The Oasis impact structure, Libya: geological characteristics from ALOS PALSAR-2 data interpretation
نویسندگان
چکیده
منابع مشابه
Frozen Ground Monitoring Using Palsar/alos Data
Microwave remote sensing has shown proof of its effectiveness for frozen ground mapping due to the high difference of permittivity between frozen and unfrozen soil. However, the characterization of seasonal frozen ground still remains a problematic application. The Japan Aerospace Exploration Agency (JAXA) launched the Advanced Land Observing Satellite (ALOS) on the 24 of January 2006. This sat...
متن کاملAlos Palsar Verification Processor
This paper presents a verification processor, developed under ESA contract, for the generation of polarimetric, interferometric and polarimetric-interferometric geocoded products derived from SAR data obtained from the ALOS PALSAR instrument. The processor, developed with a modular approach, contains the following main elements: Phase-preserving fine resolution processor; Phase-preserving ScanS...
متن کاملStandwise Change Detection for Growing Stock Using Repeat-pass Alos Palsar / Palsar-2 Data
This study demonstrates the possibility of detecting the changes of growing stocks in mountainous forest stands derived from ALOS PALSAR and PALSAR-2 images. The ALOS PALSAR were obtained over the Kwangneung Experiment Forest (KEF, Korea) during the period of nineteen and a half months from the April 26, 2009 to December 12, 2010, whereas the PALSAR-2 data were acquired on the April 7, 2015. Th...
متن کاملSAR interferometry using ALOS-2 PALSAR-2 data for the Mw 7.8 Gorkha, Nepal earthquake
The Advanced Land Observing Satellite-2 (ALOS-2, “DAICHI-2”) has been observing Nepal with the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) in response to an emergency request from Sentinel Asia related to the Mw 7.8 Gorkha earthquake on April 25, 2015. PALSAR-2 successfully detected not only avalanches and local crustal displacements but also continental-scale deformation. Es...
متن کاملParticle Swarm Optimization for Geological Feature Detection from Palsar Data
Synthetic aperture radar (SAR) has been recognized as a powerful tool for geological feature detection. This work introduces a new approach using Particle Swarm Optimization automatically detected geological features from PALSAR SAR data. The result shows that the new formula based on Particle Swarm Optimization can be delineated lineament features in PALSAR data. The new approach using Particl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Earth, Planets and Space
سال: 2017
ISSN: 1880-5981
DOI: 10.1186/s40623-017-0620-8