Variabilidade espacial e temporal na detecção de focos de queima no estado do Pará, Brasil

WHITE, Benjamin Leonardo Alves

Benjamin Leonardo Alves WHITE ^*Corresponding author: benjmk@hotmail.com

Instituto Federal de Sergipe, Campus Tobias Barreto. Tobias Barreto, Sergipe, Brazil

https://orcid.org/0000-0001-8491-1853

Corresponding author: benjmk@hotmail.com

ASSOCIATE EDITOR:

Henrique Barbosa

Figuras (5)
Tabelas (4)

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Figure 1
Distribution of land cover types in Pará state (Brazil). The inserts show the location of Pará (light grey) in Brazil (dark grey), and the outlines of the 144 municipalities of Pará. Credit: B. White. Data Source: IBGE (2020)IBGE. 2020. Cobertura e Uso da Terra do Brasil na escala 1:250.000. ( (https://www.ibge.gov.br/geociencias/informacoes-ambientais/cobertura-e-uso-da-terra/15833-uso-da-terra.html?=&t=sobre ). Accessed on 27 May 2024.
https://www.ibge.gov.br/geociencias/info... .

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Figure 2
Yearly number of fire foci detected in Pará state (Brazil) by the AQUA (2003-2023) and S-NPP (2012-2023) satellites. The dashed line indicates the regression line of AQUA detections over time, indicating a significant downward trend over the period 2003-2023.

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Figure 3
Linear regression between the total number of fire foci detected in 144 municipalities of Pará state (Brazil) by the AQUA and S-NPP satellites during 2012-2023. The solid line indicates the line of best fit.

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Figure 4
Monthly numbers of fire foci detected by the AQUA satellite in each year of the period 2003-2023. Vertical bars indicate the monthly range, and the horizonal mid-line the mean. Different letters indicate significative difference between the mean monthly values according to a Tukey-Kramer test.

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Figure 5
Classification of the 144 municipalities of Pará state (Brazil) according to their fire foci density (White 2020White, B.L.A. 2020. Spatiotemporal variation of fire occurrence in the State of Bahia, Brazil, between 2003 and 2019. Journal of Hyperspectral Remote Sensing 10: 153-167. ), based on the number of wildland fires detected by the AQUA satellite (afternoon passage) in the period 2003-2023.

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Table 1
Classification of hotspot density values detected by the AQUA satellite (afternoon passage) over one year according to White (2020White, B.L.A. 2020. Spatiotemporal variation of fire occurrence in the State of Bahia, Brazil, between 2003 and 2019. Journal of Hyperspectral Remote Sensing 10: 153-167. ).

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Table 2
Total, mean and standard deviation of the yearly number of fire foci detected in Pará state (Brazil) by the AQUA and S-NPP satellites. AQUA data are shown for its total active period and for its overlap period with S-NPP.

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Table 3
Municipalities of Pará state (Brazil) ranked according to density of fire foci (FF) from 2003 to 2023 according to data from AQUA satellite, afternoon passage. Values for number FF are the mean ± standard deviation. Classification of fire foci density according to White (2020White, B.L.A. 2020. Spatiotemporal variation of fire occurrence in the State of Bahia, Brazil, between 2003 and 2019. Journal of Hyperspectral Remote Sensing 10: 153-167. ).

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Table 4
Pearson correlation matrix of all variables potentially related to fire foci density in the municipalities of Pará state (Brazil). Correlation coefficients in bold are significant at p < 0.001; those underlined are significant at p < 0.05.

Frequency class	Number of hotspots detected per year	Density of hotspots
Very Low	None or one hotspot for an area > 600 km²	< 0.0017 hotspots km^-2 year^-1
Low	One hotspot for an area > 300 and ≤ 600 km²	> 0.0033 and ≤ 0.0017 hotspots km^-2 year^-1
Average	One hotspot for an area > 150 and ≤ 300 km²	> 0.0067 and ≤ 0.0033 hotspots km^-2 year^-1
High	One hotspot for an area > 75 and ≤ 150 km²	> 0.0133 and ≤ 0.0067 hotspots km^-2 year^-1
Very High	One hotspot for an area > 25 and ≤ 75 km²	> 0.04 and ≤ 0.0133 hotspots km^-2 year^-1
Extreme	One hotspot for an area ≤ 25 km²	≥ 0.04 hotspots km^-2 year^-1

	AQUA		S-NPP
Period	2003-2023 (21 years)	2012-2023 (12 years)	2012-2023 (12 years)
Total	913,249	416,315	1,872,461
Mean ± standard deviation	43,488 ± 15,653	34,693 ± 8,910	156,038 ± 42,867

