Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)

It is estimated that most of the problems in forestry associated with the spatial attributes.    From the perspective of forest function that includes production, ecological, and social functions, the spatial aspects has always been a very important part. In Indonesia, the forestry areas is always d...

Full description

Bibliographic Details
Main Author: I Nengah Surati Jaya
Format: Article
Language:English
Published: Bogor Agricultural University 2014-04-01
Series:Jurnal Manajemen Hutan Tropika
Online Access:http://journal.ipb.ac.id/index.php/jmht/article/view/7932
id doaj-a7556e82f44246db8b7670c1badd9bb2
record_format Article
spelling doaj-a7556e82f44246db8b7670c1badd9bb22020-11-25T02:31:42ZengBogor Agricultural UniversityJurnal Manajemen Hutan Tropika2087-04692089-20632014-04-0120110.7226/jmht.20.1.666821Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)I Nengah Surati Jaya0Department of Forest Management, Faculty of Forestry, Bogor Agricultural University, Academic Ring Road, Campus IPB Dramaga, PO Box 168, Bogor, Indonesia 16680It is estimated that most of the problems in forestry associated with the spatial attributes.    From the perspective of forest function that includes production, ecological, and social functions, the spatial aspects has always been a very important part. In Indonesia, the forestry areas is always dealing with very large areas which is mostly inaccessible due to limitation of roads, mountainous with steep slopes, cliffs, hills or wetland such as peat, swamp or marsh.  This condition makes it difficult to collect the data in quick manner comprehensively with low cost. Veronique et al. (2012) recognized that remote technology may provide objective, practical and cost-effective solution.   Currently, one of the most reliable data source that can be repetitively acquired with a unique and consistent traits are those derived from satellite imageries.  It had been known that since the 1990s, earth resources remote sensing sensor is progressively developed either with finer spatial resolution, higher spectral resolution, more frequent revisit or wider dynamic range.   The advent of high spectral resolution (e.g. hyperspectral) is quite challenging and prospectively gives a significant contribution, especially in forest management with higher level of detailed information.  Without having adequate spatial information supported by strong scientific arguments, the forestry sector will be persistently pressured by many other sectors.http://journal.ipb.ac.id/index.php/jmht/article/view/7932
collection DOAJ
language English
format Article
sources DOAJ
author I Nengah Surati Jaya
spellingShingle I Nengah Surati Jaya
Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)
Jurnal Manajemen Hutan Tropika
author_facet I Nengah Surati Jaya
author_sort I Nengah Surati Jaya
title Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)
title_short Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)
title_full Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)
title_fullStr Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)
title_full_unstemmed Hyper Spectral Remote Sensing of Tropical and Sub-Tropical Forest (Editors: Margaret Kalacsca & G. Arturo Sances–Publisher: Azofeita CRC Press, Year 2008, 320 pages)
title_sort hyper spectral remote sensing of tropical and sub-tropical forest (editors: margaret kalacsca & g. arturo sances–publisher: azofeita crc press, year 2008, 320 pages)
publisher Bogor Agricultural University
series Jurnal Manajemen Hutan Tropika
issn 2087-0469
2089-2063
publishDate 2014-04-01
description It is estimated that most of the problems in forestry associated with the spatial attributes.    From the perspective of forest function that includes production, ecological, and social functions, the spatial aspects has always been a very important part. In Indonesia, the forestry areas is always dealing with very large areas which is mostly inaccessible due to limitation of roads, mountainous with steep slopes, cliffs, hills or wetland such as peat, swamp or marsh.  This condition makes it difficult to collect the data in quick manner comprehensively with low cost. Veronique et al. (2012) recognized that remote technology may provide objective, practical and cost-effective solution.   Currently, one of the most reliable data source that can be repetitively acquired with a unique and consistent traits are those derived from satellite imageries.  It had been known that since the 1990s, earth resources remote sensing sensor is progressively developed either with finer spatial resolution, higher spectral resolution, more frequent revisit or wider dynamic range.   The advent of high spectral resolution (e.g. hyperspectral) is quite challenging and prospectively gives a significant contribution, especially in forest management with higher level of detailed information.  Without having adequate spatial information supported by strong scientific arguments, the forestry sector will be persistently pressured by many other sectors.
url http://journal.ipb.ac.id/index.php/jmht/article/view/7932
work_keys_str_mv AT inengahsuratijaya hyperspectralremotesensingoftropicalandsubtropicalforesteditorsmargaretkalacscagarturosancespublisherazofeitacrcpressyear2008320pages
_version_ 1724822688273268736