Tunisia-Merguellil

Overview

  1. Crop identification and Crop Area Estimation
    Crops types are discriminated using multitemporal NDVI data. A decision tree algorithm have been implemented for each year, we intend to develop a more general and robust method. Information about land cover type is required to parameterize the models used (ET, Biomass, etc.).
  2. Crop Condition/StressOur main goal is to monitor crop consumption and irrigation requirements using the coupling of FAO-56 method and NDVI time series (see results section). Crop water budget is useful operational information at plot scale (farmers) and at perimeter scale (irrigation managers). This type of products is also a valuable input for watershed integrated modelling, aimed at basins scale management, including groundwater.Crop water stress is monitored using thermal image processing, and the results are aimed at being assimilated in the crop water budget model (PhD student).
  3. Soil Moisture
    Soil moisture is the primary objective tackled using microwave data, relying on ground measurements for cal/val purpose. This type of information may also be input in the crop water budget model (A new PhD is currently on this topic by using Sentinel-1 and Sentinel-2 satellites data).
  4. Yield Prediction and Forecasting
    Based on NDVI relationships and vegetation model.
  5. Crop Residue, Tillage and Crop Cover Mapping
    We don’t study yet residues nor tillage (this will be done in 2017). Crop cover mapping is related to the first point.

Project Objectives

Mapping Agricultural Areas

Operational Implementation Plan

Scale

Land Cover
  • Spatial Resolution:
  • Temporal Resolution:

Estimating Crop Area

Operational Implementation Plan

Field size measurement

Estimating Crop Conditions

Operational Implementation Plan

Crop Conditions
  • Drought
  • Biological Stress

Estimation of Biophysical Variables

Operational Implementation Plan

Biophysical Variables
  • Vegetation Indices (NDVI, EVI, SAVI, etc.)
  • Biomass
  • Residue and Tillage mapping
  • Flux measurements

Forecasting Agricultural Variables

Operational Implementation Plan

Agricultural Variables (large scale)
  • Yield
  • Soil Moisture

Site Description

Landscape TopographyAlluvial plain
Typical Field Size1 to 4 ha
Climatic ZoneSubtropics, warm/ mod cool
Major Crops and Calendars

Cantaloupes and other melons (Early):
Calendar: March - June

Cantaloupes and other melons (Normal):
Calendar: April - July

Watermelons (Normal):
Calendar: June - October

Tomatoes (Normal):
Calendar: June - October

Chilies and peppers (Normal):
Calendar: June - September

Tomatoes (Late):
Calendar: September - November

Chilies and peppers (Late):
Calendar: September - November

Broad beans (Normal):
Calendar: September - March

Olives (Normal):

Almonds (Normal):

Oats (Normal):
Calendar: November - May

Barley:
Calendar: December - May

Wheat (Normal):
Calendar: January - June

Forage (Normal):

Soil Type & Texture

Inorganic:

  • Sand
  • Loamy Sand
  • Sandy Loam
  • Sandy Clay Loam
  • Sandy Clay
  • Loam
  • Silt Loam
  • Clay Loam
Soil Drainage Class["Well drained"]
Irrigation Infrastructure["Surface irrigation","Localized irrigation"]
Other Site Details

     
Figure 1. The study area, in red the boundary of the upper watershed, in yellow the boundary of the irrigated area.

Crop calendar:

 

In Situ Observations

Radiometric measurements

  • Crop Type(s):
  • Collection Protocol:

    (CropScan : 16 bands VIS-MIR, including Landsat TM bands)

  • Frequency:

Crop identification ground campaigns for land cover classification training

  • Crop Type(s):
  • Collection Protocol:

    Data collected during three campaigns with about 150 plots observed each time

  • Frequency:

LAI, fraction cover, biomass

  • Crop Type(s):
  • Collection Protocol:

    Collected on annual crops and olive trees

  • Frequency:

Temperature, Humidity, Wind Speed, Net Radiation, Rainfall

  • Crop Type(s):
  • Collection Protocol:

    Three permanent meteorological stations

  • Frequency:

Energy, Water, Carbon

  • Crop Type(s):
  • Collection Protocol:

    Two Flux stations on irrigated wheat and rainfed olive orchard

  • Frequency:

Area-averaged surface fluxes of sensible heat

  • Crop Type(s):
  • Collection Protocol:

    One X-LAS scintillometer transect (1 km) starting spring 2013

  • Frequency:

EO Data

Optical Data Requirements

  • Approximate Start Date of Acquisition: 01/02
  • Approximate End Date of Acquisition: 31/10
  • Spatial resolution: Medium resolution (20-60m)High resolution (5-20m)
  • temporal_frequency: Biweekly
  • Level of Expertise: Intermediate
  • Latency of Data Delivery:
  • Challanges:

    • SAR Data Requirements

  • Approximate Start Date of Acquisition: 01/02
  • Approximate End Date of Acquisition: 31/10
  • Spatial resolution: High resolution (5-20m)Very high resolution (below 5m)
  • temporal_frequency: Biweekly
  • Frequency: C
  • Incidence Angle: Medium
  • Polarisation:
  • Level of Processing: Level 2
  • Orbit: Any
  • Level of Expertise: Intermediate
  • Latency of Data Delivery: 2-5 days
  • Challanges:

    • Passive Microwave Data Requirements

    Thermal Data Requirements

    Results

    Documents and Files

    Links to paper

    Project Reports

    Study Team

    Team Leader

  • Name: Zohra Lili Chabaane
  • Affiliation: Université de Carthage/Institut National Agronomique de Tunis (INAT) Tunisie
  • Affiliation Webpage: http://www.inat.tn/fr
  • Position:
  • Email: zohra.lilichabaane@ucar.rnu.tn
  • Personal Webpage:
  • Phone number:
  • Postal Address:

    • Other Team Members

  • Name: Bernard Mougenot
  • Affiliation: Centre d'études Spatiales de la Biosphère
  • Affiliation Webpage: http://www.cesbio.ups-tlse.fr/
  • Position:
  • Email: bernard.mougenot@ird.fr
  • Personal Webpage:
  • Role: Co-Lead

  • Name: Mehrez Zribi
  • Affiliation: Institut de recherche pour le développement
  • Affiliation Webpage: https://en.ird.fr/the-ird
  • Position:
  • Email: mehrez.zribi@ird.fr
  • Personal Webpage:
  • Role: Co-Lead