Classification and Monitoring of Reed Belts Using Dual-Polarimetric TerraSAR-X Time Series
"> Figure 1
<p>Overview of the study area Lake Fürstenseer, near Neustrelitz, Germany. The ascending and descending SAR images are quicklooks of the TerraSAR-X scenes. The quicklook images are RGB composites (<math display="inline"> <semantics> <mrow> <msub> <mi>δ</mi> <mrow> <mi>H</mi> <mi>H</mi> </mrow> </msub> </mrow> </semantics> </math>,<math display="inline"> <semantics> <mrow> <mo> </mo> <msub> <mi>δ</mi> <mrow> <mi>V</mi> <mi>V</mi> </mrow> </msub> </mrow> </semantics> </math>, and <math display="inline"> <semantics> <mrow> <msub> <mi>δ</mi> <mrow> <mi>H</mi> <mi>H</mi> <mo>−</mo> <mi>V</mi> <mi>V</mi> </mrow> </msub> </mrow> </semantics> </math>) with a reduced pixel size of ca. 25 m. The ascending and descending SAR images were acquired in November 2014 (14 November 2014, 22 November 2014). The look direction (range) of the sensor is indicated by arrows.</p> "> Figure 2
<p>Overview of Lake Fürstenseer with the training areas (points) and validation area (polygons) of the five classes. The classes are: reed (pink), water (blue), meadow (orange), deciduous (bright green) and coniferous forest (brown). Base layer is the digital orthophoto with 40 cm resolution (DOP40) from 2013. Photos were taken at the southwestern shoreline (grey cross).</p> "> Figure 3
<p>Photos of a reed belt at the southwestern part of the lake in June 2014 (<b>a</b>,<b>b</b>); November 2015 (<b>c</b>,<b>d</b>); and January 2016 (<b>e</b>). The location of the photos is marked in <a href="#remotesensing-08-00552-f002" class="html-fig">Figure 2</a>. Photos (<b>a</b>,<b>c</b>,<b>e</b>) were taken in a northwestern direction, the photos (<b>b</b>,<b>d</b>) in a southeastern direction.</p> "> Figure 4
<p>Lake level changes of Lake Fürstenseer between January 2006 and March 2015. The monitoring period of this study (August 2014 until May 2015) is highlighted in orange.</p> "> Figure 5
<p>Time series of mean values for the 16 parameters from the validation areas (cf. <a href="#remotesensing-08-00552-t002" class="html-table">Table 2</a> and <a href="#remotesensing-08-00552-f002" class="html-fig">Figure 2</a>). The mean of the reed area is pink, the “true reed” area is black, meadow is orange, water is blue, coniferous is brown and deciduous forest light green. Acquisitions in asc orbit are noted in grey, dates in desc orbit are in black.</p> "> Figure 6
<p>RGB images (<math display="inline"> <semantics> <mrow> <msub> <mi>δ</mi> <mrow> <mi>H</mi> <mi>H</mi> <mo>−</mo> <mi>V</mi> <mi>V</mi> </mrow> </msub> </mrow> </semantics> </math>, <math display="inline"> <semantics> <mrow> <mrow> <mo>|</mo> <mrow> <msub> <mi>γ</mi> <mrow> <mi>H</mi> <mi>H</mi> <mi>V</mi> <mi>V</mi> </mrow> </msub> </mrow> <mo>|</mo> </mrow> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <msub> <mover accent="true"> <mo>∝</mo> <mo>¯</mo> </mover> <mrow> <mi>d</mi> <mi>u</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> </mrow> </semantics> </math>) acquired in summer on 4 August 2014 (<b>a</b>) and winter on 22 November 2014 (<b>b</b>). The colors are stretched from minimum value to maximum value within the current map extent. Both images are acquired in desc orbit with a western look direction.</p> "> Figure 7
<p>Classification accuracies of each observed polarimetric parameter stacked for each date. The proportions within each stack are sorted from the bottom to the top. The correct classified proportion (<b>a</b>); omission error (<b>b</b>); and commission error (<b>c</b>) are illustrated seperatedly. The colors of each parameter are the same for all graphs. The labels of the dates are grey for asc images and black for desc images.</p> "> Figure 8
