DOI: https://doi.org/10.14710/geoplanning.3.2.137-146

TEMPORAL VEGETATION DYNAMICS IN PEAT SWAMP AREA USING MODIS TIME-SERIES IMAGERY: A MONITORING APPROACH OF HIGH-SENSITIVE ECOSYSTEM IN REGIONAL SCALE

*Yudi Setiawan  -  Center for Environmental Research, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680, Indonesia
Hidayat Pawitan  -  Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680, Indonesia
Lilik Budi Prasetyo  -  Department of Forest Conservation and Ecotourism, Faculty of Forestry, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680, Indonesia
May Parlindungan  -  Department of Geophysics and Meteorology, Faculty of Mathematics and Natural Sciences, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680, Indonesia
Prita Ayu Permatasari  -  Center for Environmental Research, Bogor Agricultural University, Kampus IPB Darmaga, Bogor 16680, Indonesia

Citation Format:
Abstract
Peat swamp area is an essential ecosystem due to high vulnerability of functions and services. As the change of forest cover in peat swamp area has increased considerably, many studies on peat swamp have focused on forest conversion or forest degradation. Meanwhile, in the context of changes in the forestlands are the sum of several processes such as deforestation, reforestation/afforestation, regeneration of previously deforested areas, and the changing spatial location of the forest boundary. Remote sensing technology seems to be a powerful tool to provide information required following that concerns. A comparison imagery taken at the different dates over the same locations for assessing those changes tends to be limited by the vegetation phenology and land-management practices. Consequently, the simultaneous analysis seems to be a way to deal with the issues above, as a means for better understanding of the dynamics changes in peat swamp area. In this study, we examined the feasibility of using MODIS images during the last 14 years for detecting and monitoring the changes in peat swamp area. We identified several significant patterns that have been assigned as the specific peat swamp ecosystem. The results indicate that a different type of ecosystem and its response to the environmental changes can be portrayed well by the significant patterns. In understanding the complex situations of each pattern, several vegetation dynamics patterns were characterized by physical land characteristics, such as peat depth, land use, concessions and others. Characterizing the pathways of dynamics change in peat swamp area will allow further identification for the range of proximate and underlying factors of the forest cover change that can help to develop useful policy interventions in peatland management.
Fulltext View|Download
Keywords: temporal vegetation dynamics; peat swamp area; MODIS

Article Metrics:

Article Info
Section: Original Research
Language : EN
Recent articles
MITIGATION SCENARIOS FOR RESIDENTIAL FIRES IN DENSELY POPULATED URBAN SETTLEMENTS IN SUKAHAJI VILLAGE, BANDUNG CITY IMPLEMENTATION OF THE MARKOV RANDOM FIELD FOR URBAN LAND COVER CLASSIFICATION OF UAV VHIR DATA ASSESSMENT OF MANGROVE FOREST DEGRADATION THROUGH CANOPY FRACTIONAL COVER IN KARIMUNJAWA ISLAND, CENTRAL JAVA, INDONESIA More recent articles
Most cited articles
LAND PRICE MAPPING OF JABODETABEK, INDONESIA THE DEVELOPMENT OF MARINE SPATIAL PLANNING AND ITS APPLICATION FOR FLOATING FISH NET CULTURE PENGARUH KEBERADAAN PERGURUAN TINGGI TERHADAP PERUBAHAN MORFOLOGI KAWASAN SEKITARNYA REFLEKSI 5 TAHUN PASKA ERUPSI GUNUNG MERAPI 2010: MENAKSIR KERUGIAN EKOLOGIS DI KAWASAN TAMAN NASIONAL GUNUNG MERAPI MODEL OF CLIMATE AND LAND-USE CHANGES IMPACT ON WATER SECURITY IN AMBON CITY, INDONESIA More cited articles

  1. Achard, F. (2002). Determination of Deforestation Rates of the World’s Humid Tropical Forests. Science, 297(5583), 999–1002. [http://doi.org/10.1126/science.1070656">CrossRef]

  2. Bouman, C. A. (2009). Digital image processing. Lecture material. Indiana: School of Electrical and Computer Engineering, Purdue University.

  3. Cole, L. E. S., Bhagwat, S. A., & Willis, K. J. (2015). Long-term disturbance dynamics and resilience of tropical peat swamp forests. Journal of Ecology, 103(1), 16–30. [http://doi.org/10.1111/1365-2745.12329">CrossRef]

  4. Erwin, K. L. (2009). Wetlands and global climate change: the role of wetland restoration in a changing world. Wetlands Ecology and Management, 17(1), 71–84. [http://doi.org/10.1007/s11273-008-9119-1">CrossRef]

  5. Evans, T. P., & Moran, E. F. (2002). Spatial Integration of Social and Biophysical Factors Related to Landcover Change. Population and Development Review, 28, 165–186.

