A Remote Sensing Field Activity: In situ Data Collection to Aid in Landsat 7 Imagery Analysis

Transcription

1 A Remote Sensing Field Activity: In situ Data Collection to Aid in Landsat 7 Imagery Analysis Fundamentals of Remote Sensing October 15, 2007 Isaac Fage Danik Bourdeau Neil Kenny Philipp Schnetzer

2 Index Introduction 1 Data Used 2 Knowledge Building Q & A 3 6 Site Specific Q & A: Urban and Anthropogenic 6 10 Agriculture and Land Use Forestry Coastal Environment Geology Conclusion 20 References 21

3 Introduction The purpose of this fieldwork assignment is to familiarize the students of the Fundamentals of Remote Sensing class to remote sensing processes. This incurs the collection and analysis of data, and documentation of findings and results in the form of this report. Students should use their knowledge of spectral responses across the different wavelengths along with previous experience and inductive/deductive logic to compare in situ information collected with that of data captured through the Landsat 7 satellite to structure educated and informed decisions as to the spectral responses of the features in study. This project also allows the students to gain hands on experience in the use of the MobileMapper GPS units and software along with experience navigating the area using topographical maps. The study area includes sites within Annapolis County surrounding the towns of Middleton, Lawrencetown and Bridgetown, all are accessible by car. One site not visited in situ is CFB Greenwood, located in Kings County. The sites were diversified to help differentiate how features are shown on Landsat 7 imagery. 1

4 Data used Digital Imagery: Landsat 7 Thematic Mapper satellite image o 30m spatial resolution o 185 X 170 km image size o Date taken: August 23, 2006 o Colour composites used: * 3, 2, 1 * 4, 5, 7 * 7, 4, 2 *4, 3, 2 o Datum: WGS84 o Projection: UTM, Zone 20 Analogue Imagery: Topographical map o Area of Bridgetown (21 A 14) o Published by Natural Resources Canada, 1999 o Datum: NAD 83 o Projection: UTM, Zone 20 Software: MobileMapper Office ArcGIS 9.2 PCI Geomatica Focus Devices: MobileMapper GPS unit Canon digital camera, 5 megapixel 2

5 Knowledge Building Q & A 1) The false colour composites provided were generated using the infrared portion of the electromagnetic spectrum (Landsat 7 bands 4, 5, and 7), which are invisible to the human eye. What portion of the EM spectrum do bands 4, 5, and 7 cover? Provide their name and range of wavelengths. Considering they are invisible to the human eye, explain why we can see them on images. Landsat 7 Thematic Mapper (TM) Spectral Bands 4, 5, and 7: Band 4: µm, near infrared Band 5: µm, mid infrared Band 7: µm, mid infrared Sensors are manmade devices and can be manufactured to be sensitive and able to capture all wavelengths of electromagnetic radiation (EMR). Human eyes are only sensitive to the narrow band of visible EMR and thus cannot actively see in any other wavelength. The satellite sensors can capture an infrared image by assigning an analogue degree of voltage to the radiance received from each pixel (for Landsat 7, one pixel is 30m X 30m on the surface of the earth). This voltage is then converted to a digital number (DN) and each of the three bands form a unique DN for the same pixel. Landsat 7 uses an 8 bit DN range and therefore can store a DN of 256 levels for each pixel. The DNs are used by image processing software to determine the appropriate colouration of each pixel. In the final resulting image, we are able to see a depiction of the infrared spectrum by digitally assigning appropriate colours from the visible EM spectrum to the DNs. 2) In all three composites the coastal waters of the Bay of Fundy are a different colour than the Annapolis River, the local lakes, and also the offshore region of the Bay of Fundy. Provide at least two possible reasons why this variation occurs. The coastal waters of the Bay of Fundy are unique in the images (figures 1 through 4) because the water is very choppy and there is much suspended sediment in this turbulent water. The Annapolis river and local lakes appear darker than the coastal region because they reflect EMR more specularly, that is, their surface is smoother and the angle of incident rays approximates the angle of the reflected rays. For this reason, specular reflectors appear darker because less EMR reaches the sensors. The coastal region is a diffuse reflector, that is, it has a rough and uneven surface imparted by the crashing waves and therefore scatters the EMR. Diffuse EMR reaches the sensor in greater quantities than specular EMR and thus it appears brighter. This vast movement of water on the coastline causes much of the sediment to become suspended in the water column. This sediment causes even further reflectance of EMR, thereby increasing reflectivity and in turn making it appear brighter in the imagery. The Annapolis River, at times, can be somewhat turbulent but is mostly still water not enough to disrupt sediment, especially in the dry month of August when this image was taken. The further one travels into the heart of the Bay of Fundy from the coastline the darker the water appears. The two factors influencing this are less sediment in the water column and at these great depths nearly all of the EMR is absorbed by the water. 3

