Spatial prediction based on Third Law of Geography

Current methods of spatial prediction are based on either the First Law of Geography or the statistical principle or the combination of these two. The Second Law of Geography contributes to the revision of these methods so they are adaptive to local conditions but at the cost of increasing demand fo...

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Main Authors: A‐Xing Zhu, Guonian Lu, Jing Liu, Cheng‐Zhi Qin, Chenghu Zhou
Format: Article
Language:English
Published: Taylor & Francis Group 2018-10-01
Series:Annals of GIS
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/19475683.2018.1534890
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author A‐Xing Zhu
Guonian Lu
Jing Liu
Cheng‐Zhi Qin
Chenghu Zhou
author_facet A‐Xing Zhu
Guonian Lu
Jing Liu
Cheng‐Zhi Qin
Chenghu Zhou
author_sort A‐Xing Zhu
collection DOAJ
description Current methods of spatial prediction are based on either the First Law of Geography or the statistical principle or the combination of these two. The Second Law of Geography contributes to the revision of these methods so they are adaptive to local conditions but at the cost of increasing demand for samples. This paper presents a new thinking about spatial prediction based on the Third Law of Geography which focuses on the similarity of geographic configuration of locations. Under the Third Law of Geography, spatial prediction can be made on the basis of the similarity of geographic configurations between a sample and a prediction point. This allows the representativeness of a single sample to be used in prediction. A case study in predicting spatial variation of soil organic matter content was used to compare the spatial prediction based the Third Law of Geography with those based on the First Law and the statistical principle. It is concluded that spatial prediction based on the Third Law of Geography does not require samples to be over certain size nor to be of a particular spatial distribution to achieve a high quality prediction. The prediction uncertainty associated with spatial prediction based on the Third Law of Geography is more indicative to quality of the prediction, thus more effective in allocating error reduction efforts. These properties make spatial prediction based on the Third Law of Geography more suitable for prediction over large and complex geographic areas.
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spelling doaj-art-e8b9ccf0396e46418e074e15a9fdc9342025-08-20T01:58:23ZengTaylor & Francis GroupAnnals of GIS1947-56831947-56912018-10-0124422524010.1080/19475683.2018.1534890Spatial prediction based on Third Law of GeographyA‐Xing Zhu0Guonian Lu1Jing Liu2Cheng‐Zhi Qin3Chenghu Zhou4Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, ChinaJiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, ChinaEarth Science Department, Santa Monica College, Santa Monica, CA, USAState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, ChinaCurrent methods of spatial prediction are based on either the First Law of Geography or the statistical principle or the combination of these two. The Second Law of Geography contributes to the revision of these methods so they are adaptive to local conditions but at the cost of increasing demand for samples. This paper presents a new thinking about spatial prediction based on the Third Law of Geography which focuses on the similarity of geographic configuration of locations. Under the Third Law of Geography, spatial prediction can be made on the basis of the similarity of geographic configurations between a sample and a prediction point. This allows the representativeness of a single sample to be used in prediction. A case study in predicting spatial variation of soil organic matter content was used to compare the spatial prediction based the Third Law of Geography with those based on the First Law and the statistical principle. It is concluded that spatial prediction based on the Third Law of Geography does not require samples to be over certain size nor to be of a particular spatial distribution to achieve a high quality prediction. The prediction uncertainty associated with spatial prediction based on the Third Law of Geography is more indicative to quality of the prediction, thus more effective in allocating error reduction efforts. These properties make spatial prediction based on the Third Law of Geography more suitable for prediction over large and complex geographic areas.https://www.tandfonline.com/doi/10.1080/19475683.2018.1534890First Law of GeographySecond Law of GeographyThird Law of Geographyspatial predictionspatial interpolationKriging
spellingShingle A‐Xing Zhu
Guonian Lu
Jing Liu
Cheng‐Zhi Qin
Chenghu Zhou
Spatial prediction based on Third Law of Geography
Annals of GIS
First Law of Geography
Second Law of Geography
Third Law of Geography
spatial prediction
spatial interpolation
Kriging
title Spatial prediction based on Third Law of Geography
title_full Spatial prediction based on Third Law of Geography
title_fullStr Spatial prediction based on Third Law of Geography
title_full_unstemmed Spatial prediction based on Third Law of Geography
title_short Spatial prediction based on Third Law of Geography
title_sort spatial prediction based on third law of geography
topic First Law of Geography
Second Law of Geography
Third Law of Geography
spatial prediction
spatial interpolation
Kriging
url https://www.tandfonline.com/doi/10.1080/19475683.2018.1534890
work_keys_str_mv AT axingzhu spatialpredictionbasedonthirdlawofgeography
AT guonianlu spatialpredictionbasedonthirdlawofgeography
AT jingliu spatialpredictionbasedonthirdlawofgeography
AT chengzhiqin spatialpredictionbasedonthirdlawofgeography
AT chenghuzhou spatialpredictionbasedonthirdlawofgeography