Spatial Data |

Distributed Clustering by Local Direction Centrality on Spark

Sun, 01 Jun 2025 00:00:00 +0000

Parallelises the clustering-by-local-direction-centrality algorithm on Apache Spark with spatial partitioning and performance optimisations for large datasets.

Citation
Gui Z., Huang Z., Chen H., Peng D., Liu Y., Fang G., Lan Q., Zhao A., Wu H. (2025). A performance-enhanced distributed computing framework for clustering by local direction centrality upon Apache Spark. Big Earth Data, 9(4), 797–827.

Cover figure: Enhanced framework of the distributed D-CDC algorithm. From Gui et al. (2025), Big Earth Data.

Dynamic Visual Sub-Embeddings for Image-Text Retrieval

Sun, 01 Jun 2025 00:00:00 +0000

Learns several dynamic visual sub-embeddings per image to capture varied semantics and adds a fast re-ranking stage to improve image-text retrieval.

Citation
Wei W., Gui Z., Wu C., Zhao A., Peng D., Wu H. (2025). Dynamic visual semantic sub-embeddings and fast re-ranking for image-text retrieval. IEEE Transactions on Multimedia, 27, 3781–3796.

Cover figure: Overview of the model. From Wei et al. (2025), IEEE Transactions on Multimedia.

Trajectory Traits: Profiling Drivers from GPS Trajectories

Sun, 01 Jun 2025 00:00:00 +0000

Introduces a Trajectory Trait Scale inspired by the five-factor personality model, scoring drivers’ extroversion, openness, neuroticism and conscientiousness from GPS trajectory features.

Citation
Liu Y., Gui Z., Xu Y., Gao S., Zhao A., et al. (2025). Profiling mobility patterns and driving behaviors of individual drivers via trajectory trait. The Innovation Geoscience, 3(1), 100114.

Graphical abstract from Liu et al. (2025), The Innovation Geoscience.

Map Retrieval Intention Recognition with Geographic Semantics

Sat, 01 Jun 2024 00:00:00 +0000

Recognises users’ map retrieval intentions from relevance feedback, with geographic ontologies guiding intention inference and its iterative updates.

Citation
Gui Z., Liu X., Zhao A., et al. (2024). Map retrieval intention recognition based on relevance feedback and geographic semantic guidance. Information Processing & Management, 61(4), 103767.

Cover figure: Map retrieval workflow enhanced by intention recognition. From Gui et al. (2024), Information Processing & Management.

Radiometric Normalisation of Cross-Sensor Gaofen Images

Tue, 01 Jun 2021 00:00:00 +0000

Normalises radiometry across Gaofen sensors by detecting unchanged pixels with change detection and a chi-square test, then fitting a relative normalisation model.

Citation
Yan L., Yang J., Zhang Y., Zhao A., Li X. (2021). Radiometric normalization for cross-sensor optical Gaofen images with change detection and chi-square test. Remote Sensing, 13(16), 3125.

Cover figure: Bitemporal change detection stage of the proposed relative radiometric normalisation method (part of Fig. 2). From Yan et al. (2021), Remote Sensing.