  6. Global Forest Watch. (2002). The state of the forest: Indonesia. Forest Watch Indonesia, Bogor, Indonesia, and Global Forest Watch, Washington DC.

  7. Hooijer, A., et al. (2006). PEAT-CO2, Assessment of CO2 emissions from drained peatlands in SE Asia, Delft Hydraulics report Q3943/2006, 36p.

  8. Huete, A. R., Justice, C., & Van Leeuwen, W. (1999). MODIS Vegetation Index: Algorithm Theoretical Basis Document. Retrieved from https://lpdaac.usgs.gov/products/modis_products_table/myd13q1">

  9. Land Resources Department/Bina Program. (1990). The Land Resources of Indonesia: A National Overview From Regional Physical Planning Programme for Transmigration (Reppprot). Jakarta.

  10. Miettinen, J., et al. (2012). Peatland degradation and conversion sequences and interrelations in Sumatra. Regional Environmental Change, 12(4), 729–737. [http://doi.org/10.1007/s10113-012-0290-9">CrossRef]

  11. Ministry of Forestry. (2013). Recalculation of Land Cover in Indonesia 2013.

  12. Myers, N., et al. (2000). Biodiversity hotspots for conservation priorities. Nature, 403(6772), 853–858.

  13. Page, S. E., Rieley, J. O., & Banks, C. J. (2011). Global and regional importance of the tropical peatland carbon pool. Global Change Biology, 17(2), 798–818. [http://doi.org/10.1111/j.1365-2486.2010.02279.x">CrossRef]

  14. Setiawan, Y., et al. (2016). Characterizing Spatial Distribution and Environments of Sumatran Peat Swamp Area Using 250 M Multi-temporal MODIS Data. Procedia Environmental Sciences, 33, 117–127. [http://doi.org/10.1016/j.proenv.2016.03.063">CrossRef]

  15. Setiawan, Y., & Yoshino, K. (2014). Detecting land-use change from seasonal vegetation dynamics on regional scale with MODIS EVI 250-m time-series imagery. Journal of Land Use Science, 9(3), 304–330. http://doi.org/10.1080/1747423X.2013.786151

  16. Setiawan, Y., Yoshino, K., & Philpot, W. D. (2013). Characterizing temporal vegetation dynamics of land use in regional scale of Java Island, Indonesia. Journal of Land Use Science, 8(1), 1–30. [http://doi.org/10.1080/1747423X.2011.605178">CrossRef]

  17. Setiawan, Y., Yoshino, K., & Prasetyo, L. B. (2014). Characterizing the dynamics change of vegetation cover on tropical forestlands using 250m multi-temporal MODIS EVI. International Journal of Applied Earth Observation and Geoinformation, 26, 132–144. [http://doi.org/10.1016/j.jag.2013.06.008">CrossRef]

  18. Stolle, F., et al. (2003). Land use and vegetation fires in Jambi Province, Sumatra, Indonesia. Forest Ecology and Management, 179(1–3), 277–292. [http://doi.org/10.1016/S0378-1127(02)00547-9">CrossRef]

  19. USGS LP DAAC. (2009). No Center, MOD13Q1. USGS/Earth Resources Observation and Science (EROS) Center. Retrieved from http://eros.usgs.gov/">

  20. Verburg, P. H.,et al. (2009). From land cover change to land function dynamics: A major challenge to improve land characterization. Journal of Environmental Management, 90(3), 1327–1335. [http://doi.org/10.1016/j.jenvman.2008.08.005">CrossRef]

  21. Wardhana, B. (2016). BRG’s Roadmap for Peatland Restoration. Retrieved August 1, 2016, from https://www.cbd.int/doc/meetings/ecr/ecrws-2016-02/other/ecrws-2016-02-presentation-day1-03-en.pdf">

  22. Wösten, J. H. M., et al. (2008). Peat–water interrelationships in a tropical peatland ecosystem in Southeast Asia. CATENA, 73(2), 212–224. [http://doi.org/10.1016/j.catena.2007.07.010">CrossRef]

  23. Xiao, X., et al. (2003). Sensitivity of vegetation indices to atmospheric aerosols: continental-scale observations in Northern Asia. Remote Sensing of Environment, 84(3), 385–392. [http://doi.org/10.1016/S0034-4257(02)00129-3">CrossRef] 


Last update:

  1. Mapping Sensitive Vegetation Communities in Mining Eco-space using UAV-LiDAR

    Bikram Pratap Banerjee, Simit Raval. International Journal of Coal Science & Technology, 9 (1), 2022. doi: 10.1007/s40789-022-00509-w

Last update: 2024-11-05 11:17:33

No citation recorded.