XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Type of content:: Konferenzschrift

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Reihe:: ISPRS archives

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Editor:: International Society for Photogrammetry and Remote Sensing

Author:: International Society for Photogrammetry and Remote Sensing, 22.; 2012; Melbourne

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Type of content:: Konferenzschrift

DOI:: 10.14463/KXP:1663822514

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Reihe:: ISPRS archives (volume 39, B8 (2012))

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Editor:: International Society for Photogrammetry and Remote Sensing

Author:: International Society for Photogrammetry and Remote Sensing, 22.; 2012; Melbourne

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/7: Forestry]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: AN INTERCOMPARISON OF PASSIVE TERRESTRIAL REMOTE SENSING TECHNOLOGIES TO DERIVE LAI AND CANOPY COVER METRICS W. L. Woodgate

Document type:: Multivolume work

Structure type:: Chapter

Verstraete, M., ency of three- ai lidar. Remote 1., Constant, T., . from terrestrial ne Beech trees ^ International y. sen, K., 2001. able probability Biological and , N.-W., 2010. he development ser 2010, 10° burg, Germany. processing to ings of the 10^ computing and etherlands. r-scanned trees dings of ISPRS rt B5, Istanbul, Schipperijn, J., 3ook, Springer, on of trees with ning. Journal of )08. chemistry — a he geoscientific ept of modern pment of planet search, 16, pp. )04. Automatic er scanner data. Comm. V, Vol. g of tree cross with free-form up VIII/2, Vol. ermany, pp. 76- , Kaartinen, H., » distribution of RS workshop Canada. Knowledge and trees. ACM ying allometric d Management, AN INTERCOMPARISON OF PASSIVE TERRESTRIAL REMOTE SENSING TECHNOLOGIES TO DERIVE LAI AND CANOPY COVER METRICS W. L. Woodgate Dept. of Infrastructure Engineering, The University of Melbourne, Australia — w.woodgate@pgrad.unimelb.edu.au Technical Commission VIII, WG 7 (Forestry) KEY WORDS: LIDAR, Forestry, Sustainable, Multisensor, Scale, Terrestrial ABSTRACT: Forest indicators such as Leaf Area Index (LAI) and vegetation cover type are recognised as Essential Climate Variables (ECVs) which € support the ...research, modelling, analysis, and capacity-building activities... , requirements of the United Nations Framework Convention on Climate Change. This research compares the use of passive terrestrial remote sensing technologies for LAI and canopy cover metrics. The passive sensors used are the LAI-2200 and Digital Hemispherical Photography (DHP). The research was conducted at a Victorian reference site containing tree species with predominantly erectophile leaf angle distributions, which are significantly under- represented in the literature. The reference site contributes to a network of sites representative of Victorian land systems and is considered to be in good condition. Preliminary results indicate a low correlation (R’=0.46) between the LAI-2200 and DHP. Further comparisons to be conducted include adding a passive CI-110 plant canopy analyser and an active Terrestrial Laser Scanner. The future objective is to scale the in situ data to aerial and satellite remotely sensed datasets. The aerial remotely sensed data include LiDAR flown by a Riegl LMS Q560, and high resolution multispectral and hyperspectral imagery flown by the ASIA Eagle and Hawk system. The in situ data can be utilised for both calibration and validation of the coincident aerial imagery and LiDAR. Finally, the derived datasets are intended for use to validate the global MODIS LAI product. 1. INTRODUCTION Sustainable forest management is fundamental to the preservation of biodiversity and mitigation of climate change (Garnaut, 2008; Lanly, 1995). Delineating criteria and indicators that provide valuable information on forests are important to assist sustainable forest management (Raison et al, 1998). Leaf Area Index (LAI) has been recognised as a key forest indicator and is one of the Essential Climate Variables Which support the ‘...research, modelling, analysis, and capacity-building activities...” requirements of the United Nations Framework Convention on Climate Change (UNFCCC) (GCOS, 2010). Another key forest indicator is canopy cover which is a primary requirement for the definition of forest as recognised by the United Nations Food and Agricultural Organisation (FAO) (FAO, 2010). LAI is a quantitative measure of the amount of leaf tissue in the canopy per unit of ground area (GTOS, 2009). It is broadly defined as ‘leaf area per unit area of land’ (Watson, 1947). LAI is a non-dimensional measurement, but is usually quantified as m’ of leaf area per m” of ground area. (Running ef al., 1986) identified LAI as ‘the single variable both amenable to measurement by satellite and of greatest importance for quantifying energy and mass exchange by plant canopies over landscapes’. ‘Canopy cover refers to the proportion of the forest floor covered by the vertical projection of the tree crowns’ (Jennings et al, 1999). Canopy cover and variations of cover such as Foliage Projective Cover (FPC) provide a useful measure of the amount and distribution of foliage and allow for analysis at a number of spatial scales (White ef al., 2000). Remote sensing technologies can be utilised to indirectly derive both LAI and canopy cover metrics. Remote sensing technologies enable the landscape to be analysed at multiple scales from ground, airborne and spaceborne platforms (Zheng & Moskal, 2009). The technologies can categorise their sensors as being either passive or active. Terrestrial remote sensing technologies used to derive LAI and canopy cover metrics are important for calibration and validation of datasets derived from the airborne and spaceborne platforms (Baret, 2007; Morrisette, 2006). Passive sensors, such as imagery, can only detect energy when naturally occurring energy exists (Zheng & Moskal, 2009). Whereas active sensors, such as LiDAR, emit their own energy source and record the energy returned from objects of interest (Zheng & Moskal, 2009). The advantage of an active sensor over a passive sensor is that it is independent of the naturally occurring energy in the environment. Active sensors are not limited in their time of operation by environmental conditions such as the amount of sunlight available. Terrestrial remote sensing technologies such as Digital Hemispherical Photography (DHP), ceptometers and Terrestrial Laser Scanning (TLS) are utilised to provide LAI and canopy cover at the in situ scale through gap fraction analysis (INRA, 2010; Zheng & Moskal, 2009). Gap fraction can be used to derive other metrics such as foliage mean tip angle (MTA), the fraction of absorbed photosynthetically active radiation (FAPAR) and the fraction of vegetation cover (FCOVER)

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