Toolbar for Analysis¶
Basic toolkit: mosaic tool , reclass toolset and tools
Mosaic Tool¶
This tool allows the user to mosaic by manually choosing cutlines between images before mosaicing.
Click ??? icon on toolbar to start use tool:
Create¶
Users want to create mosaic preparation manually with given choices.
Step 1: Click Create Mosaic Preparation button
Step 2: Type data:
Type Name
Select images from list images, at least 2 images (Search image from list)
Select cutline method
Minimum Squared Difference: A cutline is determined in each overlapped area between two adjacent images, with minimum square difference of gray values at the same locations of the region.
Minimum Difference: A cutline is determined in each overlapped area between two adjacent images, with minimum difference of gray values at the same locations of the region.
Edge: Provides better output in urban-area mosaicking, or in images containing many linear features. The objective is to avoid placing cutlines across linear features.
Maximum Data: Places cutlines on the boundary of the real image pixels, meaning that NoData pixels will be ignored when the image boundary is determined.
Note: Avoid placing cutlines on any of the following:
Buildings or man-made features, because they can lean in different directions in the imagery
Large bodies of water, because waves and the color of the water can differ among the various images
Areas that are significantly different in color and texture, such as forests and cultivated land, because they, too, can differ image to image
Check Simplify Cutlines, if not check, skip (5)
Type Simplification Level
Select Color Balancing Method: Color balancing evens out the color contrasts from one image to another to reduce the visibility of the seams and produce a mosaic that is appealing visually. There are 4 methods:
Bundle: firstly, all overlapping image areas after removing anomalies in the data will compute the statistics. A bundle color adjustment (both the mean and sigma of the brightness and contrast) is applied to minimize the overall difference between all overlapping areas. Secondly, the remaining differences are modified with dodging.
Overlap: computes the color-balancing histogram using only the pixels in the overlapping area of the images being added to the mosaic file.
Histogram: Builds histograms for each image starting from the center of the mosaic, determines the optimum radiometry for the input image from the data then applies the transformation to the entire image.
Neighborhood: using all surrounding images to modify the gain and bias of the histogram, regardless of their z-order (based on sorting order) and works iteratively to modify neighboring pixels.
Click Generate button
After generating, a task will be created. Wait for task success, mosaic preparation will be created. Please back to the Mosaic Preparation page to check.
Search¶
Users want to search mosaic preparation by name in the list. Type name in search input -> Enter
=> Return list contains the type name.
Edit¶
Step 1: Click ?? icon
Step 2: You can:
Move layer image by drag
Highlight by click layer or click image directly
Add to map
Zoom
Edit ?? : Click image directly on map -> Edit -> Click ?? icon to save
Step 3: Click Submit button to run prepare mosaic or Back to save change.
Rename¶
Users want to Rename mosaic preparation names. Click pen icon:
Type new name -> Click Save button
=> Name is changed.
Run¶
Users want to run mosaic preparation to create mosaiced images.
Step 1: Click ?? icon to run:
Step 2: Type Mosaic image name -> Click Submit button
Step 3: Confirm pay cost
=> => Task will be created in Tasks, wait task success, check result in Imagery.
Delete¶
Users want to delete Mosaic Preparation. Click ?? icon of Mosaic Preparation you want delete. Then Click the Delete button to confirm delete.
Reclass Toolset¶
Reclass toolset will reclassify (or change) the value in a raster- a range of value pixels will be reclassified or a single pixel (unique) will be assigned to another value.
You can choose image first, then click icon or click icon, then select image.
Choose image -> Click icon:
Step 1: Select band (Only one, you can search if there are many bands)
Step 2: Click Classify button
Step 3: Type input:
Select mode
Standard Deviation: the method shows you how much a feature’s attribute value varies from mean. Class breaks are created with equal value ranges that percentage of the standard deviation using mean value and the standard deviation from the mean
Equal interval: the method divides the range of values into equal-sized subranges.
Quantile: the method will assign the same number of values to each class. There are no empty classes or classes with too few or too many values. This method works well with the linearly distributed data.
Type Amount of value (If mode is Standard Deviation, the default Amount of value will be 6)
Step 4: Click Classify button
After click Classify button, please see Histogram and Break Values based mode and amount of value
Step 5: Click Confirm button
Step 6:
You can add Max value - Min value - Value
Type new data
or you can edit by type directly
or delete by click ??? icon
You can Revert values
You can Clear all values
Default: No data value equal 0. If you want to change No data value, type input directly. And click checkbox if you want to change miss value to No data
Click Unique if you want each old value to correspond to a unique new value
Step 7: Click Submit button
Type name -> Click Confirm button
=> Tasks will be created in Tasks. Wait task was successful, please check at Imagery with the correct name.
Tools¶
There are 4 types of tools: ARD, Vector toolkit, Unsupervised and Result toolkit.
ARD Toolkit: includes the tool for analysing raster/ images.
Click ?? icon to start use tools:
Select tool:
Select type ARD:
For more informations about tool, click ?? icon.
Advanced Mosaic¶
This tool support merge/ combination list of images into a single image automatically
Step 1: Type input
Type name
Select images from list images (type search input to search image)
Step 2: Click Submit button
Step 3: Click Confirm to pay cost
=> Task will be created. When task is success, please check result in menu Imagery
Align Pixel¶
This tool is able to take several rasters as input and to align them perfectly, that means:
reproject to the same CRS,
resample to the same cell size and offset in the grid,
clip to a region of interest,
rescale values when required.
