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Gis And Suitability Analysis One of the most useful application of GIS-based planning is the suitability analysis, including land-use suitability, utility and commercial site selection, etc. Usually, specific physical, cultural and economic requirements are modeled into multiple factors that are further analyzed in a systematic way to generate maps. The result is often with highlighted area as the most suitable sites for the specific purposes. The following case demonstrates how this procedure looks like. In this case, El Yunque, a place located at the northeast corner of Puerto Rico, has five cell towers providing telecommunication services for the residents near by. It is planning to build its sixth tower to increase service coverage. To determine the suitable site for the sixth tower, four criteria were generated based on available data: (1) Distance to existing towers; (2) Elevation; (3) Road Density; (4) Road Proximity;

Locations of existing towers

The new tower should be located away from existing towers so as to reduce coverage overlap. “Eculidean Distance” and “Reclassify” tool were used to illustrate the distance to existing towers.

Suitable elevation for towers was computed by averaging the elevations for existing towers. “Zonal Statistics (Mean)” and “Reclassfiy” were used to generate the suitable cells (in blue).

Road density represents the population density. To provide target services, the tower should be built in dense area. “Focal Statistics (Sum)” were used to compute the density map.

For transportation purposes, in this model, towers should be built over 50m but within 200m from exiting roads. “Euclidean Distance” and “Reclassify” were used to map the suitable area. Using “Raster Calculator” and “Reclassify” were finally used to generate the suitability map. Different weights could be assigned to the factors based on their levels of importance. In this model, the blue area highlights the most suitable sites for building the new tower.

Low Suitability

High Suitability

Site suitability for new tower

Gis And Network Analysis Traditionally, network events are analyzed with spatial methods assuming Euclidean distance on a plane, referred to as planar spatial analysis. However, this assumption is difficult to accept in practice when analyzing network events, in particular, in urbanized areas, because Euclidean distances and their corresponding shortest-path distances are significantly different. Alternatively, network spatial analysis assumes the shortest-path distance on networks. (SANET manual, 2013) SANET is a ArcGIS toolbox developed by professionals from University of Tokyo for analyzing events that occur on networks or alongside works, such as car crashes. Networks may be roads, rivers, pipe-lines etc. The following case depicts the difference between planar density and network density using San Francisco 2011 traffic accident data, and its implication in real life applications. The study area is the South Market neighborhood.

Traditional planar density of taffic accidents in San Francisco

The two maps below demonstrate the advantage of network density analysis.Taking into consideration the actual network, it provides a more acurate result (conceptual model explained to the right) . For example, in the zoomed-in location, the street section rather than the intersection is the place that needs emergency management.

B 150m

150m A



In this model, point A and B are accident locations, point C is non-accident place. Dashed line AB means no direct network, solid line AC-BC represents a connected network. In planar density analysis, point B will be included in point A’s 150m search radius, inceasing the density at point A. However, in network density, point A’s 150m on-network search radius can only cover point C, and the actual distance from A to B is 300m.

Planar density of taffic accidents in South Market Neighborhood

When zooming in, it is noticeable that the intersection without crashes were computed to have high crash density.

Network density of taffic accidents in South Market Neighborhood

In network density map, the high crash density location was identified correctly. It is the street section that has 3 crashes.

Gis And Maket Analysis Business Analyst in ArcGIS provides various tools for spatial analysis for business purposes. ArcGIS desktop could also be used for some basic similar analysis. Huff Model, a theory in spatial analysis that is based on the principle that the probability of a given consumer visiting at a given site is a function of the distance to that iste, its attractiveness, and the distance and attractiveness of competing sites, is commonly used in analyze the customer potential for new businesses, such as retail stores, grocery stores or malls. In practice, census polygons are usually substituted for individual consumers because of the difficulty in calculating distances to people. Gross leasable area is often used to represent attractiveness. This case analyze the market, i.e. regional consumer potential for a new mall at 30th Station in Philadelphia using the Huff Model. Detailed steps are: (1) Converting the census tracts polygon to points; (2) Distance to the new mall and existing malls are calculated; (3) The product of store square footage and weighted population is substituted for attractiveness; (4)Probablity is calculated with distance decay coefficient as 2.

Location of new mall (star) and existing competitors (triangles)

Consumer probability of each tract to visit the new mall

Gis And APIs Both private firms and public entities have offered APIs for the public to gain limited access to their database. The following case demonstrates the use of Twitter API in spatial analysis. The research hypothesis is that Android celphone and iPhone have different spatial distribution regarding the distances to city CBD. In terms of data source, Twitter API is used to retrieve real time data under the assumption that the spatial distribution of cellphone brands revealed in the tweets information reflects the actual distribution of cellphone brands. Four cities -- New York City, Chicago, Houston, Los Angeles -- were chosen as study areas. In order to test the hypothesis, the kernel density of both cellphone types are calculated, and for each cell in each density raster, the distance to recoganized CBD are then calculated. Next line graphs are drawn in R to compare the density distribution for both cellphone types. Finally, a general concept model is developed for each city. **This is a work of Shijia Lu & Hongmou Zhang,. Python and R code available upon request.

A Conceptual Model for Spatial Distribution of Android and iPhone New York City



Los Angeles

We found a similarity in Android and iPhone distribution patterns: there is a ring just outside af each city’s CBD where the unified density of Android phone is relatively higher than that of iPhone. Based on Ernest Burgess’s concentric zonel model, we propsed a concentric cellphone zone model in which the center zone is the high-density center of both brands, just outside the center is an Android zone, and the outlier is the iPhone zone.

New York City



Los Angeles



Lansdowne Downtown Site Plan Lansdowne Borough has a dense, walkable downtown centered on the intersection of Baltimore Avenue and Lansdowne Avenue. It features several historical buildings. However, the street wall is disrupted by several surface parking lot. Also, the parking space (in dashed blue line below) currently severs as frequently connection between Lansdowne and Owen Avenue because of the long block. The site plan features a new garage that greatly reduces surface parking in the area, a new street, and new buildings that would complete the street wall. Some parking spaces are retained in backin angled parking along the new street. And one new building is designed as a civic center that provides community services and programming. Existing Conditions of downtown Lansdowne, PA


Site plan of downtown Lansdowne, PA

N New Street Section (View Direction: East to West)

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