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Forest Land Use Cover Changes (LUCC) and Impacts on Environment...
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Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecology and Management".

Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 87197

Special Issue Editors

Dr. Krishna Vadrevu

E-Mail Website
Guest Editor
Earth Science Office, NASA Marshall Space Flight Center, Huntsville, AL, USA
Interests: remote sensing and GIS applications; land cover/land use changes; land-atmosphere interactions; satellite remote sensing of fires; biogeochemical cycling; biodiversity and ecology; agroecosystems and sustainability
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Kasturi Devi Kanniah

E-Mail Website
Co-Guest Editor
Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, UTM, Johor Bahru 81310, Malaysia
Interests: remote sensing; land use land cover change mapping; urban land use changes, vegetation processes and atmospheric aerosols
Special Issues, Collections and Topics in MDPI journals
Dr. Garik Gutman

E-Mail Website
Co-Guest Editor
NASA Headquarters, Washington, DC, USA
Interests: remote sensing of land use/cover change; land-atmospheric interactions; big-data processing; remote sensing of the environment
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chris Justice

E-Mail Website
Co-Guest Editor
Department of Geographical Sciences, University of Maryland, College Park, MD, USA
Interests: global change research; land use/cover change; satellite-based agriculture monitoring; satellite-based fire monitoring; terrestrial observing systems/remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forests in South/Southeast Asia (S/SEA) are undergoing rapid changes due to pressures from increased population and economic development. Addressing land-use cover changes (LUCC) in the forestry sector is one of the most important scientific challenges in global change research. LUCC are important drivers of environmental change in South/Southeast Asia (S/SEA). In the region, LUCC in the forestry sector manifest in a variety of phenomena, such as deforestation, logging, reforestation, etc. Slash-and-burn agriculture continues to be a major driver of forest-cover changes in the hilly regions of India, Myanmar, Thailand, Laos, and Cambodia. Further, a recent rise in the global prices for commodity crops like rubber and oil palm has resulted in an increase in commercial plantations, replacing natural forests. Drivers of LUCC in the forestry sector vary widely in the region, such as economic development, government policies, international trade, inappropriate forest management, and land tenure issues. In addition, variability in the weather, climate, and socioeconomic factors is another driver of forest LUCC. Some of the LUCC impacts on forests include disruption of biogeochemical cycles and changes in the radiation and the surface energy balance of the atmosphere. Following the Intergovernmental Panel on Climate Change (IPCC) guidelines, greenhouse gas emissions from land-use change in the forestry sector are related to changes in biomass stocks as a result of forest management, logging, fuelwood collection, and conversion of existing forests to other land-use categories. Thus, documenting these changes and associated impacts in the forestry sector gains significance, as the results can be used to address improved forest management, including GHG mitigation. To document LUCC in the forestry sector, spatially explicit, time-series data are essential. Further, in S/SEA, there is an increasing need to develop consistent and reliable forestry datasets that are useful for management and policy-making. We invite articles covering the above topics and those listed below, focusing on South and Southeast Asian countries: · Applications of optical, thermal, multispectral, hyperspectral, lidar, and airborne remote sensing data for forest mapping, monitoring and impact assessment studies; · LUCC in the forestry sector and impacts on carbon cycling and greenhouse gas emissions; · documenting changes in the forestry sector due to slash-and-burn agriculture; · forest fires and associated impacts; · forest biodiversity inventory studies; · mapping and monitoring of land management practices, disturbances, and interactions; · Detecting long-term trends in the forestry sector and impacts on hydrological variables, such as runoff, evapotranspiration, and soil moisture; · deforestation and its impact on the socioeconomic status of indigenous people; · forest protected area management; · scalable approaches (statistical and modeling) for improving forestry datasets and impacts at large spatial scales; · forest dynamics in secondary forests; · spatiotemporal data mining, modeling, and analysis for forestry LU/CC data and impact assessment studies; · new tools and methods for forestry data generation and dissemination.

