Comparison of Land Cover Categorical Data Stored in OSM and Authoritative Topographic Data
Abstract
:1. Introduction
2. Related Works
2.1. Categorical Data Comparison—Literature Review
2.2. OpenStreetMap Data Quality
3. Materials and Methods
3.1. Study Area and Data Used
3.2. Method Applied
3.2.1. Main Methodological Assumptions and Research Question
3.2.2. Research Schema
3.2.3. Compound Correspondence Index Calculation
- 1.
- Problem description
- 2.
- Calculation of the normalized decision matrix (nij) using the quotient method (Equation (2)):
- 3.
- Calculation of the weighted normalized decision matrix—Equation (3):
- 4.
- Determine the positive (PIS) and negative (NIS) ideal solutions, as shown by Equations (4) and (5).
- 5.
- Calculate the separation measure Si of each alternative (relative closeness to the positive ideal solution) as (Equations (6) and (7)):
- 6.
- Calculate the closeness coefficient of the alternatives (CCi) as:
- 7.
- Sort alternatives in descending order, whereby the highest CCi indicates the best performance in relation to the evaluation criteria.
4. Results
4.1. Local CCI Diversity
4.2. Regional CCI Diversity and Sensitivity Analysis
4.3. Local vs. Regional CCI
5. Discussion
5.1. Semantic Uncertainty
5.2. Validity and Applicability of Data Comparison
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Description | Piaseczno | Sokólski | Sanocki | Słupski | Ostrowski | Otwocki | Międzyrzecki |
---|---|---|---|---|---|---|---|
Geographical Subprovinces 1 | Central Polish Lowlands | Podlasie- Bialystok Upland | Eastern Beskids | South Baltic Coast | Central Polish Lowlands | Central Polish Lowlands | Greater Poland Lake District |
Area (km2) 2 | 621.12 | 2054.34 | 1223.62 | 2347.59 | 1159.92 | 616.46 | 1387.61 |
People | 190,607 | 64,902 | 92,900 | 98,761 | 161,581 | 124,283 | 57,100 |
Population density | 311 | 32 | 81 | 43 | 139 | 202 | 41.5 |
Number of cities | 4 | 4 | 2 | 2 | 2 | 3 | 3 |
Urbanization level (%) | 47.8 | 41.7 | 47.2 | 20.7 | 53.7 | 61.8 | 52.3 |
Land use 2 (km2): Built-up and artificial | 82.51 | 72.93 | 43.65 | 85.15 | 55.62 | 58.91 | 24.08 |
Forest | 132.88 | 547.91 | 586.67 | 864.13 | 347.59 | 250.15 | 735.43 |
Agriculture | 387.37 | 1426.28 | 512.14 | 1234.97 | 728.53 | 276.51 | 513.42 |
Water bodies | 16.44 | 6.71 | 13.60 | 110.65 | 13.31 | 11.14 | 38.39 |
Protected area | Chojnów Landscape Park, protected landscape areas | Knyszyn Forest, Biebrza National Park | Słonne Mountains Landscape Park, protected landscape areas | Słowiński National Park | Landscape Park Dolina Baryczy, protected landscape area | Masovian Landscape Park, Landscape Park Dolina Środkowego Świdra | Notecka Forest, Pszczewska Landscape Park |
