Paolo Villa, Monica Pinardi, Mariano Bresciani CNR-IREA ...

18
User Uptake Workshop 16-17 November 2017 European Environment Agency, Copenhagen, Denmark Paolo Villa, Monica Pinardi, Mariano Bresciani CNR-IREA ([email protected]) Macrophytes products

Transcript of Paolo Villa, Monica Pinardi, Mariano Bresciani CNR-IREA ...

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Paolo Villa, Monica Pinardi, Mariano Bresciani CNR-IREA ([email protected])

Macrophytes products

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• Aquatic vegetation, or macrophytes, fulfil a pivotal role in biogeochemical cycles.

• Synoptic capabilities of EO data make them a powerful tool for monitoring macrophyte characteristics and functionality

• Spectral and temporal features of different macrophytes used for producing maps of community type and bio-physical parameters

Introduction

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• Helophytes: Phragmites australis, Typha angustifolia

• Emergent rhizophytes: Nelumbo nucifera

• Floating-leaved: Nymphaea alba, Nuphar lutea, Trapa natans, Ludwigia hexapetala,

• Free-floating: Spirodela polyrrhiza, Lemna minor, Salvinia natans, Azolla caroliniana

• Submerged: Ceratophyllum demersum, Myriophyllum spicatum, Najas marina marina, Vallisneria spiralis

Target species Emer

gent

he

loph

ytes

P. australis (KB)

P. australis (M)

P. australis (M)

T. angustifol. (KB)

Emer

gent

m

acro

phyt

es

N. nucifera (M)

N. nucifera (M)

N. nucifera (M)

Floa

ting

mac

roph

ytes

N. alba (KB)

N. alba (M)

N. lutea (M)

N. lutea (M)

P. natans (KB)

T. natans (KB)

T. natans (KB)

T. natans (KB)

T. natans (M)

T. natans (M)

Floa

ting

mac

roph

ytes

i

ti

N. alba + N. lutea

(KB)

N. alba + N. lutea

(KB)

Subm

erge

d-Fl

oatin

g h

t

C. demersum + N.

lutea (KB)

C. demersum + N.

lutea (KB)

C. demersum + T.

natans (M)

C. demersum + L.

minor (M)

C. demersum + L

minor (M)

Subm

erge

d m

acro

phyt

es

C. demersum (KB)

N. marina (KB)

N. marina (KB)

U. vulgaris (KB)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• Classification approach – EO data: Landsat TM, ETM+, OLI – Case study: Mantua lakes, Kis Balaton wetland, Lake Trasimeno, Lake Taihu – Input: Multi-temporal WAVI features – Algo: Rule-based classification tree (C4.5) – Output: 4 macrophyte community types (H, ER, FM, SF) + 2 classes (TV, OW)

• Validation: – Overall Accuracy > 90% – Error higher than 20% for Submerged-floating association – Good, consistent performance (error < 20%) for all other groups/classes – Tested over different area (Lake Varese) and with different spectral data (ALOS

AVNIR-2)

Community type mapping

(Villa et al., 2015)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Lake Trasimeno (TM-ETM+, 2008)

Lake Taihu (OLI-ETM+, 2013)

Kis Balaton wetland (OLI-ETM+, 2014)

Mantua lakes (OLI, 2014)

Mantua lakes (AVNIR-2, 2010)

Lake Varese (OLI, 2014)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• Target canopy bio-physical parameters (BPs): – Fractional cover (fC) – Leaf area index (LAI) – Above-water biomass (kgdw m-2)

• EO data with different spectral resolution:

– Narrowband (APEX) – Broadband (OLI, S5T5, Sentinel-2)

Bio-physical parameters

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• Estimation approach: – Data: in situ canopy spectra, APEX data, multi-temporal S2A data (Mantua, Kis-

Balaton) – Algo: Semi-empirical regression modelling – Input: Best performing spectral index for each BP and each EO dataset – Output: maps of fC, LAI, AW biom

• Validation: – High reliability for fC and LAI products (R2>0.6)

Bias = -10%, MAPE = 13% for fC Bias = -0.19, MAPE = 19% for LAI

– Medium reliability for AW biom (R2 = 0.35) Bias = -0.04 kgdw m-2, MAPE = 34% (underestimation of high biomass)

Macrophyte BPs mapping

(Villa et al., 2017)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Kis-Balaton wetland (19 July 2014)

Detail on Kányavár island area

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Mantua lakes,

early growth (biomass)

(22 May 2016)

Mantua lakes growth peak (biomass) (28 July 2016)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

(inter) Seasonal differences

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• Estimation approach: – Data: in situ canopy spectra, 2015 yearly L8 - S5T5 - S2A data (Mantua, Grand

Lieu), 2016 data for S2A (Mantua) – Algo: Semi-empirical regression modelling for LAI estimation, TIMESAT for time

series analysis – Input: Best performing spectral index for S5T5 broadband data – Output: Time series of macrophyte LAI, macrophyte phenology parameters (SoS,

PoS, EoS, growth/senescence rate)

• Validation: – High reliability for LAI time series (R2>0.8)

Bias = -0.04, MAPE = 10% (underestimation of high density)

(intra-) Seasonal dynamics

(Villa et al., under review)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Mantua lakes - Phenology maps (2015 growing season)

(Villa et al., under review)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Lac de Grand Lieu- Phenology maps (2015 growing season)

(Villa et al., under review)

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

• New generation EO data can reliably provide spatial and temporal information about macrophytes, by mapping: – community types – bio-physical parameters – seasonal dynamics (phenology)

• Scale of detail can vary between 5 m (airborne, VHR spaceborne) and 20-30 m (operational spaceborne platforms) spatial grid resolution.

• Performance is lower for submerged vegetation (esp. in turbid systems) and for high density beds (tendency to underestimate fC and AW biom).

Conclusions

User Uptake Workshop

16-17 November 2017

European Environment Agency, Copenhagen, Denmark

Thank you for your attention