{"title":"空间点数据集中密度模式分类的新总体和实际密度见解","authors":"Shazad Jamal Jalal","doi":"10.1007/s12518-025-00646-2","DOIUrl":null,"url":null,"abstract":"<div><p>An essential aspect of spatial science is determining and classifying density patterns in spatial point data. This process includes determining the point coverage ratio (PCR) across the entire geographical area, which is crucial for analysing various spatial science-related topics. Nevertheless, the point and the empty area positions in a whole area are usually not considered in the common density value of points. Therefore, this study introduced novel concepts and formulas for calculating the gross and actual densities (<i>D</i><sub><i>g</i></sub> and <i>D</i><sub><i>a</i></sub>) using the minimum distance between points to determine the PCR for individuals and multiple entire areas. The methodology was implemented on a hypothetical dataset comprising 10 scenarios and two distinct datasets, including 45,443 rural settlement clusters across Region1 (the eastern and southern states) and Region 2 (northern and western states, which includes the Federal Capital Territory (FCT), Abuja) of Nigeria. Consequently, the 10 and five-scale density patterns could quantitatively characterise the actual density utilising the PCR. This contribution assists in better analysing single or multiple spatial point datasets quantitatively.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":"17 4","pages":"791 - 802"},"PeriodicalIF":2.3000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel gross and actual density insights for density pattern classification in spatial point datasets\",\"authors\":\"Shazad Jamal Jalal\",\"doi\":\"10.1007/s12518-025-00646-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>An essential aspect of spatial science is determining and classifying density patterns in spatial point data. This process includes determining the point coverage ratio (PCR) across the entire geographical area, which is crucial for analysing various spatial science-related topics. Nevertheless, the point and the empty area positions in a whole area are usually not considered in the common density value of points. Therefore, this study introduced novel concepts and formulas for calculating the gross and actual densities (<i>D</i><sub><i>g</i></sub> and <i>D</i><sub><i>a</i></sub>) using the minimum distance between points to determine the PCR for individuals and multiple entire areas. The methodology was implemented on a hypothetical dataset comprising 10 scenarios and two distinct datasets, including 45,443 rural settlement clusters across Region1 (the eastern and southern states) and Region 2 (northern and western states, which includes the Federal Capital Territory (FCT), Abuja) of Nigeria. Consequently, the 10 and five-scale density patterns could quantitatively characterise the actual density utilising the PCR. This contribution assists in better analysing single or multiple spatial point datasets quantitatively.</p></div>\",\"PeriodicalId\":46286,\"journal\":{\"name\":\"Applied Geomatics\",\"volume\":\"17 4\",\"pages\":\"791 - 802\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12518-025-00646-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-025-00646-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Novel gross and actual density insights for density pattern classification in spatial point datasets
An essential aspect of spatial science is determining and classifying density patterns in spatial point data. This process includes determining the point coverage ratio (PCR) across the entire geographical area, which is crucial for analysing various spatial science-related topics. Nevertheless, the point and the empty area positions in a whole area are usually not considered in the common density value of points. Therefore, this study introduced novel concepts and formulas for calculating the gross and actual densities (Dg and Da) using the minimum distance between points to determine the PCR for individuals and multiple entire areas. The methodology was implemented on a hypothetical dataset comprising 10 scenarios and two distinct datasets, including 45,443 rural settlement clusters across Region1 (the eastern and southern states) and Region 2 (northern and western states, which includes the Federal Capital Territory (FCT), Abuja) of Nigeria. Consequently, the 10 and five-scale density patterns could quantitatively characterise the actual density utilising the PCR. This contribution assists in better analysing single or multiple spatial point datasets quantitatively.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements