Paper5 - Canopy 3D 3 Mangroveand Ecosystem Structure...

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61 3 Mangrove Canopy 3D Structure and Ecosystem Productivity Using Active Remote Sensing* Marc Simard, Lola E. Fatoyinbo, and Naiara Pinto CONTENTS 3.1 Introduction ................................................................................................ 3.2 Active Remote Sensing ............................................................................... 62 3.3 Measurement of Vegetation Structure ........................................................ 65 3.4 Field Data .................................................................................................... 65 3.5 Combining Radar and LiDAR to Estimate Canopy Height and Biomass .. 67 3.6 Using LiDAR to Estimate Tree Height Class Distribution ......................... 71 3.7 Estimating Ecosystem Productivity ............................................................ 73 3.8 Conclusions ................................................................................................. 76 Acknowledgments ................................................................................................ 76 References ............................................................................................................ 76 3.1 INTRODUCTION Mangrove forests are the dominant coastal ecosystem in tropical and subtropical regions. They form an important link between aquatic and terrestrial ecosystems and are the most productive aquatic ecosystem with a primary productivity of 2.5 g ±carbon/m 2 per day [1]. Mangrove litter provides large amounts of carbon (C) to coastal and offshore marine ecosystems and contributes over 10% of the dissolved organic C (DOC) to ocean sediments worldwide [2]. Mangroves also protect coastal areas from wave action, erosion, storms, and tidal waves. Despite their known bene² ts as coastal buffers and biodiversity harbors, mangrove areas are being altered and destroyed by anthropogenic impacts and their cover has decreased by 35% in the past 20 years [3]. Because of their ecological and economic importance, mangrove forests have been * Copyright © 2009 by the Jet Propulsion Laboratory, Pasadena, CA. Published with permission. Q1 94416_C003.indd 61 94416_C003.indd 61 6/16/2009 8:09:10 PM 6/16/2009 8:09:10 PM
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62 Remote Sensing of Coastal Environments estimated at 200,000–900,000 USD/km 2 per year by the United Nations Environment Programme World Conservation Monitoring Center [4]. Remotely sensed images provide an efF cient and cost-effective way to gain insight into mangrove areas that are often difF cult to access and survey [5–11]. Both optical and active remote sensing techniques have been commonly used to study mangrove forests, and in the past years the combination of radar (RAdio Detection And Ranging) and LiDAR (Light Detection And Ranging) has yielded interesting results that reach further than determining mangrove cover alone. Generally, optical remote sensing instruments such as Landsat, MODIS, and SPOT measure the color of forests and thus are often considered more intuitive. To this day, mangrove forests have also been studied using polarimetric and interferometric radar and airborne and space-borne LiDAR systems. Several studies were carried out using radar data for mangrove map- ping and monitoring [12]. In addition, three-dimensional (3D) modeling of mangrove forests was made possible by the Shuttle Radar Topography Mission (SRTM) data. The 3D rendition was validated with airborne and space-borne LiDAR and F eld data to provide large-scale height and biomass estimates of mangrove forests [9–11].
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Paper5 - Canopy 3D 3 Mangroveand Ecosystem Structure...

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