6 Figure 1. Selection of Landsat 7 image. Showing is the North Mountain and coastal Bay of Fundy in bands 4, 3, 2. Figure 2. Selection of Landsat 7 image. Showing is the North Mountain and coastal Bay of Fundy in bands 7, 4, 2. Figure 3. Selection of Landsat 7 image. Showing is the North Mountain and coastal Bay of Fundy in bands 4, 5, 7. Figure 1. Selection of Landsat 7 image. Showing is the North Mountain and coastal Bay of Fundy in bands 3, 2, 1. 3) Which direction does the Annapolis River flow? Careful inspection of the river in the provided digital and analogue data will provide evidence of flow direction. Provide an explanation of how you derived your choice of direction. The Annapolis River flows through the Annapolis Valley from the Northeast towards the southwest. Water always drains downhill. Conclusive proof of the direction of drainage is found in the relative elevation difference on the river at the map boundaries. The river is below the 20m contour where it enters the map in the northeast corner. It flows off the map in the southwest corner below the 10m contour. Other indicators of flow direction were observed. Gradual widening of the river in the southwest direction suggests increased water volume as it flows downstream. The majority of streams draining into the river bend towards the presumed direction of flow as they enter the river. Figure 5. Selection of Bridgetown area (21 A 14) topographic map. 4

7 4) The majority of the larger lakes (e.g. Paradise Lake) in the imagery have a different colour or discolouration to them in comparison to the smaller lakes (McEwan Lake, Cedar Lake, etc.). Discuss what could be contributing to the variation in colour between the larger and smaller lakes. The composites show that the discolouration of the larger lakes (e.g. Paradise Lake) is due to many small islands with vegetation being within the lake(s). Though these islands can be seen through all composites, the islands can be best distinguished from composite 7, 4, 2 due to the near infrared Band 4 highlighting the separation between the water and the vegetation. This Band is best for the separation between water and vegetation as it is in this wave range that the reflectance of vegetation rapidly increases. This contrast is also helped by the fact that the composites provided were taken in August when vegetation would be at its peak. 5) How can you tell the difference between urban features (buildings and roads) vs. clearcuts? They both produce very similar spectral responses. Though clearcuts and urban features provide similar spectral responses they can be distinguished by their unique geometrical shapes and by the features surrounding them. Clearcuts usually have irregular shapes and are surrounded by trees, while urban features usually show as having straight edged borders and are usually surrounded by similar features. The distinction between the two can be best observed on composite 4, 5, 7 (near infrared, midinfrared) where the contrast between vegetative features and non vegetative features is at its greatest. The clearcuts are easily picked out as light blue features surrounded by very dark features (e.g. trees) and while urban features are also the same colour as the clearcuts they can be distinguished by the surrounding features and geometric shapes. Also, clearcuts in the mid to later stages of re growth can be distinguished even more as their DN values reflect the new vegetation that is growing. 6) Bare fields show mottling or varying tone due to changes in moisture content. Would you expect drier soil to be darker or lighter than moist soil? Why? Which bands / wavelengths best show this? Bands 4, 5 and 7 are best at displaying moisture content in fields. Bands 4 and 5 both represent the near infrared while band 7 represents the middle infrared. When a field is drier it would appear lighter in colour. This is due to the nature of the wavelength and the water molecule. Water absorbs most infrared wavelengths that come into contact with it, especially in the middle infrared. As a result there is less reflectivity for the satellite to pick up on. As there is less moisture in the fields higher amounts of infrared are reflected thereby showing brighter on a Landsat image, while more moisture would make the image darker. Also, in the event a field is flooded the water creates a smoother surface by evening out the small vertical differences in topography and this would lead to a darker image being portrayed as a result of increased specular reflection (this phenomenon can be related to a rain soaked street at night time in that it appears very dark even though high beams are used, the EMR is not as diffusely scattered as on a dry road and thus less radiance reaches the eyes of the driver). 5

