Ditapis dengan
UAV-based reference data for the prediction of fractional cover of standing d…
Increasing tree mortality due to climate change has been observed globally. Remote sensing is a suitable means for detecting tree mortality and has been proven effective for the assessment of abrupt and large-scale stand-replacing disturbances, such as those caused by windthrow, clear-cut harvesting, or wildfire. Non-stand replacing tree mortality events (e.g., due to drought) are more difficul…
- Edisi
- Vol.8, April 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 12 hlm PDF, 14.697 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Assessment of camera focal length influence on canopy reconstruction quality
Unoccupied aerial vehicles (UAV) with RGB-cameras are affordable and versatile devices for the generation of a series of remote sensing products that can be used for forest inventory tasks, such as creating high-resolution orthomosaics and canopy height models. The latter may serve purposes including tree species identification, forest damage assessments, canopy height or timber stock assessmen…
- Edisi
- Vol.6, December 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 8 hlm PDF, 10.100 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Transfer learning from citizen science photographs enables plant species iden…
Accurate information on the spatial distribution of plant species and communities is in high demand for various fields of application, such as nature conservation, forestry, and agriculture. A series of studies has shown that Convolutional Neural Networks (CNNs) accurately predict plant species and communities in high-resolution remote sensing data, in particular with data at the centimeter sca…
- Edisi
- Vol.5, August 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 23 hlm PDF, 83.917 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Spatially autocorrelated training and validation samples inflate performance …
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote sensing are becoming standard analytical tools in the geosciences. A series of studies has presented the seemingly outstanding performance of CNN for predictive modelling. However, the predictive performance of such models is commonly estimated using random cross-validation, which does not account for spat…
- Edisi
- Vol.5, August 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 10 hlm PDF, 5.589 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
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