# The Periodic Table for Spatial Analysis

## Introducing: The Periodic Table for Spatial Analysis

Each element in the **Periodic Table for Spatial Analysis** contains a set of spatial analysis tools. We’ve grouped common tools by color with vector analysis tools on the left and raster analysis on the right.

### Vector Analysis/Conversion

**1. Vector Conversion [VC]** – Converts file formats for points, lines, and polygons and alters data models from vector to raster or vice versa. (Feature to raster, rasterization vs vectorization)**2. Extract [EX]** – Creates a subset of features by clipping, selecting, and splitting vector features. (Clip, select, and split)**3. Overlay [OV]** – Overlays 2 or more vector layers and outputs layers based on overlapping features. (Intersect, union, erase tool)**4. Proximity [PX]** – Generates output based on distances or proximity functions. (Buffer, Voronoi diagrams, and near functions)**5. Spatial Join [SJ]** – Joins attributes from a separate layer based on distance or spatial relationship. (1-M Spatial join “Contains”, 1-1 Touches)**6. Plot Diagrams [PD]** – Builds a graph or diagram based on a set of attributes and geographical locations. (Scatter plot, histograms, bar plots)**7. Geometry Shape [GS]** – Computes the geometric shape of an object. (Compactness, perimeter/area ratio, rectangular fit).

### Tables

**8. Table Tools [TB]** – Performs table functions for storing attribute data (Add field, create domains, reorder fields)**9. Add XY Coordinates [XY]** – Converts a table of XY coordinates (latitude/longitude) into a layer with a defined coordinate system. (Add lat/long coordinates)**10. Calculate Geometry [CG]** – Computes the length of the geometric measurements in the attribute table of vector features. (Calculate length/area)**11. Join Table [JT]** – Appends the attribute columns from one table into another table based on matching record keys. (1:1, 1:M, M:N)**12. Relate [RL]** – Generates a temporary table that displays matching records that associate with one or more matching records. (Relate vs Join)**13. Statistics [ST]** – Calculates statistics based on a numerical field in a table. (RMSE, MAE, sum, mean, count, standard deviation).

### Editing/Cartography

**14. Editing [ED]** – Performs an editing function using the vertices and geometry in one or more layers. (Editing tools, densify, trim, snap, and extend)**15. Conflation [CF]** – Resolves conflicts between two layers that display the same features with mismatching geometries. (Edge-matching, rubber sheeting, conflation)**16. Grid Index [GI]** – Produces a set of consecutive rectangular map sheets that follow a linear feature for mapbook production. (Strip Map, fishnet, tessellation, QGIS Atlas, data driven pages)**17. Cartographic [CA]** – Enhances or generalizes features in a dataset for cartographic display and aesthetic quality. (Smooth, simplify, aggregate).

### 3D Analysis

**18. 3D Analysis [3D]** – Performs an overlay or proximity analysis with 3D features. (3D analysis buffer, intersect, or union)**19. Line of Sight Visibility [LS]** – Identifies obstruction and non-obstruction sections of a straight line from an observer. (Line of sight)**20. Volume [VS]** – Calculates the amount of space above, below, within, or for the purpose of removing or adding material. (Cut/fill)**21. Viewshed [VW]** – Determines locations visible to an observer in all directions with the output as a visibility raster.**22. Skyline [SL]** – Displays visible and obstructed shadowed areas similar to a 3D fan pointing from an observer’s point of view.**23. Space-time Cubes [SC]** – Builds temporal and 3D cubes representing slices of time in a geographic area. (Space-time cubes)

### Network Analysis

**24. Route [RT]** – Finds the optimal route using a set of points and a network dataset. (Network analysis fastest route, find nearest, or shortest distance)**25. Directions [DR]** – Lists the turns, streets, and directions from an origin to a destination point using a network dataset.**26. Optimal Site [OS]** – Selects optimal sites from existing facilities, competing stores, and available demand. (Location-allocation)**27. Coverage [CV]** – Computes the coverage or accessibility that a facility can be reached for a given distance, time, and network dataset. (Service area)**28. OD Cost Matrix [CM]** – Measures the least cost path from multiple origin points to multiple destination points.**29. Huff Model [HM]** – Predicts the probability that consumers will patron retail stores using store size, distance, and census tract population. (Huff gravity model)

