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Application of Multi-Spectral Imagery
The following presents a brief example of using remote sensing for mapping the Exodus route. It deals with locating Elim.
To begin with, Exodus chapter 15 tells us the Israelites emerged from the Red Sea and went three days journey into the wilderness and came to Marah. Their next stop was at Elim. The Book of Numbers chapter 33, provides the places the Israelites camped at. I concluded that Elim must be one days journey from Marah (based on the sequences in the Scriptures). Elim is referred to in the Bible as having 12 wells of water and seventy Palms. In other words it is a desert oasis. The event occurred over 3200 years ago. Is it possible there could be any evidence of this place today?
Numbers 33:8-9
8They departed from before Hahiroth and passed through
the midst of the sea into the wilderness, went three days' journey in the
Wilderness of Etham, and camped at Marah. 9They moved from Marah and
came to Elim. At Elim were twelve springs of water and seventy palm trees;
so they camped there.
You can view our area of interest by clicking the link below:
Space Shuttle image of the southern Suez canal and Gulf of Suez (600 kB)
Using GIS software and assuming the Israelites traveled about 10 miles per day, I traced the Israelites to a location in the desert just east of the Red Sea (modern Gulf of Suez) The yellow lines in the figure below depict the route of the Israelites. Each tick mark (on the yellow line) represents a days journey (10 miles). A total distance of 40 miles is traveled from the Bitter Lake (Red Sea) crossing point. I then checked to see if there is a place that could be an oasis or some ancient spot that could have once been an oasis. Oasis are formed because there is a water supply in the area. Could there still be water in this location today?
Referring to the GIS map below, the end of the yellow line indicates the point where the Israelites completed their 4th day's journey since emerging from the sea (Great Bitter Lake). The GIS data indicates the presence of a Wadi and water run off. This is the light blue area near the bottom end of the yellow line.
The end of the yellow line is now our area of interest. The next step is to analyze satellite imagery for the presence of water and vegetation.
The image shown below is a Landsat TM image of the Northern Sinai Peninsula. Landsat TM (Thematic Mapper) is a remote sensing satellite that provides 30 meter resolution imagery. It is unique because it images in 7 spectral bands. Although we have seven bands, we would typically view them in groups of three (Red, Green and Blue). In Landsat terminology Bands 1, 2, and 3 represent the visible portion of the spectrum. In order to view other bands we have to improvise how the images are viewed. These remaining bands are invisible and represent the infrared portions of the spectrum.
In the above image, the area of interest is in the red box.
In the examples below, you will be introduced to the Landsat 7 spectral bands. To familiarize yourself, see if you can locate our area of interest in the photo below. (Hint - it is at the area at the center of the photo just upward). Notice the changes that occur in each of the black and white pictures. This is due to the use of special band pass filters in the satellite camera system. The seven images can be analyzed to find anomalies that may be of interest to the analyst. Typically, remote sensing software uses classification algorithms to search all seven bands and classify things of interest.
Band 1 - Blue (0.45 - 0.52 µm)
Band 1 is designed for water body penetration, making it useful for coastal water mapping. Also, useful for soil/vegetation discrimination, forest type mapping and cultural feature identification. Notice we can see beneath the water (to some degree).
Band 2 - Green (0.52 -0.60 µm)
Band 2 is useful for measuring green reflectance of vegetation. It can also be used for cultural feature identification.
Band 3 - Red (0.63 -0.69 µm)
Band 3 is sensitive to chlorophyll absorption region. It is useful for vegetation analysis and can even be used to differentiate plant types. It is also useful for cultural feature identification.
Band 4 - Near Infrared (0.76 -0.90 µm)
This band is useful for determining vegetation types, vigor and biomass survey, delineating water bodies, and for soil moisture discrimination.
Band 5 - Mid-Infrared (1.55 -1.75 µm)
Band 5 is useful for analyzing vegetation moisture content and soil moisture. Also useful for differentiation of snow from clouds. Notice how bright the land features are. This is caused by the soil reflecting infrared light in that band. The water appears dark because it absorbs infrared light.
Band 6 - Thermal Infrared (10.4 -12.5 µm)
Band 6 is useful in vegetation stress analysis, soil moisture discrimination, and thermal mapping applications. It is fuzzy because this band has 120 meter resolution.
Band 7 - Mid-Infrared (2.08 -2.35 µm)
Band 7 is useful for discrimination of mineral and rock types. Also sensitive to vegetation moisture content.
Viewing Remote Sensing Images
Traditionally, we can only view infrared as black and white images, for there is no such thing as color in this region of the spectrum. What we can do is improvise and produce what is called false color infrared by designating any of the bands as red, green and blue. That is, we can combine three different black and white bands to produce a color picture. Remember that red, green and blue are the primary colors that our human eyes respond to. When we produce false color IR images, it is important to understand the effects that IR has upon our new color pictures.
Now lets take a brief look at what happens when we combine different Landsat bands. In this case, I was trying to locate an oasis in the desert. Therefore, water and vegetation are the primary interest. Some of the results are shown below:
Bands 1, 2, and 3 show the the visible spectrum of light. This is the spectrum that our eyes actually see in. By examining the image notice the dark areas. This indicates there could be moisture and places where water has flowed. To further analyze the area we must look in the invisible portions for the spectrum . We can combine them with other (IR.) bands and produce false color images.
Bands 2, 3, and 5 - These bands were used to evaluate the moisture content of the soil.
Bands 2, 3, and 4 - In this configuration band 4 is the Near IR Band. Vegetation shows up as reddish in color. Although it is not too noticeable, see the next picture.
Bands 2, 3, and 4 magnified
The redish areas are indicative of vegetation (at this magnification the image becomes pixelated due to the 30 meter per pixel resolution which is about 98 ft). The middle area is about 400 meters. Tree groupings would cause the reddish pixels.
Bands 1, 4, 3 - In this image vegetation responding to IR is in green
Final Analysis Phase - Ground Truthing
Ground truth is the collection of reference data that is used to prove or disprove the remote sensing analysis work. Ground truth data can include a variety of information such as ground photographs, maps, textual information, aerial photos and other related remote sensing data.
From the imagery data, there are several wadies in the immediate area that are capable of supporting vegetation. I checked a variety of data sources on this area. Sure enough, it turns out to be an oasis. The name of the place is Uyun Musa which means means "Springs of Moses" (also called Moses - Quellen). I have obtained photographs taken on the ground of the oasis (unfortunately I still don't have publication rights for them). I also located an old map that was made before the construction of the Suez Canal, dating back into the 19th century. This oasis can be confirmed as existing over a century ago. (Click here to see map)
Last Updated 2-2-2005
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