Use of remote sensing for crop yield and area estimates in Southern Brazil Denise Cybis Fontana Faculdade de Agronomia - UFRGS Remote Sensing support to crop yield forecast and area estimates 30 th November to 1 th December 2006 Stresa - Italy
Brazil General information: Area: 8.514.204,8 km² Population: 184.739.395 people Main biomes Floresta Amazônica (Amazon Forest) Caatinga Pampa (Rangelands) Cerrado (Pantanal) Mata Atlântica (Atlantic forest) Main crops: Soybean (46,533,261 ton) Maize (40,630,504 ton) Rice (11,486,733 ton) Wheat (4,620,679 ton)
Agricultural production 17% (grain) Soybean, maize (spring-summer) Wheat (winter) Porto Alegre Rice (spring-summer) Rangelands Rio Grande do Sul State
UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL Dimension 2.120 professors and researchers ( 50 % PhD) 2.880 technicians 22.100 undergraduate students 6.970 graduate students 1.800 basic education students Organization 54 undergraduate courses 200 graduate courses 376 extension courses Research groups - 355
Faculdade de Agronomia Graduate courses CROP SCIENCE http://www.ufrgs.br/ppgfitotecnia/
CEPSRM Centro Estadual de Pesquisa em Sensoriamento Remoto e Meteorologia Graduate course REMOTE SENSING http://www.ufrgs.br/srm
Infra-structure available Computers and softwares (Envi, Erdas, Idrisi, SPRING, ArcGIS, SAS, ) Research equipments (experimental area): - Automatic meteorological station, - Micrometeorological equipments; - Plant equipments (LAI, photosynthesis,...) - Soil equipments (tensiometer, lisimeter, ) Radiometry Laboratory NOAA/AVHRR receiving station
GeoSafras Project Project coordinated by CONAB (Companhia Nacional de Abastecimento) and supported by UNDP Multi-institutional network UFRGS, EMBRAPA, IBGE, INMET, INPE, UNICAMP, IAC, IAPAR, SIMEPAR,
Objective of GeoSafras To improve Brazilian crop area and yield estimation system through a multiinstitutional network for the development of methodologies, looking for an harvest forecasting system with higher objectivity.
TEAM at UFRGS: Ações Ana Paula Wagner, M.Sc. (Physics) Anibal Gusso, M.Sc. (Physics) Denise Cybis Fontana, D.Sc. (Agronomy) Eliana Lima da Fonseca, D.Sc. (Agronomy) Eliana Klering, M.Sc. (Meteorology) Eliseu Weber, M.Sc. (Agronomy) Gilca Marques Alves, B.Sc. (Agronomy) Homero Bergamaschi, D.Sc. (Agronomy) Jorge Ricardo Ducati, D.Sc. (Physics) Laurindo Guasselli, D.Sc. (Geography) Moacir Antonio Berlato, D.Sc. (Agronomy) Mônica Tagliari Kreling, M.Sc. (Geography) Ricardo Wanke de Melo, D.Sc. (Agronomy) Rita Marques Alves, D.Sc. (Meteorology)
GeoSafras Methodology Segments: estimates of crop area, estimates of crop yields and crop monitoring activities Remote Sensing measurement of the surface dynamics (imagery); Geoprocessing location and quantification; Agrometeorology crop yield modeling. Crops: wheat (winter) soybean and rice (spring-summer)
GeoSafras SOYBEAN (Spring-summer crop; Non-irrigated) Brazil 23.6% 60 BR RS 50 World Brazil Production (million ton) 40 30 20 10 14,58 18,34 13,32 18,45 11,18 4,78 14,44 0 2000 2001 2002 2003 2004 2005 2006 Harvests
GeoSafras Remote Sensing at UFRGS (GeoSafras) The use of a combination of satellite images with different resolutions: LANDSAT/TM (30m, 16 days) TERRA/MODIS (250m, 2 days or MVC 16 days) NOAA/AVHRR (1100m, 1 day or MVC 15/30days)
GeoSafras LANDSAT/TM Crop area mapping 224 / 079 2 3 / 079 2 2 / 079 2 1 / 079 225 / 080 224 / 080 2 3 / 080 2 2 / 080 2 1 / 080 2 0 / 080 2 5 / 081 224 / 081 2 3 / 081 2 2 / 081 2 1 / 081 220 / 081 2 3 / 082 2 2 / 082 2 1 / 082 2 0 / 082 2 2 / 083 2 1 / 083 2006 Harvest Soybean area estimation: 11 Landsat/TM images
GeoSafras TERRA/MODIS Crop area - mapping and monitoring NDVI OCT NOV DEC JAN FEB MAR
GeoSafras TERRA/MODIS Soybean mapping February Image (boolean) November Image (boolean) Landsat image Resultant Image : Mapping and quantification of the soybean area
GeoSafras TERRA/MODIS Soybean Mapping 2006
GeoSafras TERRA/MODIS Soybean Mapping 2006 120000 100000 MODIS Area (ha) 80000 60000 40000 20000 R 2 = 0.9545 0 0 20000 40000 60000 80000 100000 120000 Landsat AREA (ha) Counties 100% covered by images without clouds
GeoSafras NOAA/AVHRR Crop monitoring and yield estimations Temporal NDVI profiles PASSO FUNDO 0,8 0,7 NDVI 0,6 0,5 0,4 0,3 2004/05 2005/06 ago set out nov dez jan fev mar abr mai jun jul ago set out months Meses www.ufrgs.br/srm
Geosafras NOAA/AVHRR Agrometeorological-Spectral Model Agrometeorological Term Water and temperature conditions Spectral Term Water and temperature conditions and others: management, diseases, pests, and other stress.
