From Geospatial Data Cube to AI Cube: the Open Geospatial Engine (OGE) Approach
| Autor: | P. Yue, K. Wang, H. Xu, J. Gong, L. Xiang |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol X-4-2024, Pp 441-446 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2194-9042 2194-9050 |
| DOI: | 10.5194/isprs-annals-X-4-2024-441-2024 |
| Popis: | The Earth Observation (EO) analytics are moving from local systems to online cloud computing platforms such as Google Earth Engine (GEE) and Open Geospatial Engine (OGE). A typical approach in existing efforts is to leverage geospatial data cubes with cloud computing to support large-scale big EO data analytics in Digital Earth systems. While online analytical processing (OLAP) can be enabled using the cube approach, it is still not clear how geospatial artificial intelligence (GeoAI) can be incorporated in data cubes to benefit the cube infrastructure. Such an investigation can consolidate the vision of an AI-ready SDI (Spatial Data Infrastructure). The paper presents a systematic approach to incorporate GeoAI models into geospatial data cubes to help create an AI Cube. It covers on-demand model retrieval, cube data and model integration, and distributed model inference. The approach is demonstrated in OGE, which is an EO cloud computing platform layered on the GeoCube implementation. The results show that such an AI Cube enriches a cube infrastructure with GeoAI capabilities, facilitates the on-demand coupling of cube data and GeoAI models, and improves the performance of GeoAI inference. |
| Databáze: | Directory of Open Access Journals |
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