Heterogenous Spatial Data: Fusion, Modeling, and Analysis for GIS Applications

Giuseppe Patanè, Michela Spagnuolo

  • 出版商: Morgan & Claypool
  • 出版日期: 2016-04-29
  • 售價: $2,050
  • 貴賓價: 9.5$1,948
  • 語言: 英文
  • 頁數: 156
  • 裝訂: Paperback
  • ISBN: 1627054626
  • ISBN-13: 9781627054621
  • 相關分類: 地理資訊系統 Gis
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

New data acquisition techniques are emerging and are providing fast and efficient means for multidimensional spatial data collection. Airborne LIDAR surveys, SAR satellites, stereo-photogrammetry and mobile mapping systems are increasingly used for the digital reconstruction of the environment. All these systems provide extremely high volumes of raw data, often enriched with other sensor data (e.g., beam intensity). Improving methods to process and visually analyze this massive amount of geospatial and user-generated data is crucial to increase the efficiency of organizations and to better manage societal challenges.

Within this context, this book proposes an up-to-date view of computational methods and tools for spatio-temporal data fusion, multivariate surface generation, and feature extraction, along with their main applications for surface approximation and rainfall analysis. The book is intended to attract interest from different fields, such as computer vision, computer graphics, geomatics, and remote sensing, working on the common goal of processing 3D data. To this end, it presents and compares methods that process and analyze the massive amount of geospatial data in order to support better management of societal challenges through more timely and better decision making, independent of a specific data modeling paradigm (e.g., 2D vector data, regular grids or 3D point clouds).

We also show how current research is developing from the traditional layered approach, adopted by most GIS softwares, to intelligent methods for integrating existing data sets that might contain important information on a geographical area and environmental phenomenon. These services combine traditional map-oriented visualization with fully 3D visual decision support methods and exploit semantics-oriented information (e.g., a-priori knowledge, annotations, segmentations) when processing, merging, and integrating big pre-existing data sets.

商品描述(中文翻譯)

新的資料收集技術不斷出現,並提供了多維空間資料收集的快速和高效手段。航空激光雷達測量、合成孔徑雷達衛星、立體攝影測量和移動式地圖系統越來越多地用於環境的數字重建。所有這些系統提供了極高容量的原始資料,通常還附帶其他感測器資料(例如,波束強度)。改進處理和視覺分析這些龐大的地理空間和用戶生成資料的方法對於提高組織效率和更好地管理社會挑戰至關重要。

在這個背景下,本書提出了一個關於時空資料融合、多變量曲面生成和特徵提取的計算方法和工具的最新觀點,以及它們在曲面逼近和降雨分析方面的主要應用。本書旨在吸引來自不同領域的興趣,如計算機視覺、計算機圖形學、測繪學和遙感,這些領域共同致力於處理三維資料的共同目標。為此,它介紹並比較了處理和分析龐大地理空間資料的方法,以支持更及時和更好的決策,獨立於特定的資料建模範式(例如,2D向量資料、規則網格或3D點雲)。

我們還展示了當前研究如何從大多數地理資訊系統軟體採用的傳統分層方法發展為智能方法,用於整合可能包含有關地理區域和環境現象的重要資訊的現有資料集。這些服務將傳統的地圖導向視覺化與完全三維的視覺決策支持方法相結合,並在處理、合併和整合大型預先存在的資料集時利用面向語義的資訊(例如,先驗知識、註釋、分割)。