8 7) Narrow logging roads are often less than 10 meters wide, significantly less than the 30 meter spatial resolution of the Landsat 7 sensor. Why is it possible to see these roads in the imagery? Even though the Landsat 7 image has a 30m spatial resolution it does not accurately represent the area. When the Landsat satellite looks at any certain area it tries to represent the area by a pixel as best it can. This means that subtle differences are not picked up upon, rather the strongest contrast is primarily represented. The reason why the logging road shows up so well relative to its surrounding area is that the reflectivity of the road is higher. While most of the pixel is probably made of vegetation, the road being barren reflects wavelengths to such an extent that it literally outshines everything else. This is why when we look at specific pixels they show one feature but in reality many more attributes may not be represented. Site Specific Q & A Urban and Anthropogenic: 1) UTM, Zone 20: E, N What is the large glass structure at this location? How does this feature appear on the satellite imagery and which bands are best for seeing these types of features? The large glass structure at this location is a large operation greenhouse. This greenhouse has twenty two rows and is approximately 60m X 70m. The best Landsat 7 composites to view this structure are 4, 5, 7 and 7, 4, 2. When viewing these composites we can see a large field where the greenhouses are situated on and a well defined small darker stripe in the North West corner. The greenhouses are represented by this darker stripe. Bands 4, 5 represent nearinfrared while band 7 represents the middle infrared, which are all good at viewing moisture. This is probably why the infrared bands are better at distinguishing the greenhouses over the other bands. It is reasonable to assume that the greenhouses would have more moisture in Figure 6. Looking South West at Den Haan s Nursery, Fitch Road,Lawrencetown. Building approximately four pixels on Landsat 7 imagery. (Site UA1). them than the surrounding field, hence the difference in colour from the two. As moisture absorbs infrared wavelengths, an area with high moisture would appear darker since less infrared wavelengths are being reflected. 6

9 2) UTM, Zone 20: E, N What is this linear feature and why does it appear as it does on Composite 3, 2, 1 and Composite 7, 4, 2? The feature at this location is a cleared strip of land, approximately 30m wide, for transmission lines. While cleared the strip is not barren, but has short vegetation cover. This strip is straight and cuts through a dense old growth forest. On composites 3, 2, 1 and 7, 4, 2 the feature is straight and very noticeable. For the most part the difference is due to vegetation. Along the strip, the vegetation is significantly shorter than the forest cover allowing composite 3, 2, 1 to represent the strip as lighter because the low vegetation allows for more reflectivity off the soil. At the time of observation the Landsat 7 image was over thirteen months old and may have had more exposed soil giving off more reflection of light. Composite 7, 4, 2 also represents the strip as lighter but this may be due to moisture content in the vegetation. Bands 7 and 4 both look at moisture content by displaying the reflectivity of infrared wavelengths. As moisture absorbs infrared wavelengths less of this radiance is captured by the Landsat 7, areas with higher moisture appear darker while drier areas appear lighter. A dense forest Figure7. Looking East, electric utility lane approximately 30m wide. (Site UA2). would have more moisture and as such absorb more infrared wavelengths than a strip of land with only short vegetation, hence their contrasting representation. 7

