Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study
Many water bodies play a crucial role as receiver of several urban basins within the water system of a city, these urban basins often face challenges of pollution and reduction in water flow, such as, the case of the Juan Angola channel in the city of Cartagena, Colombia. Current remote sensing stra...
- Autores:
-
Naufal, Camilo
Solano-Correa, Yady T.
Marrugo, Andres G.
- Tipo de recurso:
- Fecha de publicación:
- 2024
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12724
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12724
- Palabra clave:
- Time series analysis
Multispectral images,
PlanetScope
Computer vision
Water channel
Pollution
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| title |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| spellingShingle |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study Time series analysis Multispectral images, PlanetScope Computer vision Water channel Pollution |
| title_short |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| title_full |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| title_fullStr |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| title_full_unstemmed |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| title_sort |
Time Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Study |
| dc.creator.fl_str_mv |
Naufal, Camilo Solano-Correa, Yady T. Marrugo, Andres G. |
| dc.contributor.author.none.fl_str_mv |
Naufal, Camilo Solano-Correa, Yady T. Marrugo, Andres G. |
| dc.subject.keywords.spa.fl_str_mv |
Time series analysis Multispectral images, PlanetScope Computer vision Water channel Pollution |
| topic |
Time series analysis Multispectral images, PlanetScope Computer vision Water channel Pollution |
| description |
Many water bodies play a crucial role as receiver of several urban basins within the water system of a city, these urban basins often face challenges of pollution and reduction in water flow, such as, the case of the Juan Angola channel in the city of Cartagena, Colombia. Current remote sensing strategies using Landsat and Sentinel-2 satellite imagery, lack the necessary spatial resolution to adequately study such as water bodies. In contrast, higher spatial resolution data, such as the PlanetScope one, allows for better spatial and temporal details. Nevertheless, PlanetScope does not count with the same spectral resolution as Landsat and Sentinel-2, requiring of further processings to extract relevant information. In this paper, we used PlanetScope satellite images, processed through computer vision techniques, to analyze the evolution of the Juan Angola channel, Laguna del Cabrero and Chambac´u over time. Our approach involved extracting water areas from PlanetScope images and comparing these over different periods. Preliminary findings revealed noticeable variations in the area of the channel due to factors such as rainfall and possible illegal human invasion, as well as, the increment in level of contamination observed by means of the Normalized Difference Turbidity Index (NDTI). The images used from PlanetScope offered a more detailed time-series analysis of different hydrographic areas, which is particularly pertinent in the Juan Angola channel. |
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2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-09-11T16:12:14Z |
| dc.date.available.none.fl_str_mv |
2024-09-11T16:12:14Z |
| dc.date.issued.none.fl_str_mv |
2024-06-10 |
| dc.date.submitted.none.fl_str_mv |
2024-09-11 |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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info:eu-repo/semantics/draft |
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http://purl.org/coar/resource_type/c_6501 |
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draft |
| dc.identifier.citation.spa.fl_str_mv |
Camilo Naufal, Yady T. Solano-Correa, and Andres G. Marrugo "Time series water body analysis through planet satellite imagery: a coastal urban case study", Proc. SPIE 13037, Geospatial Informatics XIV, 1303705 (10 June 2024); https://doi.org/10.1117/12.3014198 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/12724 |
| dc.identifier.doi.none.fl_str_mv |
10.1117/12.3014198 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Camilo Naufal, Yady T. Solano-Correa, and Andres G. Marrugo "Time series water body analysis through planet satellite imagery: a coastal urban case study", Proc. SPIE 13037, Geospatial Informatics XIV, 1303705 (10 June 2024); https://doi.org/10.1117/12.3014198 10.1117/12.3014198 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/12724 |
| dc.language.iso.spa.fl_str_mv |
eng |
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eng |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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openAccess |
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8 páginas |
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application/pdf |
| dc.publisher.place.spa.fl_str_mv |
Cartagena de Indias |
| dc.publisher.faculty.spa.fl_str_mv |
Ingeniería |
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Maestría en Ingeniería |
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Proc. SPIE 13037, Geospatial Informatics XIV |
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Universidad Tecnológica de Bolívar |
