Multi-Distance Spatial Cluster Analysis (Ripleys K Function) Tool ArcGIS

Multi-Distance Spatial Cluster Analysis (Ripleys K Function) Tool, Analyzing Patterns Toolset, Spatial Statistics ArcToolbox
Summary
Determines whether features, or the values associated with features, exhibit statistically significant clustering or dispersion over a range of distances.
Usage
This tool requires projected data to accurately measure distances.Tool output is a table with fields: ExpectedK and ObservedK containing the expected and observed K values, respectively. Because the L(d) transformation is applied, the ExpectedK values will always match the Distance value. A field named DiffK contains the Observed K values minus the Expected K values. If a confidence interval option is specified, two additional fields named LwConfEnv and HiConfEnv will be included in the Output Table as well. These fields contain confidence interval information for each iteration of the tool, as specified by the Number of Distance Bands parameter. The K function will optionally create a graph layer summarizing results.When the observed K value is larger than the expected K value for a particular distance, the distribution is more clustered than a random distribution at that distance (scale of analysis). When the observed K value is smaller than the expected K value, the distribution is more dispersed than a random distribution at that distance. When the observed K value is larger than the HiConfEnv value, spatial clustering for that distance is statistically significant. When the observed K value is smaller than the LwConfEnv value, spatial dispersion for that distance is statistically significant. Additional information about interpretation is found in How Multi-Distance Spatial Cluster Analysis (Ripley's K-function) works .Enable the Display Results Graphically parameter to create a line graph summarizing tool results. The expected results will be represented by a blue line while the observed results will be a red line. Deviation of the observed line above the expected line indicates that the dataset is exhibiting clustering at that distance. Deviation of the observed line below the expected line indicates that the dataset is exhibiting dispersion at that distance. The line graph is created as a graph layer; graph layers are temporary and will be deleted when you close ArcMap. If you right-click the graph layer and select Save, the graph can be written to a Graph File. If you save your map document after saving your graph, a link to the graph file will be saved with your .mxd. For more information about graph files, see Exploring and visualizing data with graphs.For line and polygon features, feature centroids are used in distance computations. For multipoints, polylines, or polygons with multiple parts, the centroid is computed using the weighted mean center of all feature parts. The weighting for point features is 1, for line features is length, and for polygon features is area.The Weight Field is most appropriately used when it represents the number of incidents or counts.When no Weight Field is specified, the largest DiffK value tells you the distance where spatial processes promoting clustering are most pronounced.
spatial analysis ,spatial statistics ,point pattern analysis ,spatial data analysis ,cluster analysis ,k function ,statistical analysis ,geo-statistical analysis ,geospatial analysis ,l function ,spatial statistics tools ,spatial clustering ,spatial distribution ,data analysis ,spatial prediction ,bivariate and network k function ,performing analysis ,spatial stats ,spatial autocorrelation ,crime analysis ,spatial data ,f function ,j function ,kd function

شرح الأداة :
لمتابعة موقع GISforWE من هنا:
موقع لكل مهتم في مجال نظم المعلومات الجغرافية GIS من هنا:
احترف التعامل مع البيانات الجغرافية من خلال برامج ArcGIS:
تعلم اساسيات إنشاء قواعد البيانات الجغرافية من هنا:
اليك صفحه ومجموعة على الفيس بوك لتعلم أكثر بما يخص نظم المعلومات الجغرافية (GIS) و برامج ArcGIS من خلال هذه الروابط:
مجموعة على الفيس بوك ArcGIS :
مجموعة على الفيس بوك GIS for WE - ArcGIS:
صفحة الفيس بوك GIS for WE:
رابط فيديو مقدمة تعلم على برامج ArcGIS بثلاثة مراحل :

#ArcGIS
#Analysis_GIS
#Data_Analysis

اعداد وتقديم المطور والباحث في مجال نظم المعلومات الجغرافية حسام جعبه
رام الله - فلسطين.

#GISforWE
GIS for World of E-Learning