Tag: satellite image

Monitoring Water Level Changes Using High Spatial and High Temporal Resolution Satellite Imagery

Author: Menglu Wang

Geovis Project Assignment @RyersonGeo, SA8905, Fall 2019

Introduction

The disappearing of the once world’s fourth largest lake, Aral Sea, was a shocking tragedy to the world, not only just the shrinkage of lake volume from 1,093.0 km3 in 1960 to 98.1 km3 in 2010 ( Gaybullaev et al., 2012), but also, the rate of shrinkage. Impacts on environment, local climate, citizen’s health, and agriculture are irreversible. This human made disaster could have been prevented in some degree if close monitoring of the lake was made and people are more educated about the importance of ecosystem. One efficient approach to monitor lake water level changes is the utilizing of satellite imagery .The spreading of free high spatial and high temporal resolution satellite imagery provides excellent opportunity to study water level changes through time. In this study, spatial resolution in 3  and 5 meters and temporal resolution as high as 3 days per visit PlanetScope Scene Satellite Imagery are obtained from Planet website. Iso-Cluster Unsupervised Classification in ArcGIS Desktop and Animation Timeline in ArcGIS Pro are used. Study area is set to Claireville Reservoir and 10 dates of imagery starting from April to late June are used to study water level changes.

Data Acquisition

To download the satellite imagery, a statement of research interest needed to be submitted to Planet Sales personal on their website (https://www.planet.com/). After getting access, go on typing in the study area and select a drawing tool to determine an area of interest. All available imagery will load up after setting a time range, cloud cover percentage, area coverage, and imagery source. To download a imagery, go select a imagery and click “ORDER ITEM” and items will be ready to download on the “Orders” tab when you click on your account profile. When downloading a item, noticing that there is a option to select between “Analytic”, “Visual”, and “Basic”. Always select “Analytic” if analysis will be made on the data. “Analytic” indicating geometric and radiometric calibration are already been made to imagery.

Methodology

ArcGIS desktop is used to implement classification and data conversion. Following after, ArcGIS Pro is used to create a animated time slide. Steps are list below:

  1. After creating a file geodatabase and opening a map, drag imagery labeled letter ending with “SR” (surface reflectance) into the map .
  2. Find or search “Mosaic To New Raster” and use it to merge multiple raster into one to get a full study area (if needed).
  3. Create a new polygon feature class and use it to cut the imagery into much smaller dataset by using “Clip”. This will speed up processing of the software.
  4. Grab “Image Classification” tool from Customize tab on top after selecting “Toolbars”.
  5. On “Image Classification” toolbar, select desired raster layer and click on “Classification”. Choose Iso Cluster Unsupervised classification. Please see Figure 1. for classified result.
  6.  Identify classes that belong to water body. Search and use “Reclassify” tool to set a new value (for example: 1) for classes belong to water body, leave new value fields empty for all the rest of classes. Check “ Change missing values to NoData” and run the tool. You will get a new raster layer contain only 1 class: water body as result (Figure 2. and Figure 3.).
  7. Use “Raster to Polygon” tool to convert resulted raster layer to polygons and clean up misclassified data by utilizing editor tool bar. After select “Start editing” from Editor drop down menu, select and delete unwanted polygons (noises).
  8. Use resulted polygons to cut imagery in order to get a imagery contain water bodies only.
  9. Do the above process for all the dates.
  10. Open ArcGIS Pro and connect to the geodatabase that has been using in ArcGIS Desktop.
  11. Search and use “Create Mosaic Dataset” tool to combine all water body raster into one dataset. Notes: Select “Build Raster Pyramids” and “Calculate Statistics” in Advanced Options.
  12. After creating a mosaic dataset, find “Footprint” under the created layer and right click to open attribute table.
  13. Add a new field, set data type as “text” and type in dates for these water body entries. Save edited table.
  14. Right click on the layer and go to properties. Under time tab, select “each feature has a single time field” for “Layer Time”, select the time field that just has been created for “Time Field”, and specify the time format same as the time field format.
  15. A new tab named “Time” will show up on first line of tabs in the software interface.
  16. Click on the “Time” tab and specify “Span”. In my case, the highest temporal resolution for my dataset is 3 days, so I used 3 days as my “Span”.
  17. Click the Run symbol in the “Play Back” section of tabs and one should see animated maps.
  18. If editing each frame is needed, go to “Animation” tab on the top and select “Import” from tabs choose “Time Slider Step”. A series will be added to the bottom and waiting to be edited.
  19. To export animated maps as videos, go to “Movie” in “Export” section of Animation tabs. Choose desired output format and resolution.  
Figure 1. Classified Satellite Imagery
Figure 2. Reclassify tool example.
Figure 3. Reclassified satellite imagery

Conclusion

A set of high temporal and high spatial resolution imagery can effectively capture the water level changes for Claireville Reservoir. The time range is 10 dates from April to June, and as expected, water level changes as time pass by. This is possibly due to heavy rains and flood event which normally happens during summer time. Please see below for animated map .

Reference

Gaybullaev, B., Chen, S., & Gaybullaev, D. (2012). Changes in water volume of the Aral Sea after 1960. Applied Water Science, 2(4), 285–291. doi: 10.1007/s13201-012-0048-z