Agricultural Monitoring Activities in Argentina
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1 Agricultural Monitoring Activities in Argentina Dr. José Paruelo Laboratorio de Análisis Regional y Teledetección Facultad de Agronomía e IFEVA Universidad de Buenos Aires CONICET ARGENTINA
2 Two major sources of crop area and yield estimates 1. National Census - 2. Agricultural Surveys
3 Agricultural expansion Stocking rate changes ha. ha -1.year -1 < a a > < -25% -25% a 0% 0% a 25% 25% a 50% > 50%
4 Remote sensing based approaches 1. INTA - Salta 2. Grupo TEA (Teledetección, Ecología y Agricultura) UBA INTA UNSL - CONICET
5 1. Pro.Re.NOA INTA - Salta Plot-based classication SAC-C and Landsat TM and ETM+ Imagen de trabajo Multi-temporal Mapa de parcelas Buffer de parcelas Extracción de estadísticos de la parcela (media y desvío estándar) ISODATA Máscara de áreas rurales Rep. Argentina Provincia de Salta Recodificación Información de campo Reconstrucción de parcela Verificación
6 1. Pro.Re.NOA INTA - Salta Volante et al Changes in cropped area Deforestation Cropping intensity
7 2. Grupo TEA (Teledetección, Ecología y Agricultura) UBA INTA UNSL - CONICET Understanding the drivers and consequences of Landuse/Land Cover Change a. Land cover classification based on Phenological patterns b. Regional Evapotranspiration estimates BOLIVIA ARGENTINA PARAGUAY BRAZIL c. On-line monitoring of forage production URUGUAY Atlantic Ocean d. Impact of Landuse/Land Cover Change on ecosystem functioning (C gains, water dynamics) Grasslands Humid forests Dry forests-savannas Río de la Plata Wetlands Cities with >1,000,000 people Cities with >5,000,000 people
8 Understanding the drivers and consequences of Landuse/Land Cover Change A FEEDBACKS DRIVERS CONSEQUENCES HUMAN BIOPHYSICAL Market (local-global) Policy (local-global) Public opinion (local-global) Technology Social structure Land Use Change Climate (global warming,,enso) Landscape resources Soil resources Invasions (e.g. pests) Commodities Food security Income Employment Aesthetic values Cultural values Water provision GHG regulation Climate regulation Hydrological regulation Landscape functioning Soil fertility Biodiversity
9 a. Land cover classification based on Phenological Patterns rec.forr. alta prod. rec.forr.baja prod. cer. inv. maíz soja trigo-soja misc Landsat TM SAC-C 6/2/2003 6/18/2003 7/4/2003 7/20/2003 8/5/2003 8/21/2003 9/6/2003 9/22/ /8/ /24/ /9/ /25/ /11/ /27/2003 1/1/2004 1/17/2004 2/2/2004 2/18/2004 3/5/2004 3/21/2004 4/6/2004 4/22/2004 5/8/2004 IVR x 1000 MODIS AVHRR/NOAA
10 a. Land cover classification based on Phenological patterns Landsat TM Clase Has. % de superficie Cultivos invernales Cultivos estivales Estepas graminosas Praderas de alta productividad Praderas de baja productividad Lagunas Laguna vegetada Guershchman et al IJRS Guershchman et al GPC
11 a. Land cover classification based on Phenological patterns 24º 30º 36º 42º 72º 48º 54º A Océano Pacífico 66º 60º 54º Brasil 24º Argentina 30º Uruguay Pastizales del Río de la Plata Océano Atlántico 36º 42º 48º 54º km 28º 32º 36º 68º 64º 60º 56º 52º del Norte del Sur Mesopotámica Ondulada Interior Plana Interior Oeste Inundable Austral Océano Atlá ntico km 48º 28º 32º 36º 72º 66º 60º 54º 48º 68º 64º 60º 56º 52º 48º 1988/ / / / / / / /2003 Interior Oeste Interior Oeste Mesopotámica del Norte Mesopotámica del Norte del Norte del Norte del Norte del Norte del Sur del Sur 1988/ / / /2003 Inundable Inundable 1988/ /2003 del Norte del Norte 1985/ / del Sur del Sur Interior Plana Ondulada Interior Plana Ondulada Austral Austral del Sur del Sur Mesopotámica Mesopotámica Baldi et al AEE
12 Fig 10 Fig 8 GEOSS Operational Agricultural Monitoring System a. Land cover classification based on Phenological patterns MODIS 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 IVR IVR soja cereales de invierno maíz trigo-soja Leyenda: Rec. Forr. B. Prod Rec. Forr. A. Prod Maíz Soja Girasol Trigo-soja Trigo Misceláneos 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 IVR IVR girasol rec. forr. alta product 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 IVR IVR rec. forr. baja product misceláneas 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 6/2/2003 7/4/2003 8/5/2003 9/6/ /8/ /9/ /11/2003 1/1/2004 2/2/2004 3/5/2004 4/6/2004 5/8/2004 IVR IVR Guerschman PhD dissert.
13 Fig 10 GEOSS Operational Agricultural Monitoring System a. Land cover classification based on Phenological patterns Soybean expansion: intergrating AVHRR/NOAA and MODIS (1) (2) (3) (4) % 50% AVHRR MODIS Paruelo et al. 2004, Interciencia Guerschman, 2005 PhD dissert
14 Fig 10 GEOSS Operational Agricultural Monitoring System b. Regional Evapotranspiration estimates Octubre 2006 Febrero 2007 Di bella et al. 2000, IJRS
15 c. On-line monitoring of forage production Octubre 2006 Febrero 2007 Grigera et al. 2007, Agric.Systems
16 MODIS 16 days composites of EVI Consultant, Rancher. ANPP (kg/ha/month) feb ma au no feb ma au no feb ma au no feb ma au no feb ma More than ha incorporated in the s and Patagonia. Starting in Uruguay Segf
17 d. Impact of Landuse/Land Cover change on ecosystem functioning Paruelo et al. 2004, IJRS
18 d. Impact of Landuse/Land Cover change on ecosystem functioning Land Ecosystem Change Utility for South America LechuSA LechuSA.unsl.edu.ar Paruelo et al. 2004, IJRS
19 Further information/details/references: lechusa.unsl.edu.ar Dr. José Paruelo Laboratorio de Análisis Regional y Teledetección Facultad de Agronomía e IFEVA Universidad de Buenos Aires CONICET ARGENTINA
20
21 a. Land cover classification based on Phenological patterns CORDOBA SANTA FE ENTRE RIOS URUGUAY SAC-C LA PAMPA Fac. Agronomía UBA Ministerio Asuntos Agrarios
22 Both approaches reproduce the spatial patterns of cropped area But, for example, the differences for the 20 counties with the largest area of wheat is in average 24% Differences (%) between estimates
23 Fig 10 Fig 8 GEOSS Operational Agricultural Monitoring System a. Land cover classification based on Phenological patterns MODIS LANDSAT
24 Land cover classification based on Phenological patterns
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