GIS and Optimisation: Potential Benefits for Emergency Facility Location in Humanitarian Logistics
Abstract
:1. Introduction
2. Literature Review
3. Geographical Procedure
3.1. Identification of Suitable Facilities
3.1.1. Shelter Standards
3.1.2. Standards for Distribution Centres
3.2. Digitization
3.3. Cartographic Model
3.3.1. Data Pre-Processing
- The layer of available DCs, obtained from authorities or elaborated by the analyst.
- The layer of available shelters, obtained from authorities or elaborated by the analyst.
- The DEM of the area under study, obtained from online sources or from authorities.
- The demand unit of the region (e.g., neighbourhoods) obtained from authorities.
3.3.2. Macro on IDRISI®
3.4. Network Analysis
4. Case Studies
- The events are two of the most notable floods lived in the country over the last 15 years, providing extreme conditions for the analysis.
- The characteristics among cases vary considerably in terms of damage, duration and number of people affected.
4.1. Veracruz, Mexico
4.1.1. Layers Used for the Case of Veracruz
4.1.2. Application of the Cartographic Model
4.1.3. Results of the GIS Procedure Applied to Veracruz
4.2. Villahermosa, Tabasco
4.2.1. Layers Used for the Case of Villahermosa
4.2.2. GIS Procedure for the Case of Villahermosa
4.2.3. Results of the GIS Procedure Applied to Villahermosa
4.3. Validation
4.3.1. GIS for the Case of Veracruz
4.3.2. GIS for the Case of Villahermosa
4.3.3. Discussion and Summary of the Results from the Geographical Procedure
5. Comparison to the Real Circumstances
5.1. Veracruz
5.2. Villahermosa
5.3. Summary and Discussion
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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- | Requirement | CENAPRED | Sphere Project |
---|---|---|---|
Conditions | Total space available per person | - | 45 m2 |
Minimum volume of air per person | 10.0 m3 | - | |
Minimum distance between beds | 0.75 m | - | |
Minimum covered floor area | 3.5 m2 | 3.5 m2 | |
Personal hygiene | Washbasin | One per 10 people | - |
Shower | One per 50 people (warm weather), one per 30 people (hot weather) | - | |
Hygiene facilities | Separate sections for male and female | - | |
Toilets | Female | One per 25 woman | - |
Male | One toilet and one urinal per 35 males | - | |
Minimum distance between buildings | 50 m | - |
Section | Requirement |
---|---|
Courtyard |
|
Building |
|
Floors |
|
Walls |
|
Ceilings |
|
Windows |
|
Doors |
|
Hygiene |
|
Ventilation |
|
Year | Location (City, State, Country) | Description |
---|---|---|
2007 | Villahermosa, Tabasco, Mexico | Flood depth: 4 m [69] Start and end date: 29 October 2007–23 May 2008 Number of people sheltered: 99,000 [70,71] |
2010 | Veracruz, Veracruz, Mexico | Flood depth: 1.5 m [72] Start and end date: 19 September 2010–19 October 2010 Number of people sheltered: 5140 [73,74,75] |
Percentage of Damage | 0.5 m | 1.5 m | 2.5 m |
---|---|---|---|
Not affected | 247 | 235 | 212 |
1 < x < 10 | 22 | 21 | 28 |
10 < x < 20 | 13 | 11 | 11 |
20 < x < 30 | 8 | 7 | 9 |
30 < x < 40 | 6 | 7 | 8 |
40 < x < 50 | 4 | 6 | 5 |
50 < x < 60 | 1 | 6 | 5 |
60 < x < 70 | 2 | 7 | 8 |
70 < x < 80 | 3 | 1 | 9 |
80 < x < 90 | 1 | 4 | 5 |
90 < x | 8 | 10 | 15 |
Level of Damage | 1 m | 2 m | 4 m |
---|---|---|---|
Not affected | 47 | 32 | 18 |
1 < x < 10 | 35 | 27 | 14 |
10 < x < 20 | 10 | 12 | 8 |
20 < x < 30 | 13 | 13 | 11 |
30 < x < 40 | 11 | 7 | 6 |
40 < x < 50 | 6 | 16 | 3 |
