Identification of gold mining vessels based on classification algorithms using Sentinel-2 images

Pereira, Diego Henrique Costa; Gomes, Roberto Arnaldo Trancoso; Carvalho Júnior, Osmar Abílio de; Guimarães, Renato Fontes

doi:10.14393/SN-v36-2024-69409x

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Papers • Soc. nat. 36 • 2024 • https://doi.org/10.14393/SN-v36-2024-69409x copy

Identification of gold mining vessels based on classification algorithms using Sentinel-2 images

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Artisanal and small-scale gold mining can occur on land or in riverbeds. However, the activity needs to be supported by a Mining Permit, issued by the Agência Nacional de Mineração, which is the Brazilian institution responsible for mining management, and the appropriate environmental license from the competent environmental agency. The use of images from Sentinel-2 satellites presents itself as a potential tool for identifying gold mining vessels due to the temporal resolution, free imagery, global coverage, and more refined spatial resolution. So, this study aimed to identify gold mining vessels on the Madeira River near Porto Velho city, Rondônia state, located at Brazilian Amazon, in 13 Sentinel-2 images from 2018 to 2021 using the classifiers: Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Random Forest (RF) and Spectral Angle Mapper (SAM). The results showed that machine learning classifiers obtained the best performance, especially the object-oriented SVM classifier, which had the best average F1 score (0.91). In addition, the detection percentage of gold mining vessels originated by this classifier was satisfactory, with only 0 to 4 active gold mining vessels with sediment plumes being omitted per image. Therefore, based on the results obtained, it was concluded that the use of machine learning classifiers proved to be effective in identifying gold mining vessels.

Keywords:
Gold mining vessels; Classifiers; Machine learning

Date	Gold Mining Vessels Without Sediment Plume	Gold Mining Vessels With Sediment Plume
06/30/2018	Yes	Yes
07/25/2018	Yes	Yes
08/19/2018	Yes	No
06/20/2019	Yes	No
07/09/2020	Yes	Yes
09/22/2020	Yes	No
06/14/2021	Yes	Yes
07/14/2021	Yes	Yes
07/24/2021	Yes	Yes
07/29/2021	Yes	Yes
08/08/2021	Yes	No
08/13/2021	Yes	Yes
08/18/2021	Yes	Yes

Date	Classes
Date	Vegetation	Soil	Water	Sediment Plumes	Vessels	Gold Mining Vessels
06/30/2018	3000	3000	1000	1000	250	95
07/25/2018	3000	3000	1200	1200	330	145
08/19/2018	3000	3000	3000	None	230	100
06/20/2019	3000	3000	3000	None	380	80
07/09/2020	3000	3000	1500	1500	390	100
09/22/2020	3000	3000	3000	None	160	45
06/14/2021	3000	3000	1000	1000	130	100
07/14/2021	3000	3000	2000	2000	300	200
07/24/2021	3000	3000	1000	1000	270	225
07/29/2021	3000	3000	1500	1500	450	160
08/08/2021	3000	3000	3000	None	285	120
08/13/2021	3000	3000	1000	1000	420	100
08/18/2021	3000	3000	1000	1000	255	135

