The variations of gravity were measured with a high precision LaCoste-Romberg D gravimeter during a total solar eclipse to investigate the effect of a solar eclipse on the gravitational field. The observed anomaly (7.0 Ϯ2.7)ϫ10 Ϫ8 m/s 2 during the eclipse implies that there may be a shielding property of gravitation.PACS number͑s͒: 04.80.Cc, 04.80.Nn, 95.10.Gi

There exists a sort of dynamic geographic phenomenon in the real world that has a property which is maintained from production through development to death. Using traditional storage units, e.g., point, line, and polygon, researchers face great challenges in exploring the spatial evolution of dynamic phenomena during their lifespan. Thus, this paper proposes a process-oriented two-tier graph model named PoTGM to store the dynamic geographic phenomena. The core ideas of PoTGM are as follows. 1) A dynamic geographic phenomenon is abstracted into a process with a property that is maintained from production through development to death. A process consists of evolution sequences which include instantaneous states. 2) PoTGM integrates a process graph and a sequence graph using a node–edge structure, in which there are four types of nodes, i.e., a process node, a sequence node, a state node, and a linked node, as well as two types of edges, i.e., an including edge and an evolution edge. 3) A node stores an object, i.e., a process object, a sequence object, or a state object, and an edge stores a relationship, i.e., an including or evolution relationship between two objects. Experiments on simulated datasets are used to demonstrate an at least one order of magnitude advantage of PoTGM in relation to relationship querying and to compare it with the Oracle spatial database. The applications on the sea surface temperature remote sensing products in the Pacific Ocean show that PoTGM can effectively explore marine objects as well as spatial evolution, and these behaviors may provide new references for global change research.

There exists a kind of trajectories of dynamic geographic phenomena, which have splitting, merging, or merging-splitting branches. Clustering these complex trajectories may help to more deeply explore and analyze the evolution mechanism of geographic phenomena. However, few methods explore the clustering patterns of such trajectories. Thus, we propose a Process-oriented Spatiotemporal Clustering Method (PoSCM) for clustering complex trajectories with multiple branches. The PoSCM includes the following three parts: the first represents the trajectories with a ''process-sequence-node'' structure inspired by a process-oriented semantic model; the second designs a hierarchical similarity measurement method to calculate the similarity of space, time, thematic attributes and evolution structure between any two trajectories; the last uses a density-based clustering algorithm to mine the trajectories' clustering patterns. Simulation experiments are used to evaluate PoSCM and to demonstrate the advantages by comparing against that of the VF2 algorithm. A case study of sea surface temperature abnormal variation (SSTAV) trajectories in the Pacific Ocean is addressed. The clustering results not only validate well-known knowledge but also provide some new insights about the evolution characteristics of SSTAVs during El Niño Southern Oscillation (ENSO); these insights may provide new references for further study on global climate change. INDEX TERMS Spatiotemporal trajectory clustering, dynamic geographic phenomena, evolutionary behaviors, Pacific ocean, sea surface temperature anomalies.