<p>Classification accuracies for each acquisition date in percent. Basis for the classification was stacks of all observed polarimetric parameters. For the evaluation the classification result was clipped to the area of Lake Fürstenseer + 50 m buffer. The correct classified proportion is illustrated in green, the commission error (false positive) in dark grey and the omission error (false negative) in light grey. The labels of the dates are grey for asc images and black for desc images.</p> "> Figure 9
<p>Stacked and sorted “mean decrease in accuracy” of the parameters. Basis for the classification were stacks of all parameters. The higher the mean decrease in accuracy, the higher the importance of the variable for classification. The labels of the dates are grey for asc images and black for desc images.</p> "> Figure 10
<p>RF classification result based on a stack of all parameters on 4 August 2014 (<b>a</b>) and on 7 August 2014 (<b>b</b>). The classified reed areas are shown in pink, the validation reed areas are outlined in black. The commission error of reed is very high in the two August images (~65%). The in situ reed areas are overestimated and there are false positive classified reed areas in the desc (<b>a</b>) and in the asc (<b>b</b>) images at the shorelines in the range direction: On the desc image (<b>a</b>) the reed areas are overestimated at western shorelines, in the asc image they are overestimated at the eastern shorelines.</p> "> Figure 11
<p>RF classification result based on a stack of all parameters on 22 November 2014 (<b>a</b>) and on 14 November 2014 (<b>b</b>). The classified reed areas are shown in pink, the validation reed areas are outlined in black. The commission error of reed is still very high in the two November images (~60%). This error is mainly caused by an overestimation of the reed areas.</p> "> Figure 12
<p>Classification accuracies (in percent) of multi-temporal stacks with only asc, only desc images or a combination of both looking directions. For the evalution, the classification result was clipped to the area of Lake Fürstenseer + 50 m buffer. The correct classified proportion is illustrated in green, the commission error (false positive) in dark grey and the omission error (false negative) in light grey.</p> "> Figure 13
<p>Classification result (colors) of the multi-temporal stack of asc and desc winter images (without dates of ice coverage). Overlaid are validation areas (black outlined polygons with different fill pattern) of the five classes: reed, water, meadow, deciduous and coniferous forest.</p> ">
Abstract
:1. Introduction
- Gain knowledge about the scattering mechanisms of reed belts during the monitoring period (August 2014 to May 2015) and their exploitation for the phenological monitoring of reeds
- The application of an automatic algorithm for classification of reed areas with recommendations for the best suitable classification input parameters and the most effective acquisition periods for a performant classification.
2. Study Area
3. Available Data
3.1. Dual-Polarimetric (HH, VV) TerraSAR-X Time Series
3.2. Validation and Training Data
4. Methods
4.1. Introduction to the Theory of Dual Polarimetry and Its Scattering Parameters
4.2. Random Forest Classification
- Single parameter images: every parameter at every date
- Parameter stacks: stack of all kinds of parameters of a date
- Multi-temporal parameter stacks: stack of all kinds of parameters of multiple dates (with different look directions)
- -
- all 19 asc and desc images;
- -
- all 15 desc images;
- -
- all four asc images;
- -
- asc and desc winter images without ice (31 October 2014, 11 November 2014, 14 November 2014, 22 November 2014, 25 November 2014, 12 March 2015, 23 March 2015, 26 March 2015);
- -
- asc winter images without ice (14 November 2014, 25 November 2014, 26 March 2015);
- -
- desc winter images without ice (31 October 2014, 11 November 2014, 22 November 2014, 12 March 2015, 23 March 2015);
- -
- two timely matching asc and desc images in November (14 November 2014 and 22 November 2014);
- -
- two timely matching asc and desc images in March (26 March 2015 and 23 March 2015).
4.3. Evaluation of the Classification
