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Violation Intensity Analysis

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Summary Statistics:
a. Violations and Fine Amount by County: County | FINE AMOUNT | VIOLATIONS | Bronx | 8% | 8% | Kings | 4% | 4% | NY County | 74% | 73% | Queens | 6% | 7% | Richmond | 8% | 9% |

b. Violations and Fine Amount by day of the Week:

Weekday | FINE AMOUNT | VIOLATIONS | 1 | 1% | 1% | 2 | 18% | 18% | 3 | 22% | 22% | 4 | 22% | 22% | 5 | 18% | 18% | 6 | 15% | 15% | 7 | 4% | 4% |

c. Violations by Violation Type: Violation Type | Percentage | 14 | 13% | 46 | 11% | 45 | 10% | 69 | 9% | 34 | 8% | 16 | 6% | 20 | 5% | 38 | 5% | 19 | 5% | 21 | 4% | 42 | 4% | 40 | 3% | 78 | 2% | 37 | 2% | 47 | 2% | 48 | 2% | 71 | 2% | 82 | 1% | 17 | 1% | 51 | 1% | 70 | 1% | 18 | 1% |
Note: The Violation types which are of less than one percentage are not shown.

Violation Intensity Analysis:
a. Hot Spots in terms of type of road segment:
The term Hot spot is self-explanatory which means a place with significant activity or danger. Here in this Study it refers to the intensity of Violations over the road segment. The higher the intensity of violations, the more we can dig into the reasons for the violations.
The preliminary objective of the Study is identify the hot spots in terms of Road segment types. The intensity is calculated in terms of number of violations over the road segments length. The density will give us an insight into the particular features of the road segment that might have been an indirect push to the cause of violation. The methodology adopted is quite adaptive and so can be redirected into many paths. The NYC is viewed on the whole and the intensity of violations on each road segment is calculated. The calculated intensity and type of road segment is used in the evaluation. This analysis is further branched into based on each county for further scrutiny. The type of Violations and Road segment type when put together yield a very affirmative answer to the question of Parking Violation. In similar path the study is directed towards the day of the week (Weekday vs Weekend) and the Road Segment type. This indirectly approaches the density of traffic over road segments over the week.
b. Intensity of Violations on Road Segments: | DENSITY BY COUNTY | WEEKLY | ROAD TYPE | DENSITY | MANHATTAN | BROOKLYN | BRONX | QUEENS | RICHMOND | WEEKDAY | WEEKEND | A11-A19 | 72.0 | 80.3 | 162.8 | 28.2 | 23.6 | NULL | 62.4 | 40.3 | A20-A29 | 95.1 | 106.3 | 30.8 | 91.4 | 44.1 | 54.7 | 93.1 | 23.3 | A30-A39 | 64.1 | 87.5 | 26.7 | 56.2 | 48.2 | 50.5 | 62.7 | 22.6 | A40-A49 | 80.2 | 149.9* | 18.3 | 32.7 | 25.3 | 23.8 | 79.3 | 19.1 | A60-A69 | 123.4 | 75.6 | 99.3 | 188.7 | 103.4 | 92.7 | 120.1 | 43.4 | A70-A79 | 36.3 | 57.2 | 30.9 | 13.1 | 14.4 | 20.6 | 35.4 | 26.6 |
The intensity of violations requires the spatial distribution of Parking Violations. The addresses of the Parking Violations are geo-coded in order to identify the spatial patterns. The geo-coded data points are associated with the road segments spatially. The intensity of the Violations are calculated by number of data points associated with each road segment. Based on Feature Code Classification of road segments the violations are then attributed to each functional class of the road segments.

Column1 | Column2 | DENSITY BY COUNTY | Column3 | Column4 | Column5 | Column6 | WEEKLY | Column7 | ROAD TYPE | DENSITY | MANHATTAN | BROOKLYN | BRONX | QUEENS | RICHMOND | WEEKDAY | WEEKEND | A11-A19 | 72.0 | 80.3 | 162.8 | 28.2 | 23.6 | NULL | 62.4 | 40.3 | A20-A29 | 95.1 | 106.3 | 30.8 | 91.4 | 44.1 | 54.7 | 93.1 | 23.3 | A30-A39 | 64.1 | 87.5 | 26.7 | 56.2 | 48.2 | 50.5 | 62.7 | 22.6 | A40-A49 | 80.2 | 149.9 | 18.3 | 32.7 | 25.3 | 23.8 | 79.3 | 19.1 | A60-A69 | 123.4 | 75.6 | 99.3 | 188.7 | 103.4 | 92.7 | 120.1 | 43.4 | A70-A79 | 36.3 | 57.2 | 30.9 | 13.1 | 14.4 | 20.6 | 35.4 | 26.6 |
Note: 1.NULL represents that there have been zero reportable violations in that category. 2. * represents exceptionally high values which may have to be interpreted differently.

