Assessment of Net Primary Productivity over India Using Indian Geostationary Satellite (INSAT-3A) Data Sheshakumar Goroshi, Raghavendra P. Singh, Rohit Pradhan and Jai Singh Parihar Presented by: Sheshakumar Goroshi PhD Research Scholar Environment and Hydrology Division, EPSA Space Applications Centre, ISRO Ahmedabad – 380 015 Email: [email protected] ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India INTRODUCTION (NPP background, Regional, Global Knowledge and Gap area) • NPP is an important component of the global carbon cycle... • Accurate estimation of NPP is required to understand the carbon dynamics within the atmosphere– vegetation–soil continuum and the response of terrestrial ecosystem to predict future climate change. • Field based NPP measurements have been conventionally carried out using long term ecological monitoring of biomass in selected ecological site. • In-situ NPP measurements are limited by its spatial distribution, which are difficult to upscale for understanding the global carbon balance. • Polar orbiting satellites (MODIS and SPOT) have been commonly used to measure terrestrial NPP at regional/global scale. • Charge Coupled Devices (CCD) instrument on geostationary INSAT-3A platform provides a unique opportunity for continuous monitoring of ecosystem pattern and process study. ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India INTRODUCTION (Ecosystem Models: Regional, Global knowledge and Gap area) Model TEM CASA Global NPP (Pg C yr-1) 53.2 48 Source Melillo et al. 1993 Potter et al. 1993; Field et al. 1995 CASA-VGPM 56.4 Field et al. 1998 GLO-PEM 69.7 Cao et al., 2004 TURC 64 Lafont et al., 2002 reduced-form model ‘NNN’ 54.4 Moldenhauer and Ludeke 2000 Chikugo model 55.4 Awaya et al. 2004 MOD17 MOD-Sim-CYCLE, Sim-CYCLE MOD17 56 Heinsch et al., 2006 59.6, 62.7 Hazarika et al. 2005 56 Heinsch et al., 2006 Regional studies (India) GLO-PEM 3.4 Singh et al., 2011 CASA 1.42 Nayak et al., 2003 & 2013 CASA 0.83 Bala et al., 2013 ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India OBJECTIVES • Estimation of NPP using an Indian Geo-stationery satellite (INSAT-3A CCD) data and Improved CASA ecosystem model • Comparison of an INSAT derived NPP values with • Global NPP products (MODIS) • Earlier estimates in India (Literature) STUDY AREA Total geographical area of 329 million hectares situated in the tropics between 7°N and 40°N and between 68°E and 100°E. Vegetation: Diverse vegetation ecosystems and biodiversity (Figure) Seasons: Southwest summer monsoon (June-August), northeast winter monsoon (December to February), spring or premonsoon (March-May) and autumn postmonsoon (September-November) ENF:EVERGREEN NEEDLE LEAF FOREST DBF: DECIDUOUS BROAD LEAF FOREST CSH: CLOSED SHRUBLAND WSA: WOODY SAVANNAS WET: WETLAND CRO/NAT. MOSAIC: CROPLAND NAURAL MOSAIC BARREN AND SPARSE VEGETATION EBF: EVERGREEN BROAD LEAF FOREST MF: MIXED FOREST OSH: OPEN SHRUBLAND SA: GRASSLANDS CRO: CROPLAND SNOW AND ICE WATER BODIES ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India DATA USED Data Temporal Frequency NDVI (INSAT-3A CCD) 10 day 0.072°x0.072° Land Cover Ver. 2.0 Solar Radiation (MEERA) Ancillary data (NDVI, fPAR) Precipitation & Temperature (CRU) Biome specific Maximum Light Use Efficiency values Spatial Resolution 0.0089°x0.0089° Monthly 0.5°x0.6° Monthly 0.072°x0.072° Monthly 0.5°x0.5° 2009 Point Source ftp://mosdac.gov.in http://edc2.usgs.gov/ glcc/glcc.php http://gmao.gsfc.nasa. gov/merra ftp://ftp.glcf.umd.edu/g lcf Yu et al., (2009) IMPROVEMENT Data TF NDVI 10 day Land cover (INSAT) SR 0.072°x0.072° Source 0.0089°x0.0089° SAC, IIRS (Agrawal