Download Mapping and modeling weed risk expansion

Christina Fotiou
Mapping and modeling weed risk expansion; looking into the future
GIS mapping technology is a powerful tool to model weed species distribution. In this study,
we chose a number of weeds that are resistant to herbicides and modeled their distribution, in
two countries, Greece and Germany, differing in their bioclimatic conditions. Weed species are
harmful for the cultivations and need management plans. Hence, it is important to create maps
depicting their distribution under differing environmental, such as land cover, altitude, soil etc.
and bioclimatic variables in current and future conditions.
To monitor the species, it is important to investigate how they are related with landscape
characteristics and vegetation. A path for finding such relationships is to use Remote Sensing
data, specifically the Normalized Difference Vegetation Index (NDVI), an index related with
vegetation density. The assessment of their expansion risk also involved methods exposing
factors affecting species distribution. Lastly, prediction models of species future distribution
were produced.
Most of the species studied are related with low vegetated areas. The core factors affecting
species current distribution in Greece are mean temperature, and annual precipitation, whereas
altitude in Germany. Concerning, species distribution in future climatic conditions, there is a
general tendency for them to move to higher altitudes, minimizing their population size.
However, in Germany, summer weeds whereas in Greece, winter weeds are promoted by
climatic changes.
The models and maps produced in this study could be used as a monitoring tool by farmers
that wish to find new areas of cultivations and/or learn how their current agricultural areas will
respond concerning weeds in the next few decades. Moreover, crop science and crop
protection companies could be supplied by useful maps and information that combined with
crop maps can become a powerful management tool, in order to find new innovative crop
protection solutions.
Keywords: Physical Geography and Ecosystem Analysis; GIS; NDVI; Regression Analysis;
Habitat; Herbicide Resistant Weeds; Climate Change; Crop protection
Advisor: Karin Hall
Master Degree Project 30 credits in Geographical Information Sciences, 2014
Original title: Evaluating habitat suitability and spectral heterogeneity models to predict weed species presence
Department of Physical Geography and Ecosystem Sciences, Lund University. LUMA-GIS thesis nr 26