Cite as:
Wallis, C. (2017): <b>Prediction map of litterfall productivity.</b> <i>Available online ( from DFG-FOR816dw.</i>

Resource Description

Title: Prediction map of litterfall productivity
Short Name: Litter productivity
FOR816dw ID: 1656
Publication Date: 2017-09-03
Last Update Date: 2017-09-03
License and Usage Rights: PAK 823-825 data user agreement. (
Temporal Coverage:
Begin: 2016-11-03
End: 2016-11-03
Geographic Coverage:
Geographic Description: South Ecuador
Bounding Coordinates:
- lon/lat [degrees]
- WGS 84
North: Information not publicly available, please log in. Max: 3200.0 ( meter )
West: Information not publicly available, please log in. East: Information not publicly available, please log in. Elevation
South: Information not publicly available, please log in. Min: 550.0 ( meter )
Dataset Owner(s):
Individual: Christine Wallis
Associated Person(s):
Individual: Jürgen Homeier
Individual: Jörg Bendix
We modeled forest productivity parameters by remote sensing metrics derived from a Landsat-8 image and four Aster elevation images in the mountain rainforest of Southern Ecuador. The validated model for annual litterfall accounted for 68 % in variation of productivity. The partial least square regression model has been predicted across the study area. Non-forest areas have been masked out (using the land cover classification of Göttlicher et al. (2009). Attention this is work in progress. For further information please contact.
| model output | litterfall | remote sensing | Partial least-square regression | forest productivity |
Associated entities to this dataset:
-------- 1 . spatial raster entity --------
Raster Name: AnnualLitterProductionEstMap
Tech. Details ...
Attribute(s) ...
Metadata Provider:
Individual: Christine Wallis
Contact Person:
Individual: Christine Wallis
Online Distribution:
Download File:
Data Publisher:
Organization: DFG-FOR816 Data Warehouse - University of Marburg, Department of Geography

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