Linking ecophysiology and forest productivity: An overview of the ECOLEAP project

1999 ◽  
Vol 75 (3) ◽  
pp. 417-421 ◽  
Author(s):  
P. Y. Bernier ◽  
R. A. Fournier ◽  
C. H. Ung ◽  
G. Robitaille ◽  
G. R. Larocque ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Process Model ◽  
Spatial Databases ◽  
Net Primary Productivity ◽  
Forest Productivity ◽  
Forest Service ◽  
Service Research ◽  
Spatially Explicit ◽  
Quebec City ◽  
Environmental Controls

ECOLEAP is a Canadian Forest Service research project that is aimed at improving our understanding of the environmental controls on boreal and sub-boreal forest productivity and at developing tools for predicting stand-level forest productivity over large areas. This interdisciplinary project combines, in a coordinated manner, ecophysiological and soils research, remote sensing research, development of scaling up procedures and process modelling of net primary productivity on a common set of field sites. The process research is carried out in different forest types across large climatic and productivity gradients. Remote sensing provides timely stand information such as composition, leaf area, and absorbed radiation that are not currently available in existing spatial databases. A geographic information system is used to integrate the diverse sources of data. Models serve both as integrators of knowledge and as vehicles for the transfer of the information and methodologies to resource managers. Currently there are three interrelated modelling exercises being carried out within ECOLEAP to address different objectives of the project: an empirical, spatially explicit model of site index, a site-specific process model of productivity, and a spatially explicit process model of productivity. Application of the spatially explicit models will be conducted on extensive pilot regions, the first of which is located north of Quebec City. Key words: modelling, GIS, remote sensing, Canadian Forest Service

scholarly journals Drone-Based Remote Sensing for Research on Wind Erosion in Drylands: Possible Applications

2021 ◽  
Vol 13 (2) ◽  
pp. 283
Author(s):  
Junzhe Zhang ◽  
Wei Guo ◽  
Bo Zhou ◽  
Gregory S. Okin
Keyword(s):  
Remote Sensing ◽  
Wind Erosion ◽  
Field Measurements ◽  
Spatially Explicit ◽  
Surface Model ◽  
High Resolution Imagery ◽  
Soil Elevation ◽  
3D Photogrammetry ◽  
Using Data ◽  
Sample Set

With rapid innovations in drone, camera, and 3D photogrammetry, drone-based remote sensing can accurately and efficiently provide ultra-high resolution imagery and digital surface model (DSM) at a landscape scale. Several studies have been conducted using drone-based remote sensing to quantitatively assess the impacts of wind erosion on the vegetation communities and landforms in drylands. In this study, first, five difficulties in conducting wind erosion research through data collection from fieldwork are summarized: insufficient samples, spatial displacement with auxiliary datasets, missing volumetric information, a unidirectional view, and spatially inexplicit input. Then, five possible applications—to provide a reliable and valid sample set, to mitigate the spatial offset, to monitor soil elevation change, to evaluate the directional property of land cover, and to make spatially explicit input for ecological models—of drone-based remote sensing products are suggested. To sum up, drone-based remote sensing has become a useful method to research wind erosion in drylands, and can solve the issues caused by using data collected from fieldwork. For wind erosion research in drylands, we suggest that a drone-based remote sensing product should be used as a complement to field measurements.

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