Out now!

Integration of ground survey and remote sensing derived data: Producing robust indicators of habitat extent and condition

New paper published: 

Henrys, P.A. and Jarvis, S.G., 2019. Integration of ground survey and remote sensing derived data: Producing robust indicators of habitat extent and condition. Ecology and Evolution.

https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.5376 

The availability of suitable habitat is a key predictor of the changing status of biodiversity. Quantifying habitat availability over large spatial scales is, however, challenging. Although remote sensing techniques have high spatial coverage, there is uncertainty associated with these estimates due to errors in classification. Alternatively, the extent of habitats can be estimated from ground‐based field survey. Financial and logistical constraints mean that on‐the‐ground surveys have much lower coverage, but they can produce much higher quality estimates of habitat extent in the areas that are surveyed. Here, we demonstrate a new combined model which uses both types of data to produce unified national estimates of the extent of four key habitats across Great Britain based on Countryside Survey and Land Cover Map. This approach considers that the true proportion of habitat per km2 (Zi) is unobserved, but both ground survey and remote sensing can be used to estimate Zi. The model allows the relationship between remote sensing data and Zi to be spatially biased while ground survey is assumed to be unbiased. Taking a statistical model‐based approach to integrating field survey and remote sensing data allows for information on bias and precision to be captured and propagated such that estimates produced and parameters estimated are robust  and  interpretable.  A  simulation  study  shows  that  the  combined  model  should  perform  best  when  error  in  the  ground  survey  data  is  low.  We  use  repeat  surveys  to  parameterize  the  variance  of  ground  survey  data  and  demonstrate  that  error in this data source is small. The model produced revised national estimates of broadleaved  woodland,  arable  land,  bog,  and  fen,  marsh  and  swamp  extent  across  Britain in 2007.