Reforestation and Deforestation in Northern Luzon, Philippines: Critical Issues as Observed from Space
<p>Satellite image of Northern Luzon showing the percentage of forest cover in the year 2000 as derived from Landsat data [<a href="#B14-forests-11-01071" class="html-bibr">14</a>] and the locations (in red) of the National Greening Program (NGP) activities from 2011 to 2016. The three sites used in the case studies are enclosed by the square boxes (in light blue).</p> "> Figure 2
<p>Normalized Difference Vegetation Index (NDVI) climatological maps (2000–2017) as derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) during (<b>a</b>) Dry season (March, April, May); (<b>b</b>) Wet Season (August, September, and October); and (<b>c</b>) Difference between Dry and Wet Season.</p> "> Figure 3
<p>(<b>a</b>) Map of Northern Luzon showing the locations of the different land cover types as classified by the National Mapping and Resource Information Authority (NAMRIA), and forest losses from 2001 to 2010 (in blue) and 2011 to 2018 (in red) using Hansen et al.’s data [<a href="#B14-forests-11-01071" class="html-bibr">14</a>]; (<b>b</b>) Annual forest losses from 2001 to 2018 in both open forest (light green) and closed forest (green); and (<b>c</b>) Annual forest losses within NGP sites.</p> "> Figure 4
<p>Yearly MODIS NDVI averages (black), accumulated forest loss (red) as derived by Hansen et al. [<a href="#B14-forests-11-01071" class="html-bibr">14</a>], and NGP area (green) as provided by the Department of Environment and Natural Resources (DENR) in (<b>a</b>) Site 1; (<b>b</b>) Site 2; (<b>c</b>) Site 3; (<b>d</b>) the Sierra Madre; (<b>e</b>) Cordillera; and (<b>f</b>) the rest of the Luzon area.</p> "> Figure 5
<p>Time series of MODIS NDVI averaged over the study (<b>a</b>) Site 1, (<b>b</b>) Site 2 and (<b>c</b>) Site 3, and also in (<b>d</b>) the Sierra Madre, (<b>e</b>) Cordillera, and (<b>f</b>) the rest of Luzon.</p> "> Figure 6
<p>NDVI composites in Northern Luzon during April for the period (<b>a</b>) 2008 to 2010; and (<b>b</b>) 2017 to 2019, representing the state of vegetation before and after the NGP, respectively; and (<b>c</b>) their difference (b minus a) depicting net gain or loss.</p> "> Figure 7
<p>Classified Landsat images in Site 1 before (2008–2010), during (2014–2016), and after (2017–2019) NGP, and associated Sankey Diagrams.</p> "> Figure 8
<p>Classified Landsat images in Site 2 before (2008–2010), during (2014–2016), and after (2017–2019) NGP, and associated Sankey Diagrams.</p> "> Figure 9
<p>Classified Landsat images in Site 2 before (2008–2010), during (2014–2016), and after (2017–2019) NGP, and associated Sankey Diagrams.</p> "> Figure 10
<p>Actual changes in vegetation cover observed on (<b>a</b>) 2 March 2014; (<b>b</b>) 15 January 2016; (<b>c</b>) 5 April 2016; and (<b>d</b>) 11 July 2019 for a segment of the area within Site 1 (Pin location: 17.161908°, 121.990356°) as observed using very high-resolution (VHR) RGB data accessed through Google Earth Pro.</p> "> Figure 11
<p>Actual changes in vegetation cover observed on (<b>a</b>) 30 January 2010; (<b>b</b>) 13 May 2014; (<b>c</b>) 23 February 2015; (<b>d</b>) 23 March 2017; (<b>e</b>) 18 June 2018; and (<b>f</b>) 17 February 2019, for a segment of the area within Site 2 (Pin location: 16.628325°, 121.944639°) as observed using VHR RGB data accessed through Google Earth Pro.</p> "> Figure 12
<p>Actual changes in vegetation cover observed on (<b>a</b>) 2 November 2012; (<b>b</b>) 20 March 2015, (<b>c</b>) 16 March 2018; and (<b>d</b>) 26 March 2019, for a segment of the area within Site 3 (Pin location: 14.904547°, 121.189158°) as observed using VHR RGB data accessed through Google Earth Pro.</p> "> Figure 13
<p>(<b>a</b>) Geotagged photo of the NGP site in the Sierra Madre and corresponding VHR RGB images taken on (<b>b</b>) 25 April 2012; (<b>c</b>) 26 May 2015; and (<b>d</b>) 18 June 2018, and accessed through Google Earth Pro. Pin location: 17.392233°, 121.925550°.</p> "> Figure 14
<p>(<b>a</b>) Geotagged photo of the NGP site in Cordillera and corresponding VHR RGB images taken on (<b>b</b>) 22 April 2010; (<b>c</b>) 6 January 2014; and (<b>d</b>) 29 November 2018, and accessed through Google Earth Pro. Pin location: 16.802003°, 120.791006°.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Areas and NGP Sites
2.2. NDVI Data from Satellites
