Results 51 to 60 of about 643,688 (353)

A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks [PDF]

open access: yes, 2019
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques for digital pattern ...
Carranza García, Manuel   +2 more
core   +1 more source

Recent Advances in Collective Behaviors of Micro/Nanomotor Swarms

open access: yesAdvanced Materials, EarlyView.
This review describes the driving forces behind collective motion, explores the self‐organization of micro/nano swarms across zero‐dimensional (0D), one‐dimensional (1D), two‐dimensional (2D), and three‐dimensional (3D) spaces, and highlights their potential in drug delivery, environmental monitoring, and smart devices.
Siwen Sun   +4 more
wiley   +1 more source

Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine

open access: yesIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Land cover information depicting the complex interactions between human activities and surface change is critically essential for nature conservation, social management, and sustainable development.
Ying Tu   +8 more
doaj   +1 more source

Correlated Dual‐Gradient Electrodes Enabling Spatially Synchronized Sulfur Redox in High‐Mass‐Loading Li–S Batteries Under High Current Densities

open access: yesAdvanced Materials, EarlyView.
Coupling a dual‐gradient carbonized framework with Fe2O3/Fe‐N‐C catalytic sites enables spatially synchronized sulfur redox across the entire electrode thickness in high‐mass‐loading Li–S batteries. This synergistic structural–catalytic design effectively mitigates concentration, ohmic, and electrochemical polarization, thereby achieving high‐capacity ...
Yuxuan Zhang   +6 more
wiley   +1 more source

Interpretasi Visual dan Digital untuk Klasifikasi Tutupan Lahan di Kabupaten Kuningan, Jawa Barat

open access: yesJurnal Ilmu Pertanian Indonesia, 2019
Land cover information are needed to support decision making process on natural resource management. Remote sensing has been provideingr a huge distribution of geographical land cover information on various spatial scales.
Dede Kosasih   +2 more
doaj   +1 more source

LAND USE LAND COVER MAPPING USING UAS IMAGERY: SCENE CLASSIFICATION AND SEMANTIC SEGMENTATION [PDF]

open access: diamond, 2022
Monica Rajkumar   +2 more
openalex   +1 more source

Land cover classification using SPOT data

open access: yesGeocarto International, 1987
Abstract SPOT multispectral data were compared statistically with 10 meters mesh numerical land use data in the study area near Tokyo. The numerical land use data have 16 categories and were produced from color aerial photographs by Geographical Survey Institute of Japan.
Ryutaro Tateishi, Youji Mukouyama
openaire   +1 more source

Magnetic Field Driven Microrobot Based on Hydrogels

open access: yesAdvanced Robotics Research, EarlyView.
Hydrogel‐based magnetic microrobots synergize remote magnetic control with the biocompatibility of flexible hydrogels, emerging as promising tools for minimally invasive biomedicine. This enables remotely controllable, untethered navigation within complex biological microenvironments.
Juncai Song, Yubing Guo
wiley   +1 more source

Land use/cover classification in the Brazilian Amazon using satellite images

open access: yesPesquisa Agropecuária Brasileira, 2012
Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment ...
Dengsheng Lu   +7 more
doaj   +1 more source

Texture classification of Mediterranean land cover

open access: yesInternational Journal of Applied Earth Observation and Geoinformation, 2007
Maximum likelihood (ML) and artificial neural network (ANN) classifiers were applied to three Landsat Thematic Mapper (TM) image sub-scenes (termed urban, agricultural and semi-natural) of Cukurova, Turkey. Inputs to the classifications comprised (i) spectral data and (ii) spectral data in combination with texture measures derived on a per-pixel basis.
Berberoglu, S.   +3 more
openaire   +2 more sources

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