10 3) UTM, Zone 20: E, N What is the linear feature on the West side of the road at this location? Does this feature show up clearly on the imagery? Why or why not? The linear feature is a landing/take off strip for the Valley View Ultralight flight training centre. Composites (7, 4, 2), (4, 3, 2) and (4, 5, 7) all show the strip on their images. However, composite 7, 4, 2 is the strongest at representing the perfectly linear, homogenous strip about a pixel wide and several long. What is remarkable about composite 7, 4, 2 is not only that it represents the strip accurately but it also distinguishes the vegetation between the strip and the road. Bands 7 (middle infrared) and 4(near infrared) both look at moisture content and ground cover. In a clearcut area these bands would represent the ground as reddish due to its lack of vegetation and moisture. The strip in this case is represented by a pinkish colour demonstrating Figure8. Looking South East at a private landing strip, Elliott Road, Lawrencetown. Approximately 20m wide. (Site UA3). the short nature of the vegetation. While no ground is exposed, the grass is so short that little moisture is present. This gives off high reflectivity at infrared wavelengths. The ground next to the strip has higher vegetation which is why its colour is slightly darker. 4) UTM, Zone 20: E, N What are the blue, black, and white features scattered throughout this field? Are they present in the imagery? Why or why not? The blue, black and white features are bee boxes. These are not represented in the Landsat 7 images. The primary reason is due to spatial resolution. The Landsat 7 images have a 30 meter spatial resolution, meaning that one pixel is equal to 30 m X 30 m ground cover. Since the Landsat 7 cannot represent the area equally it must demonstrate what is most highly reflective, which in this case is the ground cover. Unfortunately the bee boxes are too small and spaced apart for the Landsat 7 to perceive them. From personal experience, we can say that these boxes have been at this particular site for many years and were present when the Landsat 7 image was taken. Figure 9. Looking South West at bee boxes. Highway 101, exit 18. Boxes approximately 1m X 1m. (Site UA4). 8

11 5) UTM, Zone 20: E, N Find this feature on the topographic map and each of the Landsat 7 composites. What is this feature? Describe how it appears on the various composities. (Not in situ). The feature at this location is the Canadian Forces Base (CFB) Greenwood Airport. This feature is highly visible in all Landsat 7 composites. The true colour composite (3, 2, 1) shows the overall airport much like all other developments in the region, as bright features. The runways are noticeable but not as distinguished as in other composites. Composite 7, 4, 2 clearly defines the runways as a dark purple. This is synonymous of barren fields and clearcuts. Exposed ground and asphalt appear similar in this composite. This is likely due to the lack of vegetation in both features giving higher reflectance in the middle infrared wavelength (band 7). Composite 4, 3, 2 distinguishes between the runways and other features, but not as clearly as composite 7, 4, 2. Both airport and runway appear as a light blue which is similar to other urban developments and low cut vegetation. Composite 4, 3, 2 highlights high levels of reflectance in the green wavelength (band 2). Composite 4, 5, 7 is the best composite to view the contrast between the runways and other features. The runways appear dark blue while surrounding areas appear lighter blue. This clearly distinguishes between the asphalt of the runways and the low cut vegetation surrounding them. This conclusion is derived from other examples of urban and road features appearing as dark blue while bare fields and low vegetation clearcuts have a lighter blue colour. Figure 10. Selection of Landsat 7 colour composite satellite imagery, bands 3, 2, 1. Greenwood airport visible in lower right corner. Figure 11. Selection of Landsat 7 colour composite satellite imagery, bands 7, 4, 2. Greenwood airport visible in lower right corner. 9

12 Figure 12. Selection of Landsat 7 colour composite satellite imagery, bands 4, 3, 2. Greenwood airport visible in lower right corner. Figure 13. Selection of Landsat 7 colour composite satellite imagery, bands 4, 5, 7. Greenwood airport visible in lower right corner. Agriculture and Land Use: 1) UTM, Zone 20: E, N From the top of the overpass, notice that between the edges of the tree lines of either side of the highway, there is asphalt, a gravel shoulder, and low cut vegetation. Which of the three features (or combination of) is most responsible for the DN values recorded across the various Landsat 7 bands? The asphalt and the gravel shoulder are most responsible for the DN values across the Landsat 7 bands. In nearly all composites the road/shoulder features dominate the DN values of the overpass area, other than an observed small number of pixels on the south east corner of the over pass where vegetation can be observed. The pavement and the shoulder have very high reflectance for Bands 1, 2, 3, 5, 7 with notably less reflectance for Band 4. This is expected as Band 4 is best used to highlight vegetation biomass and does not discriminate against road features very well. Figure 14. Looking East, Highway 101, exit 19. (Site ALU1). 10

