Results 21 to 30 of about 1,061,712 (345)

Actual Satellite Imagery Sources

IOP Conference Series: Earth and Environmental Science, 2021
Abstract The huge benefit of the Internet is that it not only connects people from all over the world but also provides information that would otherwise be unavailable. Anyone who needs access to the latest satellite imagery can take it via many platforms provided remote sensing data, either for free from the websites belonging to ...
Izvoltova, Jana, Kriauciunaite-Neklejonoviene, Vilma, Sasik, Robert   +2 more
openaire   +2 more sources

Pasture Productivity Assessment under Mob Grazing and Fertility Management Using Satellite and UAS Imagery

Drones, 2022
Pasture management approaches can determine the productivity, sustainability, and ecological balance of livestock production. Sensing techniques potentially provide methods to assess the performance of different grazing practices that are more labor and ...
Worasit Sangjan, Lynne A. Carpenter-Boggs, Tipton D. Hudson, Sindhuja Sankaran   +3 more
doaj   +1 more source

A Vision Transformer Model for Convolution-Free Multilabel Classification of Satellite Imagery in Deforestation Monitoring

IEEE Transactions on Neural Networks and Learning Systems, 2022
Understanding the dynamics of deforestation and land uses of neighboring areas is of vital importance for the design and development of appropriate forest conservation and management policies.
Maria Kaselimi, A. Voulodimos, I. Daskalopoulos, N. Doulamis, A. Doulamis   +4 more
semanticscholar   +1 more source

Detail‐In‐Context Visualization for Satellite Imagery [PDF]

Computer Graphics Forum, 2008
AbstractWe use the complex logarithm as a transformation for the visualization and navigation of highly complex satellite and aerial imagery. The resulting depictions show details and context with greatly different scales in one seamless image while avoiding local distortions.
Böttger, Joachim, Preiser, Martin, Balzer, Michael, Deussen, Oliver   +3 more
openaire   +2 more sources

Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques

Remote Sensing, 2022
Accurate land use land cover (LULC) classification is vital for the sustainable management of natural resources and to learn how the landscape is changing due to climate.
S. Basheer, Xiuquan Wang, A. Farooque, Rana Ali Nawaz, Kai Liu, T. Adekanmbi, Suqi Liu   +6 more
semanticscholar   +1 more source

Advancing Skyborne Technologies and High-Resolution Satellites for Pasture Monitoring and Improved Management: A Review

Remote Sensing, 2023
The timely and accurate quantification of grassland biomass is a prerequisite for sustainable grazing management. With advances in artificial intelligence, the launch of new satellites, and perceived efficiency gains in the time and cost of the ...
Michael Gbenga Ogungbuyi, Caroline Mohammed, Iffat Ara, Andrew M. Fischer, Matthew Tom Harrison   +4 more
doaj   +1 more source

Using publicly available satellite imagery and deep learning to understand economic well-being in Africa

Nature Communications, 2020
Accurate and comprehensive measurements of economic well-being are fundamental inputs into both research and policy, but such measures are unavailable at a local level in many parts of the world. Here we train deep learning models to predict survey-based
Christopher Yeh, Anthony Perez, Anne Driscoll, G. Azzari, Zhongyi Tang, D. Lobell, Stefano Ermon, M. Burke   +7 more
semanticscholar   +1 more source

Deep learning detects invasive plant species across complex landscapes using Worldview‐2 and Planetscope satellite imagery

Remote Sensing in Ecology and Conservation, 2022
Effective management of invasive species requires rapid detection and dynamic monitoring. Remote sensing offers an efficient alternative to field surveys for invasive plants; however, distinguishing individual plant species can be challenging especially ...
Thomas A. Lake, Ryan D. Briscoe Runquist, D. A. Moeller   +2 more
semanticscholar   +1 more source

SeaMAE: Masked Pre-Training with Meteorological Satellite Imagery for Sea Fog Detection

Remote Sensing, 2023
Sea fog detection (SFD) presents a significant challenge in the field of intelligent Earth observation, particularly in analyzing meteorological satellite imagery. Akin to various vision tasks, ImageNet pre-training is commonly used for pre-training SFD.
Haotian Yan, Sundingkai Su, Ming Wu, Mengqiu Xu, Yihao Zuo, Chuang Zhang, Bin Huang   +6 more
doaj   +1 more source

Wildfire Detection From Multisensor Satellite Imagery Using Deep Semantic Segmentation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Deriving the extent of areas affected by wildfires is critical to fire management, protection of the population, damage assessment, and better understanding of the consequences of fires.
D. Rashkovetsky, F. Mauracher, M. Langer, Michael Schmitt   +3 more
semanticscholar   +1 more source