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Qiaoyun Xie Phenology 2018 presentation on agricultural phenology

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University of Technology Sydney Qiaoyun Xie's Phenology 2018 conference presentation on grass functional type distribution across eastern Australia.

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Qiaoyun Xie Phenology 2018 presentation on agricultural phenology

  1. 1. Qiaoyun Xie, Alfredo Huete, Song Leng, Nguyen Ngoc Tran v University of Technology Sydney Ecosystem Dynamics, Health and Resilience Faculty of Science 1 Grass functional type distribution across eastern Australia -- from satellite phenology
  2. 2. Questions 1. What is the C3 and C4 grass distribution in Australia and why do we look at it? --> Functional type informed by phenology 2. From MODIS (250m) to Sentinel-2 (10m): finer resolution phenology product --> unveil details of mixed grass areas 3. What controls the grass functional distributions? --> soil moisture --> land surface temperature 2
  3. 3. v Distribution of subtropical and temperate grass species Subtropical species Temperate species Medek et al. Aerobiologia 2016 Background • The highly productive eastern Australia belt is essential contributor to the agricultural production of wool, lamb, and beef. The area is composed of mixed native/ exotic species of C3 temperate and C4 subtropical grasses. • Native grasslands are under threat. • Phenology can inform on the health & status of grass functional types. • Remote sensing offers opportunities to monitor grasslands and distinguish functional types over large areas. 3
  4. 4. Methods 4
  5. 5. Study area -- eastern Australia grass / pasture Land cover data citation: Geoscience Australia (2010) Dynamic Land Cover Dataset. Bioregional Assessment Source Dataset. Viewed 27 September 2017, http://data.bioregionalassessments.gov.au/dataset/1556b944-731c-4b7f- a03e-14577c7e68db. 5 Blank / white areas: non-grass
  6. 6. MODIS EVI Time Series (greenness) Enhanced Vegetation Index (EVI) and phenology -- 1 Enhanced Vegetation Index (EVI): • A proxy of canopy “greenness”, which is defined as an integrative composite property of green leaf area, green foliage cover and structure, and leaf chlorophyll content. • A function of remotely sensed reflectance (ρ) in the near infrared (nir), red, and blue bands. 6
  7. 7. Enhanced Vegetation Index (EVI): Can, for example, define: • Start of Growing Season (SGS) • Peak of Growing Season (PGS) Figure credit: Ma et al. 2013 Remote Sensing of Environment Integral EVI • End of Growing Season (EGS) • Length of Growing Season (LGS) 7 Enhanced Vegetation Index (EVI) and phenology -- 2
  8. 8. SMAP (Soil Moisture Active Passive) • L3_SM_AP product (9km) MODIS, Sentinel-2, SMAP satellite missions MODIS • EVI product (250m) • Land Surface Temperature product (0.05Deg) 8 Sentinel-2 • L1C product (10m) Phenology Landscape heterogeneity/ species mixtures Drivers & controls
  9. 9. Approach -- MODIS and Sentinel-2 phenology Ø Discriminating grass classes into C3, C4, and mixed • For every 250m MODIS pixel, we determined if EVI peaked in Spring, Autumn, or both (double peak). 9 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 6 12 18 24 EVI C3 C4 Jan 2016 Apr 2016 Jul 2016 Oct 2016 Jan 2017 autumn spring
  10. 10. Approach -- MODIS and Sentinel-2 phenology Ø Discriminating grass classes into C3, C4, and mixed 10 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 6 12 18 24 EVI C3 C4 mixed Jan 2016 Apr 2016 Jul 2016 Oct 2016 Jan 2017 autumn spring • For every 10m Sentinel-2 pixel, we mapped the grass distribution and compared them with 250m pixel (MODIS) maps. • Study was conducted for one hydrological year, from July 2016 to June 2017. • To validate our grass distribution map, we compared our map with other studies and climate data (temperature and soil moisture).
  11. 11. Ø SMAP Soil Moisture: • Daily composite SMAP soil moisture was converted to 16 day moving average for comparison with EVI time series. • Correlation (R2) between MODIS EVI and SMAP soil moisture was calculated for different grass functional type. • Study was conducted from March 2015 to June 2018 (SMAP is available since March 2015). Approach -- MODIS phenology and SMAP soil moisture 11
  12. 12. Results 12
  13. 13. C3 C3 & C4 mixed C4 v Subdivisional % C4 (native) map for Australia -- using meteorology method P.W.Hattersley et al. 1983 Oecologia C3 & C4 grass distribution map (250m) -- from remote sensing phenology 13 Peak of growing season Spring (C3) Autumn (C4) Both (mixed)
