Prof. G. Robert Brakenridge
March 12, 2011
Director, Dartmouth Flood Observatory
http://floodobservatory.colorado.edu/
CSDMS, INSTAAR, University of Colorado
Campus Box 450
Boulder, CO 80309-0450 USA
Office: 303-735-5485
Cell: 603-252-0659
Email: Robert.Brakenridge@Colorado.edu
1.
Image Data Acquisition
2.
Identification of water pixels
3.
Create vector GIS (water boundary) polygon around
water pixels
4.
Import GIS file into Surface Water Record
5.
Sort GIS files, within workspace; create map
6.
Publish map
 Web
browsers: the usual suspects
(final product should be viewable by all)
 Remote
sensing: Envi
 GIS: MapInfo
 Web
publisher: Dreamweaver
 http://rapidfire.sci.gsfc.nasa.gov/subsets/
These and other
subsets are
available from
this website in
Geotiff format;
choose 250 m
images and the
721 band
combination

Geotiffs are in byte format (range of 0-255 shades of gray or
numbers, per band). Thus, original radiometric resolution of
the MODIS sensors is reduced in this format.

The files are geocoded at full spatial resolution (bands 1 and 2
at 250 m).

Band 7, originally at 500 m resolution, has been resampled to
250 m).

Band 2 provides the most information for water/land
discrimination. Simple thresholding of the band 2 images can
separate water (dark) from land (relatively light) pixels,
however cloud shadows will be misclassified as water if simple
thresholding is employed.
To solve the cloud shadow problem:
acquire six images (preferably, Terra and
Aqua, today and two days prior).
The next four slides, as examples, show
dark water, and (also dark) shifting cloud
shadows. Images from May 18 and 17,
2009, G (green band, MODIS band 2)
from the RGB tiff.

DFO finds the following approach works well:
1. Use ENVI band math tool. After reading in all four
geotiffs, follow (two) steps below.
a. Bandmath step 1: (float(b2) gt 150 ) or
(((float(b1)+1)/(float(b2)+80)) gt .7) or float (b3) >50
where b1 is green band of the 721 (red,green,blue)
geotiff, b2 is the blue band, and b3 is the red band.
(this is calculating an adjusted ratio of MODIS band
2/band1, after removing clouds and cloud shadow on
cloud: failed thresholds assign a “1” value)
b.Band math step 2:
float(b1)+float(b2)+float(b3)+float(b4)+float(b5)+flo
at(b6)
where b1 through b6 are the results of the step 1
math, applied to six images (commonly, three
consecutive days, Terra and Aqua)
(“float” sets the band math operations into floating
point notation, so values may range from +/– 1e38)
2. Apply threshold to the result. Pixels < 4 are water, so
all pixels with values of 0, 1,2, or 3.

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For each single image, clouds are masked: they receive a value of
1.
Where corrected ratio of the two bands is > 0.7, a 1 also assigned.
Ratio is corrected in order to avoid dividing by 0, and, empirically,
to provide best threshold for water/land in most scenes. The band
ratio approach also improves scene-scene calibration
The result for each scene is binary: all pixels are assigned 1 (cloud
or land) or 0 (water or cloud shadow)
Adding the values for four such scenes and thresholding water at
<4, segregates water pixels (at least three scenes with 0 values)
from land, and from cloud, or cloud shadow pixels.
The following four slides show the result of
the first band math equation. Then a fifth
slide shows the addition of the four bands
(second equation), with red threshold
indicating pixels < 3 (water pixels)
Experience indicates that using 6 images,
with threshold set at <4, more effectively
removes cloud shadows than using 4.

Method is fast: requires only several minutes on older PCs.

With 6 images, nearly all cloud shadows are eliminated.


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Cloud-obscured or missing data areas, if in only three of six
images, are filled in.
Thesholds and overall approach may be kept constant for most
global mapping: raising the opportunity for full automation.
Reference water layers can be obtained during times of normal
water for the same subsets and using the identical processing
technique and data source.
ENVI 4.5 and higher allows for immediate enclosure of
the red pixels, from the threshold window, into ENVI
.evf vector format.
Then, export .evf to .shp format.
Then, Mapinfo “universal translator” imports .shp to
MapInfo native format. Specify projection: latitude and
longitude, WGS 84. Sample result follows.
.
GIS outlines (vectors) of entire
scene, blue-filled
polygons
GIS outlines (vectors) of
detail, blue-filled
polygons
GIS outlines (vectors) of
detail, unfilled
polygons
Task 4. Import GIS file into
Surface Water Record
In this example, solid blue layer is comparison water, March 15, 2009 and is
superimposed above solid red layer, which is current surface water, May 25,
2010. Much “red” is hidden below blue, visible red is flooding
Identification of flood water is dependent on comparison
data, obtained by mapping of normal surface water
extent .
GIS workspaces have capability to store and display
multiple water map layers. If normal range of annual
variability is imaged, and mapped, then flood layer can
be evaluated in comparison to normal water variability.
Flood Inundation map should indicate where unusual
high water is inundating land. Following is approach
used at DFO.





Assemble map data layers: shaded relief (raster; all others are vector);
drainage, latitude and longitude (graticule), cities and towns, national
boundaries, watersheds, possibly roads, other features.
DFO uses drainage features and towns from the Digital Chart of the World
(DCW) for many of its maps;. Access to more recent national GIS data can
be of much benefit.
Publically available topography includes GTOPO (1 km) and SRTM (80
m); both available online.
Commence mapping water and building water layers using the same
sensor to be used for mapping floods…in this case, MODIS aboard Terra
and Aqua. Create workspace and display.
DFO calls these GIS workspaces, and resulting displays, a “Surface Water
Record”. Mapping of floods result in a permanent, and constantly growing
record of lands observed at various times to be subject to inundation.

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Large format JPG or Geotiff output can be ingested into other GIS if coordinates
and projection are provided. Vector GIS data export (flood inundation polygons), in
contrast, can be cumbersome and require additional processing to be useful to end
users. Still, many end users request the GIS vector data.
It is essential display normal surface water. Arrange any new layer, showing
currently flooded land, beneath such reference water layers.
Using our fixed-area Surface Water Records, DFO rapidly ingests newly mapped
water, and locates such above previously mapped floods but below normal water
areas. Dark blue = current flooding; light red = previously flooded land; light blue
is normal surface water. Map conveys at a glance where flooding is now underway
and where it has occurred in the past.
When new data are acquired and ingested, these water areas are now coded in
dark blue and previous date water areas are recoded to the appropriate light red
colors for previous flooding.
Examples of Surface Water Record Maps
Current and Past Flooding, E30N10 (next slide) then 140ES30
Dark Blue is current flooding
Light Blue is permanent surface water.
Medium red is land flooded earlier this year.
Light red is mapped flooding, 2001 to January 1 of this year..
Clickable white dots provide AMSR-E estimated river discharge, 2002-present.