Evaluating pixel and object based image classification techniques for mapping plant invasions from UAV derived aerial imagery : Harrisia pomanensis as a case study

Invasive alien plants (IAPs) not only pose a serious threat to biodiversity and water resources but also have impacts on human and animal wellbeing. To support decision making in IAPs monitoring, semi-automated image classifiers which are capable of extracting valuable information in remotely sensed data are vital. This study evaluated the mapping accuracies of supervised and unsupervised image classifiers for mapping Harrisia pomanensis (a cactus plant commonly known as the Midnight Lady) using two interlinked evaluation strategies i.e. point and area based accuracy assessment. Results of the point-based accuracy assessment show that with reference to 219 ground control points, the supervised image classifiers (i.e. Maxver and Bhattacharya) mapped H. pomanensis better than the unsupervised image classifiers (i.e. K-mediuns, Euclidian Length and Isoseg). In this regard, user and producer accuracies were 82.4% and 84% respectively for the Maxver classifier. The user and producer accuracies for the Bhattacharya classifier were 90% and 95.7%, respectively. Though the Maxver produced a higher overall accuracy and Kappa estimate than the Bhattacharya classifier, the Maxver Kappa estimate of 0.8305 is not significantly (statistically) greater than the Bhattacharya Kappa estimate of 0.8088 at a 95% confidence interval. The area based accuracy assessment results show that the Bhattacharya classifier estimated the spatial extent of H. pomanensis with an average mapping accuracy of 86.1% whereas the Maxver classifier only gave an average mapping accuracy of 65.2%. Based on these results, the Bhattacharya classifier is therefore recommended for mapping H. pomanensis. These findings will aid in the algorithm choice making for the development of a semi-automated image classification system for mapping IAPs.The South African National Department of Environment Affairs through its funding of the South African National Biodiversity Institute Invasive Species Programme, project number P038.http://www.elsevier.com/ locate/ isprsjprs2018-07-30hj2018Geography, Geoinformatics and Meteorolog

A new national unit for invasive species detection, assessment and eradication planning

CITATION: Wilson, J. R. U., Ivey, P., Manyama, P. & Nanni, I. 2013. A new national unit for invasive species detection, assessment and eradication planning. South African Journal of Science, 109(5/6), Art. #0111, doi: 10.1590/sajs.2013/20120111.The original publication is available at http://sajs.co.zaEven with no new introductions, the number of biological invasions in South Africa will increase as introduced species naturalise and become invasive. As of 2010 South Africa had ~8750 introduced plant taxa, 660 recorded as naturalised, 198 included in invasive species legislation, but only 64 subject to regular control (i.e. only widespread invaders are managed post-border). There is only one documented example of a successful eradication programme in continental South Africa – against the Mediterranean snail (Otala punctata) in Cape Town. Here we describe the establishment in 2008 of a unit funded by the Working for Water Programme as part of the South African National Biodiversity Institute's Invasive Species Programme (SANBI ISP) designed to (1) detect and document new invasions, (2) provide reliable and transparent post-border risk assessments and (3) provide the cross-institutional coordination needed to successfully implement national eradication plans. As of the end of 2012, the ISP had an annual budget of R36 million, employed 33 staff working across all nine provinces, supported 10 postgraduate students, hosted 35 interns (including those as part of a drive to collect DNA barcodes for all invasive taxa) and created over 50 000 days of work as part of government poverty alleviation programmes. The unit has worked towards full risk assessments for 39 plant taxa and has developed eradication plans for seven species; the unit is now helping implement these plans. By focusing on science-based management and policy, we argue that SANBI ISP can play a leading role in preventing introduced species from becoming widespread invaders.http://sajs.co.za/new-national-unit-invasive-species-detection-assessment-and-eradication-planning/john-r-u-wilson-philip-ivey-phetole-manyama-ingrid-n%C3%A4nniPublisher's versio

Radiometric calibration framework for ultra-high-resolution UAV-derived orthomosaics for large-scale mapping of invasive alien plants in semi-arid woodlands : Harrisia pomanensis as a case study

Orthomosaics derived from consumer grade digital cameras on board unmanned aerial vehicles (UAVs) are increasingly being used for biodiversity monitoring and remote sensing of the environment. To have lasting quantitative value, remotely sensed imagery should be calibrated to physical units of reflectance. Radiometric calibration improves the quality of raw imagery for consistent quantitative analysis and comparison across different calibrated imagery. Moreover, calibrating remotely sensed imagery to units of reflectance improves its usefulness for deriving quantitative biochemical and biophysical metrics. Notwithstanding the existing radiometric calibration procedures for correcting single images, studies on radiometric calibration of UAV-derived orthomosaics remain scarce. In particular, this study presents a cost- and time-efficient radiometric calibration framework for designing calibration targets, checking scene illumination uniformity, converting orthomosaic digital numbers to units of reflectance, and accuracy assessment using in situ mean reflectance measurements (i.e. the average reflectance in a particular waveband). The empirical line method was adopted for the development of radiometric calibration prediction equations using mean reflectance values measured in only one spot within a 97 ha orthomosaic for three wavebands, i.e. red, green and blue of the Sony NEX-7 camera. A scene illumination uniformity check experiment was conducted to establish whether 10 randomly distributed regions within the orthomosaic experienced similar atmospheric and illumination conditions. This methodological framework was tested in a relatively flat terrain semi-arid woodland that is invaded by Harrisia pomanensis (the Midnight Lady). The scene illumination uniformity check results showed that at a 95% confidence interval, the prediction equations developed using mean reflectance values measured from only one spot within the scene can be used to calibrate the entire 97 ha RGB orthomosaic. Furthermore, the radiometric calibration accuracy assessment results showed a correlation coefficient r value of 0.977 (p < 0.01) between measured and estimated reflectance values with an overall root mean square error of 0.063. These findings suggest that given the entire scene being mapped is experiencing similar atmospheric and illumination conditions, then prediction equations developed using mean reflectance values measured in only one spot within the scene can be used to calibrate the entire orthomosaic in semi-arid woodlands. The proposed methodological framework can potentially be tested and adapted for use in large-scale crop mapping and monitoring in precision agriculture, land-use/land-cover classification as well as plant species delimitation, particularly for mapping widespread invasive alien plants such as H. pomanensis.The South African National Department of Environmental Affairs through its funding of the South African National Biodiversity Institute Directorate: Biological Invasions, project number [P038].http://www.tandfonline.com/loi/tres202019-07-03hj2018Geography, Geoinformatics and Meteorolog