Wide-area mapping of invasive species propagation and containment zones in somaliland using phenometric trends and generalized linear modelling

Spatial information on the occurrence and propagation of invasive species is imperative in order to manage their risk and spread. In this contribution we used phenology and vegetation productivity trends (2001 to 2014) from 250-meter MODIS (Moderate Resolution Imaging Spectroradiometer) EVI (Enhanced Vegetation Index) time-series data to map propagation and possible containment areas for Prosopis juliflora and Parthenium hysterophorus in western Somaliland (eastern Africa). Generalized Linear Modeling (GLM) with a binomial logistics function was used to link available reference data (Landsat-based) on both invasive species to the MODIS-based vegetation trends. Spread corridors and containment zones were, furthermore, identified for both species. Variable relevance in GLM showed that the variables ‘EVI trend’ and ‘peak value’ were highly relevant for P juliflora (log odds ratio >200, p<0.001 and regression estimate >|5|). Riverside and peri-urban areas were identified as important propagation and risk zones.

[1]  Claire Spottiswoode,et al.  A survey for the Critically Endangered Liben Lark Heteromirafra archeri in Somaliland, north-western Somalia , 2015 .

[2]  S. Cleaveland,et al.  Lessons from the 2006-2007 Rift Valley fever outbreak in East Africa: implications for prevention of emerging infectious diseases , 2008 .

[3]  G. Henebry,et al.  Land surface phenology, climatic variation, and institutional change: Analyzing agricultural land cover change in Kazakhstan , 2004 .

[4]  Michele Meroni,et al.  Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[5]  Petr Pyšek,et al.  Competition among native and invasive Impatiens species: the roles of environmental factors, population density and life stage , 2015, AoB PLANTS.

[6]  Tobias Landmann,et al.  Mapping vegetation productivity dynamics and degradation trends over East Africa using a decade of medium Resolution MODIS time-series data , 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

[7]  Alfredo Huete,et al.  Land surface phenological response to decadal climate variability across Australia using satellite remote sensing , 2014 .

[8]  Jessica J. Walker,et al.  Mapping Presence and Predicting Phenological Status of Invasive Buffelgrass in Southern Arizona Using MODIS, Climate and Citizen Science Observation Data , 2016, Remote. Sens..

[9]  Benjamin F. Zaitchik,et al.  Classifying rangeland vegetation type and coverage from NDVI time series using Fourier Filtered Cycle Similarity , 2005 .

[10]  M. Gichua,et al.  Invasive species in east Africa: current status for informed policy decisions and management , 2014 .

[11]  R. L. Hadden.  The Geology of Somalia: A Selected Bibliography of Somalian Geology, Geography and Earth Science. , 2011 .

[12]  P. Eilers,et al.  Evaluating the effectiveness of smoothing algorithms in the absence of ground reference measurements , 2011 .

[13]  B. Bradley.  Remote detection of invasive plants: a review of spectral, textural and phenological approaches , 2014, Biological Invasions.

[14]  Sally Archibald,et al.  Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa , 2011 .

[15]  Jan-Peter Mund,et al.  Phenomapping of rangelands in South Africa using time series of RapidEye data , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[16]  K. Dhileepan,et al.  How widespread is Parthenium hysterophorus and its biological control agent Zygogramma bicolorata in South Asia , 2009 .

[17]  L. W. Strathie,et al.  Current and potential geographical distribution of the invasive plant Parthenium hysterophorus (Asteraceae) in eastern and southern Africa. , 2011 .

[18]  J. Obiri,et al.  Invasive plant species and their disaster-effects in dry tropical forests and rangelands of Kenya and Tanzania , 2011 .

[19]  Per Jönsson,et al.  TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..