Mapping giant salvinia with satellite imagery and image analysis

  title={Mapping giant salvinia with satellite imagery and image analysis},
  author={James H. Everitt and Reginald S. Fletcher and Howard S. Elder and C. Yang},
  journal={Environmental Monitoring and Assessment},
QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands), normal color (blue, green and red bands), and four-band composite (blue, green, red, and near-infrared bands) images were studied. Unsupervised image analysis was used to classify the imagery… 

Evaluating Airborne Multispectral Digital Video to Differentiate Giant Salvinia from Other Features in Northeast Texas

Aerial multispectral digital videography has potential as a remote sensing tool for differentiating giant salvinia from other terrestrial and aquatic features.

Comparison of Broadband and Hyperspectral Sensors for Lantana Mapping

Remote sensing provides a useful tool for mapping invasive species across large areas. This study compared the effectiveness of imagery derived from three multi-spectral (Landsat Thematic Mapper

Evaluation and Comparison of QuickBird and ADS40-SH52 Multispectral Imagery for Mapping Iberian Wild Pear Trees (Pyrus bourgaeana, Decne) in a Mediterranean Mixed Forest

The availability of images with very high spatial and spectral resolution from airborne sensors or those aboard satellites is opening new possibilities for the analysis of fine-scale vegetation, such

Using remote sensing indices to evaluate habitat intactness in the Bushbuckridge area : a key to effective planning

Anthropological influences are threatening the state of many savanna ecosystems in most rural landscapes around the world. Effective monitoring and management of these landscapes requires up to date


Aquatic macrophytes (AM) can serve as useful indicators of water pollution along the littoral zones. The spectral signatures of various AM were investigated to determine whether species could be

Mapping and Estimating Weeds in Cotton Using Unmanned Aerial Systems-Borne Imagery

In recent years, Unmanned Aerial Systems (UAS) have emerged as an innovative technology to provide spatio-temporal information about weed species in crop fields. Such information is a critical input

Mapping invasive plant Prosopis juliflora in arid land using high resolution remote sensing data and biophysical parameters

In this study, high resolution remote sensing data is used to extract Prosopis juliflora (P.juliflora), which is a major invader in the study area. Support Vector Machine (SVM) classification is

Mesquite encroachment impact on southern New Mexico rangelands: remote sensing and geographic information systems approach

Honey mesquite (Prosopis glandulosa Torr.) invasion can negatively impact grazing capacity, spatial livestock distribution, and forage production in Chihuahuan Desert rangelands. High spatial

Remote sensing applications : understanding the landscape ecology of invasive para grass (Urochloa mutica) on monsoonal wetlands, Kakadu National Park, Australia

Invasive para grass (Urochloa mutica), is widespread on monsoonal wetlands of Northern Australia, including World Heritage listed Kakadu National Park (KNP). A rational spatial framework is required

Effects of class granularity and cofactors on the performance of unsupervised classification of wetlands using multi-spectral aerial photography

This research focuses on improving image analysis using multi-spectral aerial photography and unsupervised classification with a high number of classes. A range of class numbers (15 to 240) were



Remote Sensing of Giant Reed with QuickBird Satellite Imagery

QuickBird high resolution (2.8 m) satellite imagery was evaluated for distinguishing giant reed ( Arundo donax L.) infestations along the Rio Grande in southwest Texas. The imagery had four bands

Remote sensing of giant salvinia in Texas waterways

Giant salvinia (Salvinia molesta Mitchell) is an invasive aquatic fern that has been discovered at several locations in southeast Texas. Field reflectance measurements were made on two classes of

Using Aerial Color‐infrared Photography and QuickBird Satellite Imagery for Mapping Wetland Vegetation

Abstract Aerial color‐infrared (CIR) photography and QuickBird high resolution (2.8 m) false color satellite imagery were evaluated for differentiating among wetland vegetation in two freshwater

Remote Sensing of Broom Snakeweed (Gutierrezia sarotbrae) and Spiny Aster (Aster spinosus)l

Computer-based image analyses of color-infrared film positive transparencies showed that broom snakeweed and spiny aster infestations could be quantitatively differentiated from associated rangeland species.

A Comparison Between Multi-Spectral and Hyperspectral Platforms for Early Detection of Leafy Spurge in Southeastern Idaho

  • Environmental Science, Mathematics
  • 2006
Knowledge of the distribution of invasive plants and early detection of these species is critical for both short and long-term management of ecological systems. This study compared the quality of

Classification of wetland habitat and vegetation communities using multi-temporal Ikonos imagery in southern Saskatchewan

The Prairie Habitat Monitoring Program, led by Environment Canada, is tasked with assessing and monitoring landscapes for waterfowl and other migratory birds in Manitoba, Saskatchewan, and Alberta.

Successful biological control of the floating weed salvinia

Successful control of the largest salvinia infestation in Australia using the beetle Cyrtobagous singularis Hustache (Curculionidae) is reported and it is suggested why this beetle has potential for controlling salvinian infestations elsewhere.

Assessing the accuracy of remotely sensed data : principles and practices

This chapter discusses Accuracy Assessment, which examines the impact of sample design on cost, statistical Validity, and measuring Variability in the context of data collection and analysis.