| VIOLATION TYPE | ROAD TYPE | 14 | 46 | 45 | 69 | A11-A19 | 162.8 | NULL | NULL | NULL | A20-A29 | 62.9 | 31.7 | 30.6 | 59.4 | A30-A39 | 39.2 | 32.3 | 34.0 | 88.0 | A40-A49 | 56.9 | 24.5 | 29.4 | 122.6 | A60-A69 | 74.9 | 54.2 | 73.3 | 100.6 | A70-A79 | 29.1 | 25.0 | 32.4 | 41.0 |

Note: 1.NULL represents that there have been zero reportable violations in that category.

c. Results:
(i) The results mainly involve violation intensities of different road functional classes. These are interpreted in a branched format to format reasonable conclusions. The intensity of Violations based on type of road segment for the entire NYC will give an out stretch of road functional classes that have higher violation intensities making it possible for the look into parking regulations on Road functional classes. Then further investigating the counties we get much more interesting results. When looking at the counties we might find a different functional class having more intensity of violations when compared with the NYC on a whole. This will further give an abstract idea on the parking regulations and reasons for violations. Then based on whether it’s a weekend or weekday the intensity of violations on road segments are evaluated. The complete picture is obtained when we deal with the intensity of violations on different road functional classes vs the type of violations. On different road functional classes, which type of violations are more frequent giving us a sound statement on reasons behind violations.

2. a. Hot spots in terms of Land use type:
Based on the land use type we try to evaluate whether there is any significant effect of land use type on the parking violation. In particular commercial vehicles are bound to specific jobs and can make patterns to be identified easily. The intensity of violations is calculated based on the number of violations attributed to the parcel and its frontal length. This is done in order to normalize the different land use types. This will give us the catalyst to make useful conclusions.
This goes on similar lines in with the previous study. The land use types for the whole NYC are looked into for any desirable patterns and then further investigated into counties to find if there are significant patterns county wise. Then on similar notches the weekday vs weekend violation intensities on different land use types are identified. Then the critical violation types are matched with the Land use types. This gives you the complete picture of parking regulations vs parking violations.
b. Intensity of Violations on Land use types:
The spatial patterns in parking violations are identified by geo-coding the addresses of parking violations on to the land use types and are spatially associated with the each land use type. The intensity is calculated by dividing associated number of violations with the front length of the Parcel. | DENSITY BY COUNTY | WEEKLY | LAND USE TYPE | DENSITY | MANHATTAN | BROOKLYN | BRONX | QUEENS | RICHMOND | WEEKDAY | WEEKEND | 1 | 104.9 | 183.6 | 52.6 | 64.7 | 59.4 | 56.1 | 50.5 | 105.4 | 2 | 74.2 | 118.6 | 51.1 | 36.7 | 26.4 | 26.8 | 73.4 | 37.3 | 3 | 53.4 | 76.9 | 10.2 | 19.1 | 15.4 | 16.6 | 52.1 | 12.6 | 4 | 119.0 | 143.6 | 49.9 | 44.1 | 56.6 | 58.2 | 116.1 | 30.9 | 5 | 110.1 | 161.6 | 28.1 | 54.0 | 39.3 | 42.0 | 107.4 | 27.0 | 6 | 53.1 | 111.0 | 19.1 | 19.4 | 19.6 | 18.0 | 52.0 | 26.3 | 7 | 40.2 | 53.9 | 8.8 | 19.6 | 26.1 | 22.7 | 38.3 | 15.9 | 8 | 48.6 | 74.6 | 16.0 | 15.1 | 15.1 | 14.6 | 48.6 | 13.2 | 9 | 12.7 | 17.1 | 8.1 | 12.3 | 3.8 | 3.9 | 12.3 | 3.3 | 10 | 55.0 | 103.7 | 26.8 | 24.9 | 19.0 | 23.6 | 55.1 | 14.4 | 11 | 44.3 | 82.5 | 53.6 | 15.4 | 26.8 | 17.5 | 42.3 | 23.9 |

| VIOLATION TYPE | ROAD TYPE | 14 | 46 | 45 | 69 | A11-A19 | 162.8 | NULL | NULL | NULL | A20-A29 | 62.9 | 31.7 | 30.6 | 59.4 | A30-A39 | 39.2 | 32.3 | 34.0 | 88.0 | A40-A49 | 56.9 | 24.5 | 29.4 | 122.6 | A60-A69 | 74.9 | 54.2 | 73.3 | 100.6 | A70-A79 | 29.1 | 25.0 | 32.4 | 41.0 |

c. Results:
(i) The violation intensities are evaluated in branched format. The NYC is viewed as a whole and then viewed as county wise in order to identify patterns. The land use type and their violation intensities form the crux of the results. The weekend vs weekday pattern of the violation intensities for different land use types are displayed. In a similar fashion we look out for patterns in violation types vs land use types based on violation intensities.

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