Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data

doi:10.3832/ifor1534-008

Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data

Ekena Rangel Pinagé⁽¹⁾ , Eraldo Aparecido Trondoli Matricardi⁽¹⁾, Fabrício Assis Leal⁽¹⁾, Marcos Antonio Pedlowski⁽²⁾

iForest - Biogeosciences and Forestry, Volume 9, Issue 3, Pages 461-468 (2016)
doi: https://doi.org/10.3832/ifor1534-008
Published: Jan 11, 2016 - Copyright © 2016 SISEF

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Selective logging is one of the leading causes of forest degradation in the Brazilian Amazon region. The Brazilian Federal government has adopted a forest concession policy as a strategy to mitigate impacts of selective logging and regulate operations of the tropical timber industry in Brazil. This study used fractional forest coverage derived from satellite imagery and field data to assess forest degradation in two selectively logged study sites within the Jamari National Forest, a protected area located in the western Brazilian state of Rondônia. Initially, we estimated the fractional coverage from vegetation indices using RapidEye imagery and compared to gap fraction data derived from hemispherical photos acquired in the field. Subsequently, we estimated the impacts of different types of selective logging activities (log decks, primary and secondary roads, tree fall gaps, and skid trails) on forest cover using the fractional coverage dataset. The NDVI showed the highest R²(0.56), indicating that 56% of the sample variation in fractional coverage derived from ground measurements can be explained by fractional coverage derived from the NDVI model. Our results also showed that the intensity of canopy impacts may vary according to the selective logging activity, ranging from skid trails to log decks which had the lightest and the heaviest canopy impacts, respectively.

Keywords

Timber Harvesting, Hemispherical Photographs, Satellite Imagery, Forest Degradation, Forest Concessions, Brazilian Amazon

Authors’ address

(1)

University of Brasília, Forestry Departament, Campus Universitário Darcy Ribeiro, 70910-900, Brasília, DF (Brazil)

(2)

Universidade Estadual do Norte Fluminense, Laboratório de Estudos do Espaço Antrópico (LEEA), Av. Alberto Lamego 2000, 28013, Campos dos Goytacazes, RJ (Brazil)

Corresponding author

Ekena Rangel Pinagé
ekenapinage@hotmail.com

Citation

Pinagé ER, Matricardi EAT, Leal FA, Pedlowski MA (2016). Estimates of selective logging impacts in tropical forest canopy cover using RapidEye imagery and field data. iForest 9: 461-468. - doi: 10.3832/ifor1534-008

Academic Editor

Matteo Garbarino

Paper history

Received: Dec 16, 2014
Accepted: Sep 19, 2015

First online: Jan 11, 2016
Publication Date: Jun 01, 2016
Publication Time: 3.80 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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List of the papers citing this article based on CrossRef Cited-by.

(1)

Anwar S, Stein A (2012)
Detection and spatial analysis of selective logging with geometrically corrected Landsat images. International Journal of Remote Sensing 33: 7820-7843.
CrossRef | Gscholar

(2)

Asner GP, Keller M, Pereira R, Zweede JC, Silva JNM (2004)
Canopy damage after selective logging in Amazonia: field and satellite studies. Ecological Applications 4: 280-298.
CrossRef | Gscholar

(3)

Asner GP, Knapp DE, Broadbent EN, Oliveira PJC, Keller M, Silva JN (2005)
Selective logging in the Brazilian Amazon. Science 310: 480-482.
CrossRef | Gscholar

(4)

Azevedo-Ramos C, Silva JNM, Merry F (2015)
The evolution of Brazilian forest concessions. Elementa - Science of the Anthropocene 3: 000048.
Online | Gscholar

(5)

Berenguer E, Ferreira J, Gardner TA, Aragão LEOC, Camargo PB, Cerri CE, Durigan M, Oliveira RC, Vieira ICG, Barlow J (2014)
A large-scale field assessment of carbon stocks in human-modified tropical forests. Global Change Biology 20: 3713-3726.
CrossRef | Gscholar

(6)

Coops NC, Hilker T, Wulder MA, St-Onge B, Newnham G, Siggins A, Trofymow JA (2007)
Estimating canopy structure of Douglas-fir forest stands from discrete-return LIDAR. Trees - Structure and Function 3: 295-310.
CrossRef | Gscholar