Type name
Select image from list images (only one image)
Select reference image (only one image):
Aspect¶
Calculates the aspect of the Digital Terrain Model in input. The final aspect raster layer contains values from 0 to 360 that express the slope direction, starting from north (0°) and continuing clockwise.
Type name
Select image from list images (only one image)
- There are 4 option:
Trigonometric: trigonometric angle instead of azimuth. Thus 0° means East, 90° North, 180° West, 270° South
Zero for flat:Return 0 for flat areas with slope=0, instead of -9999
Compute Edges: Generates edges from the elevation raster
Use Zevenbergen Thorne formula instead of the Horn’s one: The literature suggests Zevenbergen & Thorne to be more suited to smooth landscapes
Cloud Free Mosaic¶
It will help users remove clouds in an area if there are collections of overlapping images.
Step 1: Type input
Type name
Select images (images must overlap)
- There are two options:
Sort by acquired date (asc) (default)
Sort by cloud percentage
Dem Extraction¶
A DSM (also referred to as a DEM) extracted from stereo images represents the earth’s surface and includes all objects on it.
Type name
Select images: select stereo images
Dem Super Resolution¶
Increasing the resolution of DEM images.
Type name
Select image (only one image):
Down Scale¶
Improve the resolution of the image from low to high resolution.
Type name
Select image
- There are two level:
2: means an increase in spatial resolution in double. For example from resolution 10m, downscale will improve the spatial resolution to 5m.
4: means increasing in spatial resolution four times.
Hillshade¶
The hillshade is calculated by using DEM image and the sun position
Type name
Select image
Type z factor: Vertical exaggeration used to pre-multiply the elevations
Type scale: Ratio of vertical units to horizontal. If the horizontal unit of the source DEM is degrees (e.g Lat/Long WGS84 projection), you can use scale=111120 if the vertical units are meters (or scale=370400 if they are in feet)
Type Azimuth of the light:Azimuth of the light, in degrees. 0 if it comes from the top of the raster, 90 from the east, …
Type Altitude of the light: Altitude of the light, in degrees. 90 if the light comes from above the DEM, 0 if it is raking light
- There are two options:
Compute Edge
Use Zevenbergen Thorne formula instead of the Horn’s one
- Select Shading type
Combined: combined shading, a combination of slope and oblique shading
Multidirectional: multidirectional shading, a combination of hill shading illuminated from 225 deg, 270 deg, 315 deg, and 360 deg azimuth.
Image Resampling¶
Decrease the resolution of the image. Change image from high resolution to low resolution.
Type name
Select image
Type level: (if you choose level 2, the spatial resolution will decrease double for example raw data has 5m resolution, after resampling with level 2, the resolution will be 10m)
Mosaic¶
This tool supports merge/ combination list of images into a single image automatically. It is similar to advanced mosaics with different algorithms.
Orthorectify¶
Orthorectify is the process of removing the effects of terrain and sensor creating a planimetrically correct image. The image will match the spatial by considering location, elevation and sensor information.
Matching band
Number of GCPs: Type the number of points that you want to collect over each image
Minimum acceptance score: enter a value from 0-1 which defines the minimum correlation score that will be considered a successful match.
- There are two Matching method:
FFTP: Fast Fourier Transform Phase Matching: when two images have a relative shift between them, the result is a phase difference in the Fourier domain. FFTP determines the shift between images using this phase difference.
NCC: Normalized Cross Correlation. This method finds the relative shift between two images by finding the shift that produces the maximum cross-correlation coefficient of the gray values in the images.
Search radius: type a number to define the search radius around the kernel
Pansharpening¶
Pansharpen will use a panchromatic image to sharpen the multispectral image to create a high resolution color image.
Polygonize¶
This tool is specially designed for post processing of the Farmboundary model. The input file is the results of farm boundary model.
Raster Clip¶
Clip the Raster using the mask layer
Slope¶
Calculate the slope from the DEM image. The slope is the angle of inclination of the terrain and is expressed in degrees
Stack¶
Layer stacking is a process for combining multiple images with same extent into a single image.
Visual Imagery¶
To convert an image to data type unit 8 with reference image or not.
Zonal¶
Calculates statistics of a raster layer for each feature of an overlapping polygon vector layer.
In Algorithm, there are 4 options:
Min: Determines the smallest value of all cells in the value raster that belong to the same zone as the output cell
Mean: Determines the mean of all cells in the value raster that belong to the same zone as the output cell
Max: Determines the largest value of all cells in the value raster that belong to the same zone as the output cell
Most value: Determines the most value of all cells in the value raster that belong to the same zone as the output cell
Step 2: Click Confirm button
Step 3: Confirm to pay cost
Result toolkit: includes the tool for analysing raster results.
Crop Scout¶
Step 1: Type input: (You can check raster results in Results or Imagery)
Step 2: Click Tool setting button -> Select raster band:
Step 3: Click Confirm button
The Task will be created in Tasks. Wait for task success, check result.
Reclassification¶
Step 1: Type input
Step 2: Click “Tool setting” button
Click color box to change color for each class
Change name for each class
Change value for each class
Step 3: Click Apply button. The Task will be created in Tasks. Wait for task success, check result.
Morphology¶
This help users in post processing to eliminate the small area and fill the hole
Step 1: Type input
Step 2: Click “Tool setting” button -> Type epsilon
Step 3: Click Confirm button. The Task will be created in Tasks. Wait for task success, check result.
Vectorization¶
Step 1: Type input
Step 2: Click “Tool setting” button -> Type epsilon
Step 3: Click Confirm button. The Task will be created in Tasks. Wait for task success, check result.