Enhanced urban functional land use map with free and open-source data

Figures & data

Figure 1. Study area in Ho Chi Minh city (false colour composite Sentinel-2 image).

Figure 2. Reference data.

Figure 3. Typical commercial and residential areas as depicted with high-resolution Google Earth (left) and false colour composite Sentinel-2 images (right).

Figure 4. Sentinel-2 and OSM data fusion flowchart.

Table 1. Re-classified attributes of the four OSM layers.

Layer	Attribute (values)	New value
Landuse (polygon)	fclass (residential)	Residential
	fclass (commercial, retail)	Commercial
	fclass (cemetery, military, recreation-ground)	Public services
	fclass (industrial)	Industrial
	fclass (forest, grass, meadow, park)	Green space
POI (polygon)	fclass (apartments, house, residential)	Residential
	fclass (bank, bookshop, cafe, hotel, mall, office, restaurant, retail)	Commercial
	fclass (cinema, college, community-centre, court-house, hospital, museum, school, university)	Public services
	fclass (park)	Green space
Building (polygon)	type (apartments, house, residential)	Residential
	type (commercial, hotel, office, retail)	Commercial
	type (chapel, church, mosque, temple, civic, hospital, school, university)	Public services
	type (industrial, manufacture, warehouse)	Industrial
POI (point)	fclass (apartments, house, residential)	Residential
	fclass (bank, hotel, office, retail)	Commercial
	fclass (chapel, church, mosque, temple, civic, hospital, school, university)	Public services

Figure 5. The gap between human-knowledge and data-driven extraction for landuse mapping.

Figure 6. Applied ontology in fusion and classification.

Figure 7. Segmented and classified result from Sentinel-2 image.

Figure 8. The distribution of extracted classes from Sentinel image within each knowledge-driven class.

Figure 9. Functional landuse map derived from Sentinel-2 and OSM data.

Figure 10. Distribution of reference objects in each detected class.

Table 2. Confusion matrix.

Reference
		Resident	Commercial	Public	Industry	Green	Open	User Acc.
Classified	Resident	532	107	26	1	3	16	77.66%
	Commercial	35	321	17	3	2	2	84.47%
	Public	28	21	179	2	1	3	76.50%
	Industry	20	12	5	113	2	3	72.90%
	Green	1	1	0	0	21	2	84.00%
	Open	19	13	0	1	2	120	77.42%
	Producer Acc.	83.78%	67.58%	78.85%	94.17%	67.74%	82.19%
			Overall accuracy	78.70%

Data availability statement

The data that support the findings of this study are available on Google Earth Engine (https://earthengine.google.com) and Geofabrik (https://www.geofabrik.de).