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Naufal, Camilo3d8659aa-4283-4c6f-84a7-93f0dd7b5521Solano-Correa, Yady T.e39f4afa-108e-499c-9f65-8993c383606aMarrugo, Andres G.c9e02917-814b-4552-a002-b99e4ab7d2612024-09-11T16:12:14Z2024-09-11T16:12:14Z2024-06-102024-09-11Camilo Naufal, Yady T. Solano-Correa, and Andres G. Marrugo "Time series water body analysis through planet satellite imagery: a coastal urban case study", Proc. SPIE 13037, Geospatial Informatics XIV, 1303705 (10 June 2024); https://doi.org/10.1117/12.3014198https://hdl.handle.net/20.500.12585/1272410.1117/12.3014198Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarMany water bodies play a crucial role as receiver of several urban basins within the water system of a city, these urban basins often face challenges of pollution and reduction in water flow, such as, the case of the Juan Angola channel in the city of Cartagena, Colombia. Current remote sensing strategies using Landsat and Sentinel-2 satellite imagery, lack the necessary spatial resolution to adequately study such as water bodies. In contrast, higher spatial resolution data, such as the PlanetScope one, allows for better spatial and temporal details. Nevertheless, PlanetScope does not count with the same spectral resolution as Landsat and Sentinel-2, requiring of further processings to extract relevant information. In this paper, we used PlanetScope satellite images, processed through computer vision techniques, to analyze the evolution of the Juan Angola channel, Laguna del Cabrero and Chambac´u over time. Our approach involved extracting water areas from PlanetScope images and comparing these over different periods. Preliminary findings revealed noticeable variations in the area of the channel due to factors such as rainfall and possible illegal human invasion, as well as, the increment in level of contamination observed by means of the Normalized Difference Turbidity Index (NDTI). The images used from PlanetScope offered a more detailed time-series analysis of different hydrographic areas, which is particularly pertinent in the Juan Angola channel.8 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Proc. SPIE 13037, Geospatial Informatics XIVTime Series Water Body Analysis Through Planet Satellite Imagery: A Coastal Urban Case Studyinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Time series analysisMultispectral images,PlanetScopeComputer visionWater channelPollutionCartagena de IndiasIngenieríaMaestría en IngenieríaInvestigadoresAlcald´ıa Mayor de Cartagena de Indias (AMCI)., C. C. C., “Estudios y dise˜nos del plan maestro de drenajes pluviales del distrito de cartagena,” Cartagena de Indias, Colombia (2009).Carrascal, G. C., Esquivia, L. S., and Reales, A. B., “Problem´atica ambiental de los cuerpos de agua de cartagena de indias,” Teknos revista cient´ıfica (2008).Baldovino Luna, P. A., Diaz Ospino, J., and Jimenez Rico, G., “Evaluaci´on de la problem´atica socioambiental presente en el ca˜no juan angola situado en la cuidad de cartagena,” (2023).Chuvieco, E., “Fundamentos de teledetecci´on espacial.,” (1990).Simic Milas, A., Cracknell, A. P., and Warner, T. A., “Drones–the third generation source of remote sensing data,” (2018).Naufal, C., Solano-Correa, Y. T., and Marrugo, A. G., “Yolo-based multi-scale ground control point detection in uav surveying,” in [2023 IEEE Colombian Caribbean Conference (C3) ], 1–5 (2023).Tran, T.-H. and Nguyen, D.-D., “Management and regulation of drone operation in urban environment: A case study,” Social Sciences 11(10), 474 (2022).Civil, A., “Reglamentos aeron´auticos de colombia,” Parte IV (2021).Bansod, B., Singh, R., Thakur, R., and Singhal, G., “A comparision between satellite based and drone based remote sensing technology to achieve sustainable development: A review,” Journal of Agriculture and Environment for International Development (JAEID) 111(2), 383–407 (2017)Mansaray, A. S., Dzialowski, A. R., Martin, M. E., Wagner, K. L., Gholizadeh, H., and Stoodley, S. H., “Comparing planetscope to landsat-8 and sentinel-2 for sensing water quality in reservoirs in agricultural watersheds,” Remote Sensing 13(9), 1847 (2021).Frazier, A. E. and Hemingway, B. L., “A technical review of planet smallsat data: Practical considerations for processing and using planetscope imagery,” Remote Sensing 13(19), 3930 (2021).Faxon, A., “Studying suspended sediment concentrations in the south chickamauga creek of chattanooga, tn using satellite imagery, digital image processing, and numeric modeling,” (2022)Ke, Y., Im, J., Lee, J., Gong, H., and Ryu, Y., “Characteristics of landsat 8 oli-derived ndvi by comparison with multiple satellite sensors and in-situ observations,” Remote sensing of environment 164, 298–313 (2015)Acharya, T. D. and Yang, I., “Exploring landsat 8,” International Journal of IT, Engineering and Applied Sciences Research (IJIEASR) 4(4), 4–10 (2015).Borr`as, J., Delegido, J., Pezzola, A., Pereira-Sandoval, M., Morassi, G., and Camps-Valls, G., “Clasificaci´on de usos del suelo a partir de im´agenes sentinel-2,” Revista de Teledetecci´on (48), 55–66 (2017).Main-Knorn, M., Pflug, B., Louis, J., Debaecker, V., M¨uller-Wilm, U., and Gascon, F., “Sen2cor for sentinel-2,” in [Image and signal processing for remote sensing XXIII], 10427, 37–48, SPIE (2017).Team, P., “Planet imagery product specification: Planetscope & rapideye,” Planet: San Francisco, CA, USA (2016).Roy, D. P., Huang, H., Houborg, R., and Martins, V. S., “A global analysis of the temporal availability of planetscope high spatial resolution multi-spectral imagery,” Remote Sensing of Environment 264, 112586 (2021).] Cartagena de Indias, A. M. d. C., “Observatorio ambiental de cartagena de indias.,” (2016).Ozelkan, E., “Water body detection analysis using ndwi indices derived from landsat-8 oli,” ¨ Polish Journal of Environmental Studies 29(2), 1759–1769 (2020).Vogt, M. C. and Vogt, M. E., “Near-remote sensing of water turbidity using small unmanned aircraft systems,” Environmental Practice 18(1), 18–31 (2016).Solano-Correa, Y. T., Bovolo, F., and Bruzzone, L., “Generation of homogeneous vhr time series by nonparametric regression of multisensor bitemporal images,” IEEE Transactions on Geoscience and Remote Sensing 57(10), 7579–7593 (2019).http://purl.org/coar/resource_type/c_c94fORIGINAL1303705.pdf1303705.pdfapplication/pdf16962279https://repositorio.utb.edu.co/bitstream/20.500.12585/12724/1/1303705.pdf8a501ecef35a610ee9d413b392878f82MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/12724/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/12724/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXT1303705.pdf.txt1303705.pdf.txtExtracted texttext/plain25696https://repositorio.utb.edu.co/bitstream/20.500.12585/12724/4/1303705.pdf.txt540533eb16a51dc107fdb299aee367d4MD54THUMBNAIL1303705.pdf.jpg1303705.pdf.jpgGenerated 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