Mapping of the Invasive Species Hakea sericea Using Unmanned Aerial Vehicle (UAV) and WorldView-2 Imagery and an Object-Oriented Approach

Invasive plants are non-native species that establish and spread in their new location, generating a negative impact on the local ecosystem and representing one of the most important causes of the extinction of local species. The first step for the control of invasion should be directed at understanding and quantification of their location, extent and evolution, namely the monitoring of the phenomenon. In this sense, the techniques and methods of remote sensing can be very useful. The aim of this paper was to identify and quantify the areas covered by the invasive plant Hakea sericea using high spatial resolution images obtained from aerial platforms (Unmanned Aerial Vehicle: UAV/drone) and orbital platforms (WorldView-2: WV2), following an object-oriented image analysis approach. The results showed that both data were suitable. WV2reached user and producer accuracies greater than 93% (Estimate of Kappa (KHAT): 0.95), while the classifications with the UAV orthophotographs obtained accuracies higher than 75% (KHAT: 0.51). The most suitable data to use as input consisted of using all of the multispectral bands that were available for each image. The addition of textural features did not increase the accuracies for the Hakea sericea class, but it did for the general classification using WV2.

[1]  Stephen Pike,et al.  Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK) , 2011, Remote. Sens..

[2]  Yubo Liang,et al.  Distribution of Spartina spp. along China's coast , 2012 .

[3]  K. Esler,et al.  A landscape-scale assessment of the long-term integrated control of an invasive shrub in South Africa , 2009, Biological Invasions.

[4]  Jana Müllerová,et al.  Remote sensing as a tool for monitoring plant invasions: Testing the effects of data resolution and image classification approach on the detection of a model plant species Heracleum mantegazzianum (giant hogweed) , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[5]  D. Richardson,et al.  Ecology and management of alien plant invasions in South African fynbos: Accommodating key complexities in objective decision making , 2009 .

[6]  J. Dubois,et al.  Evaluation Of The Grey-level Co-occurrence Matrix Method For Land-cover Classification Using Spot Imagery , 1990 .

[7]  D. Richardson,et al.  The effects of alien shrub invasions on vegetation structure and fire behaviour in South African fynbos shrublands: a simulation study. , 1985 .

[8]  Ali Shamsoddini,et al.  Pine plantation structure mapping using WorldView-2 multispectral image , 2013 .

[9]  S. Cirujano,et al.  Cartografía de la superficie invadida por azolla filiculolides en el parque nacional de doñana mediante imágenes landsat. , 2009 .

[10]  James M. Keller,et al.  A fuzzy K-nearest neighbor algorithm , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  R. Hall,et al.  Incorporating texture into classification of forest species composition from airborne multispectral images , 2000 .

[12]  N. Coops,et al.  Mapping the distributions of two invasive plant species in urban areas with advanced remote sensing data , 2016 .

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

[14]  H. Gerós,et al.  Phosphate transport by proteoid roots of Hakea sericea , 2007 .

[15]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[16]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[17]  U. Benz,et al.  Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information , 2004 .

[18]  Jiaping Wu,et al.  Monitoring the Invasion of Spartina alterniflora from 1993 to 2014 with Landsat TM and SPOT 6 Satellite Data in Yueqing Bay, China , 2015, PloS one.

[19]  P. Pyšek,et al.  Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring , 2017, Front. Plant Sci..

[20]  E. Marchante,et al.  Big troubles are already here: risk assessment protocol shows high risk of many alien plants present in Portugal , 2017 .

[21]  Sunil Kumar,et al.  Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[22]  Arko Lucieer,et al.  apping invasive Fallopia japonica by combined spectral , spatial , and temporal nalysis of digital orthophotos , 2012 .

[23]  Manuel A. Aguilar,et al.  Non-Parametric Object-Based Approaches to Carry Out ISA Classification From Archival Aerial Orthoimages , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[24]  D. Richardson,et al.  Aspects of the reproductive ecology of four australian Hakea species (Proteaceae) in South Africa , 1987, Oecologia.

[25]  Jeff Sauro,et al.  Estimating Completion Rates from Small Samples Using Binomial Confidence Intervals: Comparisons and Recommendations , 2005 .

[26]  Stephen R. Yool,et al.  Plant invasions in dynamic desert landscapes. A field and remote sensing assessment of predictive and change modeling , 2008 .

[27]  Huamei Huang,et al.  A study of the population dynamics of Spartina alterniflora at Jiuduansha shoals, Shanghai, China. , 2007 .

[28]  J. Pergl,et al.  Aerial photographs as a tool for assessing the regional dynamics of the invasive plant species Heracleum mantegazzianum , 2005 .

