Remote detection of giant reed invasions in riparian habitats: challenges and opportunities for management planning

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1 Remote detection of giant reed invasions in riparian habitats: challenges and opportunities for management planning Maria do Rosário Pereira Fernandes Forest Research Centre, University of Lisbon

2 Number of articles (SCI) Remote sensing of invasive species 60 Evolution of "Remote Sensing Invasive Species" articles in ISI WEB Large scale analysis Systematic monitorizations Early detection Potencial distribution

3 Which is the most appropriate remote sensing approach to map alien invasive species? Q1. It is possible to distinguish the invasive species from the surrounding vegetation? Image type - spectral resolution and acquisition time Q2. What is the smallest invasive patch size that must be mapped? Image type - spatial resolution Remote Sensing Approach = Image type + Method of image analysis

4 Q1- To distinguish the invasive species from the surrounding vegetation A- Phenological traits - flowers and bracts, plant pubescence, plant distinct greenup/senescence, fall coloration B- Structural traits - spatial arrangement (patches or clumps), plant height, canopy density and architecture Yellow flowers of Acacia longifolia C- Physiological and Biochemical traits - water and chlorophyll contents, structural carbohydrate molecules (lignin and cellulose) Photo:Francisca Aguiar White panicle of pampas grass (Cortaderia selloana)

5 Q2- To select the appropriate spatial resolution Image Spatial Resolution = one-fourth of the area of the smallest patch Pixel size = Patch size Most patches are not detected Pixel size < Patch size Increase the number of patches detected GPS accuracy=one-half of image spatial resolution

6 Platform Type Spatial Resolution (pixel size) Film or digital photography Very high (< 1m) Spectral resolution (number and width bands) Low Panchromatic; (true color image-rgb) or color-infrared RG +NIR) Relative Cost Technical expertise Low Photointerpretation and GIS skills Advantages Appropriate for Invasive species with unique visual characteristics Intuitive and straightforward technique Collected anytime Many vendors Disadvantages May need to georectify Manual classifications (Extensive labor and time-intensive interpretation) Photointerpretation is art! Aircraft (airborne and UAV imagery) Multispectral Very high < 2m Moderate to High < 20 bands Medium (Image pre and posprocessing) Identification of invasive species using spectral characteristics. Possibility of automated classifications May need to georectify Need to coordinated flight acquisition with field measurements (calibration and validation) Hyperspectral High < 5m Very high > 200 bands High (Image pre and posprocessing Identification of invasive species using additional biochemical characteristics. Automated classifications High accuracy in distinguish invasive species Difficult to process Large storage computer requirements Only for local scale monitoring due to small swath width Terrestrial Multispectral to Hyperspectral Very high (< 1m) Variable Up to 2100 bands High High performance of data analysis) Prospective spectral separability analysis for future classifications Only local-scale observations Extensive labor field

7 Platform Type Spatial Resolution (pixel size) Spectral resolution (number and width bands) Relative Cost Technical expertise Advantages Disadvantages Orbital (satellite) Multispectral Passive remote sensing Multispectral Passive remote sensing High-Resolution < 2m (Quick Bird, Ikonos, World- View ; Geo-Eye, SPOT6,7, Sky Sat) Moderate 30 m (Landsat-8, Sentinel-2) European Copernicus Program Moderate (4 to 8 bands) Moderate to High 20 bands Medium (Image posprocessing) Free Medium (Image posprocessing) Appropriate for Invasive species with particular phenological and structural characteristics Automated classifications Appropriate for continuously widespread, dense and monospecific invasions Products radiometrically and geometrically rectified with high revisit period Automated classifications Need to select images in the right season. Sensitive to atmospheric conditions (cloud cover) Difficult to identify invasive species from a mixture of different plants. Need to select images in the right season. Sensitive to atmospheric conditions (cloud cover) Aircraft Or Satellite LiDAR RADARSAT Ative remote sensing Variable (1m- 100m) Pancromatic Variable Medium (Image posprocessing) Appropriate for Invasive species with particular structural characteristics, by analyzing the tri-dimensional (3-D) structure. No spectral information and data only useful with good field knowledge. Insensitive to atmospheric conditions Image Fusion (combination of passive and active remote sensing) Very High < 0.5m Very high > 200 bands Very High (Image pre and pos-processing, multidimensional analysis) Enables the identification of invasive species of different height-levels (overstory and understory) at the very fine spatial scale. High performance computing power Specific software and hardware

