scholarly journals Fractional Cover Mapping of Invasive Plant Species by Combining Very High-Resolution Stereo and Multi-Sensor Multispectral Imageries

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 540 ◽  
Author(s):  
Siddhartha Khare ◽  
Hooman Latifi ◽  
Sergio Rossi ◽  
Sanjay Kumar Ghosh
Keyword(s):  
High Resolution ◽  
Plant Species ◽  
Spatial Resolution ◽  
Spectral Reflectance ◽  
Invasive Plant ◽  
Training Data ◽  
Landsat 8 ◽  
Invasive Plant Species ◽  
Fractional Cover ◽  
Very High

Invasive plant species are major threats to biodiversity. They can be identified and monitored by means of high spatial resolution remote sensing imagery. This study aimed to test the potential of multiple very high-resolution (VHR) optical multispectral and stereo imageries (VHRSI) at spatial resolutions of 1.5 and 5 m to quantify the presence of the invasive lantana (Lantana camara L.) and predict its distribution at large spatial scale using medium-resolution fractional cover analysis. We created initial training data for fractional cover analysis by classifying smaller extent VHR data (SPOT-6 and RapidEye) along with three dimensional (3D) VHRSI derived digital surface model (DSM) datasets. We modelled the statistical relationship between fractional cover and spectral reflectance for a VHR subset of the study area located in the Himalayan region of India, and finally predicted the fractional cover of lantana based on the spectral reflectance of Landsat-8 imagery of a larger spatial extent. We classified SPOT-6 and RapidEye data and used the outputs as training data to create continuous field layers of Landsat-8 imagery. The area outside the overlapping region was predicted by fractional cover analysis due to the larger extent of Landsat-8 imagery compared with VHR datasets. Results showed clear discrimination of understory lantana from upperstory vegetation with 87.38% (for SPOT-6), and 85.27% (for RapidEye) overall accuracy due to the presence of additional VHRSI derived DSM information. Independent validation for lantana fractional cover estimated root-mean-square errors (RMSE) of 11.8% (for RapidEye) and 7.22% (for SPOT-6), and R2 values of 0.85 and 0.92 for RapidEye (5 m) and SPOT-6 (1.5 m), respectively. Results suggested an increase in predictive accuracy of lantana within forest areas along with increase in the spatial resolution for the same Landsat-8 imagery. The variance explained at 1.5 m spatial resolution to predict lantana was 64.37%, whereas it decreased by up to 37.96% in the case of 5 m spatial resolution data. This study revealed the high potential of combining small extent VHR and VHRSI- derived 3D optical data with larger extent, freely available satellite data for identification and mapping of invasive species in mountainous forests and remote regions.

scholarly journals DOES THE DATA RESOLUTION/ORIGIN MATTER? SATELLITE, AIRBORNE AND UAV IMAGERY TO TACKLE PLANT INVASIONS

2016 ◽  
Vol XLI-B7 ◽  
pp. 903-908 ◽  
Author(s):  
Jana Müllerová ◽  
Josef Brůna ◽  
Petr Dvořák ◽  
Tomáš Bartaloš ◽  
Michaela Vítková
Keyword(s):  
Remote Sensing ◽  
Plant Species ◽  
Spectral Resolution ◽  
Invasive Plant ◽  
Plant Invasions ◽  
Economic Feasibility ◽  
Invasive Plant Species ◽  
Trade Offs ◽  
Very High ◽  
Resolution Data

Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

scholarly journals DOES THE DATA RESOLUTION/ORIGIN MATTER? SATELLITE, AIRBORNE AND UAV IMAGERY TO TACKLE PLANT INVASIONS

2016 ◽  
Vol XLI-B7 ◽  
pp. 903-908 ◽  
Author(s):  
Jana Müllerová ◽  
Josef Brůna ◽  
Petr Dvořák ◽  
Tomáš Bartaloš ◽  
Michaela Vítková
Keyword(s):  
Remote Sensing ◽  
Plant Species ◽  
Spectral Resolution ◽  
Invasive Plant ◽  
Plant Invasions ◽  
Economic Feasibility ◽  
Invasive Plant Species ◽  
Trade Offs ◽  
Very High ◽  
Resolution Data

Invasive plant species represent a serious threat to biodiversity and landscape as well as human health and socio-economy. To successfully fight plant invasions, new methods enabling fast and efficient monitoring, such as remote sensing, are needed. In an ongoing project, optical remote sensing (RS) data of different origin (satellite, aerial and UAV), spectral (panchromatic, multispectral and color), spatial (very high to medium) and temporal resolution, and various technical approaches (object-, pixelbased and combined) are tested to choose the best strategies for monitoring of four invasive plant species (giant hogweed, black locust, tree of heaven and exotic knotweeds). In our study, we address trade-offs between spectral, spatial and temporal resolutions required for balance between the precision of detection and economic feasibility. For the best results, it is necessary to choose best combination of spatial and spectral resolution and phenological stage of the plant in focus. For species forming distinct inflorescences such as giant hogweed iterative semi-automated object-oriented approach was successfully applied even for low spectral resolution data (if pixel size was sufficient) whereas for lower spatial resolution satellite imagery or less distinct species with complicated architecture such as knotweed, combination of pixel and object based approaches was used. High accuracies achieved for very high resolution data indicate the possible application of described methodology for monitoring invasions and their long-term dynamics elsewhere, making management measures comparably precise, fast and efficient. This knowledge serves as a basis for prediction, monitoring and prioritization of management targets.

Reference Data and Methods for Validation of Very High Resolution Optical Data Within ESA / EDAP Project

2021 ◽  
Author(s):  
Sébastien Saunier
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Spatial Resolution ◽  
Reference Data ◽  
Test Site ◽  
Optical Data ◽  
Surface Model ◽  
Landsat 8 ◽  
Validation Process ◽  
Very High

<p>In this paper, the authors propose to describe the methodologies developed for the validation of Very High-Resolution (VHR) optical missions within the Earthnet Data Assessment Pilot (EDAP) Framework.  The use of surface-based, drone, airborne, and/or space-based observations to build calibration reference is playing a fundamental role in the validation process. A rigorous validation process must compare mission data products with independent reference data suitable for the satellite measurements. As a consequence, one background activity within EDAP is the collection, the consolidation of reference data of various nature depending on the validation methodology.</p><p>The validation methodologies are conventionally divided into three categories; i.e. validations of the measurement, the geometry and the image quality. The validation of the measurement requires an absolute calibration reference. This latter on is built up by using either in situ measurements collected with RadCalNet[1] stations or by using space based observations performed with “gold” mission (Sentinel-2, Landsat-8) over Pseudo Invariant Calibration Site (PICS). For the geometric validation, several test sites have been set up. A test site is equipped with data from different reference sources. The full usability of a test site is not systematic. It depends on the validation metrics and the specifications of the sensor, particularly the spatial resolution and image acquisition geometry. Some existing geometric sites are equipped with Ground Control Point (GCP) set surveyed by using Global Navigation Satellite System (GNSS) devices in the field.  In some cases, the GCP set comes in support to the refinement of an image observed with drones in order to produce a raster reference, subsequently used to validate the internal geometry of images under assessment. Besides, a limiting factor in the usage of VHR optical ortho-rectified data is the accuracy of the Digital Surface Model (DSM) / Digital Terrain Model (DTM). In order to separate errors due to terrain elevation and error due to the sensor itself, some test sites are also equipped with very accurate Light Detection and Ranging (LIDAR) data.</p><p>The validation of image quality address all aspect related to the spatial resolution and is strongly linked to both the measurement and the geometry. The image quality assessments are performed with both qualitative and quantitative approaches. The quantitative approach relies on the analysis of artificial ground target images and lead to the estimate of Modulation Transfer Function (MTF) together with additional image quality parameters such as Signal to Noise Ratio (SNR). On the other hand, the qualitative approach assesses the interpretability of input images and leads to a rating scaling[2] which is strongly related to the sensor Ground Resolution Distance (GRD). This visual inspection task required a database including very detailed image of man-made objects. This database is considered within EDAP as a reference.</p><div> <div> <p>[1] https://www.radcalnet.org</p> </div> <div> <p>[2] https://fas.org/irp/imint/niirs.htm</p> </div> </div>

scholarly journals Invasion landscapes as social‐ecological systems: Role of social factors in invasive plant species control

2021 ◽  
Author(s):  
Johanna Yletyinen ◽  
George L. W. Perry ◽  
Olivia R. Burge ◽  
Norman W. H. Mason ◽  
Philip Stahlmann‐Brown
Keyword(s):  
Plant Species ◽  
Social Factors ◽  
Invasive Plant ◽  
Ecological Systems ◽  
Invasive Plant Species ◽  
Social Ecological Systems ◽  
Social Ecological

Valorisation of invasive plant species in the production of polyelectrolytes

2021 ◽  
Vol 167 ◽  
pp. 113476
Author(s):  
Ricardo Almeida ◽  
Fernando Cisneros ◽  
Cátia V.T. Mendes ◽  
Maria Graça V.S. Carvalho ◽  
Maria G. Rasteiro ◽  
...  
Keyword(s):  
Plant Species ◽  
Invasive Plant ◽  
Invasive Plant Species
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