series to support REDD+ Supervisor : Pro f. Kunihiko Yoshino - - PowerPoint PPT Presentation

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series to support REDD+ Supervisor : Pro f. Kunihiko Yoshino - - PowerPoint PPT Presentation

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University of Tsukuba Graduate School of Life and Environmental Sciences Research topic Estimation of forest carbon stock in Thua Thien Hue Province, Viet Nam using MODIS EVI time series to support REDD+ Supervisor : Pro f. Kunihiko Yoshino

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University of Tsukuba Graduate School of Life and Environmental Sciences

Research topic Estimation of forest carbon stock in Thua Thien Hue Province, Viet Nam using MODIS EVI time series to support REDD+

Supervisor: Prof. Kunihiko Yoshino Presenter: Pham Thi Thanh ID: 201225028

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REDD +?

Global Environmental Degradation Urban development/LUC Climate change effects Economic growth Rapid growth population Deforestation & forest degradation Other causes

  • 1. Background

Source IPCC 2007

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What is REDD + ?

REDD Reducing Emission from

Deforestation and

Forest degradation

Conservation

+ = Sustainable

Management of Forest

Enhancement of Forest

Carbon Stocks

REDD+

  • 1. Background
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National REDD+ readiness Implementation

  • f REDD+

policies and measures Full scale REDD+ implementation

Phase 1: 2008 - 2012 Phase 2 2012 - 2015 Phase 3 from 2016 National REDD+ strategy

  • Complete legal frame work

related to land, financing, technical…

  • Basic MRV implementation

measures

  • Full MRV
  • Full scale

implementation and integrate to CC

REDD+ implementation

Key component

  • 1. Background
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  • 1. Background
  • Necessary for successful REDD+ machanism
  • Building RLs and RELs for CO2 mechanism
  • Mapping the potential for REDD+
  • Payment, reporting for verified performance

(How many % of CO2 emission or , removal)

  • Payment bases on types of forest

MRV

Source: UN-REDD

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  • 1. Background

Remote sensing is powerful tool for MRV Meet standards for REDD+

  • Acquire, Monitor, Update forest information

at large scales,

  • Estimate & assess vegetation biomass
  • Set a reference level/ Carbon credit

mechanism

  • Promote effective REDD+
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  • 1. Background

Why MODIS EVI?

  • RED and BLUE band (visible range): 0,4 – 0,7 μm
  • Near-infrared band: 0.7 – 1.3 μm
  • From visible to near-infrared (NIR)range: the

reflectance of healthy vegetation increases

  • In the range of NIR: plant leaf reflects 40-50% of the

energy , 8 layers of leaf in canopy, permit to discriminated between species (Hue., et all 1997)

C1 = 6 coefficent of resistance C2 = 7.5 L = 1 (the canopy background adjustment) G = 2.5 (gain factor)

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  • 1. Background

Previous studies

  • Have shown positive correlation between

vegetation indices: NDVI, RDVI, MSR, RVI, MSAVI, OSAVI with biomass (Das and Singh 2012)

  • Several studies with application RS to make forest

biomass carbon, make forest biodiversity

  • However, there was no report about forest

volume with specific types of forest with specific species

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  • 2. Hypothesis and Objectives

Hypothesis EVI has close correlation with carbon stock and its value is different in different forest Objectives

① To find the correlation between MODIS EVI、

forest volume and precipitation ② To evaluate accuracy of assessment forest volume by using RS ③ To discuss availability of MODIS EVI to MRV

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  • Hue 16 40 N, 107 68 E, 55

feet (17 meters) above sea level

  • Lowland rain forest
  • Natural forest

(evergreen forest, deciduous forest)

  • 3. Study site
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  • 3. Outline of study site

Forest issue in Hue

  • Many strength points about forest

+ Forest cover 56,7% (natural forest 202.600 ha, plantation forest 92 000

ha)

+ Participate Payment Environmental Service (REDD+ (2016))

  • Remain many problems:

+ New and complex issue + Forest inventory data is expensive, difficult to update forest

information as REDD + require

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  • 4. Materials and Methods
  • MODIS EVI 16 days satellite data in 2011

(from internet)

ftp://e4ftl01u.ecs.nasa.gov/MOLT/MOD13Q1.005/

  • Forest volume data (field inventory)

(from Department of Forestry, Agriculture Planning and Projection, Hue)

  • Precipitation in 2011

(from: The Vietnam Institute of Meteorology, Hydrology and Environment )

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  • 4. Materials and Methods

MODIS 16 days (2011) MODIS EVI 16 days (2011) Layer stacking MODIS EVI (2011) Wavelet transform to reduce noise Reconstruct

Collect Field survey data Analyze EVI signal

Find correlation between EVI & Forest Volume & precipitation in different type

  • f forest

Assess Accuracy Carbon map

Data processing flow chart

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  • 5. Results

y = 199.77x - 62.315 R² = 0.8174 35 45 55 65 75 85 95

0.5 0.7 0.9

Forest volume (m3/ha) AverageEVI

EVI Linear (EVI)

y = 310.76x - 200.34 R² = 0.675 25 30 35 40 45 50 55 60 65 70 75 0.7 0.8 0.9

Forest volume (m3/ha)

Average EVI

EVI Linear (EVI)

Trâm: Syzygyum cumini (evergreen) Vạng: Endospermun chineses (deciduous) Ngát: Gironniera subaequalis (evergreen) Máu chó: Knema corticosa () Kiền: Hopea pierrei (evergreen) Trâm: Syzygyum cumini (evergreen) Trám: Canarium tramdeum (evergreen) Dẻ: Castanea mollissima (evergreen) Sim lan: Rhodomyrtus tomentosa (evergreen)

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  • 5. Results

5 10 15 20 25 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 01/01/2011 16/01/2011 02/02/2011 18/02/2011 05/03/2011 21/03/2011 06/04/2011 22/04/2011 08/05/2011 24/05/2011 09/06/2011 25/06/2011 11/07/2011 27/07/2011 12/08/2011 28/08/2011 13/09/2011 29/09/2011 15/10/2011 31/10/2011 16/11/2011 02/12/2011 18/12/2011 Average Precipitation (mm) Average EVI Date

EVI and Precipitation

5 10 15 20 25

0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

01/01/2011 16/01/2011 02/02/2011 18/02/2011 05/03/2011 21/03/2011 06/04/2011 22/04/2011 08/05/2011 24/05/2011 09/06/2011 25/06/2011 11/07/2011 27/07/2011 12/08/2011 28/08/2011 13/09/2011 29/09/2011 15/10/2011 31/10/2011 16/11/2011 02/12/2011 18/12/2011 Average precipitation (mm) Average EVI Date

EVI and Precipitation Trâm: Syzygyum cumini (evergreen) Vạng: Endospermun chineses (deciduous) Ngát: Gironniera subaequalis (evergreen) Máu chó: Knema corticosa () Kiền: Hopea pierrei (evergreen) Trâm: Syzygyum cumini (evergreen) Trám: Canarium tramdeum (evergreen) Dẻ: Castanea mollissima (evergreen) Sim lan: Rhodomyrtus tomentosa (evergreen)

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  • 5. Results

y = -621.88x + 476 R² = 0.5466

40 60 80 100 120 140 160 180

0.4 0.6 0.8

Forest volume (m3/ha)

Average EVI

EVI Linear (EVI)

Giổi: Michelia balansae (evergreen) Ươi: Beumee ex (Deciduous) Giổi: Michelia balansae (Evergreen broad leaf) Đào: Persica vulgaris (Deciduous) y = 598.77x - 305.48 R² = 0.704

40 50 60 70 80 90 100 110

0.55 0.6 0.65 0.7

Forest volume (m3/ha)

Average EVI

EVI Linear (EVI)

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  • 5. Results

Giổi: Michelia balansae (evergreen) Ươi: Beumee ex (Deciduous) Giổi: Michelia balansae (Evergreen broad leaf) Đào: Persica vulgaris (Deciduous)

5 10 15 20 25 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 01/01/2011 16/01/2011 02/02/2011 18/02/2011 05/03/2011 21/03/2011 06/04/2011 22/04/2011 08/05/2011 24/05/2011 09/06/2011 25/06/2011 11/07/2011 27/07/2011 12/08/2011 28/08/2011 13/09/2011 29/09/2011 15/10/2011 31/10/2011 16/11/2011 02/12/2011 18/12/2011 Average Precipitation (mm) Average EVI Date

EVI and Precipitation

5 10 15 20 25

0.2 0.4 0.6 0.8 1 1.2

01/01/2011 16/01/2011 02/02/2011 18/02/2011 05/03/2011 21/03/2011 06/04/2011 22/04/2011 08/05/2011 24/05/2011 09/06/2011 25/06/2011 11/07/2011 27/07/2011 12/08/2011 28/08/2011 13/09/2011 29/09/2011 15/10/2011 31/10/2011 16/11/2011 02/12/2011 18/12/2011 Average Precipitation (mm) Average EVI Date

EVI and Precipitation

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  • 5. Results

y = 1374.7x - 953.51 R² = 0.6149

10 20 30 40 50 60 70 80 0.7 0.72 0.74 0.76

Forest volume (m3/ha)

Average EVI

EVI Linear (EVI)

Dẻ: Castanea mollissima Mít nài: Artocarpus rigidus Chân Chim: Schefflera octophylla Dẻ: Castanea mollissima Chân Chim: Schefflera octophylla Evergreen Forest

y = 972.44x - 678.13 R² = 0.6039

20 40 60 80 100 120 140

0.7 0.75 0.8 0.85

Forest volume (m3/ha) EVI

EVI Linear (EVI)