Dr. Krishna Prasad Vadrevu
Dr. Kasturi Kanniah
Dr. Garik Gutman
Dr. Chris Justice
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Applications of optical, thermal, multispectral, hyperspectral, lidar, and airborne remote sensing data for forest mapping, monitoring, and impact assessment studies
  • LUCC in the forestry sector and impacts on carbon cycling and greenhouse gas emissions
  • documenting changes in the forestry sector due to slash-and-burn agriculture
  • forest fires and associated impacts
  • forest biodiversity inventory studies
  • mapping and monitoring of land management practices, disturbances, and interactions
  • detecting long-term trends in the forestry sector and impacts on hydrological variables, such as runoff, evapotranspiration, and soil moisture
  • deforestation and its impact on the socioeconomic status of indigenous people
  • forest protected area management
  • scalable approaches (statistical and modeling) for improving forestry datasets and impacts at large spatial scales
  • forest dynamics in secondary forests
  • spatiotemporal data mining, modeling, and analysis for forestry LU/CC data and impact assessment studies
  • new tools and methods for forestry data generation and dissemination

Published Papers (9 papers)

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Research

22 pages, 5692 KiB  
Article
Carbon Emissions from Oil Palm Induced Forest and Peatland Conversion in Sabah and Sarawak, Malaysia
by Wan Shafrina Wan Mohd Jaafar, Nor Fitrah Syazwani Said, Khairul Nizam Abdul Maulud, Royston Uning, Mohd Talib Latif, Aisyah Marliza Muhmad Kamarulzaman, Midhun Mohan, Biswajeet Pradhan, Siti Nor Maizah Saad, Eben North Broadbent, Adrián Cardil, Carlos Alberto Silva and Mohd Sobri Takriff
Forests 2020, 11(12), 1285; https://doi.org/10.3390/f11121285 - 29 Nov 2020
Cited by 24 | Viewed by 6368
Abstract
The palm oil industry is one of the major producers of vegetable oil in the tropics. Palm oil is used extensively for the manufacture of a wide variety of products and its production is increasing by around 9% every year, prompted largely by [...] Read more.
The palm oil industry is one of the major producers of vegetable oil in the tropics. Palm oil is used extensively for the manufacture of a wide variety of products and its production is increasing by around 9% every year, prompted largely by the expanding biofuel markets. The rise in annual demand for biofuels and vegetable oil from importer countries has caused a dramatic increase in the conversion of forests and peatlands into oil palm plantations in Malaysia. This study assessed the area of forests and peatlands converted into oil palm plantations from 1990 to 2018 in the states of Sarawak and Sabah, Malaysia, and estimated the resulting carbon dioxide (CO2) emissions. To do so, we analyzed multitemporal 30-m resolution Landsat-5 and Landsat-8 images using a hybrid method that combined automatic image processing and manual analyses. We found that over the 28-year period, forest cover declined by 12.6% and 16.3%, and the peatland area declined by 20.5% and 19.1% in Sarawak and Sabah, respectively. In 2018, we found that these changes resulted in CO2 emissions of 0.01577 and 0.00086 Gt CO2-C yr−1, as compared to an annual forest CO2 uptake of 0.26464 and 0.15007 Gt CO2-C yr−1, in Sarawak and Sabah, respectively. Our assessment highlights that carbon impacts extend beyond lost standing stocks, and result in substantial direct emissions from the oil palm plantations themselves, with 2018 oil palm plantations in our study area emitting up to 4% of CO2 uptake by remaining forests. Limiting future climate change impacts requires enhanced economic incentives for land uses that neither convert standing forests nor result in substantial CO2 emissions. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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20 pages, 12996 KiB  
Article
Reforestation and Deforestation in Northern Luzon, Philippines: Critical Issues as Observed from Space
by Gay Jane Perez, Josefino C. Comiso, Lemnuel V. Aragones, Harry C. Merida and Perry S. Ong
Forests 2020, 11(10), 1071; https://doi.org/10.3390/f11101071 - 6 Oct 2020
Cited by 18 | Viewed by 33936
Abstract
Among the richest in biodiversity globally has been the Philippine rainforest, which used to cover about 90% of the country’s land area. During the last few decades, the forest cover has been reduced to less than 10% of the original, only a fraction [...] Read more.
