Estimating grassland curing with remotely sensed data

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

doi: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

Viewed

Total article views: 3,650 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
2,098	1,384	168	3,650	173	209

HTML: 2,098
PDF: 1,384
XML: 168
Total: 3,650
BibTeX: 173
EndNote: 209

Views and downloads (calculated since 11 Apr 2017)

Month	HTML	PDF	XML	Total
Apr 2017	99	10	6	115
May 2017	69	11	5	85
Jun 2017	37	8	5	50
Jul 2017	7	3	1	11
Aug 2017	5	3	0	8
Sep 2017	12	3	1	16
Oct 2017	7	2	0	9
Nov 2017	13	7	0	20
Dec 2017	17	6	1	24
Jan 2018	17	6	0	23
Feb 2018	21	6	5	32
Mar 2018	8	5	0	13
Apr 2018	7	3	0	10
May 2018	12	7	0	19
Jun 2018	155	43	7	205
Jul 2018	62	17	3	82
Aug 2018	51	21	3	75
Sep 2018	25	15	1	41
Oct 2018	18	17	3	38
Nov 2018	16	20	1	37
Dec 2018	11	11	5	27
Jan 2019	6	10	0	16
Feb 2019	12	5	0	17
Mar 2019	13	10	2	25
Apr 2019	5	6	0	11
May 2019	15	8	1	24
Jun 2019	23	11	0	34
Jul 2019	10	10	1	21
Aug 2019	8	6	0	14
Sep 2019	4	5	0	9
Oct 2019	8	5	1	14
Nov 2019	4	6	1	11
Dec 2019	3	30	1	34
Jan 2020	12	31	3	46
Feb 2020	12	26	1	39
Mar 2020	5	29	1	35
Apr 2020	8	29	2	39
May 2020	11	28	1	40
Jun 2020	22	27	4	53
Jul 2020	20	26	9	55
Aug 2020	9	10	4	23
Sep 2020	10	7	0	17
Oct 2020	3	5	0	8
Nov 2020	10	12	2	24
Dec 2020	10	7	0	17
Jan 2021	18	10	0	28
Feb 2021	8	7	1	16
Mar 2021	8	4	0	12
Apr 2021	10	8	0	18
May 2021	8	5	0	13
Jun 2021	6	7	0	13
Jul 2021	6	5	0	11
Aug 2021	9	13	1	23
Sep 2021	15	14	2	31
Oct 2021	10	33	1	44
Nov 2021	15	29	0	44
Dec 2021	12	10	1	23
Jan 2022	6	13	0	19
Feb 2022	7	10	1	18
Mar 2022	10	12	1	23
Apr 2022	17	10	3	30
May 2022	14	9	1	24
Jun 2022	11	4	1	16
Jul 2022	7	3	2	12
Aug 2022	15	12	0	27
Sep 2022	15	9	1	25
Oct 2022	12	8	1	21
Nov 2022	45	12	0	57
Dec 2022	47	16	1	64
Jan 2023	44	20	1	65
Feb 2023	48	14	1	63
Mar 2023	48	10	2	60
Apr 2023	12	12	0	24
May 2023	13	17	3	33
Jun 2023	16	13	1	30
Jul 2023	9	7	2	18
Aug 2023	11	10	2	23
Sep 2023	16	18	0	34
Oct 2023	12	16	1	29
Nov 2023	9	2	0	11
Dec 2023	21	15	2	38
Jan 2024	13	19	1	33
Feb 2024	9	11	3	23
Mar 2024	8	26	2	36
Apr 2024	17	8	3	28
May 2024	20	12	3	35
Jun 2024	12	21	2	35
Jul 2024	26	11	3	40
Aug 2024	27	6	5	38
Sep 2024	14	8	1	23
Oct 2024	30	15	3	48
Nov 2024	9	10	2	21
Dec 2024	7	10	3	20
Jan 2025	12	7	0	19
Feb 2025	28	9	1	38
Mar 2025	23	13	0	36
Apr 2025	35	14	0	49
May 2025	26	7	0	33
Jun 2025	44	15	4	63
Jul 2025	19	22	2	43
Aug 2025	14	15	1	30
Sep 2025	32	16	0	48
Oct 2025	26	26	3	55
Nov 2025	30	28	1	59
Dec 2025	28	22	1	51
Jan 2026	39	25	8	72
Feb 2026	33	12	2	47
Mar 2026	15	6	0	21