2.3. Data on Forest Loss
2.4. Forest Cover Change Analysis
3. Results and Discussions
3.1. Estimates of Forest Loss from Landsat
3.2. Regional and Large Scale Assessments of Greening
3.3. Case Studies in Sierra Madre Forest Using Landsat
3.4. Monitoring NGP Sites Using VHR Images
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Heaney, L.; Mittermeier, R.A. The Philippines. In Megadiversity: Earths Biologically Wealthiest Nations; Robles, G.P., Ed.; CMEX: Taipei, Taiwan, 1997; pp. 236–255. [Google Scholar]
- Bankoff, G. One Island Too Many: Reappraising the Extent of Deforestation in the Philippines prior to 1946. J. Hist. Geogr. 2007, 33, 314–334. [Google Scholar] [CrossRef]
- Catibog-Sinha, C.; Heaney, L.R. Philippine Biodiversity: Principles and Practice; Haribon Foundation for the Conservation of Natural Resources, Inc.: Quezon City, Philippines, 2006. [Google Scholar]
- Ong, P.S.; Rosell-Ambal, R.G.; Afuang, L.E. Philippine Biodiversity Conservation Priorities: A Second Iteration of the National Biodiversity Strategy and Action Plan; Department of Environment and Natural Resources, Conservation International, University of the Philippines Center for Integrative and Development Studies, and Foundation for the Philippine Environment: Quezon City, Philippines, 2002. [Google Scholar]
- Moya, T.B.; Malayang, B.S. Climate variability and deforestation-reforestation dynamics in the Philippines. Environ. Dev. Sustain. 2004, 6, 261–277. [Google Scholar] [CrossRef]
- Araño, R.R.; Persoon, G.A. Action research for community-based resource management and development: The case of the northern Sierra Madre Natural Park conservation project, in Northeastern Philippines. In Research in Tropical Rain Forests: Its Challenges for the Future; Tropenpos International: Wageningen, The Netherlands, 1997; p. 101. [Google Scholar]
- Suarez, R.K.; Sajise, P.E. Deforestation, Swidden Agriculture and Philippine Biodiversity. Philipp. Sci. Lett. 2010, 3, 91–99. [Google Scholar]
- Apan, A.; Suarez, L.A.; Maraseni, T.; Castillo, A. The rate, extent and spatial predictors of forest loss (2000–2012) in the terrestrial protected areas of the Philippines. Appl. Geogr. 2017, 81, 32–42. [Google Scholar] [CrossRef]
- Novick, K.A.; Katul, G.G. The duality of reforestation impacts on surface and air temperature. J. Geophys. Res. Biogeosci. 2020, 125, e2019JG005543. [Google Scholar] [CrossRef]
- Department of Environment and Natural Resources–Expanded National Greening Program. Available online: https://www.denr.gov.ph/index.php/priority-programs/national-greening-program (accessed on 31 July 2020).
- Fostering Education and Environment for Development, Inc. Enhanced National Greening Program. Available online: https://feed.org.ph/engagement-activities/enhanced-national-greening-program/ (accessed on 5 October 2020).
- Wilkie, L.M. Whither the forests of Asia and the Pacific. In The Future of Forests in Asia and the Pacific: Outlook for 2020, Chiang Mai, Thailand, 16–18 October 2007; Leslie, R.N., Ed.; Food and Agriculture Organization of the United Nations, Asia-Pacific Forestry Commission: Washington, DC, USA, 2009; pp. 31–51. [Google Scholar]
- Song, X.P.; Hansen, M.C.; Stehman, S.; Potapov, P.V.; Tyukavina, A.; Vermote, E.F. Global land change from 1982 to 2016. Nature 2018, 560, 639–643. [Google Scholar] [CrossRef]
- Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-resolution global maps of 21st-century forest cover change. Science 2013, 342, 850–853. [Google Scholar] [CrossRef] [Green Version]
- Turner, B.L., II; Lambin, E.F.; Reeberg, A. The emergence of land change science for global environmental change and sustainability. Proc. Natl. Acad. Sci. USA 2007, 104, 20666–20671. [Google Scholar] [CrossRef] [Green Version]
- Foley, J.A.; DeFries, R.; Asner, G.P.; Barford, C.; Bonan, G.; Carpenter, S.R.; Chapin, F.S.; Coe, M.T.; Daily, G.C.; Gibbs, H.K.; et al. Global consequences of land use. Science 2005, 309, 570–574. [Google Scholar] [CrossRef] [Green Version]
- Poulsen, M.K. The Threatened and Near-Threatened Birds of Luzon, Philippines, and the Role of the Sierra Madre Mountains in Their Conservation. Bird Conserv. Int. 1995, 5, 79–115. [Google Scholar] [CrossRef] [Green Version]
- Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8, 127–150. [Google Scholar] [CrossRef] [Green Version]