Among the richest in biodiversity globally has been the Philippine rainforest, which used to cover about 90% of the country’s land area. During the last few decades, the forest cover has been reduced to less than 10% of the original, only a fraction of which is old-growth forest. The negative impacts of deforestation led to the launching of the National Greening Program (NGP) that involved the planting of more than a billion seedlings over a few million hectares of land from 2011 to 2016. To assess the success of the NGP, satellite data from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) were analyzed before, during, and after the NGP. Reforestation in the NGP sites was examined concurrently with observed deforestation in Luzon using forest loss data derived from Landsat for the period 2001 to 2018. The results show that losses declined from 2011 to 2015 but increased from 2016 to 2018. Because of such losses, the net effect is a balance of reforestation and deforestation or no significant gain from the NGP. Case studies were done in three sites in the Sierra Madre forest, where half of the remaining old-growth forest is located, using a combination of Landsat and Very High Resolution (VHR) data. The Landsat data were classified into closed forest, open forest, and other vegetation cover types. The conversion from one vegetation cover type to another was evaluated through the use of the Sankey Diagram. While some non-forest types became open or closed forests, the loss of open or closed forests is more pronounced. VHR data reveal critical issues happening within the NGP sites during the NGP period. More comprehensive data from MODIS also confirm that there was no significant increase in the forest cover in Luzon, Sierra Madre, and Cordillera from 2001 to 2018. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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15 pages, 2620 KiB  
Article
Estimating Mangrove Above-Ground Biomass Loss Due to Deforestation in Malaysian Northern Borneo between 2000 and 2015 Using SRTM and Landsat Images
by Charissa J. Wong, Daniel James, Normah A. Besar, Kamlisa U. Kamlun, Joseph Tangah, Satoshi Tsuyuki and Mui-How Phua
Forests 2020, 11(9), 1018; https://doi.org/10.3390/f11091018 - 22 Sep 2020
Cited by 16 | Viewed by 4042
Abstract
Mangrove forests are highly productive ecosystems and play an important role in the global carbon cycle. We used Shuttle Radar Topography Mission (SRTM) elevation data to estimate mangrove above-ground biomass (AGB) in Sabah, Malaysian northern Borneo. We developed a tree-level approach to deal [...] Read more.
Mangrove forests are highly productive ecosystems and play an important role in the global carbon cycle. We used Shuttle Radar Topography Mission (SRTM) elevation data to estimate mangrove above-ground biomass (AGB) in Sabah, Malaysian northern Borneo. We developed a tree-level approach to deal with the substantial temporal discrepancy between the SRTM data and the mangrove’s field measurements. We predicted the annual growth of diameter at breast height and adjusted the field measurements to the SRTM data acquisition year to estimate the field AGB. A canopy height model (CHM) was derived by correcting the SRTM data with ground elevation. Regression analyses between the estimated AGB and SRTM CHM produced an estimation model (R2: 0.61) with a root mean square error (RMSE) of 8.24 Mg ha−1 (RMSE%: 5.47). We then quantified the mangrove forest loss based on supervised classification of multitemporal Landsat images. More than 25,000 ha of mangrove forest had disappeared between 2000 and 2015. This has resulted in a significant decrease of about 3.96 million Mg of mangrove AGB in Sabah during the study period. As SRTM elevation data has a near-global coverage, this approach can be used to map the historical AGB of mangroves, especially in Southeast Asia, to promote mangrove carbon stock conservation. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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24 pages, 5365 KiB  
Article
Synergy of Active and Passive Remote Sensing Data for Effective Mapping of Oil Palm Plantation in Malaysia
by Nazarin Ezzaty Mohd Najib, Kasturi Devi Kanniah, Arthur P. Cracknell and Le Yu
Forests 2020, 11(8), 858; https://doi.org/10.3390/f11080858 - 6 Aug 2020
Cited by 21 | Viewed by 3558
Abstract
Oil palm is recognized as a golden crop, as it produces the highest oil yield among oil seed crops. Malaysia is the world’s second largest producer of palm oil; 16% of its land is planted with oil palm. To cope with the ever-increasing [...] Read more.
