Ditapis dengan
Land use and land cover classification for change detection studies using con…
Efficient land use land cover (LULC) classification is crucial for environmental monitoring, urban planning, and resource management. This study investigates LULC changes in Nanjangud taluk, Mysuru district, Karnataka, India, using remote sensing (RS) and geographic information systems (GIS). This paper mainly focuses on the classification and change detection analysis of LULC in 2010 and 2020 …
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 17 hlm PDF, 11.125 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Automatic variogram inference using pre-trained Convolutional Neural Networks
A novel approach is presented for inferring covariance functions from sparse data using Convolutional Neural Networks (CNNs). Two workflows are proposed: (1) direct prediction of variogram model parameters, and (2) prediction of experimental variogram values at specified lag distances, which are smooth and easily autofit. Workflow 1 achieves an r-squared of 0.80, while Workflow 2 attains a high…
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 6.887 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
An UNet3+ Network based on global pyramid aggregation for change detection in…
Change detection (CD) is a meaningful and challenging task for remote sensing (RS) image analysis. Deep learning (DL) based methods have shown great potential in change detection tasks, there are still two problems with existing deep learning methods such as CNN and Transformer: (1) They do not target different depths to extract global semantics in the network; (2) The increase in network depth…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 4.185 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Neural network approach for shape-based euhedral pyrite identification in X-r…
We explore an attenuation and shape-based identification of euhedral pyrites in high-resolution X-ray Computed Tomography (XCT) data using deep neural networks. To deal with the scarcity of annotated data we generate a complementary training set of synthetic images. To investigate and address the domain gap between the synthetic and XCT data, several deep learning models, with and without domai…
- Edisi
- Vol.21, March 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 1.619 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Evaluating deep-learning models for debris-covered glacier mapping
In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accur…
- Edisi
- Vol.12, December 2021
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 17 hlm PDF, 31.040 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Using three dimensional convolutional neural networks for denoising echosound…
It is estimated that over 80% of the world’s oceans are unexplored and unmapped limiting our understanding of ocean systems. Due to data collection rates of modern survey technologies such as swathe multibeam echosounders (MBES) and initiatives such as Seabed 2030, there is ever-increasing increasing volume of seafloor data collected. These large data volumes present significant challenges ar…
- Edisi
- Vol.5, March 2020
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 2.691 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Semantic segmentation of raw multispectral laser scanning data from urban env…
Real-time semantic segmentation of point clouds has increasing importance in applications related to 3D city modelling and mapping, automated inventory of forests, autonomous driving and mobile robotics. Current state-of-the-art point cloud semantic segmentation methods rely heavily on the availability of 3D laser scanning data. This is problematic in regards of low-latency, real-time applicati…
- Edisi
- Vol.12, April 2024
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 17 hlm PDF, 21.188 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Improving spatial transferability of deep learning models for small-field cro…
Predicting crop yield using deep learning (DL) and remote sensing is a promising technique in agriculture. In smallholder agriculture (
- Edisi
- Vol.12, April 2024
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 11 hlm PDF, 7.586 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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