13 2) UTM, Zone 20: E, N What are the large ground features surrounding the road at this location? How do they appear in the various Landsat 7 images? The large ground features surround this location are agricultural fields currently cultivated with grass, corn or have been recently ploughed exposing bare soil. 3, 2, 1 In this composite the fields directly to the west of the road are very reflective across all three bands and show as white in the image, this is most likely because the fields have no vegetation and have been ploughed, as they have similar spectral responses to roads. The fields farther west are light green, indicating there is some type of vegetation growing in the form of crops or grass. The fields east of the road are white, light green and light brown. Again, the white features would be due to no vegetation growing on the fields, while the light green would indicate some type of vegetation growing. The light brown response also indicates the lack of vegetation and is most likely due to bare soil. 7, 4, 2 One field directly to the west of the road is a dark pink, indicating low reflectance by Band 7 (Mid infrared) along with Band 2 (Green). The low reflectance from Band 7 shows that there is not very much moisture in this field. Other fields adjacent to this field are light green which show high reflectance by Band 4 (Near infrared), indicating vegetation is present. Finally the fields on the east side of the road are a light pink indicating that they have less moisture than the other pink field. 4, 5, 7 One field to the east of the road is white, showing high reflectivity across all infrared bands which would indicate low moisture content for this area. The surrounding fields to the east and the west are all a shade of light blue, indicating high spectral responses across all bands, but especially the band going through the Blue gun which is Band 5 (Mid infrared) which shows low moisture and little vegetation in this area. The fields to the north west and north east are shades of brown, showing that all three bands are being absorbed by the features indicating high moisture content most likely caused by vegetation. 4, 3, 2 Most fields to the north west, north east and south west are bright pink, showing that they are dominated by Band 4 and again indicating vegetation on these features. One field to the west of the road is light blue which shows high reflectivity on Band 3 and Band 2, but not as much on Band 4, indicating very little vegetation in this area. 11

14 3) Considering the spectral responses of these features in the imagery, how would you expect them to appear after a rainfall? There would be no observed changes other than through bands 4, 5, 7 (Near infrared, Mid infrared), as these bands are the only bands able to discriminate moisture content. Even among these bands, Bands 5 and 7 would be the best for observing moisture content as at their respective wavelengths water is the least reflective allowing for greater contrast between features that do and do not have moisture. In the event of large pools of standing water the area would appear darker due to absorption of EMR by the water in band 7 and also more specular reflectance. Figure 15. Looking South West, Fitch Road, Lawrencetown. (Site ALU2). Figure 16. Looking North, Fitch Road, Lawrencetown. (Site ALU2). 4) UTM, Zone 20: E, N What is the large, relatively flat ground feature on the East side of the road? Does this area appear to be in active use? The feature on the east side of the road is an agricultural field that is still in use. It currently has vegetation in the form of short grass. Though at the time the Landsat 7 image was taken the field may have been ploughed or recently mowed as it had high reflectivity in most bands. 12

15 5) Are there other features in this imagery that have similar spectral responses? Are they all the same type of feature? Support your decision. Yes, there are other features in the imagery that have the same spectral response. These features include other agricultural fields, with little or no vegetation, along with urban features and roads. These features have a similar spectral response as they hold similar properties, i.e. little moisture, relatively equal surface texture and little vegetation. Figure 17. Looking East, on top of Mount Rose. (Site ALU3). Forestry: 1) UTM, Zone 20: E, N Describe the general feature that you are standing in. What is it about this area that makes it highly reflective across all Landsat 7 bands? This point is located in a clearcut. It possesses numerous characteristics which increase reflectance across all bands. Tree canopy is absent, exposing bare to sparsely covered soil. This produces high reflectance in the mid infrared and red spectrum (bands 7, 5, 3). With reduced cover, the sun dries out the ground surface more quickly than surrounding forested areas. Lack of soil moisture lights up the mid and near infrared bands, specifically 4 and 7. The clear cut possesses a distinct lack of biomass when compared to the surrounding stands of trees. High reflectance observed in the nearinfrared (Band 4) accurately reflects the low levels of biomass found on the ground here. Low amounts of chlorophyll register with high reflectance in the red and blue range of the spectrum (bands 3, 1), which chlorophyll readily absorbs in the surrounding treed areas. 13

