Results 51 to 60 of about 49,010,873 (166)
Advancements in remote sensing have led to the development of Geographic Object-Based Image Analysis (GEOBIA). This method of information extraction focuses on segregating correlated pixels into groups for easier classification.
Shridhar D. Jawak +3 more
doaj +1 more source
Environmental Stressors Influence Spatial Complexity in a Fluvial Macrophyte meadow
This research investigates the nonlinear relationships between environmental stressors and the fine‐scale spatial complexity of a fluvial macrophytes meadow. The use of multivariate spatial analysis allowed us to identify two major environmental gradients (nutrients and light) and two major complexity gradients (related to abundance and fragmentation).
Arthur de Grandpré +2 more
wiley +1 more source
Deep learning for land use and land cover classification from the Ecuadorian Paramo.
The paramo, plays an important role in our ecosystems as They balance the water resources and can retain substantial quantities of carbon. This research was carried out in the province of Tungurahua, specifically the Quero district. The aim is to develop
Marco Castelo-Cabay +2 more
doaj +1 more source
Abstract Tropical forests in sub‐Saharan Africa (SSA) harbor around one‐third of the world's species but are becoming more fragmented due to the expansion of human settlements and small‐scale agricultural (SCA) areas. This study systematically reviewed the approaches and methods used to analyze forest fragmentation and its impact on biodiversity in SSA,
Gillie Cheelo +4 more
wiley +1 more source
Trait‐Based Community Assembly in Early Tropical Forest Succession
We found that in early tropical forest succession, dispersal (landscape forest cover), management (previous land use extent and duration), and environmental filters (understory light availability) collectively shaped community assembly, each playing distinct roles.
Tomonari Matsuo +5 more
wiley +1 more source
Geographic object-based image analysis (GEOBIA) has been widely used in the remote sensing of agricultural crops. However, issues related to image segmentation, data redundancy and performance of different classification algorithms with GEOBIA have not ...
Lingbo Yang +3 more
doaj +1 more source
AN UNSUPERVISED SEGMENTATION METHOD FOR REMOTE SENSING IMAGERY BASED ON CONDITIONAL RANDOM FIELDS [PDF]
Segmentation is a fundamental problem in image processing and a common operation in Remote Sensing, which has been widely used especially in Geographic Object-Based Image Analysis (GEOBIA).
A. R. Soares +3 more
doaj +1 more source
This study examines the invasion dynamics of the predatory invertebrate flatworm Kontikia andersoni, and its impacts on the invertebrate communities of sub‐Antarctic Macquarie Island. Our findings indicate that at higher elevations where K. andersoni is present there are significant reductions in invertebrate richness.
Kita M. Williams +4 more
wiley +1 more source
Image segmentation is a crucial stage at the very beginning of many geographic object-based image analysis (GEOBIA) workflows. While segmentation quality is generally deemed of great importance, selecting adequate tuning parameters for a segmentation ...
Sebastian Böck +2 more
doaj +1 more source
Abstract This study employs object‐based image analysis to investigate land cover dynamics and channel changes in the managed corridor of the Orljava River following anthropogenic vegetation removal and a flood event. By classifying RGB and near‐infrared (NIR) images from the decade 2011–2021, five land cover classes within the river corridor were ...
Katarina Pavlek +2 more
wiley +1 more source

