Spatial interaction analysis: Some suggestive thoughts from general relativity physics

1971 ◽  
Vol 27 (1) ◽  
pp. 16-38 ◽  
Author(s):  
Walter Isard
Keyword(s):  
General Relativity ◽  
Interaction Analysis ◽  
Spatial Interaction

Quantitative, Demographic, and Geographic Approaches to Internal Migration

1976 ◽  
Vol 8 (3) ◽  
pp. 261-269 ◽  
Author(s):  
D Courgeau
Keyword(s):  
Life Span ◽  
Markov Processes ◽  
Internal Migration ◽  
Interaction Analysis ◽  
Spatial Interaction ◽  
Cohort Analysis ◽  
Spatial Differentiation ◽  
Epoch Analysis ◽  
Migration Analysis

The mainly temporal viewpoint adopted by the demographer allows him to analyse internal migration either by comparing consecutive periods (epoch analysis) or by following the life span of an individual (cohort analysis). This analysis leads to models of migration that are based on Markov processes. The principally spatial viewpoint taken by the geographer enables him to see how migration affects the distribution of the population in an area (spatial-differentiation analysis), and to study the flows between zones (spatial-interaction analysis). In fact only a combined spatial and temporal approach can throw fresh light on migration analysis.

Entropy Theory and Spatial Interaction Analysis

1992 ◽  
pp. 17-38
Author(s):  
Peter Nijkamp ◽  
Aura Reggiani
Keyword(s):  
Interaction Analysis ◽  
Spatial Interaction ◽  
Entropy Theory

scholarly journals A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Weifeng Li ◽  
Xiaoyun Cheng ◽  
Zhengyu Duan ◽  
Dongyuan Yang ◽  
Gaohua Guo
Keyword(s):  
Mobile Phone ◽  
Large Scale ◽  
Pattern Mining ◽  
Interaction Analysis ◽  
Spatial Interaction ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
Mobile Phone Data ◽  
Interaction Patterns ◽  
Critical Activity

The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework.

scholarly journals On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Cleo-Aron Weis ◽  
Benedict Walter Grießmann ◽  
Christoph Scharff ◽  
Caecilia Detzner ◽  
Eva Pfister ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Scalar Field ◽  
Interaction Analysis ◽  
Spatial Interaction ◽  
Serial Sections

scholarly journals Perkembangan dan Corak Kegiatan Agroindustri Keripik Tempe di Kelurahan Purwantoro Kecamatan Blimbing

2020 ◽  
Vol 5 (2) ◽  
pp. 154-166
Author(s):  
Marsela Rinielda Dua ◽  
Ahmad Faruq Hamdani ◽  
Ika Meviana
Keyword(s):  
Household Income ◽  
Crop Production ◽  
Interaction Analysis ◽  
Raw Materials ◽  
Spatial Interaction ◽  
Transportation Equipment ◽  
Spatial Approach ◽  
Food Crop Production ◽  
Spatial Linkages ◽  
Soybean Food

Berdasarkan data UMKM Kota Malang, tempe menjadi salah satu sentra produk agroindustri yang berkembang di Kota Malang. Permasalahannya adalah  Kota Malang tidak memiliki produksi tanaman pangan kedelai. Penelitian bertujuan untuk mengetahui perkembangan dan corak agroindustri, keterkaitan (interaksi) spasial dan kontribusi kegiatan agroindustri. Penelitian menggunakan metode deskriptif kuantitatif dengan menggunakan analisis deskriptif persentase dan tabulasi frekuensi. Tema analisis pendekatan keruangan yang digunakan yaitu analisis interaksi keruangan. Hasil dari perkembangan dan corak kegiatan agroindustri adalah potensi bahan baku kegiatan agroindustri menggunakan 28-321 lonjor perbulan, potensi jasa distribusi dan jasa perdagangan menyalurkan hasil produksinya dengan 2 alur, potensi infrastruktur transportasi menggunakan alat transportasi sepeda motor dan potensi instutusi permodalan yang digunakan Rp.17.250.000 – Rp.31.500.000 perbulan. Keterkaitan (interaksi) spasial kegiatan agroindustri adalah lokasi asal bahan baku agroindustri tempe berada di Kelurahan Purwantoro. Tempat produksi  berada dilokasi yang sama dengan lokasi asal bahan baku di Kelurahan Purwantoro dan Kota Malang menjadi target utama tempat pemasaran. Kontribusi kegiatan agroindustri menciptakan tenaga kerja yang merekrut sebanyak 370 tenaga kerja dan kontribusi terhadap pendapatan rumah tangga Rp.250.000–Rp.400.000 perminggu serta keuntungan bagi pengusaha agroindustri tempe Rp.1.000.000 – Rp.6.750.000 perbulan.Penelitian diharapkan dapat menambah wawasan dan pengetahuan untuk perkembangan agroindustri tempe dan dapat dijadikan sebagai informasi dan referensi dalam penyusunan penelitian. Based on data UMKM in Malang , tempe is one of the centers of developing agroindustrial products in Malang. The problem is that Malang does not have soybean food crop production. The research aims to determine the development and patterns of agroindustry, spatial linkages and the contribution of agroindustry activities. The study used descriptive quantitative method using descriptive percentage analysis and frequency tabulation. The theme of spatial approach analysis used is spatial interaction analysis. The results of the development and pattern of agroindustry activities are the potential of raw materials for agroindustrial activities using 28-321 spikes per month, the potential of distribution services and trade services to channel their production products with 2 grooves, the potential of transportation infrastructure using motorcycle transportation equipment and the potential of capital institutions used Rp.17,250 .000 - Rp.31,500,000 per month. The spatial linkages (interaction) of agroindustry activities are the locations of origin of tempe agroindustry in Purwantoro Village. The production site is located in the same location as the origin of raw materials in Purwantoro Village and Malang City is the main target of the marketing place. The contribution of agroindustry activities creates a workforce that recruits as many as 370 workers and contributes to household income Rp.250,000-Rp.400,000 per week and profits for tempe agroindustry entrepreneurs Rp.1,000,000 - Rp.6,750,000 per month. Research is expected to add insight and knowledge for the development of tempe agroindustry and can be used as information and references in the preparation of research.

SPATIAL INTERACTION ANALYSIS*

1984 ◽  
Vol 24 (4) ◽  
pp. 535-539 ◽  
Author(s):  
Thijs Raa
Keyword(s):  
Interaction Analysis ◽  
Spatial Interaction

Visual Data Mining in Spatial Interaction Analysis with Self-Organizing Maps

2009 ◽  
Vol 36 (3) ◽  
pp. 466-486 ◽  
Author(s):  
Jun Yan ◽  
Jean-Claude Thill
Keyword(s):  
Data Mining ◽  
Interaction Analysis ◽  
Spatial Interaction ◽  
Visual Data ◽  
Visual Data Mining ◽  
Self Organizing Maps ◽  
Self Organizing
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