Statistics | Piaseczno | Sokólski | Sanocki | Słupski | Ostrowski | Otwocki | Międzyrzecki |
---|---|---|---|---|---|---|---|
Mean | 0.0915 | 0.0390 | 0.0678 | 0.0414 | 0.0427 | 0.0989 | 0.0353 |
Median | 0.0754 | 0.0304 | 0.0533 | 0.0313 | 0.0314 | 0.0832 | 0.0271 |
Minimum | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Maximum | 0.4828 | 0.5329 | 0.4995 | 0.4764 | 0.5765 | 0.5069 | 0.5899 |
Q1 | 0.0420 | 0.0159 | 0.0315 | 0.0165 | 0.0181 | 0.0542 | 0.0129 |
Q3 | 0.1196 | 0.0499 | 0.0790 | 0.0507 | 0.0538 | 0.1246 | 0.0427 |
Variance (σ2) | 0.0052 | 0.0015 | 0.0039 | 0.0018 | 0.0017 | 0.0046 | 0.0016 |
Std. Dev. (σ) | 0.0723 | 0.0386 | 0.0627 | 0.0426 | 0.0406 | 0.0680 | 0.0405 |
Coeff. of variation | 78.9755 | 98.8908 | 92.3641 | 103.0427 | 95.1072 | 68.7311 | 114.7669 |
Interquartile range (IQR) | 0.0775 | 0.0340 | 0.0475 | 0.0342 | 0.0357 | 0.0704 | 0.0298 |
Class | Description | Range | Percentage of the County’s Area (%) | ||||||
---|---|---|---|---|---|---|---|---|---|
Piaseczno | Sokólski | Sanocki | Słupski | Ostrowski | Otwocki | Międzyrzecki | |||
1 | maximum compliance | −0.50 σ < CCIL | 35.5 | 32.1 | 30.6 | 30.6 | 33.2 | 34.1 | 29.1 |
2 | moderate compliance | −0.5 σ < CCIL ≤ 0.5 σ | 42.3 | 49.6 | 52.2 | 52.9 | 46.5 | 43.5 | 56.2 |
3 | semi-compliance | 0.5 σ ≤ CCIL ≤ 1.5 σ | 13.1 | 12.7 | 10.6 | 10.3 | 13.3 | 13.1 | 9.6 |
4 | moderate noncompliance | 1.5 σ ≤ CCIL ≤ 2.5 σ | 5.6 | 2.7 | 3.1 | 3.1 | 4.6 | 9.3 | 2.5 |
5 | maximum noncompliance | CCIL > 2.5 σ | 3.4 | 2.9 | 3.5 | 3.2 | 2.5 | - | 2.6 |
Statistics | CCIR4 1 | CCIR5 | CCIR6 | CCIR7 |
---|---|---|---|---|
Mean | 0.0327 | 0.0272 | 0.0281 | 0.0263 |
Median | 0.0241 | 0.0201 | 0.0208 | 0.0193 |
Minimum | 0 | 0 | 0 | 0 |
Maximum | 0.4971 | 0.5289 | 0.5299 | 0.5389 |
Q1 | 0.0123 | 0.0104 | 0.0108 | 0.01 |
Q3 | 0.0410 | 0.0340 | 0.0352 | 0.0327 |
Variance (σ2) | 0.0012 | 0.0008 | 0.0008 | 0.0008 |
Std. Dev. (σ) | 0.0343 | 0.0287 | 0.0289 | 0.0278 |
Coefficient of variation (cv) | 104.9797 | 105.3271 | 102.7925 | 105.6453 |
Interquartile range (IQR) | 0.0287 | 0.0236 | 0.0244 | 0.0227 |
Class | Description | Interval Size | Percentage of the Counties Area (%) | |||
---|---|---|---|---|---|---|
Regional CCIR4 | Regional CCIR5 | Regional CCIR6 | Regional CCIR7 | |||
1 | maximum compliance | −0.50 σ < CCIRn | 31.9 | 31.5 | 32.3 | 32.1 |
2 | moderate compliance | −0.5 σ < CCIRn ≤ 0.5 σ | 50.9 | 51.3 | 50.1 | 51.2 |
3 | semi-compliance | 0.5 σ ≤ CCIRn ≤ 1.5 σ | 11.1 | 10.9 | 11.0 | 10.4 |
4 | moderate noncompliance | 1.5 σ ≤ CCIRn ≤ 2.5 σ | 6.1 | 3.6 | 3.9 | 6.3 |
5 | maximum noncompliance | CCIRn > 2.5 σ | - | 2.7 | 2.7 | - |
County | CCIRn | Mean | Median | Min | Max | Q1 | Q3 | IQR | σ2 | σ |
---|---|---|---|---|---|---|---|---|---|---|
