(Stars)extended Tools In Remote Sensing_book 5
Image Analysis, Orthorectification, Feature Extraction, Vegetation and Mapping, Image Enhancement
- 1.
Satellite images made up of three or more bands of data area called
- A.
Air photographs
- B.
Multispectral images
- C.
Single band imagery
- D.
Subset images
Correct Answer
B. Multispectral imagesExplanation
Multispectral images are satellite images that are composed of three or more bands of data. These bands capture different wavelengths of light, allowing for the detection and analysis of various features on the Earth's surface. This type of imagery is commonly used in remote sensing applications, such as land cover classification, vegetation analysis, and mineral exploration. By analyzing the different bands, researchers can gain valuable insights into the composition and characteristics of the observed area.Rate this question:
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- 2.
A “clipped” portion of an original image data layer is called a(n)
- A.
Air photograph
- B.
Multispectral image
- C.
Single band image
- D.
Subset image
Correct Answer
D. Subset imageExplanation
A "clipped" portion of an original image data layer is called a subset image. This means that a specific portion or area of the original image has been selected or extracted, resulting in a smaller subset image that only contains the data within that selected area. This can be useful for focusing on specific features or regions of interest within the original image.Rate this question:
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- 3.
The process of joining together two or more georeferenced image data layers into a single data layer is called
- A.
Clipping
- B.
Georeferencing
- C.
Mosaicking
- D.
Reprojecting
Correct Answer
C. MosaickingExplanation
Mosaicking is the process of combining two or more georeferenced image data layers into a single data layer. This can be done to create a seamless image or map by blending the overlapping areas of the images together. Mosaicking is commonly used in remote sensing and GIS applications to create composite images or maps that cover a larger area than any individual image or map.Rate this question:
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- 4.
What Image Analysis tool is used for feature extraction?
- A.
Categorization tool
- B.
Clip tool
- C.
Control point tool
- D.
Seed tool
Correct Answer
D. Seed toolExplanation
The seed tool is used for feature extraction in image analysis. This tool allows users to manually select specific points or regions of interest in an image, which can then be used as seeds for further analysis. These seeds serve as starting points for algorithms that can identify and extract relevant features from the image. By using the seed tool, users can accurately extract important features from an image for various applications such as object recognition, image segmentation, and pattern detection.Rate this question:
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- 5.
What type of analysis allows you to find all areas of an image that have the same pixel characteristics?
- A.
Image subsetting
- B.
Mosaicking
- C.
Orthorectification
- D.
Supervised classification
Correct Answer
D. Supervised classificationExplanation
Supervised classification is a type of analysis that allows you to find all areas of an image that have the same pixel characteristics. It involves training a computer algorithm to recognize and classify different pixel values based on a set of known reference samples. This analysis is useful for identifying and delineating specific features or land cover types in an image, such as vegetation, water bodies, or urban areas.Rate this question:
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- 6.
The process of examining infrared satellite images to determine regions of vegetation health and stress is called
- A.
Change detection
- B.
Image categorization
- C.
Normalized Difference Vegetation Index
- D.
Orthorectification
Correct Answer
C. Normalized Difference Vegetation IndexExplanation
The process of examining infrared satellite images to determine regions of vegetation health and stress is called Normalized Difference Vegetation Index (NDVI). NDVI is a numerical indicator that uses the difference between near-infrared and red light reflectance to assess the density and health of vegetation. By comparing the reflectance values, NDVI can identify areas with healthy vegetation (high values) and areas with stressed or sparse vegetation (low values). This index is widely used in agriculture, forestry, and environmental monitoring to monitor vegetation conditions and detect changes over time.Rate this question:
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- 7.
The process of examining two images or feature layers of the same area over a period of time is called
- A.
Change detection
- B.
Image categorization
- C.
Normalized Difference Vegetation Index
- D.
