China-Leizhou

Overview

Crop identification and Crop Area Estimation

  • Object-based Image Analysis and The Support Vector Machine (SVM) classification method
  • The fusion of SAR and Optical satellite data
  • Statistical analysis
  • Determine to what level of accuracy Radarsat-2 can classify crops with different cropping system in China
  • Determine whether Radarsat-2 data alone can produce classification accuracies targeted by CAAE (overall and individual accuracies of 90%) at the early stages of the growing season
  • Develop comprehensive algorithms using Radarsat-2 in combination with other data resources in the operational crop monitoring system

Crop Condition/Stress

  • Normalized Difference Vegetation Index (NDVI)
  • The ground truth information

Yield Prediction and Forecasting

  • Artificial Neural networks (NN) method

Phenological Events and Estimation of Rice biophysical variables

  • Multiple regression analysis
  • Leaf Area Index (LAI) measured with Hemispherical lens

Crop Biophysical Parameters Estimation

  • Leaf Area Index monitoring using Radarsat-2 images at regional scale

Project Objectives

Estimating Crop Conditions

Operational Implementation Plan

Crop Conditions
  • Biological Stress

Measuring Phenological Events

Phenological Events
  • Seeding
  • Seedling
  • Vegetative Growth
  • Flowering
  • Fruit Development
  • Maturity
  • Harvest

Estimation of Biophysical Variables

Operational Implementation Plan

Biophysical Variables
  • LAI (Leaf Area Index)

Site Description

Landscape Topographyflat area, and low hills around
Typical Field Size 0.1 to 10.0 ha
Climatic ZoneTropics, warm
Crop Details

Rice (Normal):
Calendar: March - June
Typical Rotation: Typical Crop Rotation is paddy rice with two harvests per year

Rice (Late):
Calendar: August - November

Sugar cane (Normal):

peanut (Normal):

Soil Type & Texture
Soil Drainage Class
  • Well drained
Irrigation Infrastructure
  • Surface irrigation
Other Site Specifications

In Situ Observations

Planting pattern, growing stage, seeding/transplanting date, plant height, Leaf area index(LAI), weather condition and digital photos during key rice growing stages concurrently with the satellite pass

  • Crop Type(s):
  • Collection Protocol:

    25 sample plots

  • Frequency:

Crop height

  • Crop Type(s):
  • Collection Protocol:
  • Frequency: About 2 times each crop year

Accuracy of rice identification

  • Crop Type(s):
  • Collection Protocol:

    Hundreds of points for land cover type were collected once per season

  • Frequency:

Crop type

  • Crop Type(s):
  • Collection Protocol:

    GPS

  • Frequency: 2 times each crop year

LAI

  • Crop Type(s):
  • Collection Protocol:

    LAI2000

  • Frequency: About 2 times each crop year

EO Data

Optical Data Requirements

  • Approximate Start Date of Acquisition: 01/04
  • Approximate End Date of Acquisition: 31/10
  • Spatial resolution: High resolution (5-20m)
  • temporal_frequency: Monthly
  • Level of Expertise: Intermediate
  • Latency of Data Delivery: 2-5 days
  • Challanges:
  • SAR Data Requirements

  • Approximate Start Date of Acquisition: 01/04
  • Approximate End Date of Acquisition: 31/10
  • Spatial resolution: High resolution (5-20m)
  • temporal_frequency: Biweekly
  • Frequency: XCL
  • Incidence Angle: ShallowMediumSteep
  • Polarisation: HHVVCross (HV, VH)Circular polarization
  • 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: Zhiyuan Pei
  • Affiliation: Ministry of Agriculture and Rural Affairs of the People's Republic of China
  • Affiliation Webpage: http://english.agri.gov.cn/
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  • Email: peizhiyuan@agri.gov.cn
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  • Name: Xiaoqian Zhang
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  • Name: Lin Guo
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  • Name: Fei Wang
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  • Name: Shangjie Ma
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  • Name: Heather Mcnairn
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  • Name: Jiali Shang
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  • Name: Juanying Sun
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