Results 41 to 50 of about 68,744 (188)
Archaeological Prospection, Volume 28, Issue 2, Page 177-186, April/June 2021., 2021 Abstract Due to complicated backgrounds and unclear target orientation, automated object detection is difficult in the field of archaeology. Most of the current convolutional neural network (CNN) object‐oriented detection techniques are based on a faster region‐based CNN (R‐CNN) and other one‐stage detectors that often lack adequate processing speeds ...
Alexander Bonhage +5 more
wiley +1 more source
Hierarchical object-based mapping of riverscape units and in-stream mesohabitats using LiDAR and VHR imagery [PDF]
, 2015 In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS) data.
BIZZI SIMONE +2 more
core +1 more source
Science of Remote Sensing, 2021 The classification of vegetation species is a fundamental technical task, necessary for the sustainable management of wetland ecosystems. GEographic-Object-Based Image Analysis (GEOBIA) and data mining have enabled classification and monitoring of ...
Luis Fernando Chimelo Ruiz +4 more
doaj +1 more source
Tropical Agrarian landscape classification using high-resolution GeoEYE data and segmentationbased approach [PDF]
, 2016 We examine the use of high spatial resolution ‘GeoEYE’ imagery for land use classification in a tropical landscape. Image objects (I-Os) derived from features identification provide a basis for segmentation process and the Geographic Object Based Image ...
Kühle, Peter, Nagabhatla, Nidhi
core +2 more sources
Reproducibility and Practical Adoption of GEOBIA with Open-Source Software in Docker Containers
Remote Sensing, 2017 Geographic Object-Based Image Analysis (GEOBIA) mostly uses proprietary software,but the interest in Free and Open-Source Software (FOSS) for GEOBIA is growing.
Christian Knoth, Daniel Nüst
doaj +1 more source
Remote Sensing, 2020 The fast and accurate creation of land use/land cover maps from very-high-resolution (VHR) remote sensing imagery is crucial for urban planning and environmental monitoring.
Bo Liu +3 more
doaj +1 more source
Fine-scale mapping of vector habitats using very high resolution satellite imagery : a liver fluke case-study [PDF]
, 2014 The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking
Charlier, Johannes +8 more
core +2 more sources
Combining multiscale features for classification of hyperspectral images: a sequence based kernel approach [PDF]
, 2016 Nowadays, hyperspectral image classification widely copes with spatial information to improve accuracy. One of the most popular way to integrate such information is to extract hierarchical features from a multiscale segmentation.
Chapel, Laetitia +2 more
core +4 more sources
Good Practices for Object-Based Accuracy Assessment
Remote Sensing, 2017 Thematic accuracy assessment of a map is a necessary condition for the comparison of research results and the appropriate use of geographic data analysis.
Julien Radoux, Patrick Bogaert
doaj +1 more source
Land Use and Land Cover Mapping with VHR and Multi-Temporal Sentinel-2 Imagery
Remote Sensing, 2023 Land Use/Land Cover (LULC) mapping is the first step in monitoring urban sprawl and its environmental, economic and societal impacts. While satellite imagery and vegetation indices are commonly used for LULC mapping, the limited resolution of these ...
Suzanna Cuypers +2 more
doaj +1 more source