Estimating grassland curing with remotely sensed data

Chaivaranont, Wasin; Evans, Jason P.; Liu, Yi Y.; Sharples, Jason J.

doi:https://doi.org/10.5194/nhess-18-1535-2018

Articles | Volume 18, issue 6

https://doi.org/10.5194/nhess-18-1535-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/nhess-18-1535-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 18, issue 6

Research article

|

04 Jun 2018

Research article |

| 04 Jun 2018

Estimating grassland curing with remotely sensed data

Wasin Chaivaranont, Jason P. Evans, Yi Y. Liu, and Jason J. Sharples

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Final revised paper (published on 04 Jun 2018)
Preprint (discussion started on 11 Apr 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of the manuscript "Estimating Grassland Curing with Remotely Sensed Data" by Wasin Chaivaranont1, Jason P. Evans1, Yi Y. Liu1, 2, Jason J. Sharples', Anonymous Referee #1, 19 Dec 2017
- AC1: 'Author Response for nhess-2017-101-RC1', Wasin Chaivaranont, 30 Jan 2018
RC2: 'Review of manuscript “Estimating Grassland Curing with Remotely Sensed Data”', Anonymous Referee #2, 21 Dec 2017
- AC2: 'Author Response for nhess-2017-101-RC2', Wasin Chaivaranont, 30 Jan 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (14 Feb 2018) by Joaquim G. Pinto

AR by Anna Mirena Feist-Polner on behalf of the Authors (27 Mar 2018) Author's response

ED: Referee Nomination & Report Request started (12 Apr 2018) by Joaquim G. Pinto

RR by Anonymous Referee #1 (26 Apr 2018)

RR by Anonymous Referee #2 (04 May 2018)

Suggestions for revision or reasons for rejection

GENERAL COMMENTS

The study conducted by this paper is a useful one for which bushfire researchers will be interested in the results. Namely, the paper investigates the extent to which the vegetation optical depth (VOD) measured by satellite-based microwave sensors could be used to estimate the degree of curing (DOC, dead fraction) of grasslands, either alone or in conjunction with optical sensors. I think the paper's results are accurately captured by this sentence in the Conclusions section: "While adding VOD to the DOC estimation model may introduce a comparable alternative to the existing optical based models, there is still no clear advantage of including VOD over the 5 current [optical] methods.".

I am satisfied that the authors have responded adequately to my comments on an earlier version of this manuscript, which the authors' response labels RC2.

Inclusion of the new Figures 3 and 4 (i.e. Figures RC2-1 and -2, being scatter plots of DOC and DOC residual versus various predictors) in response to my comment A.6 is a big improvement. They allow the reader to see the correlations between the variables for themselves. The representation of two or three datasets as coloured open circles on the same axes is a little difficult to take in although manageable with effort.

Regarding my comments A.10 and A.11, which were concerned that the comparison of Grassland Fire Danger Index (GFDI) calculated with various versions of DOC, I accept the authors' justification for including the analysis, namely that it demonstrates that GFDI with dynamic DOC can reduce overestimation in GFDI with 100 % constant DOC; that is, essentially, that using DOC estimated from VOD is better than using no DOC information to calculate GFDI.

SPECIFIC COMMENTS

It would be good if you can quote in your paper any relevant numbers from the Liu et al. references on the magnitude of VOD errors relevant to grassland in Australia.

Page 4, line 28 and line 36: Change "land use" to "land cover". They are different.

Page 5: In line 37 append "s" to "alternative, and in line 38 change "purposed" to "proposed".

New Figure RC1-2: The use of colour is more confusing than it needs to be: for four classes you have used four colours plus the presence or absence of hatching. Use two colours only, and with and without hatching to give the four possibilities needed. To me the dark hatching suggests "burned", so I suggest using the two colours to distinguish Referenced from Recalculated.

Page 7, line 24: The grammar is incorrect and the meaning is unclear for "At every selected observed DOC sites (excluding the forest areas)". Does it mean "Across all selected observed DOC sites (excluding the forest areas)"?

Page 7, sentence on lines 36-38: Insert "the" before each of "NDVI", "(VOD)(NDVI)" and "VOD".

Page 9, line 10: The grammar is wrong for the sentence starting "Though …". For better wording, I suggest deleting this sentence and inserting "higher probability of fire ignition and" after "indicates" in line 8.

Page 10, line 19: Delete "models".

Page 11, line 3: Delete "and near-infrared", since optical includes infrared. In the same line, change "use" to "used".

Page 11, line 5: Change "as Advance" to "as the Advanced".

Page 11, line 6: Change "VOD" to "VOD's".

Page 11, line 11: Change "active" to "the MODIS active".

Page 11, line 15: I think "500 m2" is wrong. That area corresponds to a square of approximate dimensions 22 m x 22 m. If you mean the size of a pixel of the MODIS DOC product, then write it unambiguously as "500 m x 500 m" or just "500 m".

Page 11, line 24: Change "detecting" to "predicting".

Page 27, line 27: Change "radiometre" to "radiometer".

Page 27, line 28: Change "detection that" to "detector that is".

Page 28, line 16: Change "significant" to "significance", if that is correct.

Page 28, line 18: Change "closeness of the data to the fitted regression line" to correlation between two variables. The value of r2 is affected not only by the spread about the regression line but also the range of values spanned.

RECOMMENDATION

This paper will be suitable for publishing in NHESS once the minor comments I have made above have been addressed.

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ED: Publish subject to minor revisions (review by editor) (05 May 2018) by Joaquim G. Pinto

AR by Wasin Chaivaranont on behalf of the Authors (14 May 2018) Author's response Manuscript

ED: Publish as is (19 May 2018) by Joaquim G. Pinto

Short summary

This study explore the feasibility of using a combination of recent and traditional satellite products to estimate the grassland fire fuel availability across space and time over Australia. We found a significant relationship between both recent and traditional satellite products and observed grassland fuel availability and develop an estimation model. We hope our estimation model will provide a more balanced alternative to the currently available grass fuel availability estimation models.