Orthorectification
Correct Answer
A. Change detectionExplanation
Change detection is the process of examining two images or feature layers of the same area over a period of time to identify and analyze the differences or changes that have occurred. It is used in various fields such as remote sensing, surveillance, and environmental monitoring to track and monitor changes in land cover, vegetation, urban development, and other phenomena. By comparing the images or layers, change detection allows for the identification and analysis of areas that have undergone significant changes, providing valuable insights and information for decision-making and analysis.Rate this question:
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- 8.
The process of dividing pixel values in an image into a specified number of classes is called
- A.
Change detection
- B.
Image rectification
- C.
Supervised classification
- D.
Unsupervised classification
Correct Answer
A. Change detectionExplanation
Change detection refers to the process of identifying and analyzing the differences or changes that have occurred between two or more images taken at different times. It involves dividing the pixel values in the images into different classes or categories to determine the areas where changes have occurred. Therefore, the process of dividing pixel values into classes is called change detection.Rate this question:
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- 9.
The process of reorganizing a histogram range in order to emphasize or de-emphasize land features in an image is called
- A.
Change detection
- B.
Histogram stretch
- C.
Image categorization
- D.
Image rectification
Correct Answer
B. Histogram stretchExplanation
Histogram stretch is the correct answer because it refers to the process of reorganizing the histogram range in order to enhance the contrast and details in an image. By stretching the histogram, the full range of pixel values is utilized, resulting in a more visually appealing and informative image. This technique is commonly used in image processing to improve the visibility of land features or other elements of interest in an image.Rate this question:
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- 10.
The process of reversing the pixel values of an image to create a negative of the original image is called a(n)
- A.
Image categorization
- B.
Image rectification
- C.
Invert stretch
- D.
Standard deviations stretch
Correct Answer
C. Invert stretchExplanation
The correct answer is "Invert stretch". Invert stretch refers to the process of reversing the pixel values of an image, creating a negative of the original image. This technique is commonly used in image processing to enhance certain features or create artistic effects. It involves changing the brightness levels of the pixels, resulting in a visually opposite representation of the original image.Rate this question:
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- 11.
The process of applying a filter to an image to make it appear clearer is called
- A.
Image rectification
- B.
Image re-resolution
- C.
Sharpening
- D.
Stretching
Correct Answer
C. SharpeningExplanation
Sharpening is the process of applying a filter to an image to enhance its clarity and make it appear clearer. This technique increases the contrast between adjacent pixels, making edges and details more pronounced. By increasing the sharpness, the image becomes more defined and easier to perceive.Rate this question:
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- 12.
The process of applying a filter to an image to lesson the amount of speckle is called
- A.
Image rectification
- B.
Sharpening
- C.
Smoothing
- D.
Stretching
Correct Answer
C. SmoothingExplanation
Smoothing is the correct answer because when we apply a filter to an image to reduce the amount of speckle, we are essentially removing noise and creating a smoother appearance. Smoothing filters work by averaging neighboring pixels to reduce high-frequency variations in the image, resulting in a more uniform and less speckled image. This process helps to improve the overall quality and clarity of the image by reducing unwanted noise.Rate this question:
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- 13.
What is the best example of when feature extraction analysis would be needed?
- A.
To identify the extent of an oil spill in the ocean
- B.
To identify land cover types in a county
- C.
To identify the locations of all railroads in a county
- D.
To identify the locations of all owl nesting grounds in a state
Correct Answer
A. To identify the extent of an oil spill in the oceanExplanation
Feature extraction analysis would be needed to identify the extent of an oil spill in the ocean. This is because feature extraction involves identifying specific characteristics or features within a dataset, in this case, the oil spill. By analyzing the features of the oil spill, such as its size, shape, and distribution, it becomes possible to determine the extent or spread of the spill. This information is crucial for effective response and containment measures to mitigate the environmental impact of the oil spill.Rate this question:
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- 14.
What is the best example of when supervised categorization analysis would be needed?
- A.
To identify precipitation values for a county
- B.
To identify land cover types in a county
- C.
To identify the locations of all railroads in a county
- D.