16 2) Bearing in mind that this imagery is from 2006, would you expect the spectral responses to be different today? In 5 years, 10 years? Yes. As regeneration occurs, we expect to observe increasing EMR absorption across multiple spectral bands. Trees will cover bare ground, producing greater absorption in the red and mid infrared spectrum. Moisture retention will improve, giving absorption in the near and mid infrared. Biomass and chlorophyll amounts will continue to increase with regeneration, showing greater absorption in the shorter wavelengths. The only band that should produce higher reflectance with regeneration would be Band 2 (green) in the summer months. It is expected that the change in spectral response will be slower during the first five years of regeneration, when the cover will remain sparse and the new trees are establishing Figure 18. Looking North East, a clear cut on Lily Lake Road, North Mountain. (Site F1). themselves. Once established, the young trees will grow quickly to fill in the area and create a thick dense cover that will give a strong spectral response in the green and near infrared range of the spectrum. These predictions are supported by the observation of imagery of clear cuts in later stages of regeneration, such as the clear cut observed in question 7. 3) UTM, Zone 20: E, N Looking at the forest on the South side of the road, what is the dominant type of tree here? In situ observation of the tree cover at this site confirms that deciduous trees are the dominant type. A mix of birch and maple make up the two dominant species here. Coniferous trees are found in minor amounts this location. They are typically smaller and usually located under the cover of the deciduous trees. Inspection of the imagery shows a brighter spectral response at the green and infrared wavelengths when compared to known stands of coniferous trees. Figure 19. Looking South at a deciduous tree stand, just West of Lily Lake. (Site F2). 14

17 4) How does this stand of trees, and those around the Southern part of the lake, appear in the various composites? These forested areas appear brighter than other surrounding stands of trees. In situ observation concluded that these stands are comprised mainly of deciduous trees. An area dominated by coniferous trees was observed on the east side of the lake. This coniferous stand is observable as a dark green patch on the 7, 4, 2 composite. Deciduous trees are known to produce a brighter spectral response in the near infrared bands when compared to coniferous trees. The leaves act as diffuse reflectors, reflecting EMR in the near infrared and green range. Figure 20. UTM, Zone 20: E, N. Looking South across Lily Lake. (Approximately 200m from site F2). 5) UTM, Zone 20: E, N Looking at the forest about 500m away on the East side of the road, what is the dominant type of tree? The dominant tree type at this site is white spruce, a coniferous tree. Tree cover near the road is patchy, interspaced with low grass and brush. The images show dark patches that denotes high absorption where the conifers are most dense. The near infrared (band 4) displays the contrast between dense and sparse cover well in all composites. 6) Compare the spectral response of this stand of trees to the previous location. Which composite best displays the contrast between these types of trees? Why is this? The contrast between the spectral responses of coniferous and deciduous tree cover is observable in all images. Composite 7, 4, 2 shows a bold distinction between near infrared reflection (light green) in deciduous trees and near infrared absorption (dark green) in coniferous trees. Near infrared is displayed with the green gun in this image and we differentiate between tree type exclusively by the intensity of green at the areas of interest. Composite 4, 5, 7 identifies more subtle variations in the tree cover, showing some minor areas of contrast that are not visible in the 7, 4, 2 composite. Coniferous trees display very dark, Figure 21. Looking East, Lily Lake Road, North Mountain. (Site F3). 15

