Application of GIS and Geostatistical Interpolation Method for Groundwater Mapping

Chakma, Ashesh; Bhowmik, Tridip; Mallik, Santanu; Mishra, Umesh

doi:10.1007/978-981-16-4629-4_29

Cited by 5 publications

(1 citation statement)

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“…Correlation: Interpolate [28] lines in space to obtain a series of elevation time series data. Find the similarity of all elevation time series data in MATLAB.…”

Section: Mathematical Operations That Represent Featuresmentioning

confidence: 99%

Time Series Characteristics of Terrain Data

2024

geors

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Traditional Chinese geography has a basic concept: people choose the terrain, and the corresponding terrain is also related to people. For a long time, the analysis of mountainous terrain from the perspective of people has influenced the understanding of terrain, but today, the explanation of terrain from the perspective of terrain profiles, Digital Elevation Model (DEM) data has updated the method of understanding terrain. DEM data provides data support for terrain profiles. This article treats terrain profiles as time series data, although there is a view that time can be studied in a fixed spatial position, or space can be analyzed at a fixed period [1]. In the specific example of the Goguryeo Mountain City, this article compares the archeological and historical data of the mountain city and finds spatial correlation between the terrain features of the mountain city and the historical development features. Traditional Chinese geography believes that terrain influences the development of history, and the connection between the two can be explained by "image". This article believes that the connection between the two can also be solved by "number". This explanation is not only applicable to the historical field, but also to other issues explaining terrain features. This article finds that time series data can represent a force in the terrain. This article proposes an analysis method that can find time series feature analysis, which can be combined with the target terrain.

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“…Correlation: Interpolate [28] lines in space to obtain a series of elevation time series data. Find the similarity of all elevation time series data in MATLAB.…”

Section: Mathematical Operations That Represent Featuresmentioning

confidence: 99%