substances and pesticides.
• Proximity_to_Surface_Water – 30m buffer to surface_water.shp, in order to consider
only those areas at least 30m from surface water.
• Proximity_to_Tidal_Water – 30m buffer to tidal_water.shp, in order to consider only
those areas at least 30m away from tidal water.
As we did not find any scientific reason to allocate our pond at a specific distance
from other water sources (we knew that it should not be linked to any other water
source, but not minimum distance from them are specified), based on our knowledge
we assumed that a distance of 30 metres would be enough to eliminate any water
contamination.
However I would change the range of the values within each layer. The new classes would
get values from 0 to 7 rather than 0 to 5 (during the process we added two more layers into
the model without increasing the values' range according to the number of layers).

7. The new layers would get the following values (table below):
LAYER NAME WEIGHT CLASSES
NEW SCALE
VALUE
1
IMPROVED
GRASSLAND
22%
IMROVED GRASSLAND
OTHER
NO DATA
7
0
NO DATA
2 SLOPE 13%
0 – 2 (degrees)
2 – 5 (degrees)
> 5 (degrees)
NO DATA
7
5
0
NO DATA
3
PROXIMITY TO
POPULATED AREAS
13%
ALL
NO DATA
0
7
4
PROXIMITY TO
RAILWAY
13%
ALL
NO DATA
0
7
5
PROXIMITY TO MAIN
ROADS
13%
ALL
NO DATA
0
7
6
PROXIMITY TO
SURFACE WATER
13%
ALL
NO DATA
0
7
7
PROXIMITY TO TIDAL
WATER
13%
ALL
NO DATA
0
7
With the reclassify function, in the layers which the buffer was applied to, all classes get 0 as
value and NO DATA gets the highest score, meaning that the model will exclude all those
areas where data exist (including the specific buffer distance given). Thus, the model will
show up only those areas where data do not exist, in order to eliminate the chance to get the
potential areas result within populated areas, railways, main roads, surface water, tidal water
(and within the distance specified by the buffer given). The final result will obviously be the
combination of all the layers according to the weight percentage given to each of them.

8. After building and running the model I would have then exported the output layer of our
potential areas into Google Earth (by converting the shape file in KML), or georeferenced a
Google Earth image in order to more easily localise our destination on the field (figure
below).
On day 2, I would have recorded one point on each potential area, if possible (it is a surface
of about 150 ha), in order to eventually exclude any non-potential area by ground validation
(we were allowed by the land owner to eventually survey the entire private property). I would
have split the group into two parts again, so two of us could survey on the East side of the
CHOSEN
LOCATION
OUR CHOSEN LOCATION LOOKS LIKE AN AGRICULTURAL LAND EVEN ON A GOOGLE EARTH IMAGE 2013

9. railway and two on the West (if we could access here somehow). In this way we could collect
much more data and choose our location among a wider range of potential areas (perhaps we
could indicate more than one location for our project as we planned in our proposal).
Excluding then by ground validation all those areas in which the land use has changed again
since 2012 we would have had all the areas in which we could potentially operate carrying
out our project.
On day 3, after choosing the most suitable locations (possibly the easiest ones for us to reach
the days to follow) we could have tracked the ponds' boundaries on the field with GPS. With
the points recorded we could have now started the 3D modeling of our ponds with AutoCAD
(exporting the shape files into CAD by DWG conversion) and the visibility analysis for each
of them, before and after creating a barrier of 2m. This analysis is very useful to determine
the visibility of an object or area from observer points. Building a barrier to eliminate
visibility can help protect the habitat from human impact and predators, as we showed in our
presentation (figures below).
VISIBILITY

10. LINE OF SIGHT – NO BARRIER LINE OF SIGHT – WITH BARRIER
FLOW DIAGRAM: LINE OF SIGHT METHOD
FLOW DIAGRAM: VIEWSHED METHOD
VIEWSHED – NO BARRIER VIEWSHED – WITH BARRIER

11. During day 4 Group 1 would have been completing the visibility analysis for each area with
ArcMap and the 3D modeling of our ponds with AutoCAD. In the meanwhile Group 2 would
have started thinking about the theory part to insert into the presentation (rationale
background, aims and objectives, action plan), refine our work and preparing the results'
layouts. Finally, the day 5 would have been dedicated to the preparation of the presentation
(assembling all the results together and summarizing all our work).
With well coordinated actions we could have saved a lot of time and spent it (in addition to
producing more work) to give more quality to our work, as for example with the 3D
modeling and rendering of our ponds. In order to create very gently sloping margins (as
established in our proposal and action plan) the maximum profundity given to our small and
large ponds are respectively 1.20m and 2.40m, with intervals of inclination of 5 and 10
degrees (figures below).
3D MODELING
SKETCH WITH DIMENSIONS

12. RENDERING

13. Generally during the whole project, we have not encountered particular technical difficulties,
except:
- during the construction of the barrier surrounding our ponds (we had to learn how to give
elevation to it by making several attempts);
- and with the Slope layer, when we had some issues creating the mosaic of the Lidar 1m
DTM's tiles covering our whole study area (the process in ArcMap took very long time),
therefore we decided to proceed using the Terrain 5m DTM.
Fortunately, we managed to use the Lidar 1m DTM to carry out the visibility analysis as the
portion of area analysed did not require assemble many tiles into mosaic (with the 1m DTM
the result is definitely more sensible).
The only real obstacle that we encountered was perhaps ourselves, as it was the first time we
worked together in a group (in my opinion we were not completely able to divide the tasks in
order to achieve an optimal result). As a result, we spent the first two days aimlessly walking
around to identify potential locations before completing and running the model that allowed
the identification of them. Working in a group, with different ideas (and especially without a
team leader), could delay the necessary actions to be taken and influence the results (even
though combining diverse skills). However, the awareness matured in this sense could help us
next time to better organize and coordinate our work as a team.

14. REFERENCES
A. K. Shrivastava (2004) Pollution Development, Environment and Health
Nature et progrès certification: (http://www.saltworks.us/salt_info/si_organic_info.asp)
DATA SOURCES
Mastermap of Sandwich Bay and Pegwell Bay Country Park – (Digimap)
Habitat Map 2012 - (Kent & Medway Biological Records Centre)
Vector district maps and other shapefiles - (Open data – Ordinance Survey)
Terrain 5m DTM - (Digimap)
Lidar 1m DTM – (Geomatics-group)
Aerial photography (Google Earth)