Vegetation Parameters CCI User requirements (LAI and FAPAR)

Introduction

Thank you for taking the time to fill in our questionnaire.
We are a consortium developing a remote sensing based time series of LAI and FAPAR, based on multiple sensors. We do this in the frame of ESA’s Climate Change Initiative (CCI) programme. see our website.
The objective of this questionnaire is to gather information from potential scientific users of the data products that help in making optimal choices in the product development.
Filling in the questions will take about 10 minutes.
You can fill in the questionnaire anonymously, but we also welcome direct recommendations (for example by e-mail) to our team.

Christiaan van der Tol

c.vandertol@utwente.nl

Some background about our project
The applications of LAI and fAPAR satellite data products that we envisage include for example:
- Understanding the role of vegetation in the global climate
- Understanding the effects of weather extremes
- Understanding the causes and effects of land cover and land-use change
- Improving estimates of land surface fluxes in land surface/ dynamic vegetation models
- Estimating agricultural crop productivity
The spatial resolution will be 300 m and 1 km. Our product will not serve applications that require higher spatial resolution, such as agricultural applications or detailed land use monitoring.

Question Title

* 1. Your main affiliation is?

University

Research Institute

Ministry/ local, state, national or European/federal government

Space Agency

Company

Other (please specify)

Question Title

* 2. How often have you used satellite-based LAI or FAPAR products?

Never

Occasionally (<2 times per year)

More often, in research projects

Routinely, in operational context

Question Title

* 3. Which data products/ sensors have you used? (Multiple answers possible)

C3S

GEOV1 (CLGLS)

CYCLOPES

JRC-FAPAR

MODIS15A2

MDfAPAR-R

QA4ECV

LSA-SAF

Other (please specify)

Question Title

* 4. For which purpose(s) have you used or will you use LAI/FAPAR data (multiple answers possible)?

Improving the accuracy of estimates of carbon sequestration

Studying (changes or anomalies in) seasonal phenology (onset, peak, end of growing season)

The response of vegetation to weather extremes, droughts, or recovery from fires

Identification of land cover change

Energy, water and/or CO2 fluxes

Assimilation in land surface models

Assimilation in weather forecast models

Crop productivity, crop stress, irrigation or other agricultural application

Other (please specify)

Question Title

* 5. Strong points of the data products you have been using are: (multiple answers possible)

The spatial resolution

The temporal resolution

Low uncertainty

Known uncertainty

Consistency

Other (please specify)

Question Title

* 6. Which do you consider are bottlenecks of the data products you are using: (multiple answers possible)

Saturation effects occur at higher values of LAI and FAPAR

The spatial resolution

The temporal resolution

Uncertainty of the values

The fact that the uncertainty is unknown

Inconsistencies in the product algorithm/definition with my application, or : It is only directly related to what I really want to know. Effective LAI or true LAI.

The dataset is too sensor-specific.

Lack of documentation.

Difficult access to the data

Other (please specify)