  14. 14. Land surface temperature and soil moisture in October 2016 (spring) Ø C3 grass is most numerous where spring is cool and wet C3 & C4 grass distribution map (250m) -- validated with climate factor 14 C3 Peak of growing season Spring (C3) Autumn (C4) Both (mixed) (P.W.Hattersley et al. 1983 Oecologia)
  15. 15. Land surface temperature and soil moisture in January 2017 (summer) Ø C4 grass is most numerous where summer is hot and wet 15 C4 Peak of growing season Spring (C3) Autumn (C4) Both (mixed) C3 & C4 grass distribution map (250m) -- validated with climate factor (P.W.Hattersley et al. 1983 Oecologia)
  16. 16. v MODIS (250m) v Sentinel-2 (10m) 16 Irrigated pasture (C4) Rainfed Pasture (C3) Peak of growing season Spring (C3) Autumn (C4) Both (mixed) v Theresa Park Grass phenology -- from MODIS (250m) to Sentinel-2 (10m)
  17. 17. 0 450 900 1,350225 km Grass phenology -- from MODIS (250m) to Sentinel-2 (10m) ? ! v MODIS (250m) v Sentinel-2 (10m) 17 Peak of growing season Spring (C3) Autumn (C4) Both (mixed)
  18. 18. 0 450 900 1,350225 km Grass phenology -- from MODIS (250m) to Sentinel-2 (10m) < 20% area v MODIS (250m) v Sentinel-2 (10m) 18 Peak of growing season Spring (C3) Autumn (C4) Both (mixed)
  19. 19. v Grass distribution map (250m)v Correlation between EVI and Soil moisture Grass phenology and soil moisture 19 R2: C3 > mixed > C4 Peak of growing season Spring (C3) Autumn (C4) Both (mixed) Tussock, hummock and scattered grass growth (EVI) is highly correlated with soil moisture. Ø Along eastern belt: Ø In western semi-arid area:
  20. 20. 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 15 30 45 60 75 EVI Soil moisture 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 C3 grass Ø SMAP soil moisture is well synchronized and correlated with MODIS EVI. Ø C3 grass photosynthesis is soil moisture dependent, in the greening & drying phase, soil moisture and EVI increase and decrease concurrently. (Reference: Sage, R. F., Sage, T. L., & Kocacinar, F. (2012). Photorespiration and the evolution of C4 photosynthesis. Annual review of plant biology, 63, 19-47.) EVI SoilMoisture(cm3/cm3) EVI SoilMoisture(cm3/cm3) R2=0.82 Apr 2015 Nov 2015 Jul 2016 Mar 2017 Nov 2017 Jul 2018 Grass phenology and soil moisture 20
  21. 21. Tussock in semi-arid area Ø Semi-arid area grass is undetermined on our grass distribution map (no peaks in spring or autumn). Ø EVI of semi-arid area grass is soil moisture dependent. Ø Soil moisture use efficiency of semi-arid area grass is lower than that of eastern belt C3 grass. 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 R2=0.69 EVI SoilMoisture(cm3/cm3) EVI SoilMoisture(cm3/cm3) 0 0.1 0.2 0.3 0.4 0.5 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 15 30 45 60 75 EVI Soil moisture Apr 2015 Nov 2015 Jul 2016 Mar 2017 Nov 2017 Jul 2018 21
  22. 22. 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 15 30 45 60 75 EVI Soil moisture Apr 2015 Nov 2015 Jul 2016 Mar 2017 Nov 2017 Jul 2018 EVI SoilMoisture(cm3/cm3) EVI SoilMoisture(cm3/cm3) C4 grass Ø C4 grass EVI is less dependent on soil moisture. Ø Photosynthesis is more efficient than C3 grass, EVI does not decrease soon after SM decreases. (Reference: Sage, R. F., Sage, T. L., & Kocacinar, F. (2012). Photorespiration and the evolution of C4 photosynthesis. Annual review of plant biology, 63, 19-47.) 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.1 0.2 0.3 0.4 0.5 0.6 R2=0.05 22
  23. 23. 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0 15 30 45 60 75 EVI Soil moisture C3 & C4 mixed grass Apr 2015 Nov 2015 Jul 2016 Mar 2017 Nov 2017 Jul 2018 0 0.1 0.2 0.3 0.4 0.5 0.6 0 0.1 0.2 0.3 0.4 0.5 0.6 R2=0.03 EVI SoilMoisture(cm3/cm3) EVI SoilMoisture(cm3/cm3) Ø Influenced by C4 grass, mixed grass EVI does not correlate well with soil moisture either. 23
  24. 24. Conclusions & Caveats 24
  25. 25. Conclusions & Caveats 1. Phenology derived from remote sensing data is able to provide spatial distribution of C3, C4, and mixed grass. • MODIS (250m) is currently the best data for long term and large scale phenology research. • Sentinel-2 provides high spatial resolution (10m) phenology, but is in lack of cloud free data to provide phenology for some area. • Integrated phenology product at multi scale will be developed in the future. 25
  26. 26. Conclusions & Caveats 2. Strong correlation was found between EVI and soil moisture for C3 grass, showing that: • SMAP daily data could fill the details missed by MODIS EVI between the 16 day gap (MODIS EVI 16day product). • For C3 grass, with high correlation between EVI and SMAP, SMAP enables prediction of grass phenology. 26
  27. 27. Thank You Acknowledgements: This research is supported by an Australian Research Council (ARC) Discovery Projects grant. Contact: Qiaoyun.Xie@uts.edu.au 27

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