(7)

Draper NR, Smith H (1998)
Applied regression analysis. John Wiley and Sons, New York, USA, pp. 736.
Gscholar

(8)

Frazer G, Canham C, Lertzman K (1999)
Gap Light Analyzer (GLA), Version 2.0: imaging software to extract canopy structure and gap light transmission indices for true-color fisheye photographs. Users manual and program documentation. Simon Fraser University, Burnaby, British Columbia and the Institute of Ecosystem Studies, Millbrook, New York, USA, pp. 36.
Online | Gscholar

(9)

Gujarati DN, Porter DC (2008)
Basic econometrics. McGraw-Hill/Irwin, New York, USA, pp. 946.
Gscholar

(10)

Huete A (1988)
A soil adjusted vegetation index (SAVI). Remote Sensing of Environment 25: 295-309.
CrossRef | Gscholar

(11)

ICMBIO (2005)
Plano de Manejo da Floresta Nacional do Jamari, Volume I, Diagnóstico [Jamari National Forest Management Plan, Volume I, Diagnosis]. ICMBio - Chico Mendes Institute for Biodiversity Conservation, Brasília, Brazil, pp. 158. [in Portuguese]
Gscholar

(12)

Lambin EF (1999)
Monitoring forest degradation in tropical regions by remote sensing: some methodological issues. Global Ecology and Biogeography 8: 191-198.
CrossRef | Gscholar

(13)

Maas SJ (2000)
Linear mixture modeling approach for estimating cotton canopy ground cover using satellite multispectral imagery. Remote Sensing of Environment 72 (3): 304-308.
CrossRef | Gscholar

(14)

Matricardi EAT, Skole DL, Cochrane MA, Qi J, Chomentowski W (2005)
Monitoring selective logging in tropical evergreen forests using Landsat: multitemporal regional analyses in Mato Grosso, Brazil. Earth Interactions 9: 1-24.
CrossRef | Gscholar

(15)

Matricardi EAT, Skole DL, Cochrane MA, Pedlowski M, Chomentowski W (2007)
Multi-temporal assessment of selective logging in the Brazilian Amazon using Landsat data. International Journal of Remote Sensing, 28: 63-82.
CrossRef | Gscholar

(16)

Matricardi EAT, Skole DL, Pedlowski M, Chomentowski W, Fernandes LC (2010)
Assessment of tropical forest degradation by selective logging and fire using Landsat imagery. Remote Sensing of Environment 114: 1117-1129.
CrossRef | Gscholar

(17)

Matricardi EAT, Skole DL, Pedlowski M, Chomentowski W (2013)
Assessment of forest disturbances by selective logging and forest fires in the Brazilian Amazon using Landsat data. International Journal of Remote Sensing 34: 1057-1086.
CrossRef | Gscholar

(18)

McRoberts RE (2010)
The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area. Remote Sensing of Environment 114: 1710-1717.
CrossRef | Gscholar

(19)

Monteiro A, Souza C (2012)
Remote monitoring for forest management in the Brazilian Amazon. In: “Sustainable Forest Management - Current Research” (Diez JJD ed). InTech, Rijeka, Croatia, pp. 67-86.
CrossRef | Gscholar

(20)

Nasi R, Putz FE, Pacheco P, Wunder S, Anta S (2011)
Sustainable forest management and carbon in tropical latin america: the case for REDD+. Forests 2: 200-217.
CrossRef | Gscholar

(21)

Nepstad DC, Veríssimo A, Alencar A, Nobre C, Lima E, Lefbvre P, Schlesinger P, Potter C, Moutinho P, Mendoza E, Cochrane M, Brooks V (1999)
Large-scale impoverishment of Amazonian forests by logging and fire. Nature 398: 505-508.
CrossRef | Gscholar

(22)

Ott RL, Longnecker M (2010)
An introduction to statistical methods and data analysis. Brooks/ Cole, Belmont, USA, pp. 1273.
Gscholar

(23)

Pacheco P, Barry D, Cronkleton P, Larson A M (2008)
The role of informal institutions in the use of forest resources in Latin America. Forests and Governance Programme Series 15, CIFOR, Bogor, Indonesia, pp. 80.
Online | Gscholar

(24)

