Identifying facilities on the map. The introduction must

Identifying places sites has become extremely important in the present
time to facilitate the sorting of facilities and sites in the map. Locating locations has become very
easy when you’ve put a mark explaining the meaning of this place. In addition, the focus on the
development of tourist attractions and the provision of facilities for them has
become one of the most important goals to obtain the satisfaction of local
tourists and international tourists.

The abstract
not into the point

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Introduction

The correct distribution of tourist places and facilities is one of the
most important tourist attractions for the region. This reflects the
arrangement and the extent to which the area accommodates tourists in terms of
availability of facilities such as hotels, markets and gardens where we can
mark them with a certain symbols that describing the specific place. Positioning
on the map through the use of specific programs such as ArcMap is a great help
to classify the facilities that are proliferating in a particular area, in
addition to facilitating the search for missing facilities in these areas. This program allows you to select
specific areas on the map and also provides several ways to identify facilities
on the map.

 

The introduction must tell the aim of the assignment, the
section of the report and something about your final findings.

Literature review

The point pattern analysis is  the
mark that is placed on the map to determine a specific place, the time of this
particular place, the study of the population and the identification of data
for a particular area.

According to (Diggle, 1983) he has defined a spatial point pattern analysis
by saying “A spatial point pattern can be defined as a set of locations,
irregularly distributed within a region of interest, which have been generated
by random mechanisms”. Where he added that the locations of the places are
randomly distributed by different systems.

As Cook et al. (1999) said “the data presented
here are the final coherency filtered results, one a coherency-filtered stack,
and the other a coherency-filtered, migrated and coherency-filtered stack”.
As  (Besag & Diggle 1977; Gignoux et
al. 1999; Diggle 2003; Lancaster & Downes 2004; Lucio & Castelucio de
Brito 2004) support Cook et al by saying “Spatial point patterns observed in
data are customarily null-hypothesis tested for complete spatial randomness”. This
shows that they combine that point pattern analysis is a set of data that is
distributed randomly and independently. This explains the importance of this
analysis, as well as its ease of use and preview.

Moving to
Wheatley and Gillings (2002:125) quote “In essence, we see formal spatial
analysis not as a means of producing complete archaeological interpretations
but as an extension of our observational equipment. Although the human mind is
a fine interpretative tool, if it is presented with a series of random dots it
does have a tendency to suggest patterns even if none exist” . To explain that,
their words illustrate that the union of the human mind with a series of random
points as point pattern analysis works to improve their role in the development
of the region, in addition to it is possible to identify the facilities
invisible to the unaided eye but specified on the map.

 

 

Data used

The data
that used in ArcMap program are the hotels and the attractions that located in
a particular area.

 

 

Study area

The study
area of the distribution of hotels and attractions  is ( Muscat ) the capital city of Sultanate
of Oman, which is a tourist destination for many local and international
tourists due to the
diversity of tourist and attractive places.

 

 

Methodology used in the analysis

There are
two methodology used to analysis the map, those are the Directional Distributing
which is a standard deviational ellipse that measure the directional of the
features, and the Average Nearest Neighbor which contain the expected
mean distance and the observed mean distance, the
Nearest Neighbor ratio and the z-score.

 

 

 

 

 

 

Results The map shows the distribute hotels and attractions in Governorate of
Muscat.

 

 

 

 

The map contains a directional distribution tool that shows that the
distribution of attractions in Muscat Governorate is concentrated on the
northwest of the governorate.

 

 

 

 

 

However, about the hotels it’s shows that the
distribution of hotels is limited to a certain area in the Muscat Governorate. Where it is
clear that the south of the Governorate does not contain any hotels.

 

 

 

 

The directional distribution tool here shows that the proliferation of
attractions and hotels in the northern Governorate of Muscat.

 

The Average
Nearest Neighbor about the attractions in Muscat Governorate shows the
expected mean distance which is 3609.1346 meters, the observed mean distance is
1626.3196 meters and the Nearest Neighbor ratio is 0.450612. this methodology
explain the features in details.

 

However,
about the hotels Average Nearest Neighbor in Muscat Governorate shows the
expected mean distance which is 1621.3899 meters, the observed mean distance is
846.5057 meters, where it’s a very less than the attractions.

 

Conclusion

to sum up,
Geographic Information System (GIS) is one of the most important programs or
systems that helps in planning cities and distributing the deficient facilities
in the regions in a balanced manner

In addition
to studying population distribution more clearly than previously. There are
many tools that help to clarify the distribution of facilities and facilitate
the use of the program such as Directional Distributing and the Average Nearest Neighbor. This system
can serve several sectors and ministries such as the tourism sector, the
Ministry of Environment and the Ministry of Regional Municipalities and Water
Resources for example,  by determine the
location of tourists and attractions and provide a suitable quantity of water
to serve these areas.

 

 

 

 

 

 

 

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