18 absorbing EMR across all bands. All bands displayed in this composite are in the near to mid infrared range of the spectrum, and all of which discriminate well between different types of vegetation cover. It is expected that using a composite sensitive to the target phenomenon across all bands would produce the most detailed results. Our observations validate this hypothesis. 7) UTM, Zone 20: E, N At what stage of regrowth is this clearcut in? What are the indicators to support your answer? The regrowth in this clearcut appears to be in its approximately fifth year of regeneration. This is clearly indicated by the growth stages of new coniferous and deciduous trees (in situ), for example, the height that some new spruce trees have reached require several years to achieve. Also, many of the felled trees that were left behind have older offshoots growing from the dead wood and there are also other types of vegetation with sufficient coverage and size to indicate numerous years of healthy growth. Ground coverage provides further evidence, according to the Landsat 7 colour composite images and in situ ground truthing there is inadequate exposed soil to have an impact on the spectral properties of this clearcut. A newer clearcut, where vegetation coverage is still in its early stages, has exposed soil, and therefore less moisture, and this will impact the radiance of that area which will in turn be portrayed in satellite imagery. When this clearcut (South Mountain) is compared to the newer clearcut (North Mountain) in the satellite imagery it is evident that the spectral characteristics behave differently. The newer clearcut appears similar to exposed soil or ploughed fields while the older clearcut does not show similar properties in the least. 8) Would a satellite image be able to show areas of regeneration? Yes, satellite imagery can effectively capture areas of regeneration. Two reasons can contribute to this process: areas of regeneration have vegetation coverage which is detectable by sensors on satellites, and this vegetation coverage allows less of the soil to be penetrated by electromagnetic radiation. Therefore, as a clearcut becomes repopulated with growth the spectral characteristic changes proportionally with the vegetation coverage, allowing new growth to be readily distinguishable through satellite imagery analysis. Landsat 7 color composite 7, 4, 2 shows this accurately. The only pinkish area (depicting barren earth, low moisture) on the image in the vicinity of the clearcut is the gravel road Figure 22. Looking South, an older clearcut on the South Mountain. (Site F4). leading through the clearcut. This means that vegetation has covered the clearcut area to the point where the majority of the soil is not visible from a bird s eye view. 16

19 Coastal Environment: 1) UTM, Zone 20: E, N What is the natural sorting of rock that has occurred on this beach and why? Rock sorting at this beach can be solely contributed to the force of the oceans water, both in the liquid and solid state. The only rock unaffected by the tides and ice of the oceans water is the massive bedrock found underneath the surface of the beach and also the exposed cliffs by the edge of the forest. Over the course of time these rocks have been sorted according to size. It was evident that the smallest rocks congregated at the average water level line achieved by high tide. The larger the rock the harder it is for the water to move, so these rocks tend to be found further North of the beach (nearer the water level line of low tide). Extreme storms can alter the natural sorting process, this was demonstrated by a storm that produced violent waves that reached above the average high tide water level line. These waves brought small and medium sized rocks closer to the cliffs and covered much of the previously exposed bedrock, visible in figure 23 as the band of rocks closest to the forest and stretching to the dark line (dulse) which is the line of recent average high tide. 2) Does this affect the radiance response collected by the sensor? This rock sorting occurrence does affect the radiance response collected by the sensor, but only minimally. If only considering the mobile rocks the radiance would not be greatly altered because of the similarity in size and matter. These rocks all act as diffuse reflectors because they are much bigger than the electromagnetic radiation being analyzed in the imagery and therefore scatter the EMR to a great extent. Even sand, when viewed in the short wavelengths of the visible spectrum, acts as a diffuse reflector and appears bright because much of the EMR is transmitted to the sensor. The rocks covering the surface of the beach will react similarly due to their alike properties and the radiance in turn will not be affected to the point that these rocks will be distinguishable on the satellite images. If the bedrock is also considered there will be greater difference in the radiance. These rocks have different mineral compositions and also have very different geometric characteristics. This contrast, between the bedrock and the other rocks (of size and matter) will cause the two types of rocks to have different and noticeable radiance responses as collected by the sensor. Band 7 is useful in discriminating mineral types, where the bedrock outcrop is granite and the beach rocks are of mixed origin. Hypothetically, if both types of rock occupied equal areas and were in long homogenous bands side by side they should be distinguishable on the satellite imagery. Another factor to consider in this matter is the water level when the image was taken, August of If low tide is at its minimum level then as much as a pixel width of beach rocks may become exposed. Nevertheless, these freshly exposed rocks would still be wet and reflectivity would increase gradually while heading closer to the forest. 17