### Data Management

**30. Data Management [DM]** – Manages layers with a set of tools to develop, alter, and maintain layers (Merge, append, data compare)**31. Projections [PJ]** – Assigns a coordinate reference system for a layer. (Project, define projection)**32. Generalize Vector [GV]** – Combines adjacent features or slivers based on common attribute values or shared borders. (Dissolve and eliminate)**33. Address Geocoding (AD)** – Translates addresses into geographic locations with latitude and longitude coordinates. (Geocode, reverse geocode)**34. Topology [TP]** – Fixes and catches editing errors such as overshoots, undershoots, slivers, overlaps, and gaps. (Topology rules)**35. Linear Referencing [LR]** – Stores relative positions on a line feature represented by m-values for point/line events. (Linear referencing systems)**36. Spatial Adjustment [SA]** – Aligns and transforms a vector layer that has been displaced, rotated, or distorted like georeferencing for vectors. (Vector bender, displacement links)**37. GeoEnrich [GE]** – Ameliorates existing data with value-added information such as demographic, education, or income attributes. (GeoEnrichment)**38. Sampling [SP]** – Creates a subset of data for sampling at set intervals or randomly. (Regular points, random points in extent)**39. Geotagging [GT]** – Assigns geographic coordinates to digital photos through GPS without georeferencing. (Geotagging)**40. Parcel Fabric [PF]** – Constructs cadastral specific to managing parcel fabric. (Cadastral divisions, split polygon)**41. Attachments [AT]** – Builds attachments to store photos internally as a table relationship.**42. Full Motion Video [FMV]** – Geo-enables video with the footprints coordinated on a map. (Full motion video)**43. COGO [CO]** – Captures coordinates, bearings, and distances from transverse land survey measurements. (COGO – Coordinate Geometry)**44. Point Cloud [PC]** – Manages LAS files with a set of tools to maintain, alter, and interpolate point clouds.**45. Web Service [WS]** – Deploys or imports features from a layer as a web feature/mapping service. (Web feature service, GeoRSS)**46. TIN [TIN]** – Creates a triangular irregular network for depicting three-dimensional terrain surfaces. (TIN mesh creation)**47. Indoor Mapping [IM]** – Incorporates indoor floor plans with digital formats like BIM, Revit, and CAD. (Indoor mapping)**48. Temporal [TM]** – Adds time properties to layers with the date and/or time (Convert time zone, update time field, temporal animation)**49. Real-time Tracking [TR]** – Streams real-time movement of objects or change in status over time. (GeoEvent server, geofencing, make tracking layer)

### Emerging Technology

**50. Big Data [BD]** – Analyzes and extracts data from datasets too large and complex with geographic locations. (GeoAnalytics Desktop Tools)**51. Machine Learning [ML]** – Uses neural networks for classification, prediction, and segmentation through training and labeling. (Deep learning toolset, machine learning)**52. Data Engineering [DE]** – Validates, cleans, and maintains spatial data into a usable form for analysis.**53. IoT [IOT]** – Analyzes real-time data feeds and sensors from the Internet of Things (IoT) platform. (ArcGIS Velocity)**54. Agent-based Simulation and Modeling [AS]** – Simulate scenarios and the emergence of phenomena through individual interactions in geographic space. (Multi-agent modeling environment)**55. Virtual Reality [VR]** – Replaces the field of vision through headsets in a spatial environment.**56. Augmented Reality [AR]** – Enhances 3D features on your phone’s display to interact spatially with the outside world. (Augmented reality)

**Learn about these emerging technologies:**

### Raster Data Management

**57. Georeferencing [GR]** – Stretches, scales, rotates, and skews raster images to better relate to geographic space. (Georeferencing)**58. Mosaic [MO]** – Combines multiple raster images into a seamless, composite raster image. (Mosaic)**59. Raster Creation [RC]** – Generates a raster for a given extent at a specific cell size. (Create a random raster, create a constant raster)**60. Spatial Autocorrelation [AL]** – Measures how dispersed or clustered cells are located in a raster. (Moran’s I)**61. Generalization [RG]** – Cleans raster data by generalizing, smoothing, and altering cells. (Nibble, shrink, expand)**62. Multidimensional [MD]** – Provides an interface for array-oriented data for storing multidimensional variables. (NetCDF)**63. Resample [RS]** – Updates the cell size for converting raster images. (Raster resample: Nearest neighbor, bilinear, and cubic convolution)**64. Raster Painting [PA]** – Draws and erases raster cells with a set of brush, fill, and erase tools.