8 Giant reed invasions in riparian habitats!

9 Our QUESTIONS It is possible to spectrally distinguish the giant reed (Arundo donax) from the surronding vegetation (herbaceous and woody vegetation)? and from its morphologically similar co-existing species, the common reed (Phragmites australis)?

10 Our QUESTIONS Additionally Does the seasonal variation of Arundo donax affects their spectral separability? and control measures, like mechanical harvesting, affects the spectral separability of Arundo donax?

11 Methods Canopy spectral measurements Field ADS spectrometer Vegetative period Senescent period

12 Methods Surrounding woody vegetation Co-existing species Phragmites australis Common reed N= 330, sites= 5 Surrounding herbaceous vegetation

13 Methods Arundo donax Arundo donax_rac (regenerated after mechanical cutting)

14 Methods Giant reed Common reed Woody Herbaceous Vegetative Senescent RAC Kruskall Wallis + CART

15 Methods Giant reed Common reed Woody Herbaceous Vegetative Senescent RAC

16 Methods Giant reed Common reed Woody Herbaceous Vegetative Senescent RAC

17 Methods Giant reed Common reed Woody Herbaceous Vegetative Senescent RAC

18 Methods Giant reed Common reed Woody Herbaceous Vegetative Senescent RAC

19 Methods Giant reed Common reed Woody Herbaceous Vegetative Senescent Arundo_RAC RAC Highest spectral separability!! (Bhattacharya distance)

20 What we also know Arundo donax invasions in riparian habitats have some peculiar structural characteristics

21 What we also know Invaded areas are characterized by: Unique or Low number of patches Low Number of Patches (NP) Large patches High Mean Patch Size (MPS) Higly connected patches Low Mean Nearest Neighbor (MNN) Simple and linear shapes High Mean Shape Index (MSI)

22 What we also know Near-natural riparian patches have complex forms!!

23 Thus. We combine spectral and spatial information using a Object-Based remote sensing approach to detect Arundo donax invasions in riparian habitats Test the method in two types of images: - Airborne multispectral image (50cm of spatial resolution, 4 bands- RGB-NIR) - Satellite multispectral image (WorldView-2) (2m of spatial resolution, 8 bands, coastal, blue, green, yellow, red, red edge, near infrared1, near infrared2

24 Airborne multispectral image Accuracy = 73% Kappa coefficient Automated classification (Object-based) Manual classification (Field validation)

25 Satellite image (WorldView-2) Accuracy = 77% Kappa coefficient Automated classification (Object-based) Manual classification (Field validation)

26 Conclusions The best remote sensing approach to map giant reed (and all invasive species) must represent a compromise among spatial, spectral, temporal resolution, costs and available expertise! Each weed invasion has a unique solution!! Giant reed is spectrally separable from the surrounding vegetation (woody and herbaceous), in both vegetative and senescent period. No need of hyperspectral images Surrounding landscape with homogeneous patches with clear boundaries - Moderate spectral resolution images (RGB+ NIR) Surrounding landscape with high heterogeneous patchiness High spectral resolution images

27 Conclusions The high spectral separability of Arundo donax_rac can be used to remotely detected new invasions or to performed post-control Arundo donax invasions Temporal analysis - Images with high revisit period Giant reed is only spectrally separable from its co-similar species (Phragmites australis) in the senescent period Need to select images in the optimal period. Low spectral resolution images (RGB). or Combination with ancillary information (contextual) Giant reed stands has some particular spatial characteristics (unique, large, simple and stretched shapes) that can be remotely sensed using a set of geometric attributes Need to combine phenological with structural traits - Very high spatial resolution

28 Thank you for your attention..