- Perez, G.J.; Comiso, J.C. Seasonal and Interannual Variability of Philippine Vegetation as Seen from Space. Philipp. J. Sci. 2014, 43, 147–155. [Google Scholar]
- Tucker, J.; Sellers, P.J. Satellite remote sensing of primary production. Int. J. Remote Sens. 1986, 7, 1395–1416. [Google Scholar] [CrossRef]
- Sexton, J.O.; Song, X.P.; Feng, M.; Noojipady, P.; Anand, A.; Huang, C.; Kim, D.H.; Collins, K.M.; Channan, S.; DiMiceli, C.; et al. Global 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS Vegetation Continuous Fields with lidar-based estimates of error. Int. J. Digit. Earth 2013, 6, 427–448. [Google Scholar] [CrossRef] [Green Version]
- Margono, B.A.; Potapov, P.V.; Turubanova, S.; Stolle, F.; Hansen, M.C. Primary forest cover loss in Indonesia over 2000–2012. Nat. Clim. Chang. 2014, 4, 730–735. [Google Scholar] [CrossRef]
- Potapov, P.; Hansen, M.C.; Laestadius, L.; Turubanova, S.; Yaroshenko, A.; Thies, C.; Smith, W.; Zhuravleva, I.; Komarova, A.; Minnemeyer, S.; et al. The last frontiers of wilderness: Tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 2017, 3, e1600821. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yuan, W.; Li, X.; Liang, S.; Cui, X.; Dong, W.; Liu, S.; Xia, J.; Chen, Y.; Liu, D.; Zhu, W. Characterization of locations and extents of afforestation from the Grain for Green Project in China. Remote Sens. Lett. 2014, 5, 221–229. [Google Scholar] [CrossRef]
- Jeong, S.J.; Ho, C.H.; Choi, S.D.; Kim, J.; Lee, E.J.; Gim, H.J. Satellite data-based phenological evaluation of the nationwide reforestation of South Korea. PLoS ONE 2013, 8, e58900. [Google Scholar] [CrossRef] [Green Version]
- Tropek, R.; Sedláček, O.; Beck, J.; Keil, P.; Musilová6, Z.; Šímová, I.; Storch, D. Comment on “High-resolution global maps of 21st-century forest cover change”. Science 2014, 344, 981. [Google Scholar] [CrossRef] [Green Version]
- Manuel, W.V. Land Cover Data in the Philippines. In Proceedings of the 5th UNREDD Regional Lessons Learned Workshop on Monitoring Systems and Reference Levels for REDD+, Hanoi, Vietnam, 20–22 October 2014. [Google Scholar]
- Roy, D.P.; Kovalskyy, V.; Zhang, H.K.; Vermote, E.F.; Yan, L.; Kumar, S.S.; Egorov, A. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sens. Environ. 2016, 185, 57–70. [Google Scholar] [CrossRef] [Green Version]
- R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Available online: https://www.R-project.org/ (accessed on 27 September 2020).
- Hijmans, R.J. Raster: Geographic Data Analysis and Modeling. R Package Version 3.0-12. Available online: https://CRAN.R-project.org/package=raster (accessed on 27 September 2020).
- Liaw, A.; Wiener, M. Classification and Regression by randomForest. R News 2002, 2, 18–22. [Google Scholar]
- Fortier, J.; Rogan, J.; Woodcock, C.E.; Runfola, D.M. Utilizing temporally invariant calibration sites to classify multiple dates and types of satellite imagery. Photogramm. Eng. Remote Sens. 2011, 77, 181–189. [Google Scholar] [CrossRef]
- Song, C.; Woodcock, C.E. Monitoring forest succession with multitemporal Landsat images: Factors of uncertainty. IEEE Trans. Geosci. Remote Sens. 2003, 41, 2557–2567. [Google Scholar] [CrossRef]
- Gesmann, M.; de Castillo, D. Using the Google visualisation API with R. R J. 2011, 3, 40–44. [Google Scholar] [CrossRef] [Green Version]
- Vista, A.; Cororaton, C.B.; Inocencio, A.B.; Tiongco, M.M.; Manalang, A.B.S. Impact Assessment of the National Greening Program of the DENR: Scoping or Process Evaluation Phase (Economic Component); Discussion Paper Series No. 2016-27; Philippine Institute for Development Studies: Quezon City, Philippines, 2016; p. 84. [Google Scholar]
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Perez, G.J.; Comiso, J.C.; Aragones, L.V.; Merida, H.C.; Ong, P.S. Reforestation and Deforestation in Northern Luzon, Philippines: Critical Issues as Observed from Space. Forests 2020, 11, 1071. https://doi.org/10.3390/f11101071
Perez GJ, Comiso JC, Aragones LV, Merida HC, Ong PS. Reforestation and Deforestation in Northern Luzon, Philippines: Critical Issues as Observed from Space. Forests. 2020; 11(10):1071. https://doi.org/10.3390/f11101071
Chicago/Turabian StylePerez, Gay Jane, Josefino C. Comiso, Lemnuel V. Aragones, Harry C. Merida, and Perry S. Ong. 2020. "Reforestation and Deforestation in Northern Luzon, Philippines: Critical Issues as Observed from Space" Forests 11, no. 10: 1071. https://doi.org/10.3390/f11101071