### Raster Analysis

**65. Raster Analysis [RA]** – Performs raster analysis functions for a raster grid dataset. (Analyze patterns)**66. Map Algebra [MA]** – Applies math-like operations in local, zonal, focal, and global configurations. (Map algebra)**67. Contours [CN]** – Produces lines of constant elevation to represent the topography of the landscape. (Contours)**68. Zonal Statistics [ZS]** – Generates statistics for defined zones of a raster surface. (Zonal statistics – mean, sum, and majority)**69. Cost Path [CP]** – Finds the most cost-effective path, from a start point to a destination, which accumulates the least amount of cost. (Least cost path)**70. Raster Processing [RP]** – Creates a subset of features by clipping, selecting, and splitting raster grids. (Raster clip, split raster)**71. Spatial Regression [RE]** – Generates a prediction surface based on explanatory variables. (Ordinary least squares regression, spatial regression)**72. Terrain Analysis [TA]** – Calculates the characteristics of the terrain from an input raster. (Slope, morphometry, TPI, and roughness)**73. Math Function [MF]** – Executes a math function to update the numerical value on a cell-by-cell basis. (Arithmetic, power, exponential, and logarithmic)**74. Suitability [SU]** – Overlays raster surfaces based on criteria to analyze suitability. (Fuzzy logic weighted sum)**75. Conditional [CON]** – Performs a conditional statement on a raster that generates a binary output. (Greater than, equal to)

**Explore raster data and imagery:**

### Remote Sensing

**76. Band Index [BA]** – Converts a set of imagery bands by leveraging the inherent wavelength properties. (NDVI, tasseled cap, wetness index)**77. Image Stretching [IS]** – Arranges the display of an image by adjusting brightness, contrast, and gamma properties.**78. Image Classification [IC]** – Assigns land cover classes to imagery pixels based on their spectral properties. (Supervised/unsupervised classification)**79. Composite Bands [CB]** – Combines single-band rasters into a composite raster for true color or false color display. (Composite bands)**80. Pansharpening [PS]** – Enhances spatial cell resolution by leveraging the panchromatic band.**81. Atmosphere Correction [AC]** – Corrects remote sensing imagery through scattering inherent in the atmosphere. (Dark object subtraction, radiative transfer models, atmosphere correction)**82. Segmentation [SG]** – Grouping similar pixels from an image into vector objects to recognize objects and features. (Segment mean shift, object-based image analysis)**83. Data Mining [DN]** – Eliminates redundant data from variables that are highly correlated, aggregating essential information. (Principal component analysis)**84. Mensuration [ME]** – Measures the geometry of two and three-dimensional features in an image. (Angles, height, perimeter, volume)**85. Photogrammetry [PH]** – Performs stereographic parallax from two or more vantage points of the same object to measure relief displacement. (Photogrammetry)**86. Oblique [OB]** – Collects images at an angle as opposed to a top-down orthographic perspective.**87. Radar [RD]** – Measures the backscatter of a sent microwave pulses to Earth whether it’s specular, diffuse, or double-bounce reflection. (Synthetic aperture radar)

### Interpolation

**88. Interpolation [IP]** – Estimates unknown values using sampled locations by creating a prediction surface. (IDW, spline, trend)**89. Kriging [KR]** – Generates a probability and prediction surface by building a mathematical function through a semi-variogram. (Kriging and semi-variograms, and geostatistics)**90. Kernel Density [KD]** – Calculates hot and cold spots by applying a density-per-unit function (Heat map)

### Conclusion: The Periodic Table for Spatial Analysis

Spatial analysis may seem like **alchemy** to the inexperienced. But there is a **science** to it. By using spatial analysis, we can find patterns, quantify area, and predict outcomes with **geography** being the common link of it all.

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question <- "is spatial statistics element of spatial analysis?"

if (question == TRUE){

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} else {

return("Excellent table. Great Job")

}

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