Lesson 1 - Part 1: Spatial Autocorrelation

this video is about spatial autocorrelation it will cover the first law of geography and ways of measuring spatial autocorrelation what is the first law of geography a famous American Swiss geographer named Waldo Tobler wrote the first law of geography which states everything is related to everything else but near things are more related than distant things geography is very much the study of the relationship between phenomena and space and the vast majority of natural phenomena closely relates to the things closest to it for example the climate in Washington DC is much more similar to the climate in Baltimore and less so to the climate of Los Angeles Tobler's law provides a simple introduction to a crucial concept in geography spatial autocorrelation spatial autocorrelation examines how similar one data point is to other data points around it to understand if phenomena relate in space positive autocorrelation leads to the clustering of data points perfect clustering would look something like this with like data sticking closely to like negative autocorrelation leads to the dispersal of data perfect dispersal would look something like a chessboard where every point is completely surrounded by features unlike it perfect negative autocorrelation is incredibly rare in the natural world a spatial autocorrelation of zero indicates randomness and that the locations of data points are not related in space spatial autocorrelation explains a lot of behavior in geography and it is very important to take it into account when doing geographic analysis sometimes though spatial autocorrelation can actually interfere with data processing many important statistics assume that all data is randomly distributed and having internal relationships between the data can cause non-negligible interferences in modeling behavior and calculating important statistics in the data set in conclusion spatial autocorrelation helps us understand how data relates to itself in space it is measured on a scale from positive to negative and it is crucial to know the spatial autocorrelation of a data set when trying to understand patterns in the data thanks for watching I hope you liked my video

Channel: GIS for Youth Empowerment

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Keywords: Spatial Analysis (Literature Subject), Geography (Field Of Study), Geographic Information System (Industry), Learning, Lesson, Open Source Initiative (Nonprofit Organization)

Id: M9ecMxVG6jQ

Length: 2min 15sec (135 seconds)

Published: Sat Jun 27 2015