Cumulative views and downloads (calculated since 11 Apr 2017)

Month	HTML	PDF	XML	Total
Apr 2017	99	10	6	115
May 2017	69	11	5	85
Jun 2017	37	8	5	50
Jul 2017	7	3	1	11
Aug 2017	5	3	0	8
Sep 2017	12	3	1	16
Oct 2017	7	2	0	9
Nov 2017	13	7	0	20
Dec 2017	17	6	1	24
Jan 2018	17	6	0	23
Feb 2018	21	6	5	32
Mar 2018	8	5	0	13
Apr 2018	7	3	0	10
May 2018	12	7	0	19
Jun 2018	155	43	7	205
Jul 2018	62	17	3	82
Aug 2018	51	21	3	75
Sep 2018	25	15	1	41
Oct 2018	18	17	3	38
Nov 2018	16	20	1	37
Dec 2018	11	11	5	27
Jan 2019	6	10	0	16
Feb 2019	12	5	0	17
Mar 2019	13	10	2	25
Apr 2019	5	6	0	11
May 2019	15	8	1	24
Jun 2019	23	11	0	34
Jul 2019	10	10	1	21
Aug 2019	8	6	0	14
Sep 2019	4	5	0	9
Oct 2019	8	5	1	14
Nov 2019	4	6	1	11
Dec 2019	3	30	1	34
Jan 2020	12	31	3	46
Feb 2020	12	26	1	39
Mar 2020	5	29	1	35
Apr 2020	8	29	2	39
May 2020	11	28	1	40
Jun 2020	22	27	4	53
Jul 2020	20	26	9	55
Aug 2020	9	10	4	23
Sep 2020	10	7	0	17
Oct 2020	3	5	0	8
Nov 2020	10	12	2	24
Dec 2020	10	7	0	17
Jan 2021	18	10	0	28
Feb 2021	8	7	1	16
Mar 2021	8	4	0	12
Apr 2021	10	8	0	18
May 2021	8	5	0	13
Jun 2021	6	7	0	13
Jul 2021	6	5	0	11
Aug 2021	9	13	1	23
Sep 2021	15	14	2	31
Oct 2021	10	33	1	44
Nov 2021	15	29	0	44
Dec 2021	12	10	1	23
Jan 2022	6	13	0	19
Feb 2022	7	10	1	18
Mar 2022	10	12	1	23
Apr 2022	17	10	3	30
May 2022	14	9	1	24
Jun 2022	11	4	1	16
Jul 2022	7	3	2	12
Aug 2022	15	12	0	27
Sep 2022	15	9	1	25
Oct 2022	12	8	1	21
Nov 2022	45	12	0	57
Dec 2022	47	16	1	64
Jan 2023	44	20	1	65
Feb 2023	48	14	1	63
Mar 2023	48	10	2	60
Apr 2023	12	12	0	24
May 2023	13	17	3	33
Jun 2023	16	13	1	30
Jul 2023	9	7	2	18
Aug 2023	11	10	2	23
Sep 2023	16	18	0	34
Oct 2023	12	16	1	29
Nov 2023	9	2	0	11
Dec 2023	21	15	2	38
Jan 2024	13	19	1	33
Feb 2024	9	11	3	23
Mar 2024	8	26	2	36
Apr 2024	17	8	3	28
May 2024	20	12	3	35
Jun 2024	12	21	2	35
Jul 2024	26	11	3	40
Aug 2024	27	6	5	38
Sep 2024	14	8	1	23
Oct 2024	30	15	3	48
Nov 2024	9	10	2	21
Dec 2024	7	10	3	20
Jan 2025	12	7	0	19
Feb 2025	28	9	1	38
Mar 2025	23	13	0	36
Apr 2025	35	14	0	49
May 2025	26	7	0	33
Jun 2025	44	15	4	63
Jul 2025	19	22	2	43
Aug 2025	14	15	1	30
Sep 2025	32	16	0	48
Oct 2025	26	26	3	55
Nov 2025	30	28	1	59
Dec 2025	28	22	1	51
Jan 2026	39	25	8	72
Feb 2026	33	12	2	47
Mar 2026	15	6	0	21

Viewed (geographical distribution)

Total article views: 3,650 (including HTML, PDF, and XML) Thereof 3,466 with geography defined and 184 with unknown origin.

Country	#	Views	%

1

1

Latest update: 13 Mar 2026

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.


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