Assessment of tropical forest degradation by selective logging and fire using Landsat imagery

Abstract

Many studies have assessed the process of forest degradation in the Brazilian Amazon using remote sensing approaches to estimate the extent and impact by selective logging and forest fires on tropical rain forest. However, only a few have estimated the combined impacts of those anthropogenic activities. We conducted a detailed analysis of selective logging and forest fire impacts on natural forests in the southern Brazilian Amazon state of Mato Grosso, one of the key logging centers in the country. To achieve this goal a 13-year series of annual Landsat images (1992–2004) was used to test different remote sensing techniques for measuring the extent of selective logging and forest fires, and to estimate their impact and interaction with other land use types occurring in the study region. Forest canopy regeneration following these disturbances was also assessed. Field measurements and visual observations were conducted to validate remote sensing techniques. Our results indicated that the Modified Soil Adjusted Vegetation Index aerosol free (MSAVI_af) is a reliable estimator of fractional coverage under both clear sky and under smoky conditions in this study region. During the period of analysis, selective logging was responsible for disturbing the largest proportion (31%) of natural forest in the study area, immediately followed by deforestation (29%). Altogether, forest disturbances by selective logging and forest fires affected approximately 40% of the study site area. Once disturbed by selective logging activities, forests became more susceptible to fire in the study site. However, our results showed that fires may also occur in undisturbed forests. This indicates that there are further factors that may increase forest fire susceptibility in the study area. Those factors need to be better understood. Although selective logging affected the largest amount of natural forest in the study period, 35% and 28% of the observed losses of forest canopy cover were due to forest fire and selective logging combined and to forest fire only, respectively. Moreover, forest areas degraded by selective logging and forest fire is an addition to outright deforestation estimates and has yet to be accounted for by land use and land cover change assessments in tropical regions. Assuming that this observed trend of land use and land cover conversion continues, we predict that there will be no undisturbed forests remaining by 2011 in this study site. Finally, we estimated that 70% of the total forest area disturbed by logging and fire had sufficiently recovered to become undetectable using satellite data in 2004.

Introduction

In recent decades, the logging of high-value tree species has became an important land use of tropical evergreen forests in Central Africa (Laporte et al. 2007) and in the Brazilian Amazon (Stone and Lefebvre, 1998, Nepstad et al., 1999, Alvarado and Sandberg, 2001). However, until the 1960s most of this logging in Brazil was restricted to flood plains (várzeas) in areas flooded annually. This situation changed drastically after the widespread construction of roads during the 1960s and 1970s which allowed the expansion of selective logging into the inter-fluvial (terra-firme) forests in the Brazilian Amazon (Uhl and Vieira, 1989, Uhl et al., 1997).

As a result of the increased access provided by roads, selective logging became a major concern in the Brazilian Amazon due to its potential negative effect on natural forests. Selective logging is a form of timber extraction of a group of trees from selected species where only the most valuable tree species are removed from the forest. Selective logging operations usually leave behind a complex landscape comprised of intact forest, treefall gaps, roads, log-loading patios, and damaged forest (Verissimo et al., 1995, Uhl et al., 1997, Laporte et al., 2007). In addition, logging activities increase the amount of dead slash or dried biomass (fuel) and, consequently, forest fire susceptibility is substantially increased (Uhl and Buschbacher, 1985, Stone and Lefebvre, 1998, Nepstad et al., 1999, Souza and Barreto, 2000). Therefore, the impacts caused by logging in tropical forests are significant both in terms of forest degradation and fire susceptibility (Uhl and Buschbacher, 1985, Stone and Lefebvre, 1998, Nepstad et al., 1999, Souza and Barreto, 2000). Selectively logged forests often become highly degraded and usually have 40–50% of their canopy cover removed during logging operations (Uhl and Vieira, 1989, Verissimo et al., 1992). Accordingly, forest fires have increased in the Brazilian Amazon, and became very common in fragmented forests located adjacent to deforested areas, which serve as ignition sources for forest fires (Uhl and Kauffman, 1990, Cochrane and Schulze, 1998, Cochrane, 2001, Cochrane et al., 2004).

Meanwhile, most studies based on remotely sensed data to estimate forest impacts of selective logging in the Brazilian Amazon have relied on study sites mostly located in Eastern Pará, Brazil. For example, Souza and Barreto (2000) used a linear mixture model and Landsat imagery to detect logging patios within selectively logged forests in a study site in the state of Pará, Brazil. Additionally, Cochrane and Souza Jr. (1998) developed a remote sensing technique to detect and classify burned forests using non-photosynthetic vegetation derived from Linear Mixture Analysis for a study site in Tailândia, Pará. Furthermore, Cochrane and Sousa, 1998, Cochrane et al., 1999 used field studies and a multi-temporal analysis of remotely sensed imagery to understand forest fire dynamics in another study site in Pará. Finally, Souza et al. (2003) developed a methodology to map classes of degraded forest for a case study in Pará using fraction images (vegetation, non-photosynthetic vegetation, soil, and shade) derived from spectral mixture models.

Asner et al. (2002) applied Landsat textural analysis to assess forest canopy damage from selective logging in yet another study site in the state of Para, Brazil. Based on those study results, the authors concluded that although this technique was useful for broad delineation of forests impacted by selective logging, it could not appropriately estimate the extent of canopy damage.

More recently, Souza et al. (2005a) conducted an evaluation of different vegetation and infrared indices and fraction images derived from spectral mixture analysis to assess multi-temporal forest degradation within nineteen transects in the eastern Brazilian Amazon, whilst Matricardi et al. (2005) estimated areas of selectively logged forests using Landsat imagery and fieldwork measurements for a study site in the Brazilian state of Mato Grosso. Souza et al. (2005b) developed a remote sensing approach based on Spectral Mixture Analysis (SMA) to map selectively logged and burned forests for a case study in the state of Mato Grosso.

Asner et al. (2005) also developed an automated remote sensing technique to map degraded forests by selective logging in the five major timber center states of the Brazilian Amazon. The authors used Landsat ETM + imagery from 1999 to 2002 and the Camegie Landsat Analysis (CLAS) based on atmospheric modeling and spatial pattern analysis to detect forests impacted by selective logging in their study area. By using the CLAS, they were able to classify forests degraded by selective logging on the Landsat imagery with 86% overall accuracy. That study did not include, however, any assessment of forest degradation by forest fires.

These previous studies have contributed to substantial improvements in remote sensing based techniques to assess both extent and impacts caused by selective logging and forest fires. However, a more comprehensive assessment of forest disturbances by forest fire and selective logging and their interactions with other land use and land cover processes is still lacking. Moreover, atmospheric changes caused by smoke from deforested and forested areas have limited multi-temporal analysis using remotely sensed data (Karnieli et al., 2001, De Moura and Galvão, 2003). This research intended to measure extent and to assess impacts of selective logging and forest fire on tropical rain forests using Landsat imagery. Therefore, we conducted a detailed multi-temporal analysis of these impacts on natural forests in the Southern Amazon State of Mato Grosso, one of the major logging centers in Brazil. It included field observations, statistical tests on performances of different vegetation indices and green vegetation fraction (GV) derived from SMA to assess forest canopy degradation in the presence of smoke, and development of a modified vegetation index more resistant to atmospheric conditions in the study site.