5. Results and Discussions
5.1. Time Series Analysis of the Validation Areas
5.2. RF Classification: Single Parameter Layer of Every Date
5.3. RF Classification with Parameter Stacks for One Date
5.4. RF Classification with Multi-Temporal Parameter Stacks
6. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Date | Mean Incidence Angle (°) | Orbit | NESZ HH (dB) | NESZ VV (dB) | SNR HH (dB) | SNR VV (dB) | Comments |
---|---|---|---|---|---|---|---|
4 August 2014 | 38.5 | Desc | −20.19 | −20.32 | 10.81 | 10.80 | |
7 August 2014 | 42 | Asc | −19.61 | −19.74 | 8.92 | 9.06 | |
15 August 2014 | 38.5 | Desc | −20.66 | −20.93 | 9.95 | 9.82 | |
6 September 2014 | 38.5 | Desc | −20.47 | −20.69 | 9.54 | 9.35 | |
28 September 2014 | 38.5 | Desc | −20.55 | −20.91 | 9.17 | 8.96 | |
9 October 2014 | 38.5 | Desc | −20.41 | −20.40 | 10.58 | 10.21 | |
20 October 2014 | 38.5 | Desc | −19.56 | −18.79 | 8.76 | 7.60 | |
31 October 2014 | 38.5 | Desc | −21.03 | −21.38 | 9.77 | 9.61 | |
11 November 2014 | 38.5 | Desc | −21.01 | −21.34 | 9.80 | 9.52 | |
14 November 2014 | 42 | Asc | −19.40 | −18.36 | 7.91 | 6.88 | |
22 November 2014 | 38.5 | Desc | −21.12 | −21.35 | 9.47 | 9.23 | |
25 November 2014 | 42 | Asc | −20.21 | −20.10 | 8.45 | 8.34 | |
18 February 2015 | 38.5 | Desc | −19.87 | −19.86 | 9.03 | 8.54 | Lake borders covered by ice |
1 March 2015 | 38.5 | Desc | −20.94 | −20.80 | 9.43 | 8.92 | |
12 March 2015 | 38.5 | Desc | −21.01 | −21.36 | 9.61 | 9.53 | |
23 March 2015 | 38.5 | Desc | −20.87 | −21.23 | 9.91 | 9.86 | |
26 March 2015 | 42 | Asc | −19.99 | −19.81 | 8.70 | 8.45 | |
3 April 2015 | 38.5 | Desc | −20.54 | −20.55 | 9.78 | 9.42 | |
6 May 2015 | 38.5 | Desc | −20.43 | −20.85 | 10.48 | 10.53 |
Parameter | Abbreviation | Unit | Range |
---|---|---|---|
Intensity of HH channel | δHH | Decibel (dB) | −25‒5 |
Intensity of VV channel | δVV | dB | −25‒5 |
Intensity of HH plus Intensity of VV | δHH+VV | dB | −25‒5 |
Intensity of HH minus Intensity of VV | δHH-VV | dB | −25‒5 |
Intensity ratio HH/VV | δHH/VV | dB | −25‒5 |
Coherence HHVV amplitude | - | 0‒1 | |
Coherence HHVV phase | radian | −π‒π | |
Intensity XX (pseudo) | dB | −25‒5 | |
Dual-polarimetric mean alpha angle | Degree (°) | −180‒180 | |
Dual-polarimetric dominant alpha angle | Degree (°) | −180‒180 | |
Entropy | - | 0‒1 | |
Anisotropy | - | 0‒1 | |
H-A-combination 1 | - | 0‒1 | |
H-A-combination 2 | - | 0‒1 | |
H-A-combination 3 | - | 0‒1 | |
H-A-combination 4 | - | 0‒1 |
Parameter | Summer | Winter, Early Spring |
---|---|---|
(only desc images) | 2.81 ± 0.09 dB | 4.47 ± 0.67 dB |
−11.92 ± 0.69 dB | −13.60 ± 0.39 dB | |
0.31 ± 0.01 | 0.45 ± 0.03 | |
−1.29 ± 0.15 rad | −2.07 ± 0.10 rad | |
44.4° ± 1.2° | 51.4° ± 1.3° | |
41.7° ± 30° | 55.2° ± 2.5° | |
0.84 ± 0.01 | 0.71 ± 0.04 | |
0.44 ± 0.01 | 0.60 ± 0.04 | |
0.08 ± 0.00 | 0.10 ± 0.00 | |
0.36 ± 0.01 | 0.40 ± 0.01 | |
0.09 ± 0.01 | 0.19 ± 0.03 | |
0.48 ± 0.02 | 0.30 ± 0.04 |
Predicted by Random Forest | ||||||
---|---|---|---|---|---|---|
Coniferous Forest | Deciduous Forest | Meadow | Reed | Water | ||
Actual Class | Coniferous forest | 36,807 | 1527 | 1503 | 2528 | 0 |
Deciduous forest | 1501 | 30,931 | 91 | 2415 | 0 | |
Meadow | 453 | 557 | 10,597 | 64 | 0 | |
Reed | 0 | 181 | 0 | 14,440 | 0 | |
Water | 0 | 0 | 0 | 247 | 32,706 |
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Heine, I.; Jagdhuber, T.; Itzerott, S. Classification and Monitoring of Reed Belts Using Dual-Polarimetric TerraSAR-X Time Series. Remote Sens. 2016, 8, 552. https://doi.org/10.3390/rs8070552
Heine I, Jagdhuber T, Itzerott S. Classification and Monitoring of Reed Belts Using Dual-Polarimetric TerraSAR-X Time Series. Remote Sensing. 2016; 8(7):552. https://doi.org/10.3390/rs8070552
Chicago/Turabian StyleHeine, Iris, Thomas Jagdhuber, and Sibylle Itzerott. 2016. "Classification and Monitoring of Reed Belts Using Dual-Polarimetric TerraSAR-X Time Series" Remote Sensing 8, no. 7: 552. https://doi.org/10.3390/rs8070552