Oil palm is recognized as a golden crop, as it produces the highest oil yield among oil seed crops. Malaysia is the world’s second largest producer of palm oil; 16% of its land is planted with oil palm. To cope with the ever-increasing global demand on edible oil, additional areas of oil palm are forecast to increase globally by 12 to 19 Mha by 2050. Multisensor remote sensing plays an important role in providing relevant, timely, and accurate information that can be developed into a plantation monitoring system to optimize production and sustainability. The aim of this study was to simultaneously exploit the synthetic aperture radar ALOS PALSAR 2, a form of microwave remote sensing, in combination with visible (red) data from Landsat Thematic Mapper to obtain a holistic view of a plantation. A manipulation of the horizontal–horizontal (HH) and horizontal–vertical (HV) polarizations of ALOS PALSAR data detected oil palm trees and water bodies, while the red spectra L-band from Landsat data (optical) could effectively identify built up areas and vertical–horizontal (VH) polarization from Sentinel C-band data detected bare land. These techniques produced an oil palm area classification with overall accuracies of 98.36% and 0.78 kappa coefficient for Peninsular Malaysia. The total oil palm area in Peninsular Malaysia was estimated to be about 3.48% higher than the value reported by the Malaysian Palm Oil Board. The over estimation may be due the MPOB’s statistics that do not include unregistered small holder oil palm plantations. In this study, we were able to discriminate most of the rubber areas. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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25 pages, 5825 KiB  
Article
Multi-Decadal Forest-Cover Dynamics in the Tropical Realm: Past Trends and Policy Insights for Forest Conservation in Dry Zone of Sri Lanka
by Manjula Ranagalage, M. H. J. P. Gunarathna, Thilina D. Surasinghe, Dmslb Dissanayake, Matamyo Simwanda, Yuji Murayama, Takehiro Morimoto, Darius Phiri, Vincent R. Nyirenda, K. T. Premakantha and Anura Sathurusinghe
Forests 2020, 11(8), 836; https://doi.org/10.3390/f11080836 - 1 Aug 2020
Cited by 24 | Viewed by 9992
Abstract
Forest-cover change has become an important topic in global biodiversity conservation in recent decades because of the high rates of forest loss in different parts of the world, especially in the tropical region. While human interventions are the major cause, natural disasters also [...] Read more.
Forest-cover change has become an important topic in global biodiversity conservation in recent decades because of the high rates of forest loss in different parts of the world, especially in the tropical region. While human interventions are the major cause, natural disasters also contribute to forest cover changes. During the past decades, several studies have been conducted to address different aspects of forest cover changes (e.g., drivers of deforestation, degradation, interventions) in different parts of the world. In Sri Lanka, increasing rates of forest loss have been recorded during the last 100 years on a regional basis, especially in the dry zone. However, Sri Lanka needs detailed studies that employ contemporary data and robust analytical tools to understand the patterns of forest cover changes and their drivers. The dry zone of Sri Lanka encompasses 59% of the total land area of the country, ergo, the most extensive forest cover. Our study analyzed forest cover dynamics and its drivers between 1992 and 2019. Our specific objectives included (i) producing a forest cover map for 2019, (ii) analyzing the spatiotemporal patterns of forest cover changes from 1992 to 2019, and (iii) determining the main driving forces. Landsat 8 images were used to develop forest-cover maps for 2019, and the rest of the forest cover maps (1992, 1999, and 2010) were obtained from the Forest Department of Sri Lanka. In this study, we found that the dry zone had undergone rapid forest loss (246,958.4 ha) during the past 27 years, which accounts for 8.0% of the net forest cover changes. From 2010 to 2019, the rates of forest loss were high, and this can be associated with the rapid infrastructure development of the country. The findings of this study can be used as a proxy to reform current forest policies and enhance the forest sustainability of the study area. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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27 pages, 13052 KiB  
Article
The Influence of Deforestation on Land Surface Temperature—A Case Study of Perak and Kedah, Malaysia
by Wan Shafrina Wan Mohd Jaafar, Khairul Nizam Abdul Maulud, Aisyah Marliza Muhmad Kamarulzaman, Asif Raihan, Syarina Md Sah, Azizah Ahmad, Siti Nor Maizah Saad, Ahmad Tarmizi Mohd Azmi, Nur Khairun Ayuni Jusoh Syukri and Waseem Razzaq Khan
Forests 2020, 11(6), 670; https://doi.org/10.3390/f11060670 - 11 Jun 2020
Cited by 87 | Viewed by 10660
Abstract
Over the past few decades, there has been a rapid change in forest and land cover, especially in tropical forests due to massive deforestation. The major factor responsible for the changes is to fulfill the growing demand of increasing population through agricultural intensification, [...] Read more.
