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Improved Remote Sensing Methods to Detect Northern Wild Rice (Zizania palustris L.)
- Source :
- Remote Sensing; Volume 12; Issue 18; Pages: 3023, Remote Sensing, Vol 12, Iss 3023, p 3023 (2020)
- Publication Year :
- 2020
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2020.
-
Abstract
- Declining populations of Zizania palustris L. (northern wildrice, or wildrice) during the last century drives the demand for new and innovative techniques to support monitoring of this culturally and ecologically significant crop wild relative. We trained three wildrice detection models in R and Google Earth Engine using data from annual aquatic vegetation surveys in northern Minnesota. Three different training datasets, varying in the definition of wildrice presence, were combined with Landsat 8 Operational Land Imager (OLI) and Sentinel-1 C-band synthetic aperture radar (SAR) imagery to map wildrice in 2015 using random forests. Spectral predictors were derived from phenologically important time periods of emergence (June–July) and peak harvest (August–September). The range of the Vertical Vertical (VV) polarization between the two time periods was consistently the top predictor. Model outputs were evaluated using both point and area-based validation (polygon). While all models performed well in the point validation with percent correctly classified ranging from 83.8% to 91.1%, we found polygon validation necessary to comprehensively assess wildrice detection accuracy. Our practical approach highlights a variety of applications that can be applied to guide field excursions and estimate the extent of occurrence at landscape scales. Further testing and validation of the methods we present may support multiyear monitoring which is foundational for the preservation of wildrice for future generations.
- Subjects :
- Synthetic aperture radar
010504 meteorology & atmospheric sciences
Range (biology)
Sentinel-1 C-band SAR
Science
0211 other engineering and technologies
02 engineering and technology
01 natural sciences
Landsat 8 OLI
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Zizania palustris
Remote sensing
wildrice
crop wild relative
emergent aquatic vegetation
Random forest
Operational land imager
Crop wild relative
Remote sensing (archaeology)
Polygon
General Earth and Planetary Sciences
Environmental science
random forest
Google Earth Engine
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Database :
- OpenAIRE
- Journal :
- Remote Sensing; Volume 12; Issue 18; Pages: 3023
- Accession number :
- edsair.doi.dedup.....494deed6f6784fb055a7ba7e2d9f830b
- Full Text :
- https://doi.org/10.3390/rs12183023