空間統計發表關于空間和時空統計的理論和應用的文章。它傾向于那些由新應用產生的理論或將新理論應用于重要實際案例的手稿。純理論研究很少被接受。沒有方法發展的純案例研究是不能發表的。空間統計是對空間和時空數據進行定量分析，包括其統計相關性、準確性和不確定性。空間統計方法在概率論、隨機建模、數理統計以及信息科學中都有廣泛的應用。空間統計用于映射、評估空間數據質量、抽樣設計優化、依賴結構建模以及從有限的時空數據集繪制有效推理。應用領域包括物理領域，如農業、地質學、土壤科學、水文學、生態學、采礦、海洋學、林業、空氣質量、遙感社會/經濟領域，例如空間計量經濟學、流行病學和疾病地圖。空間統計的目的是發表可重復的科學。作者被鼓勵提交和出版程序和數據，連同手稿。

Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies without methodological development are not acceptable for publication.Spatial statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of dependence structures, and drawing of valid inference from a limited set of spatio-temporal data. Application fields includeThe physical domains, e.g. agriculture, geology, soil science, hydrology, ecology, mining, oceanography, forestry, air quality, remote sensingThe social/economic domains, e.g. spatial econometrics, epidemiology and disease mapping.Spatial Statistics aims to publish reproducible science. Authors are encouraged to submit and publish procedures and data, along with the manuscript.