Over the past few decades, there has been a rapid change in forest and land cover, especially in tropical forests due to massive deforestation. The major factor responsible for the changes is to fulfill the growing demand of increasing population through agricultural intensification, rural settlements, and urbanization. Monitoring forest cover and vegetation are essential for detecting regional and global environmental changes. The present study evaluates the influence of deforestation on land surface temperature (LST) in the states of Kedah and Perak, Malaysia, between 1988 and 2017. The trend in forest cover change over the time span of 29 years, was analyzed using Landsat 5 and Landsat 8 satellite images to map the sequence of forest cover change. With the measurement of deforestation and its relationship with LST as an end goal, the Normalized Difference Vegetation Index (NDVI) was used to determine forest health, and the spectral radiance model was used to extract the LST. The findings of the study show that nearly 16% (189,423 ha) of forest cover in Perak and more than 9% (33,391 ha) of forest cover in Kedah have disappeared within these 29 years as a result of anthropogenic activities. The correlation between the LST and NDVI is related to the distribution of forests, where LST is inversely related to NDVI. A strong correlation between LST and NDVI was observed in this study, where the average mean of LST in Kedah (25 °C) is higher than in Perak (22.6 °C). This is also reflected by the decreased NDVI value from 0.6 to 0.5 in 2017 at both states. This demonstrated that a decrease in the vegetation area leads to an increase in the surface temperature. The resultant forest change map would be helpful for forest management in terms of identifying highly vulnerable areas. Moreover, it could help the local government to formulate a land management plan. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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16 pages, 1536 KiB  
Article
Carbon Stock and Sequestration Potential of an Agroforestry System in Sabah, Malaysia
by Normah Awang Besar, Herawandi Suardi, Mui-How Phua, Daniel James, Mazlin Bin Mokhtar and Minhaz Farid Ahmed
Forests 2020, 11(2), 210; https://doi.org/10.3390/f11020210 - 12 Feb 2020
Cited by 40 | Viewed by 5468
Abstract
Total aboveground carbon (TAC) and total soil carbon stock in the agroforestry system at the Balung River Plantation, Sabah, Malaysia were investigated to scientifically support the sustaining of natural forest for mitigating global warming via reducing carbon in the atmosphere. Agroforestry, monoculture, and [...] Read more.
Total aboveground carbon (TAC) and total soil carbon stock in the agroforestry system at the Balung River Plantation, Sabah, Malaysia were investigated to scientifically support the sustaining of natural forest for mitigating global warming via reducing carbon in the atmosphere. Agroforestry, monoculture, and natural tropical forests were investigated to calculate the carbon stock and sequestration based on three different combinations of oil palm and agarwood in agroforestry systems from 2014 to 2018. These combinations were oil palm (27 years) and agarwood (seven years), oil palm (20 years) and agarwood (seven years), and oil palm (17 years) and agarwood (five years). Monoculture oil palm (16 years), oil palm (six years), and natural tropical forest were set as the control. Three randomly selected plots for agroforestry and monoculture plantation were 0.25 ha (50 × 50 m), respectively, whereas for the natural tropical forest it was 0.09 ha (30 × 30 m). A nondestructive sampling method followed by the allometric equation determined the standing biomass. Organic and shrub layers collected in a square frame (1 × 1 m) were analyzed using the CHN628 series (LECO Corp., MI, USA) for carbon content. Soil bulk density of randomly selected points within the three different layers, that is, 0 to 5, 5 to 10, and 10 to 30 cm were used to determine the total ecosystem carbon (TEC) stock in each agroforestry system which was 79.13, 85.40, and 78.28 Mg C ha−1, respectively. The TEC in the monoculture oil palm was 76.44 and 60.30 Mg C ha−1, whereas natural tropical forest had the highest TEC of 287.29 Mg C ha−1. The forest stand had the highest TEC capacity as compared with the agroforestry and monoculture systems. The impact of planting systems on the TEC showed a statistically significant difference at a 95% confidence interval for the various carbon pools among the agroforestry, monoculture, and natural tropical forests. Therefore, the forest must be sustained because of its higher capacity to store carbon in mitigating global warming. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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16 pages, 3910 KiB  
