Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals
Satellite imagery provides impartial, inclusive, and timely geospatial data regarding global issues, supplementing traditional ground-based methods. The volume, velocity, and variety of satellite imagery present novel capabilities to support the United Nations' Sustainable Development Goa...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10146399/ |
| _version_ | 1797785544575418368 |
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| author | Cecilia N. Clark Adane Bedada Benjamin Huff Bogdan Lita Amy B. Newbury Fabio Pacifici |
| author_facet | Cecilia N. Clark Adane Bedada Benjamin Huff Bogdan Lita Amy B. Newbury Fabio Pacifici |
| author_sort | Cecilia N. Clark |
| collection | DOAJ |
| description | Satellite imagery provides impartial, inclusive, and timely geospatial data regarding global issues, supplementing traditional ground-based methods. The volume, velocity, and variety of satellite imagery present novel capabilities to support the United Nations' Sustainable Development Goals by providing repeatable data to assess progress and support reliable statistics connecting policy with evidence. Currently, the relationship between spatial resolution and accurate detection of sub-meter- to meter-scale objects supporting policy-making remains unexplored. This study investigates the resolution-performance trade-off by comparing results of object detection models and their implications for two sustainability-motivated use cases. These include vehicle detection, used to inform traffic flow and density for understanding infrastructure needs and lockdown policies, and solar panel detection, where accuracy is crucial in monitoring green energy production and sustainable energy access. The results show a largely linear degradation of object detection models using imagery at 30, 40, 50, and 60 cm resolutions simulated from 7 cm aerial imagery. Object detection models using 30 cm imagery improve F<inline-formula><tex-math notation="LaTeX">$_{1}$</tex-math></inline-formula> score by 65% compared to 60 cm models. Further investigation into a preprocessing step using 30 cm imagery to generate 15 cm imagery shows an average F<inline-formula><tex-math notation="LaTeX">$_{1}$</tex-math></inline-formula> score increase by 5% for detection of small objects across multiple use cases. The results and analysis provide a basis for more robust investigations into the capabilities of very high resolution satellite imagery to support the Sustainable Development Goals. |
| first_indexed | 2024-03-13T00:56:29Z |
| format | Article |
| id | doaj.art-dd03888e60c54501b75b56594989106c |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-03-13T00:56:29Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-dd03888e60c54501b75b56594989106c2023-07-06T23:00:13ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352023-01-01165695571310.1109/JSTARS.2023.328430910146399Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development GoalsCecilia N. Clark0https://orcid.org/0000-0002-4826-2152Adane Bedada1Benjamin Huff2Bogdan Lita3Amy B. Newbury4Fabio Pacifici5Maxar Technologies, Westminster, CO, USAMaxar Technologies, Westminster, CO, USAMaxar Technologies, Westminster, CO, USAMaxar Technologies, Westminster, CO, USAMaxar Technologies, Westminster, CO, USAMaxar Technologies, Westminster, CO, USASatellite imagery provides impartial, inclusive, and timely geospatial data regarding global issues, supplementing traditional ground-based methods. The volume, velocity, and variety of satellite imagery present novel capabilities to support the United Nations' Sustainable Development Goals by providing repeatable data to assess progress and support reliable statistics connecting policy with evidence. Currently, the relationship between spatial resolution and accurate detection of sub-meter- to meter-scale objects supporting policy-making remains unexplored. This study investigates the resolution-performance trade-off by comparing results of object detection models and their implications for two sustainability-motivated use cases. These include vehicle detection, used to inform traffic flow and density for understanding infrastructure needs and lockdown policies, and solar panel detection, where accuracy is crucial in monitoring green energy production and sustainable energy access. The results show a largely linear degradation of object detection models using imagery at 30, 40, 50, and 60 cm resolutions simulated from 7 cm aerial imagery. Object detection models using 30 cm imagery improve F<inline-formula><tex-math notation="LaTeX">$_{1}$</tex-math></inline-formula> score by 65% compared to 60 cm models. Further investigation into a preprocessing step using 30 cm imagery to generate 15 cm imagery shows an average F<inline-formula><tex-math notation="LaTeX">$_{1}$</tex-math></inline-formula> score increase by 5% for detection of small objects across multiple use cases. The results and analysis provide a basis for more robust investigations into the capabilities of very high resolution satellite imagery to support the Sustainable Development Goals.https://ieeexplore.ieee.org/document/10146399/Satellite imagerysmall object detectionsolar photovoltaic panel detectionSustainable Development Goals (SDGs)vehicle detectionvery high spatial resolution |
| spellingShingle | Cecilia N. Clark Adane Bedada Benjamin Huff Bogdan Lita Amy B. Newbury Fabio Pacifici Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Satellite imagery small object detection solar photovoltaic panel detection Sustainable Development Goals (SDGs) vehicle detection very high spatial resolution |
| title | Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals |
| title_full | Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals |
| title_fullStr | Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals |
| title_full_unstemmed | Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals |
| title_short | Investigating the Resolution-Performance Trade-off of Object Detection Models in Support of the Sustainable Development Goals |
| title_sort | investigating the resolution performance trade off of object detection models in support of the sustainable development goals |
| topic | Satellite imagery small object detection solar photovoltaic panel detection Sustainable Development Goals (SDGs) vehicle detection very high spatial resolution |
| url | https://ieeexplore.ieee.org/document/10146399/ |
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