18/05/2019

Multisource Forest Inventory


  • ORGANISATION/COMPANY
    Institut de l'Information Géographique et Forestière
  • RESEARCH FIELD
    Engineering
    Environmental scienceEcology
    Mathematics
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
    Recognised Researcher (R2)
    Established Researcher (R3)
    Leading Researcher (R4)
  • APPLICATION DEADLINE
    18/07/2019 00:00 - Europe/Brussels
  • LOCATION
    France › Nancy
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time

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The main objective of the French National Inventory (NFI) is to provide continuous evaluation of forest resources and their evolutions. The sampling design is set up to produce estimates at the national and regional scales, and to contribute to forest policies and their evaluation. With the development of bio-economy, there is a need to provide information at a finer scale, i.e. the forest territories. 

Multisource inventory methods were developed to provide more precise estimations of forest attributes at those operational scales. Multisource inventory methods rely, through appropriate statistical methods, on the combination of field plot data, precise but punctual, with auxiliary data, that are spatially continuous but providing information at a lower precision. Such a combination allows providing precise estimates of forest attributes at smaller scales, with a limited cost.

The establishment of such method in France faces multiple difficulties. French forests are among the more diverse of Europe, due to the topographical and climatic gradients found over the country, and to the diversity of forest management practices. Such diversity requires adapting the methods to the landscape properties, with expected impacts on the genericity of the approach and the precision gains within the various territories.

The main objective of this doctoral research is to contribute to the development of the first multisource inventory approach adapted to the French forest. To do so, the research will benefits from auxiliary data available over the whole territory and regularly updated, like aerial photograph covers, among others.

The detailed objectives are :

-        To optimize the selection of auxiliary data. Current methods rely on the forest map, 3D models derived from aerial photos and high-resolution satellite images (i.e. Landsat). The objective will be to test the potential of data describing climate (temperatures, rainfalls) and biochemical and biophysical soil properties (pH, C/N, water storage capacity, hydromorphy). We will also consider times series of forest structure (diachronic 3D model generated form aerial photographs), and spectral properties of forest canopies (times series of vegetation indices). 

-        To estimate the precision gains with respect to the forest complexity. Emphasize will be given to estimate wood resource per diameter classes, as well as flux variables, which are mandatory for sustained forest management.  Flux estimates will be further used in an innovative application related to sanitary crises. The goal will be to quantify forest resources impacted by bark beetle in the Eastern part of France.

-        To develop statistical estimators coherent with those in use by the French NFI. A first step will be to harmonize the forest area estimations from the NFI and from the forest map. A second step will be to develop statistical estimators compatible with the one the NFI, to compute precision gains. 

The PhD will benefit from the NFI field data and auxiliary data acquired by IGN (forest map, Lidar and aerial photograph coverages), over the Vosges department (~ 6000 km2) and a territory of lowland hardwood forests in center of France (Sologne, 7500 km2). It will also benefit from high-resolution predictive maps of soil properties produced by the research unit Silva.

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Offer Requirements

Specific Requirements

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Map Information

Job Work Location Personal Assistance locations
Work location(s)
1 position(s) available at
Institut de l'Information Géographique et Forestière
France
Nancy

EURAXESS offer ID: 409275
Posting organisation offer ID: 85576

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