Geomorphic mapping and investigation of the uplifted piedmont zone between Ha…

Active tectonics plays a crucial role in the landscape evolution at the decadal to thousand to million-year time scale. Datasets to examine landscape changes at a decadal scale are rare in the Indo-Gangetic Plain (IGP), which is one of the most dynamic areas in the Himalayan orogenic front. In this paper, we report decadal-scale landscape changes, which occurred in the last 40 years in the pied…

Development of a monitoring system for ionospheric TEC variability before the…

Total Electron Content (TEC) in the ionosphere changes before an earthquake and is one of the important parameters in the study of earthquake precursors. Monitoring of TEC in real-time may prove an excellent input for the effective precursory study of earthquakes. In the present study, a Monitoring system was developed to integrate TEC, geomagnetic storm, and solar flare data and to carry out a…

PS-InSAR derived deformation study in the Kachchh, Western India

The accumulation of crustal strain towards the western part of India, especially in the Kachchh Rift basin, is making one of the most seismically active parts of the Indian plate. Several strong to major earthquakes, including the recent 2001 (M7.7) Bhuj earthquake, were triggered in the Kachchh rift basin during the last two centuries. Therefore, in the present study, we have attempted to quan…

Transfer learning and single-polarized SAR image preprocessing for oil spill …

This study addresses the challenge of oil spill detection using Synthetic Aperture Radar (SAR) satellite imagery, employing deep learning techniques to improve accuracy and efficiency. We investigated the effectiveness of various neural network architectures and encoders for this task, focusing on scenarios with limited training data. The research problem centered on enhancing feature extractio…

Hyperspectral unmixing with spatial context and endmember ensemble learning w…

In recent years, transformer-based deep learning networks have gained popularity in Hyperspectral (HS) unmixing applications due to their superior performance. Most of these networks use an Endmember Extraction Algorithm(EEA) for the initialization of their network. As EEAs performance depends on the environment, single initialization does not ensure optimum performance. Also, only a few networ…

Deep learning techniques for hyperspectral image analysis in agriculture: A r…

In recent years, there has been a growing emphasis on assessing and ensuring the quality of horticultural and agricultural produce. Traditional methods involving field measurements, investigations, and statistical analyses are labour-intensive, time-consuming, and costly. As a solution, Hyperspectral Imaging (HSI) has emerged as a non-destructive and environmentally friendly technology. HSI has…

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…

Produk domestik regional bruto Kabupaten Morowali menurut lapangan usaha

Edisi

-

ISBN/ISSN

-

Deskripsi Fisik

xiv, 80 hlm. : illus.

Judul Seri

-

No. Panggil

R 339.3 BAD p

Pelestarian sumberdaya laut: partisipasi dan kesejahteraan penduduk di kawasa…

Edisi

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ISBN/ISSN

978-602-8942-48-5

Deskripsi Fisik

xvi, 174 hlm.: 21 cm.

Judul Seri

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No. Panggil

333.9164 DAL p

Perancangan kontrak dan memorandum of understanding (MoU)

Edisi

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ISBN/ISSN

978-979-007-024-0

Deskripsi Fisik

ix, 229 hlm.

Judul Seri

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No. Panggil

346.02 Sal P