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Monitoring and mapping of the extent...
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Pham, Uy Duc.
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Monitoring and mapping of the extent of industrial forests in Malaysia.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Monitoring and mapping of the extent of industrial forests in Malaysia./
作者:
Pham, Uy Duc.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:
278 p.
附註:
Source: Dissertation Abstracts International, Volume: 77-12(E), Section: B.
Contained By:
Dissertation Abstracts International77-12B(E).
標題:
Forestry. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10142896
ISBN:
9781339981628
Monitoring and mapping of the extent of industrial forests in Malaysia.
Pham, Uy Duc.
Monitoring and mapping of the extent of industrial forests in Malaysia.
- Ann Arbor : ProQuest Dissertations & Theses, 2016 - 278 p.
Source: Dissertation Abstracts International, Volume: 77-12(E), Section: B.
Thesis (Ph.D.)--Michigan State University, 2016.
There are scattered studies in the international forestry sector that Industrial Forests (IFs) have been expanding as a newly-emerging Land Use and Land Cover Change (LULCC) in the tropics, especially in the Asia-Pacific region. However, these new tree plantations have not yet been well-documented; the area, along with its geography and land use dynamics, are not well known. Additionally, the drivers are not well understood, but it is widely believed that changes in tropical silviculture and increased international demand for wood and fiber are shifting to new demand centers in Asia. These trends have the potential to create global shifts in source producing areas, from long-standing IFs in North America and Europe to newer areas to the tropics. Considerable remote sensing research and product development have been focusing on monitoring closed canopy natural forests, but less work has been done on intensively managed IFs, which involve techniques for remote characterization of the establishment, management, and rotation. Moreover, the studies to date have been geographically limited to some key areas, such as the Amazon and Indonesia, and more work needs to be done outside of these closed natural forest regions. This research is conducted in the tropical Asia-Pacific region with a focus on the new IFs in the Sabah and Sarawak states of Malaysia. This study aims to improve the knowledge base and understanding of the extent and characteristics of new IFs as a new agent of LULCC, and to develop the methods for Landsat data, in particular by using forest fractional cover (fC) and vegetation indices (VIs) analyses in time series integrated with textural, spectral, visual, and other analyses to detect and quantify IF LULCC patterns and dynamics in the country.
ISBN: 9781339981628Subjects--Topical Terms:
895157
Forestry.
Monitoring and mapping of the extent of industrial forests in Malaysia.
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There are scattered studies in the international forestry sector that Industrial Forests (IFs) have been expanding as a newly-emerging Land Use and Land Cover Change (LULCC) in the tropics, especially in the Asia-Pacific region. However, these new tree plantations have not yet been well-documented; the area, along with its geography and land use dynamics, are not well known. Additionally, the drivers are not well understood, but it is widely believed that changes in tropical silviculture and increased international demand for wood and fiber are shifting to new demand centers in Asia. These trends have the potential to create global shifts in source producing areas, from long-standing IFs in North America and Europe to newer areas to the tropics. Considerable remote sensing research and product development have been focusing on monitoring closed canopy natural forests, but less work has been done on intensively managed IFs, which involve techniques for remote characterization of the establishment, management, and rotation. Moreover, the studies to date have been geographically limited to some key areas, such as the Amazon and Indonesia, and more work needs to be done outside of these closed natural forest regions. This research is conducted in the tropical Asia-Pacific region with a focus on the new IFs in the Sabah and Sarawak states of Malaysia. This study aims to improve the knowledge base and understanding of the extent and characteristics of new IFs as a new agent of LULCC, and to develop the methods for Landsat data, in particular by using forest fractional cover (fC) and vegetation indices (VIs) analyses in time series integrated with textural, spectral, visual, and other analyses to detect and quantify IF LULCC patterns and dynamics in the country.
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Results showed that the selected IFs-including acacia, rubber, and other IFs-have expanded quickly from 2000 to 2014 with a net increase of 288,547 ha at the annual mean rate of 20.1% in Sabah, and 459,898 ha at the annual mean rate of 59.9% in Sarawak. The annual mean expansion rate of faster-growing, shorter-rotation acacia IFs at 28.4% in Sabah and 376.5% in Sarawak was much faster than that of slower-growing, longer-rotation rubber IFs at 13.7% in Sabah and 5.8% in Sarawak, as well as other IFs at 10.9% in Sabah and 78.2% in Sarawak. The development of IFs in both states was primarily dominated by the larger scale holdings; however, the role of the small-scale IFs in developing new IFs in the region grew through an increase of its total area and rate of change in area. The expansion of IFs in Sabah and Sarawak significantly contributed to a LULCC in the regions. Most of these new IFs replaced disturbed natural forests (81--95%), followed by agricultural land (4--18%), and waste land (< 1%). These have caused a significant decline for the aboveground C stock in Sabah (11.5 Tg C) and Sarawak (24.7 Tg C), and resulted in an emission of 42.1 Tg CO2 in Sabah and 90.5 Tg CO2 in Sarawak over the period. The expansion of these new IFs had also led to a reduction in biodiversity in Sabah at 2.79--4.98% and in Sarawak at 2.77--4.96%. The results also showed a possibility of developing the fC and VIs-based methods in a time series for Landsat datasets that could detect and monitor the extent, pattern, and scale of IFs in the tropics. The accuracy for detecting the IF land using the fC-based method (with its producer's accuracy at 83% and Kappa coefficient at 0.46) was higher than that of the VIs-based method. Among VIs, ARVI worked the best with its producer's accuracy at 64% and Kappa coefficient at 0.4, followed by SAVI, SARVI, EVI, NDVIaf, and MSAVIaf. For both the fC-based method and the VIs-based method, the accuracy of detecting acacia and rubber IFs was better than that of other IFs in the region. In brief, this study successfully developed the fC- and VIs-based methods in multi-dated Landsat data to detect and quantify IF LULCC.
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