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

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

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

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

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

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

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.

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

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

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

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/6: Agriculture, Ecosystems and Bio-Diversity]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: ESTIMATION OF VEGETATION HEIGHT THROUGH SATELLITE IMAGE TEXTURE ANALYSIS Z. I. Petrou, C. Tarantino, M. Adamo, P. Blonda, M. Petrou

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia ESTIMATION OF VEGETATION HEIGHT THROUGH SATELLITE IMAGE TEXTURE ANALYSIS Z. I. Petrou?^", C. Tarantino^, M. Adamo“, P. Blonda®, M. Petrou® aDepartment of Electrical and Electronic Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom - z.petroul0 @imperial.ac.uk Information Technologies Institute, P.O.Box 60361, 6th km Harilaou - Thermi, 57001, Thessaloniki, Greece - (zpetrou, petrou) @iti.gr ‘Institute for Studies on Intelligent System for Automation (ISSIA), National Research Council (CNR), Via Amendola 122/D-O 70126, Bari, Italy. - (tarantino, adamo, blonda) @ba.issa.cnr.it KEY WORDS: Texture analysis, land cover, vegetation classification, Quickbird, mapping ABSTRACT: Vegetation height plays a crucial role in various ecological and environmental applications, such as biodiversity assessment and monitoring, landscape characterization, conservation planning and disaster management. Its estimation is traditionally based on in situ measurements or airborne Light Detection And Ranging (LiDAR) sensors. However, such methods are often proven insufficient in covering large area landscapes due to high demands in cost, labor and time. Considering a multispectral image from a passive satellite sensor as the only available source of information, we propose and evaluate new ways of discriminating vegetated habitat species according to their height, through calculation of texture analysis measures, based on local variance, entropy and local binary patterns. The methodology is applied in a Quickbird image of Le Cesine protected site, Italy. The proposed methods are proven particularly effective in discriminating low and mid phanerophytes from tall phanerophytes, having a height of less and more than 2 meters, respectively. The results indicate a promising alternative in vegetation height estimation when in situ or LiDAR data are not available or affordable, thus facilitating and reducing the cost of ecological monitoring and environmental sustainability planning tasks. 1 INTRODUCTION Estimation of canopy structure and vegetation height is funda- mental for a series of ecological studies, including biodiversity monitoring, conservation planning, fire modeling and biomass es- timation (Hyde et al., 2006, Dong and Wu, 2008). In addition, in various landscape mapping applications, certain land cover and habitat categories are discriminated based on their height, thus its measurement is of fundamental importance. Characteristic ex- amples of such categories are included in the Land Cover Clas- sification System (LCCS), proposed by the Food and Agricul- ture Organization of the United Nations (Di Gregorio and Jansen, 1998), and the General Habitat Categories (Bunce et al., 2008), for land cover and habitat mapping, respectively, both adopted by the BIO_SOS (BIOdiversity Multi-Source Monitoring System: from Space To Species) European project, concerned with biodi- versity monitoring. Numerous studies have been proposed in the literature on vegeta- tion height measurement through field campaigns with hand-held devices (Payero et al., 2004, Weltz et al., 1994, Buckley et al., 1999), considered as the most accurate approach. In cases where in situ measurements were not available or possible, LIDAR data, mainly from airborne sensors, have been recorded as the most ef- ficient alternative (Nilsson, 1996, Kwak et al., 2007, Dubayah et al., 2010, Lefsky et al., 2005). Airborne Synthetic Aperture Radar (SAR) data have also been used to a lesser extent (Praks et al., 2009). However, such methods provide coverage to a re- stricted spatial extent and can be particularly expensive and time and labor demanding. Satellite data, on the other hand, mainly from passive sensors, providing a large area coverage often at a reasonable cost, seem to constitute a rational potential alternative. Different studies have been conducted recently, trying to investigate potential correla- tion of the spectral characteristics of areas captured in satellite —À———— "Corresponding author. E-mail: z.petrou10 Q imperial.ac.uk. images with their vegetation height, usually in a synergy with airborne LiDAR data. Stojanova et al. (2010) calculated statistic measures in the segments of Landsat imagery and, together with LiDAR, tried to extract vegetation height in a Slovenian forested area. Various vegetation indices were calculated from Landsat data by Dong and Wu (2008) and, in combination with LiDAR satellite data, were used to estimate vegetation height in a moun- tainous protected region in China. Similar vegetation indices from Landsat were used by Yanhong ef al. (2010) to approxi- mate height in a Chinese inland river basin. Hyde ef al. (2006) used airborne LiDAR and SAR and satellite Landsat and Quick- bird data and compared their potential in height estimation in a forested site in USA. LiDAR clearly outperformed all other sin- gle sensors in height estimation accuracy; when data from other sensors, especially Landsat, were combined with LiDAR, the re- sults were further improved. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor have also been used recently for large area vegetation height estimation in forests of USA and Costa Rica (Wang et al., 2011). In all the aforementioned studies, where data from passive sen- sors were used, only reflectance-based characteristics were em- ployed. In this paper, we introduce the use of textural charac- teristics in vegetation height estimation through passive satellite sensors. Textural characteristics are expected to reveal spatial structural properties of the studied areas. The main idea behind this approach is the fact that in areas with short and shrubby vege- tation the texture of the image appears more homogeneous than in areas with high vegetation, where vegetation canopy, tree trunks and bare ground alternate, making the texture variant and inho- mogeneous. Different texture measures are proposed and evalu- ated as far as their efficiency in discriminating habitat types based on their vegetation height, is regarded. In particular, the discrimi- nation of low and mid from tall phanerophyte habitats, according to the GHC scheme, is regarded. In addition, extended in situ measurements and LiDAR data are

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