Crop yield forecasting based on Remote sensing 12-14 October 2011, Rabat, Morocco Balaghi R., Jlibene M., Tychon B., Eerens H. 1 Book in press.

Slides:



Advertisements
Similar presentations
Experience and Achievement of Remote Sensing Applications in Agriculture Tang Huajun Institute of Agricultural Resources and Regional Planning CAAS, China.
Advertisements

Work-package 6 Statistical integration Allard de Wit & Raymond van der Wijngaart.
DRSRS E-AGRI: ACTIVITIES IN Kenya 24 th March,2011 Charles Situma Nairobi, Kenya
Presentation of the tasks and activity planning for the work group BioMA WP 3: BioMA (Multi-model crop yield estimates) Roberto Confalonieri & Marcello.
(Multi-model crop yield estimates)
Correlation and Regression Analysis Many engineering design and analysis problems involve factors that are interrelated and dependent. E.g., (1) runoff.
Climate Impact Team WMO XV Commission for Agricultural Meteorology Belo Horizonte, Brazil July 2010 FAO data, tools & methods for climate impact.
Application of Earth Observation data in Agricultural drought monitoring Farai Kuri University of Zimbabwe.
E-AGRI Kick-off meeting, March 2011, VITO (Mol, Belgium) RS based crop forecasting in Morocco Riad BALAGHI National Institute for Agricultural Research.
Climate Trends and Wheat Straw Supplies Dave Sauchyn, Prairie Adaptation Research Collaborative, University of Regina North American Mushroom Conference,
Crop Area estimation in Morocco
Eerens H. (VITO - Belgium) Balaghi R., Jlibene M., (INRA - Morocco) Tahiri (DSS - Morocco) Aydam M. (JRC - Italie) 1 WP 4 : Yield Estimation with Remote.
FIELD CROPS Top graphic from
Central Bureau of Statistics Ministry of Planning and National Development Department of Resource Surveys and Remote Sensing Ministry of Environment and.
Use of Remote Sensing and GIS in Agriculture and Related Disciplines
Numbers
Crop monitoring as an E-agriculture tool in developing countries (E-AGRI) Overview and Management FP7 STREP Project (GA ) 1 st Progress Meeting ( )
Crop Monitoring with Land Data Assimilation and Remote Sensing Michael Marshall Climate Hazards Group (FEWSNET) UC Santa Barbara (office),
CGMS/WOFOST model principles
April 28-29, 2015 at Hotel Serena, Islamabad
Mohammed Jlibene, Nasserlehaq Nsarellah, Riad Balaghi (INRA – Morocco) 1 WP 31.1 : Ground data collection for BioMA (Morocco) Leading institution : UNIMI.
FP7 e-Agri meeting, January 2014, Alterra, Wageningen-UR, the Netherlands CGMS-MOROCCO STATUS El Hairech T., Balaghi R., De Witt A., Van Der Wijngaart.
Relationships Between NDVI and Plant Physical Measurements Beltwide Cotton Conference January 6-10, 2003 Tim Sharp.
Richard Soppe, John Hornbuckle, Janelle Montgomery 26 th June 2012 CSIRO LAND AND WATER/SUSTAINABLE AGRICULTURE FLAGSHIP Cotton water productivity in the.
EXPERT MEETING ON WEATHER, CLIMATE AND FARMERS November 2004, Geneva, Switzerland ZOLTÁN DUNKEL OMSZ -Hungarian Meteorological Service H-1525 Budapest.
Application of Remote Sensing in Agricultural Research and Regional Productivity Assessment I. Ortiz-Monasterio and D. Lobell.
Central Bureau of Statistics Ministry of Planning and National Development Department of Resource Surveys and Remote Sensing Ministry of Environment and.
Diego Rocha 7 to 18 February,  The application of the Agrometeorological spectral model, based on Report No. 33 of FAO for Estimating the harvest.
Crop monitoring as an E-agriculture tool in developing countries (E-AGRI) Overview and Management FP7 STREP Project (GA ) 2 nd Progress Meeting ( )
E-AGRI Work Package 3 BioMA multi-model monitoring Roberto Confalonieri 1, Simone Bregaglio 1, Caterina Francone 1, Valentina Pagani 1, Giovanni Cappelli.
Sensor Technology in India R.K. Gupta, B. Singh, P. Chandna, R.K. Sharma, M.L. Jat.
Liliana Balbi Senior Economist, Team Leader GIEWS FAO Trade and Markets Division Agricultural Market Information Network in the Mediterranean Region Kick.
FP7 e-Agri meeting, January 2014, Alterra, Wageningen-UR, the Netherlands 1 Balaghi R., Eerens H., Dong Q.
Central Bureau of Statistics Ministry of Planning and National Development Department of Resource Surveys and Remote Sensing Ministry of Environment and.
Prediction of Wheat Yields Using Multiple Linear Regression Models in the Huaibei Plain of China Beier Zhang (AIER - China ) Qinhan Dong (VITO - Belgium)
AMFUCoimbatorePalampurJothpur LocationCoimbatore Kangra Kullu Jothpur Crop – RainfedSorghumWheat 1.Preal millet 2.Clusterbean Crop – IrrigatedMaize - Rice.
L i n k i n g S c i e n c e t o S o c i e t y cover box Global change information needs for decision makers dealing with food security Walter E. Baethgen.
Some of the best books of  &mid= A23D2FC75CD A23D2FC75CD7.
Remote Sensing for agricultural statistics Main uses and cost-effectiveness in developing countries Insert own member logo here Pietro Gennari, Food and.
WP2 progress CGMS Anhui/Morocco Allard de Wit, Steven Hoek, Riad Balaghi, Tarik el Hairech, Bell Zhang, Jappe Franke, Hugo de Groot, Bas vanMeulebroek,
Improving Quality of Area & Production Estimates of Crops By Directorate of Economics & Statistics Department of Agriculture & Cooperation Ministry of.
CGMS Anhui & Yield estimation with RS CGMS Anhui & Yield estimation with RS.
Agronomic Spatial Variability and Resolution Data Normalization and Temporal Variability.
Crop Damage Assessment using Remote Sensing & Agrometeorological data Mahalanobis National Crop Forecast Centre, DACFW, New Delhi Space Applications Centre,
Three Alternative Nitrogen Management Strategies for Cereal Grain Production Brian Arnall Brian Arnall Plant and Soil Sciences Department Oklahoma State.
REMOTE SENSING INDICATORS FOR CROP GROWTH MONITORING AT DIFFERENT SCALES Zongnan Li 1, 2 and Zhongxin Chen 1, 2* 1 Key Laboratory of Resources Remote Sensing.
Famine Early Warning Systems Network Where do we need your help? The FEWS NET III Approach, current food insecurity, and implications for science partner.
Famine Early Warning Systems Network Agroclimatic Outlook April 12, 2016 / EWIWG meeting Kabul, Afghanistan.
10-1 人生与责任 淮安工业园区实验学校 连芳芳 “ 自我介绍 ” “ 自我介绍 ” 儿童时期的我.
Date of download: 6/22/2016 Copyright © 2016 SPIE. All rights reserved. Localization of the study area and monitored fields superimposed with a colored.
Theory of Predicting Crop Response to Non-Limiting Nitrogen.
CEE 6440: GIS in Water Resources Prepared by: Roula Bachour
RSA: Crop Estimates Overview AfriGEOSS-EOPower-GEOGLAM
Yahoo Mail Customer Support Number
Most Effective Techniques to Park your Manual Transmission Car
How do Power Car Windows Ensure Occupants Safety
Soumya Sudhakar Mechanical and Aerospace Engineering Class of 2018
Green Revolution 2.0 Remote Sensing.
Precision Ag Use by Today's Agronomists
By Blake Balzan1, with Ramesh Sivanpillai PhD2
THANK YOU!.
Late-Season Prediction of Wheat Grain Yield and Protein
Thank you.
Thank you.
Predictors Observed rainfall up to May.
Variability in Corn Response to N Fertilizer along a 1000-ft Hillslope
Reflectance and Sensor Basics
YP0 = (NDVI / Days, GDD>0) YP0 = INSEY YPN = (YP0*RI)
National Agricultural Statistics Service
Presentation transcript:

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco Balaghi R., Jlibene M., Tychon B., Eerens H. 1 Book in press

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco 2

Rainfall variability in Morocco

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco Relationship between rainfall and cereal area

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco Relationship between rainfall and cereal yield

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco Statistical cereal yield models

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco Statistical cereal yield models (rainfall)

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco 8

Relationship between NDVI and cereal yield

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco Statistical cereal yield models (NDVI)

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco 11 Relationship between NDVI and Soft wheat yield (province level)

Crop yield forecasting based on Remote sensing October 2011, Rabat, Morocco شكرا 謝謝您 Thank you 12

Feedback: Privacy Policy Feedback
Do Not Sell My Personal Information
About project: SlidePlayer Terms of Service

© 2024 SlidePlayer.com. Inc. All rights reserved.