Development of a unified framework for environmental monitoring based on a global sampling grid system (GSG)
Final Report Abstract
Environmental monitoring has been emerging as key factor in many international and national processes related to ecological and environmental challenges. At the same time the increasing availability of large archives of freely available high resolution and geo-referenced imagery through virtual globes like Google Earth, Microsoft Virtual Earth (bing) or NASA World Wind and others is still relatively underexploited by scientific applications in this global environmental monitoring context. In this project we tested the suitability of a global sampling grid for the assessment of land cover and land use. We generated different observation designs for visual interpretations of high resolution remote sensing imagery and compared their performance against each other. Further, we developed an R package and Shiny Server interface that allows generating sampling grids based on a discrete global grid system (GSG) and observation units based on point clusters of different extent and spatial configuration. In context of multiple case studies we collected data on land cover and land use in a project area in Indonesia (Sumatra), Eritrea, India and Germany. It turned out that the Openforis Collect Earth toolbox is a very useful interface for the collection of data, while the generation of grids and observation units is done with the application developed in this project. For some cases the data collection was straightforward and results were promising, however, a larger study on global forest cover was not successful because of remaining limitations in regard to image resolution over large forest areas around the world. About the configuration of observation units, we found that clusters of points are much more efficient for on screen data collection than digitizing land cover in fixed area plots. The required time consumption per plot (and the technical complexity that is required for such digitizing options) is simply too high and makes such digitizing exercises very inefficient compared to point clusters. Finally we conclude that the presented GSG is an easy to communicate and useful grid system for environmental monitoring.
Publications
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2015. A unified framework for environmental monitoring based on a discrete global sampling grid (GSG) system. In: Bridging the gap between information needs and forest inventory capacity. Proceedings of the 5th international DAAD workshop, Durban and Pietermaritzburg, South Africa, 06.-13.09.2015, P. 99-111, ISBN 978-3-7369-9497-3
Fehrmann, L.
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2019. A unified framework for land cover monitoring based on a discrete global sampling grid (GSG). Environmental Monitoring and Assessment 191:46
Fehrmann, L., Kukunda, C.B., Nölke, N., Schnell, S., Seidel, D., Magnussen, S., Kleinn, C.