Article
Assessing the Importance of Tree Cover Threshold for Forest Cover Mapping Derived from Global Forest Cover in Myanmar
by Kay Khaing Lwin, Tetsuji Ota, Katsuto Shimizu and Nobuya Mizoue
Forests 2019, 10(12), 1062; https://doi.org/10.3390/f10121062 - 22 Nov 2019
Cited by 11 | Viewed by 4477
Abstract
Comprehensive forest cover mapping is essential for making policy and management decisions. However, creating a forest cover map from raw remote sensing data is a barrier for many users. Here, we investigated the effects of different tree cover thresholds on the accuracy of [...] Read more.
Comprehensive forest cover mapping is essential for making policy and management decisions. However, creating a forest cover map from raw remote sensing data is a barrier for many users. Here, we investigated the effects of different tree cover thresholds on the accuracy of forest cover maps derived from the Global Forest Change Dataset (GFCD) across different ecological zones in a country-scale evaluation of Myanmar. To understand the effect of different thresholds on map accuracy, nine forest cover maps having thresholds ranging from 10% to 90% were created from the GFCD. The accuracy of the forest cover maps within each ecological zone and at the national scale was assessed. The overall accuracies of ecological zones other than tropical rainforest were highest when the threshold for tree cover was less than 50%. The appropriate threshold for tropical rainforests was 80%. Therefore, different optimal tree cover thresholds were required to achieve the highest overall accuracy depending on ecological zones. However, in the unique case of Myanmar, we were able to determine the threshold across the whole country. We concluded that the threshold for tree cover for creating a forest cover map should be determined according to the areal ratio of ecological zones determined from large-scale monitoring. Our results are applicable to tropical regions having similar ecological zones. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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19 pages, 4975 KiB  
Article
Relationship Between Fire and Forest Cover Loss in Riau Province, Indonesia Between 2001 and 2012
by H. A. Adrianto, D. V. Spracklen and S. R. Arnold
Forests 2019, 10(10), 889; https://doi.org/10.3390/f10100889 - 8 Oct 2019
Cited by 33 | Viewed by 6323
Abstract
Forest and peatland fires occur regularly across Indonesia, resulting in large greenhouse gas emissions and causing major air quality issues. Over the last few decades, Indonesia has also experienced extensive forest loss and conversion of natural forest to oil palm and timber plantations. [...] Read more.
Forest and peatland fires occur regularly across Indonesia, resulting in large greenhouse gas emissions and causing major air quality issues. Over the last few decades, Indonesia has also experienced extensive forest loss and conversion of natural forest to oil palm and timber plantations. Here we used data on fire hotspots and tree-cover loss, as well as information on the extent of peat land, protected areas, and concessions to explore spatial and temporal relationships among forest, forest loss, and fire frequency. We focus on the Riau Province in Central Sumatra, one of the most active regions of fire in Indonesia. We find strong relationships between forest loss and fire at the local scale. Regions with forest loss experienced six times as many fire hotspots compared to regions with no forest loss. Forest loss and maximum fire frequency occurred within the same year, or one year apart, in 70% of the 1 km2 cells experiencing both forest loss and fire. Frequency of fire was lower both before and after forest loss, suggesting that most fire is associated with the forest loss process. On peat soils, fire frequency was a factor 10 to 100 lower in protected areas and natural forest logging concessions compared to oil palm and wood fiber (timber) concessions. Efforts to reduce fire need to address the underlying role of land-use and land-cover change in the occurrence of fire. Increased support for protected areas and natural forest logging concessions and restoration of degraded peatlands may reduce future fire risk. During times of high fire risk, fire suppression resources should be targeted to regions that are experiencing recent forest loss, as these regions are most likely to experience fire. Full article
(This article belongs to the Special Issue Forest Land Use Cover Changes (LUCC) and Impacts on Environment in South/Southeast Asian Countries)
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