With the huge number of pilgrims performing Hajj (Islamic Pilgrimage), the use of urban space is a major concern for engineers, urban
designers, and urban planners. Pilgrims must stay in the Holy Area (Arafat) for one day as part of Hajj rituals. For this reason, pilgrims are housed
in lightweight temporary structures: tents. In Arafat, these tents are constructed before each Hajj season. The arrangement of these tents differs
from one year to another and from location to location. For the spatial and temporal constraints of ritual happening in Arafat, space optimization is
an important issue. The extensive demand for a rapid, automatic, and high quality algorithm for feature extraction has been the subject of much
recent research. In this paper, we present an approach for detecting and extracting tents using airborne images. The approach is used to calculate
the areas covered by tents. It utilizes the intensity in digital images in two stages. First, it classifies tents from other features in Arafat\'s
environment. Second, it calculates the number of tents based on image matching subroutines. This can evaluate the design and planning of tents\'
layout and space optimization. Using this automatic approach, the number of pilgrims in a tested area can also be estimated according to the
average capacity of one-meter squares covered by tents. Moreover, services, utilities, and transportation needs can be determined more precisely.
An actual sample area in Arafat during the Hajj season is used to test the approach developed in this research.
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