Rank	Municipality	Number of FF		Density (FF km^-2 year^-1)	Classification
Rank	Municipality	Mean	Standard deviation	Density (FF km^-2 year^-1)	Classification
1	Bujaru	223.05	93	0.2242	Extreme
2	Concórdia do Pará	144.90	61	0.2068	Extreme
3	São Domingos do Capim	307.33	134	0.1822	Extreme
4	Acará	692.71	189	0.1595	Extreme
5	Mocajuba	129.05	38	0.1481	Extreme
6	Garrafão do Norte	209.81	148	0.1305	Extreme
7	São Miguel do Guamá	132.57	65	0.1211	Extreme
8	Cametá	337.67	104	0.1096	Extreme
9	Moju	951.57	307	0.1046	Extreme
10	Irituia	143.90	83	0.1039	Extreme
11	Nova Esperança do Piriá	279.76	149	0.0996	Extreme
12	Aurora do Pará	180.33	88	0.0995	Extreme
13	Santa Maria das Barreiras	986.67	740	0.0955	Extreme
14	Bonito	55.14	27	0.0939	Extreme
15	Cachoeira do Piriá	221.81	94	0.0917	Extreme
16	Pacajá	1076.38	289	0.0910	Extreme
17	Santana do Araguaia	1038.33	996	0.0896	Extreme
18	Abaetetuba	143.14	50	0.0889	Extreme
19	Marapanim	71.10	29	0.0884	Extreme
20	Eldorado do Carajás	258.71	236	0.0875	Extreme
21	Bannach	251.81	243	0.0852	Extreme
22	Placas	605.10	224	0.0844	Extreme
23	São Francisco do Pará	39.00	26	0.0813	Extreme
24	Terra Alta	16.67	11	0.0813	Extreme
25	Magalhães Barata	26.19	10	0.0808	Extreme
26	Santa Maria do Pará	36.86	23	0.0805	Extreme
27	Mojuí dos Campos	398.90	167	0.0800	Extreme
28	Capitão Poço	231.48	162	0.0798	Extreme
29	Tucumã	197.76	145	0.0787	Extreme
30	Itupiranga	612.19	443	0.0777	Extreme
31	Ourém	43.48	26	0.0774	Extreme
32	São João da Ponta	14.86	9	0.0758	Extreme
33	Tailândia	328.90	144	0.0742	Extreme
34	Conceição do Araguaia	427.38	276	0.0733	Extreme
35	Igarapé-Açu	57.62	37	0.0733	Extreme
36	São João do Araguaia	93.29	70	0.0729	Extreme
37	Rurópolis	506.38	190	0.0721	Extreme
38	Novo Repartimento	1089.62	652	0.0708	Extreme
39	Maracanã	55.52	16	0.0687	Extreme
40	Cumaru do Norte	1165.52	1160	0.0682	Extreme
41	Marabá	1032.00	821	0.0682	Extreme
42	Curuá	96.10	41	0.0671	Extreme
43	Pau D’Arco	111.38	50	0.0666	Extreme
44	Inhangapi	31.48	16	0.0666	Extreme
45	Primavera	17.05	6	0.0659	Extreme
46	Castanhal	67.62	41	0.0657	Extreme
47	Augusto Corrêa	70.95	33	0.0645	Extreme
48	Tomé-Açu	330.90	119	0.0643	Extreme
49	Abel Figueiredo	38.86	19	0.0633	Extreme
50	Oeiras do Pará	243.48	98	0.0632	Extreme
51	Bragança	134.00	48	0.0631	Extreme
52	Santarém Novo	14.14	7	0.0616	Extreme
53	Uruará	652.67	241	0.0605	Extreme
54	São Félix do Xingu	5067.24	3440	0.0602	Extreme
55	Nova Ipixuna	92.90	69	0.0594	Extreme
56	Floresta do Araguaia	200.52	103	0.0582	Extreme
57	Igarapé-Miri	115.90	35	0.0580	Extreme
58	Ulianópolis	289.10	157	0.0568	Extreme
59	Nova Timboteua	27.81	17	0.0568	Extreme
60	Baião	213.43	67	0.0568	Extreme
61	Novo Progresso	2161.19	1090	0.0566	Extreme
62	Rondon do Pará	462.10	221	0.0560	Extreme
63	Barcarena	72.86	32	0.0556	Extreme
64	Peixe-Boi	24.95	11	0.0554	Extreme
65	Ipixuna do Pará	288.05	108	0.0552	Extreme
66	São Caetano de Odivelas	25.62	16	0.0552	Extreme
67	Dom Eliseu	285.43	164	0.0542	Extreme
68	São João de Pirabas	35.81	13	0.0536	Extreme
69	Curuçá	36.05	14	0.0533	Extreme
70	Mãe do Rio	24.90	16	0.0531	Extreme
71	Breu Branco	203.90	138	0.0517	Extreme
72	Salvaterra	47.00	13	0.0512	Extreme
73	Santa Luzia do Pará	68.76	27	0.0511	Extreme
74	Tracuateua	42.00	19	0.0484	Extreme
75	Capanema	28.38	14	0.0457	Extreme
76	Vigia	18.33	11	0.0457	Extreme
77	Santo Antônio do Tauá	23.62	14	0.0439	Extreme
78	Viseu	216.81	88	0.0436	Extreme
79	Anapu	517.86	175	0.0435	Extreme
80	Trairão	515.86	200	0.0430	Extreme
81	São Domingos do Araguaia	59.52	52	0.0427	Extreme
82	Santa Izabel do Pará	30.19	19	0.0421	Extreme
