• Tobler’s second law of geography, “the phenomenon external to a geographic area of interest affects what goes on inside,” is probably the most widely accepted.
• the uncertainty principle: “that the geographic world is infinitely complex and that any representation must therefore contain elements of uncertainty, that many definitions
used in acquiring geographic data contain elements of vagueness, and that it is impossible to measure location on the Earth’s surface exactly.
 Dividing the land differently may produce different statistical results from the same underlying dataset, an example of which can be found in Simpson’s paradox.
 Arbia’s law builds on Tobler’s first law of geography which states, “Everything is related to everything else, but near things tend to be more related than distant.”
Other Proposed Second Laws of Geography Some have argued that geographic laws do not need to be numbered.
Arbia’s law of geography states, “Everything is related to everything else, but things observed at a coarse spatial resolution are more related than things observed at a finer
 The laws of geography need not be numbered, however.
Importantly, when working with spatially aggregate data (either in vector or raster) at a coarse resolution, it is impossible to make assumptions about what that data looks
like at a finer resolution.
 Background Since Tobler first invoked the first law of geography in his 1970s paper, there have been many attempts at a second law, including Tobler’s second
law of geography, and Arbia’s law is one such contender.
Thus, a coarse resolution has a soothing effect on the image, making land cover appear more homogenous than an image with a fine spatial resolution.
[‘Arbia, Giuseppe; Benedetti, R.; Espa, G. (1996). “”Effects of MAUP on image classification””. Journal of Geographical Systems. 3: 123–141.
o ^ Jump up to:a b c d e f g h i Tobler, Waldo (2004). “On the First Law of Geography: A Reply”. Annals of the
Association of American Geographers. 94 (2): 304–310. doi:10.1111/j.1467-8306.2004.09402009.x. S2CID 33201684. Retrieved 10 March 2022.
o ^ Jump up to:a b Smith, Peter (2005). “The laws of geography”. Teaching Geography. 30 (3): 150.
o ^ Otto,
Philipp; Dogan, Osman; Taspınar, Suleyman (November 8, 2022). “A Dynamic Spatiotemporal Stochastic Volatility Model with an Application to Environmental Risks”. arXiv:2211.03178 [stat.ME].
o ^ Jump up to:a b c Hecht, Brent; Moxley, Emily (2009).
“Terabytes of Tobler: Evaluating the First Law in a Massive, Domain-Neutral Representation of World Knowledge”. Spatial Information Theory 9th International Conference, COSIT 2009, Aber Wrac’h, France, September 21–25, 2009, Proceedings. Lecture
Notes in Computer Science. Springer. 5756: 88. Bibcode:2009LNCS.5756…88H. doi:10.1007/978-3-642-03832-7_6. ISBN 978-3-642-03831-0.
o ^ Amdaoud, Mounir; Arcur, Giuseppe; Levratto, Nadine; Succurro, Marianna; Costanzo, Damiana (2020). “Geography
of COVID-19 outbreak and first policy answers in European regions and cities”.
o ^ Zhang, Boen; Xu, Gang; Jiao, Limin; Liu, Jiafeng (January 2019). “The scale effects of the spatial autocorrelation measurement: aggregation level and spatial resolution
January 2019 International J”. International Journal of Geographical Information Science. 33 (5): 1–22. doi:10.1080/13658816.2018.1564316. S2CID 68155432. Retrieved 6 January 2023.
o ^ Jump up to:a b c d e f Goodchild, Michael (2004). “The Validity
and Usefulness of Laws in Geographic Information Science and Geography”. Annals of the Association of American Geographers. 94 (2): 300–303. doi:10.1111/j.1467-8306.2004.09402008.x. S2CID 17912938.
o ^ Wu, Jianguo (2004). “Effects of changing scale
on landscape pattern analysis: scaling relations” (PDF). Landscape Ecology. 19 (2): 125–138. doi:10.1023/B:LAND.0000021711.40074.ae. S2CID 16977988.
o ^ Taylor, Peter (1983). Distance Decay in Spatial Interactions (PDF). ISBN 0-86094-090-X.
Doignon, Yoann; Oliveau, Sébastien (2015). “Territorial grids in the Mediterranean: space versus population”. Bollettino dell’Associazione Italiana di Cartografia. 154: 46–63. doi:10.13137/2282-472X/11827.
o ^ Jensen, John (2016). Introductory
digital image processing: a remote sensing perspective. Glenview, IL: Pearson Education, Inc. p. 623. ISBN 978-0-13-405816-0.
o ^ Tobler, Waldo (1969). “Geographical filters and their inverses”. Geographical Analysis. 1 (3): 234–53. doi:10.1111/j.1538-4632.1969.tb00621.x.
Jump up to:a b Openshaw, Stan (1983). The Modifiable Areal Unit Problem (PDF). ISBN 0-86094-134-5.
o ^ Jump up to:a b Chen, Xiang; Ye, Xinyue; Widener, Michael J.; Delmelle, Eric; Kwan, Mei-Po; Shannon, Jerry; Racine, Racine F.; Adams, Aaron; Liang,
Lu; Peng, Jia (27 December 2022). “A systematic review of the modifiable areal unit problem (MAUP) in community food environmental research”. Urban Informatics. 1. doi:10.1007/s44212-022-00021-1. S2CID 255206315. Retrieved 27 December 2022.