To identify the locations of all wetlands in a county
Correct Answer
D. To identify the locations of all wetlands in a countyExplanation
Supervised categorization analysis would be needed to identify the locations of all wetlands in a county because this task requires the classification of specific areas as wetlands based on certain criteria. This analysis would involve training a model with labeled data of known wetland locations and using it to predict and categorize other areas in the county as wetlands or non-wetlands.Rate this question:
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- 15.
What is the best example of when unsupervised categorization analysis would be needed?
- A.
To identify the extent of an oil spill in the ocean
- B.
To identify land cover types in a county
- C.
To identify the locations of all railroads in a county
- D.
To identify the locations of all owl nesting grounds in a state
Correct Answer
B. To identify land cover types in a countyExplanation
Unsupervised categorization analysis would be needed to identify land cover types in a county because this task involves grouping and classifying different types of land cover without any prior knowledge or labeled data. This analysis would allow for the discovery of patterns and similarities among the land cover types, helping to understand the distribution and composition of different land cover categories in the county.Rate this question:
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- 16.
What is the best example of when change detection analysis would be needed?
- A.
To identify the extent of an oil spill in the ocean
- B.
To identify land cover types in a county
- C.
To identify the reduction or addition of all railroads in a county
- D.
To identify the loss of wetlands in a county
Correct Answer
D. To identify the loss of wetlands in a countyExplanation
Change detection analysis is used to identify and monitor changes in a specific area over time. In this case, the best example of when change detection analysis would be needed is to identify the loss of wetlands in a county. This analysis would help in monitoring and assessing the extent of wetland loss, which is crucial for conservation efforts and understanding the impact on the ecosystem.Rate this question:
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- 17.
Orthorectification differs from rectification because
- A.
orthorectification is performed on feature data and rectification is performed on image data.
- B.
orthorectification is performed on aerial photographs and rectification is performed on satellite images.
- C.
rectification can only be performed using Image Analysis extension program.
- D.
orthorectification uses elevation data to account for the natural variation in the Earth’s surface.
Correct Answer
D. orthorectification uses elevation data to account for the natural variation in the Earth’s surface.Explanation
Orthorectification uses elevation data to account for the natural variation in the Earth’s surface. This process corrects for distortions caused by terrain and topographic relief, ensuring that the features in the image are accurately represented in their true geographic locations. On the other hand, rectification is the process of removing geometric distortions from an image, typically caused by sensor or platform errors. It is performed on image data, not feature data like orthorectification.Rate this question:
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- 18.
What is the best example of when using an invert stretch on an image would be needed?
- A.
When only a photograph negative is available
- B.
When you want to change the image bands used
- C.
When you want to clip an image to a smaller geographic extent
- D.
When you want to perform a resolution merge
Correct Answer
A. When only a photograph negative is availableExplanation
The invert stretch is used to convert a negative image into a positive image. When only a photograph negative is available, using an invert stretch would be necessary to convert the negative into a viewable positive image.Rate this question:
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- 19.
When performing orthorectification, geocorrection properties must be entered with regard to the camera used for data collection because
- A.
cameras are not typical geographical data collection devices.
- B.
cameras or sensors have a certain amount of error or discrepancy related to them.
- C.
certain remote sensing data collection projects (NAPP, NHAP, etc.) have error associated with them and others do not.
- D.
regular, commonly-used cameras have error associated with them and professional, GIS-used cameras do not.
Correct Answer
B. cameras or sensors have a certain amount of error or discrepancy related to them.Explanation
Cameras or sensors used for data collection have a certain amount of error or discrepancy associated with them. This means that the images captured by the cameras may not accurately represent the true geographical features. Therefore, when performing orthorectification, which involves correcting the distortions in the images to align them with the true geographic coordinates, it is important to consider these errors and enter the appropriate geocorrection properties specific to the camera used. This ensures that the resulting orthorectified images are as accurate as possible.Rate this question:
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- 20.
When orthorectifying an image, it is best to select control points that are not clustered together because
- A.
the portion of the image where the control points are located would be closely aligned and the rest of the image would be highly distorted.
- B.
this would cause a runtime error and the program would shut down and cause you to lose all associated data.
- C.
the portion of the image where the control points are located would be highly distorted and the rest of the image would align properly.