83	Tucuruí	87.67	32	0.0421	Extreme
84	Água Azul do Norte	295.10	239	0.0415	Extreme
85	Medicilândia	339.76	102	0.0411	Extreme
86	Quatipuru	12.29	7	0.0406	Extreme
87	Goianésia do Pará	282.86	140	0.0403	Extreme
88	Redenção	153.67	113	0.0402	Extreme
89	Piçarra	133.05	128	0.0402	Extreme
90	Rio Maria	154.29	98	0.0375	Very high
91	Bom Jesus do Tocantins	102.90	50	0.0365	Very high
92	São Geraldo do Araguaia	111.90	101	0.0353	Very high
93	Prainha	518.71	179	0.0351	Very high
94	Portel	882.10	409	0.0347	Very high
95	Brasil Novo	216.38	130	0.0340	Very high
96	Paragominas	651.19	307	0.0337	Very high
97	Brejo Grande do Araguaia	42.76	31	0.0332	Very high
98	Jacundá	65.52	49	0.0326	Very high
99	Curionópolis	76.19	52	0.0322	Very high
100	Terra Santa	60.48	30	0.0319	Very high
101	Santa Cruz do Arari	33.71	26	0.0313	Very high
102	Colares	11.71	7	0.0305	Very high
103	Salinópolis	6.86	4	0.0303	Very high
104	Santarém	517.86	177	0.0289	Very high
105	Juruti	236.57	87	0.0285	Very high
106	Vitória do Xingu	83.24	69	0.0269	Very high
107	Xinguara	100.10	71	0.0265	Very high
108	Cachoeira do Arari	81.00	25	0.0261	Very high
109	Óbidos	722.86	268	0.0258	Very high
110	Belterra	113.43	45	0.0258	Very high
111	Canaã dos Carajás	80.86	55	0.0257	Very high
112	Curralinho	92.19	34	0.0255	Very high
113	Porto de Moz	440.10	211	0.0253	Very high
114	Aveiro	426.81	142	0.0250	Very high
115	Monte Alegre	451.95	143	0.0249	Very high
116	Senador José Porfírio	352.48	151	0.0244	Very high
117	Palestina do Pará	22.95	20	0.0233	Very high
118	Itaituba	1421.95	416	0.0229	Very high
119	Ourilândia do Norte	303.48	207	0.0211	Very high
120	Parauapebas	144.57	95	0.0210	Very high
121	Alenquer	477.29	184	0.0202	Very high
122	Santa Bárbara do Pará	5.52	4	0.0199	Very high
123	Ponta de Pedras	66.24	22	0.0197	Very high
124	Altamira	3084.24	1157	0.0193	Very high
125	Muaná	71.48	26	0.0190	Very high
126	Sapucaia	23.67	17	0.0182	Very high
127	Bagre	77.90	38	0.0177	Very high
128	Benevides	2.76	2	0.0147	Very high
129	Limoeiro do Ajuru	20.62	13	0.0138	Very high
130	Soure	38.48	21	0.0135	Very high
131	Chaves	166.62	94	0.0133	High
132	Breves	119.67	39	0.0125	High
133	São Sebastião da Boa Vista	20.29	12	0.0124	High
134	Jacareacanga	636.10	209	0.0119	High
135	Gurupá	90.90	45	0.0106	High
136	Melgaço	56.43	23	0.0083	High
137	Belém	5.29	4	0.0050	Average
138	Almeirim	362.67	152	0.0050	Average
139	Ananindeua	0.86	1	0.0045	Average
140	Oriximiná	447.10	145	0.0042	Average
141	Faro	35.43	15	0.0030	Low
142	Anajás	16.90	17	0.0024	Low
143	Marituba	0.19	0	0.0018	Low
144	Afuá	10.76	11	0.0013	Very low

	Forest area	Natural formation area	Pasture area	Agricultural area	Urbanized area	Deforested area	Mean annual temperature	Annual rainfall	Population density	Fire foci density
Forest area	1.00	-0.27	-0.73	0.05	-0.07	-0.22	-0.05	0.28	-0.07	-0.19
Natural formation area		1.00	-0.30	-0.10	-0.06	-0.31	0.11	0.28	-0.06	-0.14
Pasture are			1.00	0.01	-0.12	0.52	-0.15	-0.60	-0.13	0.36
Agricultural area				1.00	-0.02	0.27	0.03	-0.05	-0.04	0.17
Urbanized area					1.00	-0.16	0.06	0.17	0.93	-0.20
Deforested area						1.00	-0.10	-0.36	-0.16	0.77
Mean annual temperature							1.00	0.23	0.07	-0.10
Annual rainfall								1.00	0.11	-0.29
Population density									1.00	-0.17
Fire foci density										1.00

[1] Corresponding author: benjmk@hotmail.com

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Variabilidade espacial e temporal na detecção de focos de queima no estado do Pará, Brasil

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