In this chapter, we discuss the main types and properties of geospatial data (Sec. 1.1) and introduce the main concepts related to spatio-temporal data fusion (Sec. 1.2). ?en, three different problems and partial solutions are discussed that all play an important role in different spatio-temporal data fusion processes. ?e first problem is the alignment of different data sets in a common coordinate system (Sec. 1.3). ?e second problem considers how to match the support or locations of data points of different data sets that are already in a common coordinate system (Sec. 1.4). ?e third major problem focuses on the harmonization of the data contents, which plays an important role when comparing and fusing satellite imagery (Sec. 1.5). In all three problems, different data sets, acquired at different moments or by different sensors, play a role. After this description of the problem setting, storage/access methods (Sec. 1.6) and existing software implementations are discussed together with practical issues considering, e.g., computational feasibility, acquisition, metadata, quality of data, and solutions (Sec. 1.7). Several examples support the discussed methodology.

Chapter 1. Spatio-temporal data fusion

2016

Abstract

In this chapter, we discuss the main types and properties of geospatial data (Sec. 1.1) and introduce the main concepts related to spatio-temporal data fusion (Sec. 1.2). ?en, three different problems and partial solutions are discussed that all play an important role in different spatio-temporal data fusion processes. ?e first problem is the alignment of different data sets in a common coordinate system (Sec. 1.3). ?e second problem considers how to match the support or locations of data points of different data sets that are already in a common coordinate system (Sec. 1.4). ?e third major problem focuses on the harmonization of the data contents, which plays an important role when comparing and fusing satellite imagery (Sec. 1.5). In all three problems, different data sets, acquired at different moments or by different sensors, play a role. After this description of the problem setting, storage/access methods (Sec. 1.6) and existing software implementations are discussed together with practical issues considering, e.g., computational feasibility, acquisition, metadata, quality of data, and solutions (Sec. 1.7). Several examples support the discussed methodology.
2016
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
9781627054621
N/A
File in questo prodotto:
File Dimensione Formato  
prod_357530-doc_116723.pdf

solo utenti autorizzati

Descrizione: Chapter 1. Spatio-temporal Data Fusion
Tipologia: Versione Editoriale (PDF)
Dimensione 1.84 MB
Formato Adobe PDF
1.84 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/320423
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact