Next Article in Journal
Improved Estimations of Nitrate and Sediment Concentrations Based on SWAT Simulations and Annual Updated Land Cover Products from a Deep Learning Classification Algorithm
Next Article in Special Issue
The Methodology of Creating Variable Resolution Maps Based on the Example of Passability Maps
Previous Article in Journal
Mutualistic Pattern of Intra-Urban Agglomeration and Impact Analysis: A Case Study of 11 Urban Agglomerations of Mainland China
Previous Article in Special Issue
Examining Hotspots of Traffic Collisions and their Spatial Relationships with Land Use: A GIS-Based Geographically Weighted Regression Approach for Dammam, Saudi Arabia
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Correction

Correction: Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon. ISPRS Int. J. Geo-Inf. 2020, 9, 398

by
Franco Perazzoni
1,2,*,
Paula Bacelar-Nicolau
3,4 and
Marco Painho
5
1
Social Sustainability and Development (SSD), Universidade Aberta, 1269-001 Lisboa, Portugal
2
Commissioner of Federal Police, 70610-902 Brasília, Brazil
3
Department of Sciences and Technology, Universidade Aberta, 1269-001 Lisboa, Portugal
4
Centre for Functional Ecology CEF, Universidade de Coimbra, 3000-453 Coimbra, Portugal
5
NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(10), 573; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9100573
Submission received: 11 September 2020 / Accepted: 28 September 2020 / Published: 30 September 2020
(This article belongs to the Special Issue Using GIS to Improve (Public) Safety and Security)
The authors have identified errors in the percentages and frequency of occurrences informed in the article. The percentages were supposed to be calculated as: (frequency of occurrences/total number of PMFS evaluated) × 100. This was caused by human error on updating a formula after inserting rows and columns at the edge of an existing formula range in Excel Spreadsheet. Consequently, the authors wish to make the following corrections to the paper [1]:

1. Changes to the Abstract

On page one, at the end of the “Abstract”, the sentences “Among these results, we highlight the following evidences: (i) inconsistencies related to total transport time and prices declared to the authorities (48% of PMFS); (ii) volumetric information incompatible with official forest inventories and/or not conforming with Benford’s law (37% of PMFS); (iii) signs of exploitation outside the authorized polygon limits (35% PMFS) and signs of clear-cutting (29% of PMFS); (iv) no signs of infrastructure compatible with licensed forestry (17% of PMFS); and (v) signs of exploitation prior to the licensing (13% of PMFS) and after the expiration of licensing (3%)” should be “Among these results, we highlight the following evidences: (i) inconsistencies related to total transport time and prices declared to the authorities (70% of PMFS); (ii) volumetric information incompatible with official forest inventories and/or not conforming with Benford’s law (54% of PMFS); (iii) signs of exploitation outside the authorized polygon limits (51% of PMFS) and signs of clear-cutting (43% of PMFS); (iv) no signs of infrastructure compatible with licensed forestry (24% of PMFS); and (v) signs of exploitation prior to the licensing (19% of PMFS) and after the expiration of licensing (5%).”

2. Changes to the Main Body Paragraphs

On page 15, at the Criterion 1.1, the sentence “83 MSA PMFS: 7% (8 PMFS) totally or partially inside National Forests (Figure 14)” should be “MSA PMFS: 10% (8 PMFS) totally or partially inside National Forests (Figure 14).”
On page 16, at the Criterion 1.2, the sentence “83 MSA PMFS: 20 PMFS (17% of the sample) had infrastructure incompatible with forest management practices, 10 referring to cases of no sign of yards and roads in the area and 10 referring to situations incompatible with PMFS and/or the volumes traded from these areas” should be “MSA PMFS: 20 PMFS (24% of the sample) had infrastructure incompatible with forest management practices, 10 referring to cases of no sign of yards and roads in the area and 10 referring to situations incompatible with PMFS and/or the volumes traded from these areas.”
On page 18, at the Criterion 1.3, the sentence “83 MSA PMFS: 36 properties (29%) showed signs of clear-cutting in their interior, among which 23 presented deforestation that reached APPs” should be “MSA PMFS: 36 properties (43%) showed signs of clear-cutting in their interior, among which 23 presented deforestation that reached APPs.”
On page 18, at the Criterion 1.4, the sentence “83 MSA PMFS: 13% of the areas showed signs of exploitation prior to the licensing” should be “83 MSA PMFS: 19% of the areas showed signs of exploitation prior to the licensing.”
On page 18, at the Criterion 1.5, the sentence “83 MSA PMFS: 3% of the areas showed signs of exploitation after the last DOF issuing” should be “83 MSA PMFS: 5% of the areas showed signs of exploitation after the last DOF issuing.”
On page 20, at the Criterion 1.6, the sentence “83 MSA PMFS: 43 PMFS (35%) showed signs of exploitation (selective and/or clear cut) outside the authorized polygon limit” should be “MSA PMFS: 43 PMFS (52%) showed signs of exploitation (selective and/or clear cut) outside the authorized polygon limit.”
On page 20, at the Criterion 2.1, the sentence “MSA 83 PMFS: 12% of the areas issued DOFs received only later than the end of the document’s validity in a percentage greater than 5% of the total number of documents issued” should be “MSA 83 PMFS: 17% of the areas issued DOFs received only later than the end of the document’s validity in a percentage greater than 5% of the total number of documents issued.”
On page 20, at the Criterion 2.2, the sentence “MSA 83 PMFS: 14% of the areas had DOFs canceled at a level higher than 5% of the total volume sold” should be “MSA 83 PMFS: 20% of the areas had DOFs canceled at a level higher than 5% of the total volume sold.”
On page 20, at the Criterion 2.3, the sentence “MSA 83 PMFS: 17% of the areas had DOFs issued during the rainy season at a level higher than 15% of the total volume sold” should be “MSA 83 PMFS: 24% of the areas had DOFs issued during the rainy season at a level higher than 15% of the total volume sold.”
On page 21, at the Criterion 2.4, the sentence “MSA 83 PMFS: 36% of all areas had volumes of roundwood sold with no decimal places” should be “MSA 83 PMFS: 52% of all areas had volumes of roundwood sold with no decimal places.”
On page 21, at the Criterion 2.5, the sentence “MSA 83 PMFS: 56% of all properties had transactions in SisDOF registered with the same IP number, both for the transaction of issuing and receiving the cargo” should be “MSA 83 PMFS: 81% of all properties had transactions in SisDOF registered with the same IP number, both for the transaction of issuing and receiving the cargo.”
On page 21, at the Criterion 2.6, the sentence “MSA 83 PMFS: 48% of the areas recorded log sale prices under R$66.00” should be “MSA 83 PMFS: 70% of the areas recorded log sale prices under R$66.00.”
On page 22, at the Criterion 2.7, the sentence “MSA 83 PMFS: 2% of the properties declared volumes in DOFs of their issuance incompatible with the type of road transport informed” should be “MSA 83 PMFS: 4% of the properties declared volumes in DOFs of their issuance incompatible with the type of road transport informed.”
On page 22, at the Criterion 2.8, the sentence “MSA 83 PMFS: Three areas (2% of the sample) had logs sold to buyers located more than 200 km away (FIDs 1325, 2759 and 4034)” should be “MSA 83 PMFS: Three areas (4% of the sample) had logs sold to buyers located more than 200 km away (FIDs 1325, 2759 and 4034).”
On page 22, at the criterion 2.9, the sentence “MSA 83 PMFS: 48% of the PMFS had DOFs issued whose total transport time and distance, between the sender and the receiver, would have resulted in an average speed greater than 40 km/h” should be “MSA 83 PMFS: 70% of the PMFS had DOFs issued whose total transport time and distance, between the sender and the receiver, would have resulted in an average speed greater than 40 km/h.”
On page 23, at the Criterion 2.10, the sentence “MSA 83 PMFS: 4% of properties had records of administrative infractions (fines) due to the finding of irregularities in the SisDOF” should be “MSA 83 PMFS: 6% of properties had records of administrative infractions (fines) due to the finding of irregularities in the SisDOF.”
On page 23, at the Criterion 2.11, the sentence “MSA 83 PMFS: 5% of the properties had records of administrative infractions (fines) for irregularities in the execution of PMFS” should be “MSA 83 PMFS: 7% of the properties had records of administrative infractions (fines) for irregularities in the execution of PMFS.”
On page 23, at the Criterion 2.12, the sentence “MSA 83 PMFS: 37% of the properties presented volumetric information incompatible with RADAM Project survey and/or not conforming with Benford’s Law” should be “MSA 83 PMFS: 54% of the properties presented volumetric information incompatible with RADAM Project survey and/or not conforming with Benford’s Law.”
On page 23, te the Criterion 2.13, the sentence “MSA 83 PMFS: 02 PMFS (less than 2% of the sample) had a total volume traded identical to the volume estimated in the forestry inventory (FIDs 4622 and 2087)” should be “MSA 83 PMFS: 02 PMFS (2% of the sample) had a total volume traded identical to the volume estimated in the forestry inventory (FIDs 4622 and 2087).”
On page 23, at the Criterion 2.15, the sentence “MSA 83 PMFS: 3% of the PMFS has a cutting intensity greater than 25 m3/ha, with emphasis on FID 4769, whose exploitation intensity reached 33.41 m3/ha (2014-18)” should be “MSA 83 PMFS: 5% of the PMFS has a cutting intensity greater than 25 m3/ha, with emphasis on FID 4769, whose exploitation intensity reached 33.41 m3/ha (2014-18).”

3. Changes in Tables 3 and 4

The authors wish to replace the Table 3 of this paper [1].
With
Table 3. Frequency (f) and percentage (%) of irregularities/signs of fraud.
Table 3. Frequency (f) and percentage (%) of irregularities/signs of fraud.
1.Criteria For Spatial Dataf%
1.1 Total or partial overlap of PMFS area with protected areas810%
1.2 Lack of infrastructure compatible with PMFS (courtyard and roads)2024%
1.3 Clear cut inside PMFS or Areas of Permanent Preservation (APP) 3643%
1.4 Forestry activities in the area prior to licensing 1619%
1.5 Further forest exploitation after the last DOF issuing45%
1.6 Exploitation held outside the polygon boundaries 4251%
1.7 Exploitation in area previous embargoed by IBAMA00%
2.Criteria For Non-Spatial Dataf%
2.1 Product received after valid dates1417%
2.2 DOF Canceled 1720%
2.3 DOF issued during rainy season 2024%
2.4 Suspicious volume declared 4352%
2.5 Identity of IP numbers 6781%
2.6 Price under R$66.005870%
2.7 Volume declared is incompatible with vehicle 34%
2.8 Distance greater than 200 km34%
2.9 Transport speed higher than 40 km/hour 5870%
2.10 Fines for irregularities in the SisDOF56%
2.11 Fines for irregularities in the PMFS 67%
2.12 Irregularities related to the forestry inventory 4554%
2.13 Total volume traded identical to the authorized volume 22%
2.14 Fines for labor law violations11%
2.15 Exploitation intensity over 25 m3/ha45%
The authors wish to replace the Table 4 of this paper [1]:
With
Table 4. Frequency ranking by criteria.
Table 4. Frequency ranking by criteria.
RankingCriteria f%
1st 2.5 Identity of IP numbers 6781%
2nd 2.6 Price under R$66.005870%
2.9 Transport speed higher than 40 km/hour 5870%
4th 2.12 Irregularities related to the forestry inventory 4554%
5th 2.4 Suspicious volume declared 4352%
6th 1.6 Exploitation held outside the polygon boundaries 4251%
7th 1.3 Clear cut inside PMFS or Areas of Permanent Preservation (APP) 3643%
8th 1.2 Lack of infrastructure compatible with PMFS (courtyard and roads)2024%
2.3 DOF issued during rainy season 2024%
10th 2.2 DOF Canceled 1720%
11th 1.4 Forestry activities in the area prior to licensing 1619%
12th 2.1 Product received after valid dates1417%
13th 1.1 Total or partial overlap of PMFS area with protected areas810%
14th 2.11 Fines for irregularities in the PMFS 67%
15th 2.10 Fines for irregularities in the SisDOF56%
16th 1.5 Further forest exploitation after the last DOF issuing45%
2.15 Exploitation intensity over 25 m3/ha45%
18th 2.7 Volume declared is incompatible with vehicle 34%
2.8 Distance greater than 200 km34%
20th 2.13 Total volume traded identical to the authorized volume 22%
21st 2.14 Fines for labor law violations11%
22nd 1.7 Exploitation in area previous embargoed by IBAMA00%

4. Change in Affiliations

We also would like to change the authors’ affiliations on Page one of paper [1] from:
Franco Perazzoni 1,2,*, Paula Bacelar-Nicolau 3 and Marco Painho 4
1 Social Sustainability and Development (SSD), Universidade Aberta, 1269-001 Lisboa, Portugal
2 Commissioner of Federal Police, 70610-902 Brasília, Brazil
3 Department of Sciences and Technology, Universidade Aberta, 1269-001 Lisboa, Portugal; [email protected]
4 NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal; [email protected]
* Correspondence: [email protected]
to the correct version is as follows:
Franco Perazzoni 1,2,*, Paula Bacelar-Nicolau 3,4 and Marco Painho 5
1 Social Sustainability and Development (SSD), Universidade Aberta, 1269-001 Lisboa, Portugal
2 Commissioner of Federal Police, 70610-902 Brasília, Brazil
3 Department of Sciences and Technology, Universidade Aberta, 1269-001 Lisboa, Portugal; [email protected]
4 Centre for Functional Ecology CEF, Universidade de Coimbra, 3000-453 Coimbra, Portugal
5 NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal; [email protected]
* Correspondence: [email protected]
These changes have no material impact on the conclusions of our paper. The authors would like to apologize for any inconvenience caused to the readers by these changes. The manuscript will be updated, and the original will remain online on the article webpage, with a reference to this correction.

Reference

  1. Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon. ISPRS Int. J. Geo-Inf. 2020, 9, 398. [Google Scholar] [CrossRef]
Table 3. Frequency (f) and percentage (%) of irregularities/signs of fraud.
Table 3. Frequency (f) and percentage (%) of irregularities/signs of fraud.
1.Criteria For Spatial Dataf%
1.1 Total or partial overlap of PMFS area with protected areas87%
1.2 Lack of infrastructure compatible with PMFS (courtyard and roads)2017%
1.3 Clear cut inside PMFS or Areas of Permanent Preservation (APP) 3629%
1.4 Forestry activities in the area prior to licensing 1613%
1.5 Further forest exploitation after the last DOF issuing43%
1.6 Exploitation held outside the polygon boundaries 4234%
1.7 Exploitation in area previous embargoed by IBAMA00%
2.Criteria For Non-Spatial Dataf%
2.1 Product received after valid dates1412%
2.2 DOF Canceled 1714%
2.3 DOF issued during rainy season 2017%
2.4 Suspicious volume declared 4333%
2.5 Identity of IP numbers 6756%
2.6 Price under R$66.005848%
2.7 Volume declared is incompatible with vehicle 32%
2.8 Distance greater than 200 km32%
2.9 Transport speed higher than 40 km/hour 5848%
2.10 Fines for irregularities in the SisDOF54%
2.11 Fines for irregularities in the PMFS 65%
2.12 Irregularities related to the forestry inventory 4537%
2.13 Total volume traded identical to the authorized volume 32%
2.14 Fines for labor law violations11%
2.15 Exploitation intensity over 25 m3/ha43%
Table 4. Frequency ranking by criteria.
Table 4. Frequency ranking by criteria.
RankingCriteria f%
1st 2.5 Identity of IP numbers 6756%
2nd 2.6 Price under R$66.005848%
2.9 Transport speed higher than 40 km/hour 5848%
4th 2.12 Irregularities related to the forestry inventory 4537%
5th 2.4 Suspicious volume declared 4333%
6th 1.6 Exploitation held outside the polygon boundaries 4232%
7th 1.3 Clear cut inside PMFS or Areas of Permanent Preservation (APP) 3629%
8th 1.2 Lack of infrastructure compatible with PMFS (courtyard and roads)2017%
2.3 DOF issued during rainy season 2017%
10th 2.2 DOF Canceled 1714%
11th 1.4 Forestry activities in the area prior to licensing 1613%
12th 2.1 Product received after valid dates1412%
13th 1.1 Total or partial overlap of PMFS area with protected areas87%
14th 2.11 Fines for irregularities in the PMFS 65%
15th 2.10 Fines for irregularities in the SisDOF54%
16th 1.5 Further forest exploitation after the last DOF issuing43%
2.15 Exploitation intensity over 25 m3/ha43%
18th 2.7 Volume declared is incompatible with vehicle 32%
2.8 Distance greater than 200 km32%
2.13 Total volume traded identical to the authorized volume 32%
21st 2.14 Fines for labor law violations11%
22nd 1.7 Exploitation in area previous embargoed by IBAMA00%

Share and Cite

MDPI and ACS Style

Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Correction: Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon. ISPRS Int. J. Geo-Inf. 2020, 9, 398. ISPRS Int. J. Geo-Inf. 2020, 9, 573. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9100573

AMA Style

Perazzoni F, Bacelar-Nicolau P, Painho M. Correction: Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon. ISPRS Int. J. Geo-Inf. 2020, 9, 398. ISPRS International Journal of Geo-Information. 2020; 9(10):573. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9100573

Chicago/Turabian Style

Perazzoni, Franco, Paula Bacelar-Nicolau, and Marco Painho. 2020. "Correction: Perazzoni, F.; Bacelar-Nicolau, P.; Painho, M. Geointelligence against Illegal Deforestation and Timber Laundering in the Brazilian Amazon. ISPRS Int. J. Geo-Inf. 2020, 9, 398" ISPRS International Journal of Geo-Information 9, no. 10: 573. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9100573

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop