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. 2009;9(6):4869-89.
doi: 10.3390/s90604869. Epub 2009 Jun 19.

Applications of remote sensing to alien invasive plant studies

Cho-Ying Huang  1 , Gregory P Asner
Affiliations

Applications of remote sensing to alien invasive plant studies

Cho-Ying Huang et al. Sensors (Basel). 2009.

Abstract

Biological invasions can affect ecosystems across a wide spectrum of bioclimatic conditions. Therefore, it is often important to systematically monitor the spread of species over a broad region. Remote sensing has been an important tool for large-scale ecological studies in the past three decades, but it was not commonly used to study alien invasive plants until the mid 1990s. We synthesize previous research efforts on remote sensing of invasive plants from spatial, temporal and spectral perspectives. We also highlight a recently developed state-of-the-art image fusion technique that integrates passive and active energies concurrently collected by an imaging spectrometer and a scanning-waveform light detection and ranging (LiDAR) system, respectively. This approach provides a means to detect the structure and functional properties of invasive plants of different canopy levels. Finally, we summarize regional studies of biological invasions using remote sensing, discuss the limitations of remote sensing approaches, and highlight current research needs and future directions.

Keywords: biological invasions; high spatial resolution; high temporal resolution; hyperspectral remote sensing; image fusion; light detection and ranging (LiDAR); moderate spatial/spectral resolution.

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Figures

Figure 1.
Figure 1.
(A) The Normalized Difference Vegetation Index (NDVI) time-series data for Native, Mixed, and Eragrostis lehmanniana (ERLE) sites from 2000 to 2005. (B) Spatial variations of NDVI through time among sites demonstrated using the coefficient of variation (CV). (C) Bi-weekly precipitation (bars) and temperature (dotted line) data based upon daily weather records from five stations at the desert grasslands of southern Arizona, USA. Months are evenly divided by four intervals with colors from bright to dark. This figure is adapted from Huang et al. [45] with permission from Taylor & Francis.
Figure 2.
Figure 2.
(A) The Enhanced Vegetation Index (EVI) in October (the Moderate Resolution Imaging Spectroradiometer [MODIS] period 19 and 20) of the extreme wet year (2000) and normal years (2001-2005) for field sites in a semi-arid environment of southern Arizona, USA across a gradient Eragrostis lehmanniana invasion (native grasslands [Native], a mixture of E. lehmanniana and native grasses [Mixed], E. lehmanniana invaded grasslands [ERLE]). (B) Mean October temperature (dashed line) and precipitation (gray bars) from 2000 to 2005 of the study region. This figure is adapted from Huang and Geiger [46] with permission from Wiley-Blackwell.
Figure 3.
Figure 3.
Demonstration of the precision co-alignment and integration of data collected by active (LiDAR) and passive (hyperspectral) remote sensing. This image was collected by the Carnegie Airborne Observatory over a site in Hawaii. The color-coding highlights variation among canopy species and their chemical properties both derived from the hyperspectral data. In this particular example, highly invasive species with unique chemical signatures are shown in red and pink colors, whereas native hardwood forest canopy species are shown in greens and blues. The embedded LiDAR data indicates the height and 3-D structure of each tree crown on the landscape.
Figure 4.
Figure 4.
Fully integrated (A) hyperspectral and (B) LiDAR instrumentation provides a means to filter rainforest canopies into comparable units for mapping invasive species. (C) Simple pre-screening of the data based on a minimum NDVI, here set to 0.8, ensures that only foliated canopies are analyzed (red color). (D) Sun-target-view geometry (here, 20°) and minimum canopy height (here, 5 m) is controlled for using the LiDAR data thus pre-screening for view angle effects (white color). (E) Combined, these filters provide a map of canopies suitable for species determinations and comparison. These example images were collected over a Hawaiian rainforest reserve. Adapted from Asner and Martin [77] with permission from Elsevier.
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