CCIR4 | 0.0500 | 0.0327 | 0.0000 | 0.4356 | 0.0170 | 0.0620 | 0.0450 | 0.0028 | 0.0527 | |
CCIR5 | 0.0403 | 0.0270 | 0.0000 | 0.3778 | 0.0141 | 0.0495 | 0.0354 | 0.0018 | 0.0425 | |
Piaseczno | CCIR6 | 0.0403 | 0.0271 | 0.0000 | 0.3778 | 0.0142 | 0.0495 | 0.0353 | 0.0018 | 0.0425 |
CCIR7 | 0.0398 | 0.0261 | 0.0000 | 0.3845 | 0.0137 | 0.0491 | 0.0354 | 0.0018 | 0.0429 | |
CCIR4 | 0.0249 | 0.0174 | 0.0000 | 0.4971 | 0.0091 | 0.0300 | 0.0209 | 0.0009 | 0.0304 | |
Sokólski | CCIR5 | 0.0208 | 0.0147 | 0.0000 | 0.3949 | 0.0078 | 0.0249 | 0.0172 | 0.0006 | 0.0254 |
CCIR6 | 0.0209 | 0.0147 | 0.0000 | 0.3912 | 0.0077 | 0.0250 | 0.0172 | 0.0007 | 0.0256 | |
CCIR7 | 0.0201 | 0.0138 | 0.0000 | 0.3909 | 0.0072 | 0.0238 | 0.0166 | 0.0006 | 0.0255 | |
CCIR4 | 0.0290 | 0.0263 | 0.0000 | 0.1741 | 0.0148 | 0.0382 | 0.0234 | 0.0004 | 0.0204 | |
Sanocki | CCIR5 | 0.0348 | 0.0315 | 0.0000 | 0.1975 | 0.0176 | 0.0458 | 0.0282 | 0.0006 | 0.0243 |
CCIR6 | 0.0291 | 0.0264 | 0.0000 | 0.1731 | 0.0149 | 0.0384 | 0.0235 | 0.0004 | 0.0204 | |
CCIR7 | 0.0279 | 0.0249 | 0.0000 | 0.1619 | 0.0141 | 0.0372 | 0.0231 | 0.0004 | 0.0196 | |
CCIR4 | 0.0336 | 0.0257 | 0.0000 | 0.3280 | 0.0133 | 0.0422 | 0.0290 | 0.0011 | 0.0331 | |
Słupski | CCIR5 | 0.0283 | 0.0215 | 0.0000 | 0.2699 | 0.0110 | 0.0355 | 0.0245 | 0.0008 | 0.0280 |
CCIR6 | 0.0283 | 0.0215 | 0.0000 | 0.2684 | 0.0111 | 0.0354 | 0.0243 | 0.0008 | 0.0279 | |
CCIR7 | 0.0269 | 0.0203 | 0.0000 | 0.2639 | 0.0105 | 0.0336 | 0.0232 | 0.0007 | 0.0269 | |
CCIR5 | 0.0272 | 0.0191 | 0.0000 | 0.5289 | 0.0111 | 0.0328 | 0.0217 | 0.0009 | 0.0298 | |
Ostrowski | CCIR6 | 0.0272 | 0.0193 | 0.0000 | 0.5299 | 0.0111 | 0.0329 | 0.0218 | 0.0009 | 0.0298 |
CCIR7 | 0.0268 | 0.0188 | 0.0000 | 0.5389 | 0.0106 | 0.0320 | 0.0213 | 0.0009 | 0.0300 | |
CCIR6 | 0.0384 | 0.0310 | 0.0000 | 0.2429 | 0.0193 | 0.0479 | 0.0286 | 0.0009 | 0.0292 | |
Otwocki | CCIR7 | 0.0369 | 0.0295 | 0.0000 | 0.2472 | 0.0183 | 0.0460 | 0.0277 | 0.0008 | 0.0289 |
Międzyrzecki | CCIR7 | 0.0217 | 0.0169 | 0.0000 | 0.2373 | 0.0084 | 0.0276 | 0.0192 | 0.0005 | 0.0223 |
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Borkowska, S.; Bielecka, E.; Pokonieczny, K. Comparison of Land Cover Categorical Data Stored in OSM and Authoritative Topographic Data. Appl. Sci. 2023, 13, 7525. https://doi.org/10.3390/app13137525
Borkowska S, Bielecka E, Pokonieczny K. Comparison of Land Cover Categorical Data Stored in OSM and Authoritative Topographic Data. Applied Sciences. 2023; 13(13):7525. https://doi.org/10.3390/app13137525
Chicago/Turabian StyleBorkowska, Sylwia, Elzbieta Bielecka, and Krzysztof Pokonieczny. 2023. "Comparison of Land Cover Categorical Data Stored in OSM and Authoritative Topographic Data" Applied Sciences 13, no. 13: 7525. https://doi.org/10.3390/app13137525