Mapping seagrass and seaweed Mapping seagrass and seaweed beds in NOWPAP Teruhisa Komatsu Atmosphere and Ocean Research Institute, The University of Tokyo Contents What is “coastal habitat”? Important ecological roles of coastal habitats Mapping methods of coastal habitats Direct and indirect methods Mapping by remote sensing Introduction of seagrass mapping What is habitat? What is habitat? Habitat is similar to biotope or biome: An area that is uniform in environmental An area that is uniform in environmental conditions and in its distribution of animals and plants. plants On land, forests, meadows and marshes are habitats They are called ecological engineers. habitats. They are called ecological engineers What habitats exist in the sea? Seaweed and seagrass beds Seaweed and seagrass beds Z t Zostera marina i Sargassum horneri Zostera caulescens Ecosystem services of habitats y • • • • • • • • • • • Gas regulation Climate regulation Disturbance regulation Erosion control and sediment retention Nutrient cycling W t t t Waste treatment t Refugia (spawning and nursery grounds ) Food production Food production Genetic resources Recreation Cultural Costanza et al. (1997) Ecological services of coastal biomes in the world Ecological services of coastal biomes in the world Biome Area (ha) Total value per ha Total value per ha Total global flow Total global flow value($yr‐1 x109) ($ha‐1 yr‐1) Estuaries Estuaries 180 180 22,832 22,832 4,110 4,110 Seagrass/seaweed beds 200 19,004 3,801 62 6,075 375 2,660 1,610 4,283 165 9,990 1,648 Total coastal biome 3,267 4,352 14,217 T i lf Tropical forest t 1 900 1,900 2 007 2,007 3 813 3,813 Temperate/boreal forests 2,955 302 894 Total forest biome forest biome 4 855 4,855 970 970 4 707 4,707 Coral reefs Shelf Tidal marsh/mangroves Constanza et al. (1997) Coastal habitats at risk Agricultural pollution Reclamation l i in i Seto S Inland Sea around 1960s Industrial pollution Seagrass beds in Seto Inland Sea Amelioration of water quality in Seto Inland Sea Komatsu (1997) Long‐term changes in the Zostera bed area in the Seto Inland Sea (Japan), especially along the coast of the Okayama Prefecture, Oceanologica. Acta, 20, 209‐216. Law on Environmental Conservation of the Seto Inland Sea Cumulative reclamation and Zostera marina Cumulative reclamation and Zostera Komatsu (1997) Long‐term changes in the Zostera bed area in the Seto Inland Sea (Japan), especially along the coast of the Okayama Prefecture, Oceanologica. Acta, 20, 209‐216. Counter measure against trawls in seagrass meadows in Okayama Prefecture, Japan Deployment of artificial reefs and columns obstructing trawl operation Deployment of artificial reefs and columns obstructing trawl operation inside the seagrass beds of Ajino Bay in 1976 Deployment Komatsu (1997) Long‐term changes in the Zostera bed area in the Seto Inland Sea (Japan), especially along the coast of the Okayama Prefecture, Oceanologica. Acta, 20, 209‐216. Management of coastal habitats • Monitoring of habitat distributions Monitoring of habitat distributions • Protection of habitat areas • Restoration of habitats Mapping coastal habitats is indispensable for sustainable use of coastal resources Mapping coastal habitats by direct and indirect surveys direct and indirect surveys Direct methods • • • • Walkingg Diving Observation from the ship p Grabbing bottom sediments Direct methods (ground survey) Characteristics density estimation, estimation species identification assured method Problems low efficiency influence of turbidity of water and high waves on field survey Mapping of habitats by indirect methods th d • Acoustics • Optics (satellite remote sensing) Optical methods Optical methods Introduction of