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  • 5. Results

Dẻ: Castanea mollissima Chân Chim: Schefflera octophylla Dẻ: Castanea mollissima Mít nài: Artocarpus rigidus Chân Chim: Schefflera octophylla

5 10 15 20 25 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 01/01/2011 16/01/2011 02/02/2011 18/02/2011 05/03/2011 21/03/2011 06/04/2011 22/04/2011 08/05/2011 24/05/2011 09/06/2011 25/06/2011 11/07/2011 27/07/2011 12/08/2011 28/08/2011 13/09/2011 29/09/2011 15/10/2011 31/10/2011 16/11/2011 02/12/2011 18/12/2011 Average Precipitation Average EVI Date

EVI and Precipitation

5 10 15 20 25 0.55 0.6 0.65 0.7 0.75 0.8 0.85 01/01/2011 16/01/2011 02/02/2011 18/02/2011 05/03/2011 21/03/2011 06/04/2011 22/04/2011 08/05/2011 24/05/2011 09/06/2011 25/06/2011 11/07/2011 27/07/2011 12/08/2011 28/08/2011 13/09/2011 29/09/2011 15/10/2011 31/10/2011 16/11/2011 02/12/2011 18/12/2011 Average Precipitation (mm)

Average EVI

Date

EVI and Precipitation

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  • 5. Summary of results

Type of forests

R2 Type of forests R2

1

Trâm: Syzygyum cumini

0.81

5

Dẻ: Castanea mollissima

0.7219

Vạng: Endospermun chineses Chân Chim: Schefflera octophylla Ngát: Gironniera subaequalis

6

Dẻ: Castanea mollissima

0.6149

Máu chó: Knema corticosa Mít nài: Artocarpus rigidus Kiền: Hopea pierrei Chân Chim: Schefflera octophylla

2

Trâm: Syzygyum cumini

0.675

7

Giổi: Michelia balansae

  • 0.5466

Trám: Canarium tramdeum Đào: Persica vulgaris Dẻ: Castanea mollissima

8

Giổi: Michelia balansae

0.704

Sim lan: Rhodomyrtus tomentosa Ươi: Beumee ex

3

Dẻ: Castanea mollissima

  • 0.0224

9

Dẻ: Castanea mollissima

  • 0.0231

Chuồn:

Máu Chó:

4

Chò: Schima wallichii

  • 0.4377

Kiền: Hopea pierrei

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  • 6. Conclusion & Discussion

① MODIS EVI has close correlation with volume of forest and precipitation ② The correlation depend on different types of forests with different species ③ In some cases, MODIS EVI has low correlation with forest volume =>need more deeper studies

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  • 6. Future work

Activity

09/2012 t0 03/2013 04/2013 to 08/2013 09/2013 to 01/2014 02/2014 to 05/2014

1, Literature review 2, Data collection

MODIS EVI Field survey data

3, Data preprocessing 4, Results 5, Writing thesis

I am here

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7.Reference

  • Eckert, S. 2012. Improved Forest Biomass and Carbon Estimations Using Texture Measures from

WorldView-2 Satellite Data. Remote Sensing 4(12), pp. 810–829. Available at: http://www.mdpi.com/2072- 4292/4/4/810/ [Accessed: 19 September 2013].

  • Eckert, S., Ratsimba, H.R., Rakotondrasoa, L.O., Rajoelison, L.G. and Ehrensperger, A. 2011. Deforestation

and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar. Forest Ecology and Management 262(11), pp. 1996–2007. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0378112711005330 [Accessed: 1 October 2013].

  • ANGELSEN, A., BROCKHAUS, M., SUNDERLIN, W. D. & VERCHOT, L. V. 2012. Analysing REDD+: Challenges

and choices, Bogor, Indonesia, Center for International Forestry Research (CIFOR).

  • IPCC. (2007). Climate Change 2007: Synthesis Report. In Core Writing Team, R. K. Pachauri & A. Reisinger

(Eds.), Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 104). Geneva, Switzerland: IPCC.

  • Pham,T.T., Moeliono, M., Nguyen,T.H., Nguyen, H.T., Vu, T.H. 2012. The context of REDD+ in Vietnam:

Drivers, agents and institutions. Occasional Paper 75. CIFOR, Bogor, Indonesia.

  • Huete,A., K. Didan, T. Miura, E.P. Rodriguez, X. Gao and L.G. Ferreira. 2002. Overview of the radiometric

and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 83:195– 213.

  • http://www.vietnam-redd.org/Web/Default.aspx?lang=en-US
  • Das, S. and Singh, T.P. 2012. Correlation analysis between biomass and spectral vegetation

indices of forest ecosystem. International Journal of Engineering Research & Technology (IJERT) 1(5), pp. 1–13.

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Thank you for your attention!