Abstract
Tidal flats (non-vegetated area) are soft-sediment habitats that are alternately submerged and exposed to the air by changeable tidal levels. The tidal flat dynamics research mainly utilizes the cell-level comparisons between the consecutive snapshots, but the in-depth study requires more detailed information of the dynamic activities. To better track, represent, and analyze tidal flats’ dynamic activities, this study proposes an integrated approach of a three-level Geographic Information Science (GIS) framework and a graph model. In the three-level GIS framework, the adjacent cells are assembled as the objects, and the objects on different time steps are linked as lifecycles by tracking the predecessor–successor relationships. Furthermore, eleven events are defined to describe the dynamic activities throughout the lifecycles. The graph model provides a better way to represent the lifecycles, and graph operators are utilized to facilitate the event analysis. The integrated approach is applied to tidal flats’ dynamic activities in the southwest tip of Florida Peninsula from 1984 to 2018. The results suggest that the integrated approach provides an effective way to track, represent, and analyze the dynamic activities of tidal flats, and it offers a novel perspective to examine other dynamic geographic phenomena with large spatiotemporal scales.
Highlights
The study of dynamic geographic phenomena is a challenging topic in Geographic
A more critical problem is how to track better, represent, and analyze the dynamic activities from the delineated results, which can help obtain the relevant information to fully describe the spatiotemporal characteristics of dynamic geographic phenomena and explain the reasons behind them
As the delineated results can represent the static state of the dynamic geographic phenomena at one single moment, the first stage makes it possible to find the temporal sequences of objects, their attributes, and relationships by associating the states at different moments along the time sequence
Summary
As the delineated results can represent the static state of the dynamic geographic phenomena at one single moment, the first stage makes it possible to find the temporal sequences of objects, their attributes, and relationships by associating the states at different moments along the time sequence. Worboys (2005) [1] highlights “the continuants that endure through time” and “the occurrents that happen or occur and are gone” This perception further deepens and expands the concept of objects in the second stage, and it yields the eventbased perspective, which provides a possible way to better model the dynamic geographic phenomena. McIntosh and Yuan (2005) [9] propose a four-level framework (zone, sequence, process, and event), which facilities the spatiotemporal query and analysis for the distributed dynamic geographic phenomena, and a case study of rainstorms is implemented. AAccaasseessttuuddyy iiss aapppplliieedd ttoo tthhee ttiiddaall flflaattss iinn tthhee ssoouutthhwweessttttiippoofftthheeFFlloorriiddaappeennininssuulalfarofrmom1918948t4ot2o012801. 8O. wOiwngintgo ttohethdeedveelvoeplompemnetnotf ohfighhig-phe-prfeorrfmoramnacnecceloculoducdomcopmuptiuntginign irnecreecnetnyteyaerasr, si,t iht ahsasbebceocmomeefefaeasisbibleletotoaacccceessss,,pprroocceessss,, aanndd aannaallyyzzee ggeeoossppaattiiaall bbiiggddaattaa,, aanndd tthheerreeffoorree,, oouurrinitnetgergartaetdedapapprporaocahcchancabne abpepalipedpltioedthteolatrhgeerlasrpgaetirotsepmatpiootreaml spcoarleasl. sWcailtehst.hWe iatvhatihlaebalevabiilgabdlaetabsiegtsd,atthaesemtsa,cthhienemlaecahrnininegleaalrgnoirnitghmalgsoarriethwmidsealryeuwseiddeilnyculoseudd icnomclopuudtincgompplautftionrgmps.laTtfhoermras.ndTohme rfaonrdesotm(RfFo)remsta(cRhFin)emleaacrhnininegleaalgrnoirnitghmalgiosruitshemd tios udseeldinteoatdeetlhineecaetell tlheveecletlildlaevl flelattidinaflofrlmataitniofonrminatthioisnsitnudthyi.s study
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