seagrass mapping Lyzenga’s Model Sun Esun Lsi Li Satellite Sea surface Deep D water Bottom surface Ri Ki Z Li = Lsi + Ai・ Ai・Ri Ri・ ・exp exp((‐Ki Ki・ ・F・Z) (W/m2/sr sr)) (Lyzenga 1978) Lyzenga (1978, 1981) (1978 1981) Depth‐invariant Index (DII) • DII = ln( Li‐Lsi ( ))‐[( Ki/Kj [( / j ))ln( Lj‐Lsj ( j j )] )] DII = ln( Ai Ri l ( i i )‐( Ki/Kj ) ( i/ j )ln( Aj )l ( j Rjj ) ) assuming g that Ki/Kj=1 j DII = c + ln (Ri/Rj) Lyzenga’s model: Li = Lsi + Ai・ Ai・Ri Ri・ ・exp( exp(‐ ‐Ki Ki・ ・f・Z) Sagawa et al. (2010) g ( ) International Journal of Remote Sensing, 31, 3051‐3064 Reflectance Index (RI) • RI = ( Li ‐Lsi )/( exp( ‐Ki・f・Z ) ) RI = Ai・Ri Lyzenga’s model: Li Lyzenga’s model: Li = Lsi + Ai・ = Lsi + Ai・Ri Ri・ ・exp(‐Ki exp(‐Ki・ ・f・Z) Example of attenuation coeeficient F=2.18 K= 0.093 m‐1 J l W Jerlov Water Type Ⅱ‐Ⅲ T ⅡⅢ R l ti b t Relation between depth d th and radiance (green band) d di ( b d) Lyzenga’s model: Li Li == Lsi + Ai・Ri・exp exp(‐ (‐Ki Ki・F・Z) (W/m2/sr ) (W/m2/sr)) DI Index 誤差行列（Error matrix） 全体の精度（Overall accuracy） = 54 % Sagawa et al. (2010) International Journal of Remote Sensing, 31, 3051‐3064 BR Index Sagawa et al. (2010) International Journal of Remote Sensing, 31, 3051‐3064 Mahares ¾ Overall accuracy DI)（％） （DI) （％） Overall accuracy (BR）（％） (BR ）（％） ＪＷＴ 54.0 90.0 Ⅱ－Ⅲ Classification with BR Idex is more correct than DI Index （p < 0.05) Sensors A i l photography Aerial h h Launch of Landsat satellite (1972) Sensors with spatial resolution (30~100 m) were most widely used (e.g. Landsat Multispectral Scanner, Landsat TM) long-time series/inexpensive data Sensors with better spatial p resolution <10 m (e.g. IKONOS, SPOT, Worldview 2, Geo Eye etc) better spectral & spatial versatility/extremely expensive data Launch of ALOS (2006) and stop in April 2011 AVNIR-2 AVNIR 2 resolution: spatial (10 m)/multispectral (420~890nm)/radiometric (8 bits) Characteristics of Landsat TM Characteristics of Landsat TM Band no. Spectral range (µm) Spatial resolution (m) 1 0.45 - 0.52 30 2 0.52 - 0.60 30 3 0.63 - 0.69 30 4 0.76 - 0.90 30 5 1, 1.55 -41.75 30 to those Bands 1 2, 2 3 and are nearly equivalent 6 10.4 - 12.5 120 of ALOS. 2 08 2.08 - 2.35 2 35 30 We 7can analyze time series data consisting of LANDSAT TM and ALOS from 1972 to 2011. Characteristics of AVNIR 2 sensor Characteristics of AVNIR‐2 sensor Swath Width Spatial Resolution Wavelength Quantization 70 km ( at nadir) 10 m (at nadir) Band 1: 0.42 – 0.50 µm (visible blue) Band 2: 0.52 – 0.60 µm (visible green) Band 3: 0.61 – 0.69 µm (visible red) Band 4: 00.76 76 – 0.89 0 89 µm m (near infrared) 8 bits We can compare habitat distributions between images of ALOS AVNIR‐2 and LANDSAT g Study Area Sibu Island, Johor Malaysia Raw ALOS AVNIR‐2 Image (29 J l 2008 11:54 am) (29 July 2008 ‐ 11 54 ) Change off corall reeff tto Sargassum Ch S beds from 2005 to 2008 Comparison C i result lt off ALOS (2008) and d LANDSAT ((2005)) over Sibu Island Detection of succession from live coral to Sargassum forest Courtesy of Prof. Ibrahim Seeni at UTM, Malaysia 28 Tentative proposal to NOWPAP Tentative proposal to NOWPAP • TTemporal changes in spatial distributions of l h i ti l di t ib ti f seaweed and seagrass beds with relation to environmental changes such as eutrophication or environmental changes such as eutrophication or reclamation • Focusing on changes in not only distributions of seagrass and seaweed beds but also land use seagrass and seaweed beds but also land use • Selection Selection of test sites, where they are distributed of test sites where they are distributed broadly, with time series data of environmental p parameters Thank you very much for your attention!
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