Classifier	Metric	Data
Classifier	Metric	06/30/18	07/25/18	08/19/18	06/20/19	07/09/20	09/22/20	06/14/21	07/14/21	07/24/21	07/29/21	08/08/21	08/13/21	08/18/21
SVM Pixel	Kappa	0,86	0,83	0,84	0,88	0,80	0,84	0,87	0,89	0,87	0,90	0,86	0,85	0,85
SVM Pixel	F1	0,88	0,86	0,87	0,91	0,83	0,87	0,89	0,91	0,89	0,92	0,88	0,88	0,87
SVM OB	Kappa	0,88	0,84	0,93	0,93	0,87	0,87	0,95	0,89	0,91	0,91	0,87	0,89	0,89
SVM OB	F1	0,89	0,86	0,94	0,94	0,88	0,89	0,96	0,91	0,92	0,92	0,89	0,90	0,91
KNN Pixel	Kappa	0,81	0,80	0,83	0,86	0,81	0,80	0,86	0,88	0,86	0,89	0,86	0,85	0,85
KNN Pixel	F1	0,84	0,84	0,86	0,89	0,83	0,84	0,88	0,90	0,88	0,91	0,88	0,87	0,88
KNN OB	Kappa	0,81	0,80	0,87	0,88	0,81	0,82	0,84	0,86	0,87	0,88	0,86	0,86	0,85
KNN OB	F1	0,84	0,83	0,89	0,90	0,83	0,85	0,86	0,89	0,89	0,90	0,88	0,88	0,87
SAM	Kappa	0,70	0,73	0,80	0,85	0,72	0,79	0,82	0,72	0,73	0,71	0,82	0,83	0,73
SAM	F1	0,74	0,76	0,84	0,87	0,76	0,82	0,85	0,77	0,77	0,75	0,85	0,85	0,78
RF Pixel	Kappa	0,73	0,79	0,83	0,74	0,71	0,74	0,81	0,86	0,87	0,89	0,83	0,83	0,92
RF Pixel	F1	0,77	0,82	0,85	0,76	0,74	0,79	0,84	0,87	0,90	0,91	0,86	0,82	0,93
RF OB	Kappa	0,74	0,85	0,85	0,84	0,84	0,79	0,84	0,83	0,84	0,82	0,85	0,85	0,82
RF OB	F1	0,77	0,87	0,86	0,86	0,86	0,80	0,86	0,84	0,85	0,84	0,87	0,85	0,84

Classifier	Mean Kappa	Standard Deviation	Mean F1	Standard Deviation
SVM OB	0,89	0,03	0,91	0,03
SVM Pixel	0,86	0,03	0,88	0,02
KNN OB	0,85	0,03	0,87	0,02
KNN Pixel	0,84	0,03	0,87	0,02
RF OB	0,83	0,03	0,84	0,03
RF Pixel	0,81	0,06	0,84	0,06
SAM	0,76	0,05	0,80	0,04

Classes	SVM Pixel		SVM OB		KNN Pixel		KNN OB		RF Pixel		RF OB		SAM
Classes	Mean Precision	Mean Recall	Mean Precision	Mean Recall	Mean Precision	Mean Recall	Mean Precision	Mean Recall	Mean Precision	Mean Recall	Mean Precision	Mean Recall	Mean Precision	Mean Recall
Water	0,88	0,96	0,90	0,99	0,92	0,95	0,85	0,96	0,89	0,95	0,88	0,91	0,75	0,78
Sediment Plume	0,88	0,94	0,91	0,94	0,90	0,87	0,90	0,88	0,82	0,81	0,82	0,82	0,65	0,70
Gold Mining Vessels	0,84	0,72	0,88	0,72	0,84	0,69	0,86	0,59	0,77	0,63	0,78	0,64	0,78	0,65
Vessels	0,80	0,78	0,89	0,88	0,76	0,79	0,77	0,83	0,78	0,69	0,81	0,72	0,73	0,72
Soil	0,89	0,93	0,87	0,99	0,87	0,93	0,84	1,00	0,86	0,96	0,85	0,93	0,88	0,93
Vegetation	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00	1,00
F1 Water	0,92		0,94		0,93		0,90		0,92		0,89		0,77
F1 Sediment Plume	0,91		0,92		0,88		0,89		0,82		0,82		0,68
F1 Gold Mining Vessels	0,78		0,79		0,76		0,70		0,69		0,70		0,71
F1 Vessels	0,79		0,89		0,77		0,80		0,73		0,76		0,72
F1 Soil	0,91		0,93		0,90		0,91		0,91		0,89		0,90
F1 Vegetation	1,00		1,00		1,00		1,00		1,00		1,00		1,00
Score Mean F1	0,88		0,91		0,87		0,87		0,84		0,84		0,80

Data	Operating Gold Mining Vessels (Total)	Operating Gold Mining Vessels Detected	% of Detection	Operating Gold Mining Vessels Omitted	% of Omission
06/30/2018	18	17	94,44	1	5,56%
07/25/2018	6	6	100	0	0,00%
08/19/2018	9	8	88,89	1	11,11%
06/20/2019	15	11	73,33	4	26,67%
07/09/2020	21	17	80,95	4	19,05%
09/22/2020	8	6	75	2	25,00%
06/14/2021	5	4	80	1	20,00%
07/14/2021	3	3	100	0	0,00%
07/24/2021	9	8	88,89	1	11,11%
Média	--	--	86,83	2	13,17

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[TFN7] Source: The authors (2023).