GeoSafras Rio Grande do Sul state and meteorological stations -28º Argentina Santa Catarina Uruguay Oceano Atlântico -33º Meteorological stations Estação meteorológica -56º -51º
Geosafras Agrometeorological-spectral Model Bianchi et al. (2006) Y = Ym x (aat + bst) Agrometeorological Term Spectral Term
Geosafras Soybean yield estimates 3000 2743 IBGE Agrometeorological-spectral model 2500 2310 2000 1935 Yields (kg.ha -1 ) 1500 1000 1427 1219 589 753 1603 500 0 2003 2004 2005 2006 Harvests
Problem to crop yield estimations Lack of meteorological data to feed the model Alternative Simulation meteorological data
GeoSafras Results presented in JRC workshop Montevideo - October 2006 Melo e Fontana (2006) Objetive: a) to compare ECMWF simulated data to observed data at surface meteorological stations; b) to evaluate the use of simulated data in the soybean yield model in Rio Grande do Sul State, Brazil
Geosafras Meteorological data: - Maximum Temperature (ºC) - Minimum Temperature (ºC) - Mean Temperature (ºC) - Rainfall (mm) - Evapotranspiration (mm) 10-days periods from 2003/01/01 to 2005/12/31
GeoSafras Simulated ECMWF data
Geosafras Observed meteorological data -28º Argentina Santa Catarina Uruguay -33º Oceano Atlântico Meteorological stations Estação meteorológica -56º -51º
GeoSafras 40 35 30 25 20 15 10 5 0 MAXIMUM TEMPERATURE 0 10 20 30 40 Temperature (ºC) - ECMWF Temperature (ºC) - Meteorological station
Geosafras MINIMUM TEMPERATURE 45 40 Temperature (ºC) - Meteorological station 35 30 25 20 15 10 5 0-5 0 5 10 15 20 25 30 35 40 45 Temperature (ºC) - ECMWF
GeoSafras MEAN TEMPERATURE 45 40 Temperature (ºC) - Meteorological station 35 30 25 20 15 10 5 0-5 0 5 10 15 20 25 30 35 40 45 Temperature (ºC) - ECMWF
Geosafras RAINFALL 350 Rainfall (mm) - Meteorological station 300 250 200 150 100 50 0 0 50 100 150 200 250 300 350 Rainfall (mm) - ECMWF
GeoSafras EVAPOTRANSPIRATION 80 70 60 ET (mm) - Meteorological station 50 40 30 20 10 0 0 10 20 30 40 50 60 70 80 ET (mm) - ECMWF
Geosafras 3000 2743 IBGE ASM met stations ASM ECMWF 2500 2310 2359 2000 Yields (kg.ha -1 ) 1500 1427 1219 1379 1000 753 920 589 500 0 2003 2004 2005 Harvest Soybean yield estimations using ground and ECMWF data
GeoSafras Yields Kg.ha -1 0 2003-28º -29º 700 1400 2100 2800 Meteorological data Mean Yield 2310 kg.ha -1-55º -54º -53º -52º -28º -29º Yields Kg.ha -1 0 700 1400 2100 2800 ECMWF Mean Yield 2359 kg.ha -1-55º -54º -53º -52º
Geosafras Yields Kg.ha -1 0 2004-28º -29º 700 1400 2100 2800 Meteorological data Mean Yield 1219 kg.ha -1-55º -54º -53º -52º -28º -29º Yields Kg.ha -1 0 700 1400 2100 2800 ECMWF Mean Yield 1379 kg.ha -1-55º -54º -53º -52º
GeoSafras Yields Kg.ha -1 0 2005-28º -29º 700 1400 2100 2800 Meteorological data Mean Yield 753 kg.ha -1-55º -54º -53º -52º -28º -29º Yields Kg.ha -1 0 700 1400 2100 2800 ECMWF Mean Yield 920 kg.ha -1-55º -54º -53º -52º
GeoSafras Final Considerations Success of the Geosafras project (UFRGS CONAB) Objectivity, accuracy, low cost and practicity of the estimations Need of continued improvement Experience exchanges are welcome
Thanks!