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Combining spatial data

Xem 1-6 trên 6 kết quả Combining spatial data
  • GIS has been coming of age. Millions of people use one GIS or another every day, and with the advent of Web 2.0 we are promised GIS functionality on virtually every desktop and web-enabled cellphone. GIS knowledge, once restricted to a few insiders working with minicomputers that, as a category, don’t exist any more, has proliferated and is bestowed on students at just about every university and increasingly in community colleges and secondary schools.

    pdf121p tailieuvip13 19-07-2012 36 5   Download

  • This article systematizes the related researches, classifies existing GIS models, reviews and recommends the combination of spatial components for the construction of residential buildings at the detailed level (LODs) in three-dimensional (3D) space, so receivable result is a GIS new data model, this new model is called IOLODs.

    pdf9p vihercules2711 26-03-2019 8 0   Download

  • Using the analytic hierarchy process (AHP) method for multi-index evaluation has special advantages, while the use of geographic information systems (GIS) is suitable for spatial analysis. Combining AHP with GIS provides an effective approach for studies of mineral potential mapping evaluation. Selection of potential areas for exploration is a complex process in which many diverse criteria are to be considered.

    pdf12p anhnhoe11 12-04-2013 79 11   Download

  • In ARIES, Ecosystem Services are the effects on human well-being of the flow of benefits from an ecosystem endpoint to a human endpoint at given extents of space and time. The methodology combines spatially explicit models of ecosystem service provision and use with dynamic flow models to describe the distribution of benefits across the landscape. The exact form of these models depends on the specific context of application and is chosen by means of machine reasoning, on the basis of data analysis and ontological connotations of the services (e.g.

    pdf12p connhobinh 07-12-2012 35 2   Download

  • The spatial information related to these factors can be derived from remote sensing data, ground based information, and several other data sources. Geographic Information System (GIS) is a very powerful tool for the integration of different types of data. Over the past few years, there have been significant developments of GIS for spatial data analysis. Efficient landslide susceptibility mapping can be carried out by combining GIS with image processing capabilities (Sarkar and Kanungo, 2004).

    pdf12p mat_vang1 16-01-2019 5 0   Download

  • In recent years, under impacts of human activities and climate change, flood has been increased in both the frequency and magnitude, causing lots of damages to people. This study presents a method to evaluate the direct spatial damages of flooding based on inundation depth and land use data. Damage functions for different types of land use arc selected and applied. Matlab strings and GIS are combined to calculate damage in monitery term. The method is applied for estimating loss caused by thc flood event November 1999 for Huong rivce basin.

    pdf10p dem_thanh 22-12-2012 23 3   Download

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