L. Arge, Aaron Lowe, Svend C. Svendsen, P. Agarwal
{"title":"地形上的1D和2D流路由","authors":"L. Arge, Aaron Lowe, Svend C. Svendsen, P. Agarwal","doi":"10.1145/3539660","DOIUrl":null,"url":null,"abstract":"An important problem in terrain analysis is modeling how water flows across a terrain creating floods by forming channels and filling depressions. In this article, we study a number of flow-query-related problems: Given a terrain Σ, represented as a triangulated xy-monotone surface with n vertices, and a rain distribution R that may vary over time, determine how much water is flowing over a given vertex or edge as a function of time. We develop internal-memory as well as I/O-efficient algorithms for flow queries. This article contains four main algorithmic results: (i) An internal-memory algorithm for answering terrain-flow queries: Preprocess Σ into a linear-size data structure so given a rain distribution R, the flow-rate functions of all vertices and edges of Σ can be reported quickly. (ii) I/O-efficient algorithms for answering terrain-flow queries. (iii) An internal-memory algorithm for answering vertex-flow queries: Preprocess Σ into a linear-size data structure so given a rain distribution R, the flow-rate function of a vertex under the single-flow direction (SFD) model can be computed quickly. (iv) An efficient algorithm that, given a path 𝖯 in Σ and flow rate along 𝖯, computes the two-dimensional channel along which water flows. Additionally, we implement a version of the terrain-flow query and 2D channel algorithms and examine a number of queries on real terrains.","PeriodicalId":43641,"journal":{"name":"ACM Transactions on Spatial Algorithms and Systems","volume":"9 1","pages":"1 - 39"},"PeriodicalIF":1.2000,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"1D and 2D Flow Routing on a Terrain\",\"authors\":\"L. Arge, Aaron Lowe, Svend C. Svendsen, P. Agarwal\",\"doi\":\"10.1145/3539660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An important problem in terrain analysis is modeling how water flows across a terrain creating floods by forming channels and filling depressions. In this article, we study a number of flow-query-related problems: Given a terrain Σ, represented as a triangulated xy-monotone surface with n vertices, and a rain distribution R that may vary over time, determine how much water is flowing over a given vertex or edge as a function of time. We develop internal-memory as well as I/O-efficient algorithms for flow queries. This article contains four main algorithmic results: (i) An internal-memory algorithm for answering terrain-flow queries: Preprocess Σ into a linear-size data structure so given a rain distribution R, the flow-rate functions of all vertices and edges of Σ can be reported quickly. (ii) I/O-efficient algorithms for answering terrain-flow queries. (iii) An internal-memory algorithm for answering vertex-flow queries: Preprocess Σ into a linear-size data structure so given a rain distribution R, the flow-rate function of a vertex under the single-flow direction (SFD) model can be computed quickly. (iv) An efficient algorithm that, given a path 𝖯 in Σ and flow rate along 𝖯, computes the two-dimensional channel along which water flows. Additionally, we implement a version of the terrain-flow query and 2D channel algorithms and examine a number of queries on real terrains.\",\"PeriodicalId\":43641,\"journal\":{\"name\":\"ACM Transactions on Spatial Algorithms and Systems\",\"volume\":\"9 1\",\"pages\":\"1 - 39\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2022-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Spatial Algorithms and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3539660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Spatial Algorithms and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3539660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
An important problem in terrain analysis is modeling how water flows across a terrain creating floods by forming channels and filling depressions. In this article, we study a number of flow-query-related problems: Given a terrain Σ, represented as a triangulated xy-monotone surface with n vertices, and a rain distribution R that may vary over time, determine how much water is flowing over a given vertex or edge as a function of time. We develop internal-memory as well as I/O-efficient algorithms for flow queries. This article contains four main algorithmic results: (i) An internal-memory algorithm for answering terrain-flow queries: Preprocess Σ into a linear-size data structure so given a rain distribution R, the flow-rate functions of all vertices and edges of Σ can be reported quickly. (ii) I/O-efficient algorithms for answering terrain-flow queries. (iii) An internal-memory algorithm for answering vertex-flow queries: Preprocess Σ into a linear-size data structure so given a rain distribution R, the flow-rate function of a vertex under the single-flow direction (SFD) model can be computed quickly. (iv) An efficient algorithm that, given a path 𝖯 in Σ and flow rate along 𝖯, computes the two-dimensional channel along which water flows. Additionally, we implement a version of the terrain-flow query and 2D channel algorithms and examine a number of queries on real terrains.
期刊介绍:
ACM Transactions on Spatial Algorithms and Systems (TSAS) is a scholarly journal that publishes the highest quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective in that it spans a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually) such as geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.