50 < x < 60 | 6 | 8 | 15 |
60 < x < 70 | 7 | 8 | 12 |
70 < x < 80 | 4 | 6 | 10 |
80 < x < 90 | 0 | 6 | 13 |
90 < x | 8 | 12 | 37 |
ID | Cost (mxn) | Unfulfilled (%) | Shelters Endangered | People at Risk | DCs Affected |
---|---|---|---|---|---|
VNG1 | 1,289,382.25 | 90.57 | 2 | 568 | 1 |
VNG2 | 1,314,943.16 | 89.71 | 3 | 615 | 1 |
VNG3 | 1,457,745.88 | 78.26 | 1 | 62 | 0 |
VNG4 | 1,596,843.04 | 69.57 | 2 | 224 | 1 |
VNG5 | 1,738,612.65 | 60.23 | 1 | 282 | 0 |
VNG6 | 1,879,685.44 | 52.82 | 2 | 352 | 0 |
VNG7 | 2,020,920.35 | 39.5 | 2 | 490 | 0 |
VNG8 | 2,161,081.47 | 27.18 | 2 | 568 | 0 |
VNG9 | 2,302,564.41 | 22.6 | 0 | 0 | 0 |
VNG10 | 2,443,454.81 | 11.84 | 0 | 0 | 0 |
VNG11 | 2,550,565.24 | 6.22 | 2 | 565 | 0 |
VNG12 | 2,572,117.95 | 4.46 | 0 | 0 | 0 |
VNG13 | 2,577,332.72 | 4.37 | 0 | 0 | 0 |
VNG14 | 2,578,529.58 | 4.33 | 0 | 0 | 0 |
VNG15 | 2,584,964.49 | 4.29 | 0 | 0 | 0 |
VNG16 | 2,602,335.43 | 4.21 | 1 | 290 | 0 |
VNG17 | 2,625,476.88 | 4.12 | 0 | 0 | 0 |
VNG18 | 2,636,437.79 | 4.07 | 0 | 0 | 0 |
VNG19 | 2,639,966.91 | 4.03 | 0 | 0 | 0 |
VNG20 | 2,689,884.41 | 3.86 | 0 | 0 | 0 |
VNG21 | 2,862,202.03 | 3.75 | 0 | 0 | 1 |
VNG22 | 3,142,947.2 | 2.87 | 0 | 0 | 0 |
VNG23 | 3,157,023.09 | 2.43 | 0 | 0 | 0 |
VNG24 | 3,388,740.71 | 2.16 | 0 | 0 | 0 |
ID | Cost (mxn) | Unfulfilled (%) | Shelters Endangered | People at Risk | DCs Affected |
---|---|---|---|---|---|
TNG1 | 37,912,695 | 95.79288 | 60 | 34,577 | 0 |
TNG2 | 39,393,530 | 92.64069 | 55 | 27,214 | 0 |
TNG3 | 42,348,714 | 73.58491 | 59 | 31,891 | 0 |
TNG4 | 45,312,141 | 65.80087 | 62 | 31,285 | 0 |
TNG5 | 48,281,093 | 60.11983 | 61 | 31,285 | 0 |
TNG6 | 49,754,160 | 58.25243 | 73 | 32,612 | 0 |
TNG7 | 51,202,469 | 57.53509 | 66 | 32,013 | 0 |
TNG8 | 52,724,503 | 54.55939 | 65 | 29,499 | 0 |
TNG9 | 55,651,605 | 51.02041 | 89 | 37,790 | 0 |
TNG10 | 57,165,905 | 48.65591 | 55 | 27,135 | 0 |
TNG11 | 58,648,895 | 48.3871 | 38 | 33,539 | 1 |
TNG12 | 60,125,523 | 46.58491 | 60 | 34,196 | 1 |
TNG13 | 61,601,567 | 44.54685 | 60 | 37,175 | 0 |
TNG14 | 64,412,961 | 42.46285 | 80 | 29,620 | 1 |
TNG15 | 66,035,112 | 41.97531 | 82 | 31,636 | 1 |
TNG16 | 67,533,346 | 40.23379 | 89 | 29,885 | 1 |
TNG17 | 70,001,418 | 39.17713 | 104 | 33,713 | 2 |
TNG18 | 74,611,184 | 38.61004 | 106 | 30,080 | 3 |
TNG19 | 76,422,606 | 35.58719 | 88 | 33,701 | 1 |
TNG20 | 99,705,500 | 27.14364 | 85 | 30,618 | 0 |
TNG21 | 101,569,322 | 23.00877 | 79 | 30,336 | 1 |
TNG22 | 102,882,459 | 22.32704 | 96 | 32,566 | 2 |
TNG23 | 106,992,320 | 22.2973 | 94 | 29,230 | 2 |
TNG24 | 111,912,735 | 22.25476 | 160 | 34,849 | 3 |
TNG25 | 111,979,634 | 22.05567 | 160 | 31,306 | 2 |
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
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Rodríguez-Espíndola, O.; Albores, P.; Brewster, C. GIS and Optimisation: Potential Benefits for Emergency Facility Location in Humanitarian Logistics. Geosciences 2016, 6, 18. https://doi.org/10.3390/geosciences6020018
Rodríguez-Espíndola O, Albores P, Brewster C. GIS and Optimisation: Potential Benefits for Emergency Facility Location in Humanitarian Logistics. Geosciences. 2016; 6(2):18. https://doi.org/10.3390/geosciences6020018
Chicago/Turabian StyleRodríguez-Espíndola, Oscar, Pavel Albores, and Christopher Brewster. 2016. "GIS and Optimisation: Potential Benefits for Emergency Facility Location in Humanitarian Logistics" Geosciences 6, no. 2: 18. https://doi.org/10.3390/geosciences6020018