et al., 2003) ftp://mosdac.gov.in Insolation (Kalpana) Daily 0.072°x0.072° ftp://mosdac.gov.in Rainfall and Temperature Daily 0.25°x0.25° ftp: imd.gov.in In-situ NPP Annual Point SAC METHODOLOGY ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India NPP x, t APAR x, t εx, t (1) APAR x, t F fPAR x, t Sx, t fPAR NDVI x, t fPAR SR x, t (2) NDVI x, t NDVI i , min fPAR max fPAR min fPAR NDVI i, max - NDVI i, min SR x, t SR i ,min fPAR max fPAR min fPAR SR i, max - SR i, min min (4) min fPAR x, t α fPAR NDVI x, t 1 - α fPAR SR x, t (5) εx, t W x, t Tε1x, t Tε 2 x, t ε max (6) W x, t 0.5 0.5 ET x, t PET x, t T1x, t 0.8 0.02Topt x 0.0005Topt x (3) (7) 2 T2 x, t 1.1814 / 1 e 0.2 Topt x 10T x, t 1 e 0.3-Topt x 10T x, t (8) (9) RESULT AND DISCUSSION Jan Feb Mar Apr May June Jul Aug Sept Oct Nov Dec Mean NPP of the country: 49.15±10.46 gCm -2 month-1 Net Primary Productivity (g C m-2 month-1) Two distinct seasons can apparently see from the figures. The winter (January to March) and monsoon (July to October) seasons. Low NPP in Jan: Dry winter spell (12% < Mean monthly NPP of the country) February month mean NPP Increases by 6% due to coincidence crops in Punjab and IndoGangetic plains ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India As the crops achieved maturity and senescence stage during the end of the winter season (March). NPP reduced by 13% from mean country’s NPP During April, NPP reduced by 20% from mean country’s NPP (Lowest NPP in the study year) Growth Profile From May, starts increasing and achieved peak in September. Total NPP=1.18 PgC INSAT NPP MODIS NPP Net Primary Productivity (g C m-2 year-1) Table 2. Agreement analysis between MODIS NPP and INSAT NPP EBF DBF MF CS OS GRA CRO CRO/NVM 1007 1039 1320 471 625 377 841 7103 INSAT NPP (T) 1001.25 867.23 976.33 680.47 358.14 523.82 640.87 594.48 MODIS NPP (C) 702.62 613.60 989.69 615.08 241.12 520.06 675.51 513.17 Difference (C-T) 298.62 253.63 13.36 65.39 117.02 3.76 34.63 81.30 0.96 0.63 0.61 0.68 0.87 0.92 0.99 0.78 339.42 346 290 158.4 136.3 113.2 114.7 133.95 N d RMSE (gC m-2 month-1) n d 1- O i 1 O n i 1 i Pi 2 i O Pi - O 2 Oi:MODIS NPP AND Pi: INSAT NPP CONCLUSIONS and FUTURE SCOPE INSAT CCD derived NPP followed the characteristic growth profile of most of the vegetation types in the country. NPP attained maximum during August and September, while minimum in April. Annual NPP for different vegetation types varied from 1104.55 gC m-2 year-1 (evergreen broadleaf forest) to 231.9 gC m -2 year-1 (grassland) with an average NPP of 590 gC m-2 year-1. We estimated 1.9 PgC of net carbon fixation over Indian landmass as compared to 1.18 PgC from MODIS NPP in 2009. Biome level comparison between INSAT derived NPP and MODIS NPP indicated a good agreement with the Willmott’s index of agreement (d) ranging from 0.61 (Mixed forest) to 0.99 (Open Shrubland). NPP can be improved using high spatial and temporal input data sets. Validation will be done using In-situ NPP measurements ISPRS TCVIII Mid-Term Symposium on Operational Remote Sensing Applications, December 09-12 , 2014, Hyderabad, India ACKNOWLEDGEMENTS • Authors gratefully acknowledge Shri. A. S. Kiran Kumar, Director, SAC, Dr. Pradeep Pal, Deputy Director EPSA and Dr. Prakash Chauhan, Group Head, BPSG/SAC for their suggestions and encouragement. • One of the authors (Sheshakumar Goroshi) wishes to acknowledge the grant of fellowship by SAC. • Sheshakumar Goroshi also wishes to acknowledge the grant of participation fee by ISPRS • The authors thank NOAA, MODIS, CRU and MERRA for providing data sets for analysis.
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