Using a hybrid model of 3D GIS and meta-heuristic methods for optimizing tree shade coverage
Author(s):

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background and Objective

Materials and Methods

Two types of data are required to perform the analysis; The building block properties, for example, dimensions, position, and size of the facade, rooftop, and opening components, and the tree properties (height and position). 3D GIS and ACO algorithms have been used to model tree shade coverage optimization. 3D GIS provides abilities for storing, analyzing, and creating 3D topologies, and ACO is used to summarize real-world conditions in a mathematical problem. GIS and trigonometric rules have been used to store geographical information and spatial topology. After storing the position, composition, and description information of 2D and 3D objects by topological data, Duffie and Beckman relations (2013) is used to extract the position of the shadow. Then, according to Church and Revelle, the Maximal Covering Location Problem (MCLP) is defined. For the following 3 reasons, ACO has been used for three-dimensional optimization; 1) The complex trigonometric rules in calculating the shadow coverage on buildings, 2) There is no deterministic solution for optimization problems because of nonlinear constraints including trigonometric functions, 3) The existence of continuous space around the building block that It is possible to place a tree in any position. The details of the steps are; 1) Define the set of possible locations for the tree based on the height, diameter of the canopy, and around space of the building block, 2) Use a method to place the first tree in all possible places around the building block during hot hours on certain days of the summer and calculate the maximum shade coverage on the building block based on the weight of the building components, 3) Remove the places that may be done in the tree canopy to prevent overlapping of tree canopies, 4) Repeat steps 2 and 3 to place the next trees in the possible places around the building block until the number of trees reaches the desired number of trees to create shade. Considering the infinite possible positions, a simplification step is required to limit the number of available positions. Therefore, the constant space is reduced to possible positions for locating Ni trees with two-meter spacing in the N-S and E-W directions. Further, the possible tree positions in front of the opening components are eliminated to make daylight available, have an outlook from the building, and comment through the doors. The minimum spacing of two meters between the trees and the building is set to prevent unnecessary shading on the rooftop.

Results and Discussion

Conclusion

Keywords:

### Optimization , tree shade coverage , 3D geographic information system (3D GIS) , Ant Colony Optimization (ACO) algorithm

Language:
Persian
Published:
Journal of Rs and Gis for natural Resources, Volume:12 Issue: 3, 2021
Pages:
18 to 39
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