[29]  Frédéric Achard,et al.  The Potential of Sentinel Satellites for Burnt Area Mapping and Monitoring in the Congo Basin Forests , 2016, Remote. Sens..

[30]  M. Baatz,et al.  Progressing from object-based to object-oriented image analysis , 2008 .

[31]  Clement Atzberger,et al.  Assessing the Potential of Sentinel-2 and Pléiades Data for the Detection of Prosopis and Vachellia spp. in Kenya , 2017, Remote. Sens..

[32]  P. Fernandes,et al.  Changes in wildfire severity from maritime pine woodland to contiguous forest types in the mountains of northwestern Portugal , 2010 .

[33]  G. Mallinis,et al.  Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of Greece , 2018 .

[34]  Nikos Koutsias,et al.  Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site , 2008 .

[35]  Manuel A. Aguilar,et al.  Influence of Data Source and Training Size on Impervious Surface Areas Classification Using VHR Satellite and Aerial Imagery Through an Object-Based Approach , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[36]  James H. Everitt,et al.  Use of Remote Sensing for Detecting and Mapping Leafy Spurge (Euphorbia esula) , 1995, Weed Technology.

[37]  CLASIFICACIÓN ORIENTADA A OBJETOS EN FOTOGRAFÍAS AÉREAS DIGITALES PARA LA DISCRIMINACIÓN DE USOS DEL SUELO , 2009 .

[38]  Roberta E. Martin,et al.  Multi-trophic invasion resistance in Hawaii: bioacoustics, field surveys, and airborne remote sensing. , 2007, Ecological applications : a publication of the Ecological Society of America.

[39]  Philippe C. Baveye,et al.  Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using quickbird satellite imagery , 2008 .

[40]  D. P. Groeneveld,et al.  Near‐infrared discrimination of leafless saltcedar in wintertime Landsat TM , 2008 .

[41]  Tomaž Podobnikar,et al.  Recognition of the invasive species Robinia pseudacacia from combined remote sensing and GIS sources , 2012 .

[42]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[43]  Fuan Tsai,et al.  Texture augmented analysis of high resolution satellite imagery in detecting invasive plant species , 2006 .

[44]  Barry R. Middleton,et al.  Vegetation Burn Severity Mapping Using Landsat-8 and WorldView-2 , 2015 .

[45]  David Aragonés,et al.  Hyperspectral Sensors as a Management Tool to Prevent the Invasion of the Exotic Cordgrass Spartina densiflora in the Doñana Wetlands , 2016, Remote. Sens..

[46]  Mingming Jia,et al.  Monitoring the Invasion of Spartina alterniflora Using Multi-source High-resolution Imagery in the Zhangjiang Estuary, China , 2017, Remote. Sens..

[47]  Johan Baard,et al.  Alien flora of the Garden Route National Park, South Africa , 2014 .

[48]  H. Jones,et al.  Remote Sensing of Vegetation: Principles, Techniques, and Applications , 2010 .

[49]  Russell Congalton,et al.  Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Second Edition , 1998 .

[50]  G G Forsyth,et al.  The prioritisation of invasive alien plant control projects using a multi-criteria decision model informed by stakeholder input and spatial data. , 2012, Journal of environmental management.

[51]  C. V. D. Sande,et al.  A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment , 2003 .

[52]  André Große-Stoltenberg,et al.  Evaluation of Continuous VNIR-SWIR Spectra versus Narrowband Hyperspectral Indices to Discriminate the Invasive Acacia longifolia within a Mediterranean Dune Ecosystem , 2016, Remote. Sens..

[53]  Gregory Asner,et al.  Applications of Remote Sensing to Alien Invasive Plant Studies , 2009, Sensors.

[54]  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..

[55]  Thomas Blaschke,et al.  Object based image analysis for remote sensing , 2010 .

[56]  H. Freitas,et al.  Exotic naturalized flora of continental Portugal – A reassessment , 2006 .

[57]  Paulo Mateus,et al.  Forest Fires in Portugal: Dynamics, Causes and Policies , 2014 .

[58]  James H. Everitt,et al.  Using Spatial Information Technologies to Map Chinese Tamarisk (Tamarix chinensis) Infestations , 1996, Weed Science.

[59]  D. Fuller.  Remote detection of invasive Melaleuca trees (Melaleuca quinquenervia) in South Florida with multispectral IKONOS imagery , 2005 .

[60]  F. Rego,et al.  Wildfires and landscape dynamics in Portugal: a regional assessment and global implications , 2014 .

[61]  Philip E. Hulme,et al.  Biological invasions: winning the science battles but losing the conservation war? , 2003, Oryx.