In this research the number of palm trees was calculated from the satellite image programmatically, taking advantage of the accuracy of the spatial resolution of satellite image, the abilities of software recognition, and characteristics of the palm tree, which give it a systematic top view can be distinguished from the satellite image and the manner of cultivation and vertical growth and stability form for long periods of time. While other trees are irregular in shape mostly because of their twisted branches. Palm trees consist of a long stem, a large head, and a large flare that is almost circular and consists of large tufts. The palms have large self-shadows other than ordinary leaves. The large shadows and the circular shape of the upper view give it a special feature that we could use to design a program that distinguishes the shape of the palm without all the trees. Then it counts the number of palms in any field shown in the satellite image. This method is useful in counting the number of palm trees for commercial, agricultural or environmental purposes. It is also can be applied to high resolution satellite imagery such as QuickBird because the resolution of the images is 0.6 meters. Less accurate images such as the 10-meter SPOT do not show the interior shadows of the top view of the palm enough, nor the accurate satellites (5 meters), while the interior shadows appear in high-resolution images only (0.6 meters) or below. It can also be applied to aerial images of less capacity because they are more accurate of course. Satellite images can be obtained free from Google Earth explorer, which can be downloaded free from the Google web site. It connects the user to a global database of high resolution images for all regions of the world.

In this historical survey, we have reviewed researches of shadow phenomenon in satellite images since the beginning of the need for treatment and interpretation in remote sensing.  Because remote sensing enters into many applications and is shared with many sciences, studies on the phenomenon of shadows have been conducted with in different ways. In this review, we attempted to link the evolution of remote sensing techniques with growing resolution of space images as research progresses in the treatment of shadows, because the evolution of space sensor abilities sure increases the options for the interpreter and processor of the satellite image in remote sensing and other purposes. There were also problems that appeared only with the emergence of high-resolution satellite images (0.6 meters) such as the problem of the semi-shadow region. Some researches included some weaknesses and limitations that could not be comprehensive for all satellite images, for all regions of the earth, or for all target shadows.

With the development of high resolution sensors in remote sensing satellites, the shadow phenomena has appeared clearly in satellite image. The shadow is a separated feature in the satellite image, some time it may be considered as a problem due to the loss of ray information at the shaded region, other may be considered as a criteria to the height of the body which has a shadow. The length of shadow depends on the height of the body, location on the earth surface, and the sun location in sky at the imaging time. The sun location is varying every hour during the day and every day during year. These varying is calculated by complex astronomic equations. In this article, we simplified these calculations to just on equation depend on one parameter, and examine this equation by field measurements. The suggested equation is sumsine equation with an enough accuracy to be used in civil, ecological, gardens designing near the high buildings, or architectural purposes. The equation can be used to estimate the building height from the shadow length in the satellite image, as will as it may used to estimate shadow length from the known body height on the earth.

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