Remote Sensing in the Cloud – Deriving chlorophyll concentration using HICO IPS

Continuing our review of the algorithms currently implemented in the cloud-based HICO Image Processing System (HICO IPS), here we provide an overview of the two algorithms utilized for deriving estimates of chlorophyll concentration in oceanic water.

HICO IPS

Objective – Implement multiple algorithms for estimating chlorophyll concentration, as well as a methodology for evaluating the difference between these algorithms.

Algorithms – Derive estimates of surface chlorophyll-a concentration using one of two ocean color algorithms, OC4 (O’Reilly et al. 2000) or OCI (Hu et al. 2012); or for comparison, the difference between these two algorithms (OC4 – OCI). These algorithms first perform spectral resampling of the HICO hyperspectral data to the multispectral SeaWiFS bands on which the algorithms are based.

Inputs – User specified HICO scene, with optional region-of-interest; optional NDWI land/water mask, with user adjustable NDWI threshold; and specification of desired chlorophyll algorithm.

HICO IPS Chesapeake Bay

Output – Surface chlorophyll-a concentration (mg/m^3) depicted using a blue-red color ramp where blue represents low chlorophyll concentration and red represents high concentration. If the NDWI land/water mask was selected, then chlorophyll concentrations are only calculated and mapped for the water pixels (as is logical).

HICO IPS Chesapeake Bay Chlorophyll

Try it out today for yourself: http://hyspeedgeo.com/HICO/

 

Related posts

Introducing the HICO Image Processing System

Calculating a land/water mask using HICO IPS

Evaluating water optical properties using HICO IPS

Characterizing shallow coastal environments using HICO IPS

 

References

Hu C, Lee Z, Franz BA (2012) Chlorophyll-a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference, Journal of Geophysical Research, vol. 117(C1), 25 pp.

O’Reilly JE, Maritorena S, O’Brien MC, et al. (2000) SeaWiFS postlaunch calibration and validation analyses, Part 3, NASA Technical Memorandum 2000-206892, vol. 11, 49 pp.

Application Tips for ENVI 5.x – Image to map registration using GCPs

This is part of a series on tips for getting the most out of your geospatial applications. Check back regularly or follow HySpeed Computing to see the latest examples and demonstrations.

Objective: Re-utilize ground control points (GCPs) originally obtained from the “Image Registration Workflow” to perform “Image to Map” registration of an image or its associated spatially equivalent images.

Scenario: This tip demonstrates the steps used to align a chlorophyll image derived from a hyperspectral HICO scene of the Turkish Straits with a multispectral Landsat 8 OLI image mosaic of the same area.

In some situations it is advantageous, or necessary, to re-use GCPs to geo-locate more than one spatially equivalent image. For example, instances where analysis is first performed on a non-registered source image and output products must be geo-located using the same GCPs as used for the source image.

Shown here is a depiction of the registration output for a HICO scene of the Turkish Straits, achieved following steps outlined in one of our previous tips: Improved geo-location using the Image Registration Workflow. What follows is an example of how to similarly geo-locate a derived chlorophyll image using the same GCPs as used in this registration.

HICO Turkish Straits

The Tip: In this example, the process isn’t as direct as using ENVI’s “Warp from GCPs” tools, or using the “Registration: Image to Map” tool, since these do not produce the desired output. Instead, as outlined below, we perform “Image to Map” registration via the “Registration: Image to Image” tool:

  • This example requires that you first use the “Image Registration Workflow” to generate a desired set of GCP points for geo-locating your selected source image.
  • Once the GCP points have been created, open and display the base image (here a Landsat 8 OLI mosaic) and non-registered warp image (here a HICO-derived chlorophyll image).
  • Start the “Registration: Image to Image” tool, found under “Geometric Correction > Registration” in the Toolbox.
  • In the opening dialog, select the desired band from the base image (in this example we use the OLI green 562.3 nm band), and then click Ok.
  • Note that the registration tool will attempt to automatically generate tie points between selected bands from the base and warp images; however, these points will be discarded and replaced using the existing file. This means that the specific bands selected for the base and warp images isn’t critical at this stage of the process.
  • In the next dialog, select the warp file to be registered, perform any desired spectral subsetting, and click Ok.
  • Now select the band from the warp image to be used for registration process (here the chlorophyll band).
  • When asked if you would like to “select an optional existing tie points file”, respond No.
  • Next, since you won’t be using the automatically generated tie points, accept the default “Automatic Registration Parameters”, being sure that “Examine tie points before warping” is set to Yes, and then click Ok.
  • The tool now opens windows for “Ground Control Points Selection” and the “Image to Image GCP List” as well as displays the base and warp images using the ENVI Classic 3-window interface.
  • In the “Ground Control Points Selection”, under “Options”, select “Clear All Points”. In the same window, under “File”, select “Restore GCPs from ASCII…”, and choose the appropriate GCP file that was previously generated using the “Image Registration Workflow”.
  • The “Image to Image GCP List” is now populated with your previously derived GCPs, which are also now shown in the two image displays.

Turkish Straits GCPs

  • In the “Ground Control Points Selection”, under “Options”, select “Warp File (as Image to Map)…”, choose the desired warp file to be registered (the chlorophyll image), perform any desired spectral subsetting, and click Ok.
  • The final window that appears is the “Registration Parameters” dialog. Here you will set the registration parameters equivalent to those of the previously registered source image. Note that the default parameters are likely not the same, and will need to be adjusted using the metadata from the original output image derived from the “Image Registration Workflow”. The metadata can be accessed directly from the image header file, or through the ENVI interface.
  • Enter the appropriate parameters for the “Output Project and Map Extent”, which includes the projection, coordinates of the upper left corner, output pixel size, and output image size.
  • Now enter the same “Warp Parameters” as used in the original registration process, select an output filename, and then click Ok.

Turkish Straits registration parameters

  • Once the registration process has completed, the output image now has the same geo-location as that obtained for the original geo-located source image.

HICO Turkish Straits chl