- D.
the portion of the elevation data for the rest of the image would be reprojected based on the image projection causing problems for future analysis.
Correct Answer
A. the portion of the image where the control points are located would be closely aligned and the rest of the image would be highly distorted.Explanation
When orthorectifying an image, selecting control points that are not clustered together is best because if the control points are closely aligned in one portion of the image, it would cause that portion to be closely aligned and the rest of the image to be highly distorted. This would result in an inaccurate and distorted representation of the entire image. Therefore, selecting control points that are spread out and not clustered together ensures a more accurate and balanced orthorectification process.Rate this question:
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- 21.
When orthorectifying an image with a geographic extent that extends beyond one quarter quadrangle of area, you may need to mosaic the digital elevation models (DEMs) to use for the analysis because
- A.
non-mosaicked data cannot be used for this analysis.
- B.
the coordinate system for the DEM must be the same as the coordinate system of the image.
- C.
the coordinate system for the DEM must differ from the coordinate system of the image.
- D.
the geographic extent of the elevation data must be at least that of the study area.
Correct Answer
D. the geographic extent of the elevation data must be at least that of the study area.Explanation
When orthorectifying an image with a geographic extent that extends beyond one quarter quadrangle of area, you may need to mosaic the digital elevation models (DEMs) to use for the analysis because the geographic extent of the elevation data must be at least that of the study area. This means that the elevation data should cover the entire area of the study to ensure accurate orthorectification. If the elevation data is not mosaicked and does not cover the entire study area, there will be gaps in the elevation information, leading to inaccuracies in the orthorectified image. Therefore, it is necessary to mosaic the DEMs to ensure complete coverage of the study area.Rate this question:
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- 22.
Specifying a larger seed radius in Seed Tool Properties typically causes a larger polygon to be drawn because
- A.
the seed radius specifies the number of pixels that can be used to establish the range of pixel values that will be used to draw the polygon.
- B.
the seed radius specifies the size of the polygon to the drawn.
- C.
the seed radius specifies whether you will click a single polygon or draw a rectangle to establish the pixel value range.
- D.
smaller seed radiuses may cause longer analysis processing times
Correct Answer
A. the seed radius specifies the number of pixels that can be used to establish the range of pixel values that will be used to draw the polygon.Explanation
Specifying a larger seed radius in Seed Tool Properties typically causes a larger polygon to be drawn because the seed radius specifies the number of pixels that can be used to establish the range of pixel values that will be used to draw the polygon. This means that a larger seed radius will include a wider range of pixel values, resulting in a larger area being selected to form the polygon.Rate this question:
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- 23.
Clicking a single pixel rather than dragging a box when using the Seed Tool typically causes a smaller polygon to be drawn because
- A.
the seed radius would automatically become smaller.
- B.
the seed radius would automatically become larger.
- C.
the number of pixels used to build the pixel value range would be smaller.
- D.
smaller polygons can cause longer analysis processing times.
Correct Answer
C. the number of pixels used to build the pixel value range would be smaller.Explanation
When using the Seed Tool, clicking a single pixel instead of dragging a box would cause a smaller polygon to be drawn because the number of pixels used to build the pixel value range would be smaller. When a box is dragged, it includes more pixels within its range, resulting in a larger polygon being drawn. By clicking a single pixel, the range of pixel values used to create the polygon is limited to that specific pixel, resulting in a smaller polygon being generated.Rate this question:
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- 24.
A resolution merge can greatly enhance an image because
- A.
it can increase the resolution of a low-resolution image
- B.
it can use the real color of a low-resolution image to enhance a monochromatic high-resolution image.
- C.
it can change a satellite image into a aerial photograph.
- D.
it allows you to hand color an image using Drawing tools.
Correct Answer
B. it can use the real color of a low-resolution image to enhance a monochromatic high-resolution image.Explanation
A resolution merge can greatly enhance an image by using the real color of a low-resolution image to enhance a monochromatic high-resolution image. This means that the low-resolution image can provide additional color information to improve the overall quality and appearance of the high-resolution image.Rate this question:
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