20 3) The many small stones covering the bedrock on this beach were brought in by storms this past winter. Given that the imagery you are viewing was taken in 2006, would you expect this change to cause a difference in the general spectral response of this area? It is probable that the spectral response of the area would be slightly altered if the same image was taken today. The bedrock on this beach has a different spectral response than the smaller stones found covering the rest of the beach. This spectral difference may be visible if there is enough area covered by each type of rock. Even though the area covered by the previously exposed bedrock (approximately the width of a road) is by no means wide enough to comprise a full pixel on the satellite image there may have been enough contrast between the bedrock and other stones that it altered, even slightly, the DNs for the pixel it resides in. Since more of the beach surface is now homogenous the DNs would have Figure 23. UTM, Zone 20: E, N. Looking West, Small Keatings Sand Beach, Port George. (Site BPL). a smaller range and this may lead to the beach appearing wider and more uniform on the image. If the image was taken during the peak height of high tide then the available rock displayed on the image would only be a narrow band comprised of bedrock and other rocks. In order to accurately portray the difference in radiance of the 2006 image to the same image taken today it is crucial to capture the image at approximately the same degree of water height. Geology: 1) UTM, Zone 20: E, N According to the 3, 2, 1 composite, this appears as a bright near white feature. What is this and why does it have such a high reflective response across many of the Landsat 7 bands? This feature is an aggregate quarry owned and operated by LaFarge. This area is highly reflective across many bands due to its composition. As can be seen in Figure 24 there are many sand/gravel piles and the roads are also comprised of the same material. Sand acts as a near perfect diffuse reflector because the surface is considered rough for very short wavelengths (i.e., visible EMR). This 18

21 roughness scatters the EMR to the greatest extent and a high percentage of this radiance reaches the sensor on the satellite. The more EMR that reaches the sensor the brighter that area will appear on the image. The smoother an area becomes (i.e., glass, still water) or the longer the wavelengths of EMR the more specular the reflection will become and the less EMR will reach the sensor, making it appear a darker tone. There is also a large pile of darker and larger crushed mineral (approximately the size of one 30 m X 30 m pixel in the imagery) but this does not seem to create a contrast in the imagery, perhaps this is because the satellite imagery is over thirteen months old at present and this pile has just recently been developed. The Landsat 7 color composite3, 2, 1 shows the highly reflective nature of this area extremely well. This composite best displays the features at this site since its composition is best portrayed by short wavelengths able to discriminate the sands fine texture. The infrared band 7 also portrays this pit well because this band is the most appropriate for distinguishing the contrast of various minerals. 2) Why is this feature here? Are there likely to be others like it in this area? Explain. This quarry is here because the resource that it utilizes is readily available. Also, it is a central location in the Annapolis Valley with fast access to highway 101. This resource can be found at various locations along the North and South Mountains. In fact, the satellite imagery, across all bands, elude that a similar pit is located approximately 1km South West of the one depicted in figure 24. Figure 24. Looking South, LaFarge aggregate supplier, Highway 201, Carelton Corner. (Site GEO). 19

22 Conclusion This fieldwork exercise gave us experience in the practical application of the remote sensing process. Collecting in situ data through the form of digital pictures and other observations we were able see how they related to the different composite images captured by the Landsat 7 satellite. The project provided challenges in trying to relate the in situ observations with the satellite imagery mainly due to the imagery being captured over a year before the in situ data was collected. It meant assumptions had to be made regarding different features based on their observed spectral responses. Along with the analysis of the data, the project familiarised us with data collection through the fieldwork. We were able to use the MobileMapper GPS units to guide our way to the different sites, which let us become more comfortable with using them for real world situations. We learned the procedure to collect and organize GPS data on the unit in the form of specific Jobs, properly collected and organized information simplifies the transfer and analysis of this data. We also learned to make full use of the resources given to us (i.e. topographical map), as we had a situation where using the GPS unit we were able to navigate our way to the desired site, but were unable to reference the location on the Landsat 7 imagery and had to use the topographical map to pinpoint our specific location. 20

23 References Jensen, J (2007). Remote Sensing of the Environment. Upper Saddle River, New Jersey: Prentice Hall. Milne, Trevor (2007). Electromagnetic Energy Interactions [Handout]. Lawrencetown, Nova Scotia: Centre of Geographical Sciences. 2007, Retrieved October 9, 2007, from Tutorial: Fundamentals of Remote Sensing Web site: Retrieved October 9, 2007, from The Remote Sensing Tutorial: Prime Developer and Writer, Dr. Nicholas M. Short, Web site: 21