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Land change history of oil palm plantations in northern Bengkulu Province, Sumatra Island, reconstructed from Landsat satellite archives.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Land change history of oil palm plantations in northern Bengkulu Province, Sumatra Island, reconstructed from Landsat satellite archives./
Author:	Tomita, Atsushi.
Description:	1 online resource (232 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-07(E), Section: B.
Subject:	Remote sensing. -
Online resource:	click for full text (PQDT)
ISBN:	9781369563290

Land change history of oil palm plantations in northern Bengkulu Province, Sumatra Island, reconstructed from Landsat satellite archives.
Tomita, Atsushi.

Land change history of oil palm plantations in northern Bengkulu Province, Sumatra Island, reconstructed from Landsat satellite archives. - 1 online resource (232 pages)

Source: Dissertation Abstracts International, Volume: 78-07(E), Section: B.

Thesis (Ph.D.)--City University of New York, 2017.

Includes bibliographical references

As of today, in the early twenty-first century, the Earth's surface has been largely exploited by human activities, which will have long-term effects on land cover and earth systems. However, precise knowledge of changes of the Earth's surface in many hotspots of land change is lacking. To fill this information gap, a method for monitoring land use changes is developed in this dissertation that uses multi-temporal satellite data to investigate the land conversion of oil palm plantation in tropical Asia, where oil palm plantations play a major role in drastic land changes and deforestation.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369563290Subjects--Topical Terms:

557272
Remote sensing.
Index Terms--Genre/Form:

554714
Electronic books.

Land change history of oil palm plantations in northern Bengkulu Province, Sumatra Island, reconstructed from Landsat satellite archives.
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100 1 $a Tomita, Atsushi. $3 1188978
245 1 0 $a Land change history of oil palm plantations in northern Bengkulu Province, Sumatra Island, reconstructed from Landsat satellite archives.
264 0 $c 2017
300 $a 1 online resource (232 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-07(E), Section: B.
500 $a Adviser: Ines M. Miyares.
502 $a Thesis (Ph.D.)--City University of New York, 2017.
504 $a Includes bibliographical references
520 $a As of today, in the early twenty-first century, the Earth's surface has been largely exploited by human activities, which will have long-term effects on land cover and earth systems. However, precise knowledge of changes of the Earth's surface in many hotspots of land change is lacking. To fill this information gap, a method for monitoring land use changes is developed in this dissertation that uses multi-temporal satellite data to investigate the land conversion of oil palm plantation in tropical Asia, where oil palm plantations play a major role in drastic land changes and deforestation.
520 $a The booming oil palm plantation industry in tropical Asia is transforming both preexisting natural landscapes and landscapes affected by human activity into a wide-spread monoculture landscape. This drastic change will cause serious environmental degradation and have long-term impacts on local socioeconomics and land use. To grasp the process of land transformation, it is important to understand the roles of the local factors that are physically, economically and societally embedded at various spatial and temporal scales.
520 $a Because most oil palm plantations have developed in tropical Asia, this area is an ideal test site for investigating the outcomes of land use changes, such as the co-evolutionary development of land in favor of oil palm plantations, land use conflicts and environmental concerns. Consequently, a satellite remote sensing method was developed in this study that could provide reliable spatio-temporal knowledge of land use and land cover changes at fine scales.
520 $a The selected study area is located in the northern part of Bengkulu Province on Sumatra Island, where natural landscapes and landscapes affected by human activity have widely been transformed to oil palm plantations since the late 1980s, which coincides with the first available regular Landsat satellite observations. Although spectral information of the land surface has been continuously recorded by the Landsat satellites since the 1980s, the availability and quality of the data were reduced by cloud cover and other atmospheric disturbances. A comprehensive, cloud-free Landsat dataset was created from all the available Landsat data from 1988 to 2015. The pixel-based dataset was converted into a polygon-based dataset by applying the multi-temporal image segmentation method. The representation of the spectral information was also reduced to a single index of IB45 (Index derived from Band4 and Band5), the ratio of the near-infrared (Band 4) to mid-infrared (Band 5) bands, which was the most suitable index for detecting and tracking the transformation of land to oil palm plantation.
520 $a To extract (or segment) targeted land changes and land uses from a given temporal profile predicted by land change scenarios, an extended concept of segmentation was applied to develop a Land Change Detection Model (LCM). The segmented profiles were then evaluated by using bio-physical metrics in the Land Definition Model (LDM) to define the land uses. The two-tiered LC/LD Model could detect not only large-scale land changes caused by private companies but also small-scale changes caused by smallholders, which is supposedly the most uncertain factor for considering the future development of oil palm development at high spatio-temporal resolutions.
520 $a Relationships between local factors and two land change phenomena, the conversion to oil palm plantations and deforestation, have been investigated using quantitative assessments such as Logistic Regression analysis. The results indicated that large sized plantation enterprises were likely to directly convert untouched natural land and are consequently the main contributor to deforestation. In contrast, smallholders mainly converted preexisting farmland to oil palm plantations. The enterprise (private companies) and smallholder plantations had very different spatial and temporal characteristics. The enterprise plantations were densely and homogeneously packed within extensive and regular shaped boundaries. Because all the land conversion occurred during a short period, the plants all had similar ages. Few connections have been detected between local variables and the development of the enterprise plantations. Smallholder developments were very spatially and temporally inhomogeneous. Some local factors that represent the 'proximity of development', such as the pre-existence of nearby oil palm plantations and mills, were strongly correlated with smallholder development along with geographical factors.
520 $a The results underwrote the assumption that mills were the major local driver of oil palm development. In addition, the results strongly indicated that oil palm development had resulted in the construction of independent mills, whose locations and dates of construction were strongly connected to the profitability resulting from receiving a sufficient supply of fresh oil palm fruit bunches. Regardless of whether plantations were formed by enterprises or independently, most mills were constructed on land previously affected by humans as of the late 1980s, and all the initial development of enterprise plantations occurred in the forest . This result strongly implied that, given the locations of pristine forests, the cultivation of land and infrastructure development, such as mill construction, strongly favored oil palm development in the northern region of Bengkulu Province, which clearly contrasts the underdevelopment in the southern part of the province.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Remote sensing. $3 557272
650 4 $a Environmental studies. $3 1180247
650 4 $a Plant sciences. $3 1179743
650 4 $a Geography. $3 654331
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710 2 $a City University of New York. $b Earth & Environmental Sciences. $3 1188979
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