Pereira R, Zweede JC, Asner GP, Keller M (2002)
Forest canopy damage and recovery in reduced-impact and conventional selective logging in eastern Para, Brazil. Forest Ecology and Management 68: 77-89.
CrossRef | Gscholar

(25)

Pinagé ER, Matricardi EAT, Osako LS, Gomes AR (2014)
Gap fraction estimates over selectively logged forests in Western Amazon. Natural Resources 5: 969-980.
CrossRef | Gscholar

(26)

Pinty B, Verstraete MM (1992)
GEMI: a non-linear index to monitor global vegetation from satellites. Vegetatio 101: 15-20.
CrossRef | Gscholar

(27)

Qi J, Chebouni A, Huete AR, Kerr YH, Sorooshian S (1994)
A modified soil adjusted vegetation index. Remote Sensing of Environment 48: 119-126.
CrossRef | Gscholar

(28)

Qi J, Marsett RC, Moran MS, Goodrich DC, Heilman P, Kerr YH, Dedieu G, Chebouni A, Zhang XX (2000)
Spatial and temporal dynamics of vegetation in the San Pedro River basin area. Agricultural and Forest Meteorology 105: 55-68.
CrossRef | Gscholar

(29)

Rouse JW, Haas RH, Schell JA, Deering DW, Harlan JC (1973)
Monitoring vegetation systems in the Great Plains with ERTS. In: Proceedings of the “3rd ERTS Symposium”. Washington (DC, USA) 10-14 Dec 1973. NASA, Washington, DC, USA, pp. 309-317.
Gscholar

(30)

Schulze M, Grogan J, Vidal E (2008)
Technical challenges to sustainable forest management in concessions on public lands in the Brazilian Amazon. Journal of Sustainable Forestry 26: 61-76.
CrossRef | Gscholar

(31)

SFB (2013)
Brazilian forests at a glance. Brazilian Forest Service, Brasília, Brazil, pp. 158.
Gscholar

(32)

Shimatani KD, Kubota Y (2004)
Spatial analysis for continuously changing point patterns along a gradient and its application to Abies sachalinensis population. Ecological Modelling 180: 359-369.
CrossRef | Gscholar

(33)

Sist P, Mazzei L, Blanc L, Rutishauser E (2014)
Large trees as key elements of carbon storage and dynamics after selective logging in the Eastern Amazon. Forest Ecology and Management 318: 103-109.
CrossRef | Gscholar

(34)

Souza C, Barreto P (2000)
An alternative approach for detecting and monitoring selectively logged forests in the Amazon. International Journal of Remote Sensing 21: 173-179.
CrossRef | Gscholar

(35)

Souza C, Firestone L, Silva LM, Roberts D (2003)
Mapping forest degradation in the Eastern Amazon from SPOT 4 through spectral mixture models. Remote Sensing of Environment 87: 494-506.
CrossRef | Gscholar

(36)

Souza CM, Roberts DA, Monteiro AL (2005)
Multitemporal analysis of degraded forests in the southern Brazilian Amazon. Earth Interactions 1: 1-25.
CrossRef | Gscholar

(37)

Souza CM, Siqueira JV, Sales MH, Fonseca AV, Ribeiro JG, Numata I, Cochrane MA, Barber C, Roberts DA, Barlow J (2013)
Ten-year Landsat classification of deforestation and forest degradation in the Brazilian Amazon. Remote Sensing 5: 5493-5513.
CrossRef | Gscholar

(38)

Uhl C, Barreto P, Veríssimo A, Vidal E, Amaral P, Barros AC, Souza C, Johns J, Gerwing J (1997)
Natural resource management in the Brazilian Amazon. BioScience 47: 160-168.
CrossRef | Gscholar

(39)

Veríssimo A, Barreto P, Tarifa R, Uhl C (1995)
Extraction of a high-value natural resource in Amazonia: the case of mahogany. Forest Ecology and Management 72: 39-60.
CrossRef | Gscholar

(40)

Zald HSJ, Ohmann JL, Roberts HM, Gregory MJ, Henderson EB, McGaughey RJ, Braaten J (2014)
Influence of lidar, Landsat imagery, disturbance history, plot location accuracy, and plot size on accuracy of imputation maps of forest composition and structure. Remote Sensing of Environment 143: 26-38.
CrossRef | Gscholar

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