Sentinel-2 data for estimation of forest net primary productivity

M-GEO
M-SE
FORAGES
M-SE Core knowledge areas
Spatial Information Science (SIS)
Spatial Planning for Governance (SPG)
Technical Engineering (TE)
Additional Remarks

• A suitable candidate would be interested in remote sensing and quantification of biophysical variables
• Fieldwork is not necessary; however, possible field visit can be discussed by the supervisor if the student is interested.
 

Topic description

Primary production is the growth or accumulated rate of biomass in plants. Where the overall rate of biomass production in plant is the gross primary productivity, the net primary production is the remaining fraction of biomass after energy losses (respiration) are taken into consideration. Net primary productivity (NPP) is an indicator of ecosystem functioning and a key component in the global carbon budget. Measuring NPP on the ground is difficult and requires a considerable amount of labour and cost. Remotely sensed images can be used to estimate NPP across large areas. NPP of vegetation is often calculated as the product of absorbed photosynthetically active radiation (APAR) and the light use efficiency. Estimation of NPP from remote sensing data has been mainly performed using low/medium resolution data. However, the potential of Sentinel-2 data has not yet been utilized for NPP estimation. It is expected that the use of data from this new sensor would increase NPP estimation accuracy. The estimated NPP can be compared with the field measured NPP or with outputs of other NPP-models.

Topic objectives and methodology

The goal of this study is to examine the Sentinel-2 data to map and model NPP and its spatial variation in a temperate forest in Germany. The student will work with Sentinel-2 high-resolution multispectral satellite images. The student will work with the existing relevant field data (LAI, biomass, flux tower data, etc.) which is available from the Bavarian forest national park in 2016-2017. Further, the student will become familiar with pre-processing of the data. Several remote sensing-based NPP models have been developed in the literature, however, the student may benefit from the Monteith model to drive the NPP. Once the model is established the estimated NPP can be validated using the field data or results from other NPP models such as Landsat. The NPP map of the study area will then be generated.