Results 51 to 60 of about 291 (148)

AN UNSUPERVISED SEGMENTATION METHOD FOR REMOTE SENSING IMAGERY BASED ON CONDITIONAL RANDOM FIELDS [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
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, T. S. Körting, L. M. G. Fonseca, A. K. Neves   +3 more
doaj   +1 more source

A Novel Invertebrate Predator on an Oceanic Island: Impacts and Invasion Dynamics of Kontikia andersoni on Macquarie Island

Ecology and Evolution, Volume 15, Issue 7, July 2025.
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, Samuel Waite, Melissa Houghton, Jennifer Firn, Justine Shaw   +4 more
wiley   +1 more source

On the Objectivity of the Objective Function—Problems with Unsupervised Segmentation Evaluation Based on Global Score and a Possible Remedy

Remote Sensing, 2017
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, Markus Immitzer, Clement Atzberger   +2 more
doaj   +1 more source

Assessing natural and human‐induced river corridor changes using object‐based image analysis (Orljava River, Croatia)

River Research and Applications, Volume 41, Issue 2, Page 285-300, February 2025.
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, Mateo Gašparović, Ronald E. Poeppl   +2 more
wiley   +1 more source

AI‐assisted interpretation of changes in riparian woodland from archival aerial imagery using Meta's segment anything model

Earth Surface Processes and Landforms, Volume 50, Issue 1, January 2025.
Meta's 2023 foundation AI model, Segment Anything (SAM), was used to assist the mapping of changes in the extent of riparian woodland along three gravel bed, meandering, river reaches in rural settings in the United Kingdom. Using visual prompts in interactive mode, this approach is shown to deliver substantial time savings over manual digitisation ...
Martin Dawson, Henry Dawson, Angela Gurnell, John Lewin, Mark G. Macklin   +4 more
wiley   +1 more source

An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

Remote Sensing, 2016
The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery.
Chandi Witharana, Heather J. Lynch
doaj   +1 more source

Investigating palaeodune orientations and contemporary wind regimes in Southeast Kazakhstan using a semi‐automated mapping framework

Earth Surface Processes and Landforms, Volume 49, Issue 14, Page 4553-4569, November 2024.
We present a semi‐automated framework applying object‐based analysis of Sentinel‐2 and digital elevation data to map dunes and quantify their orientation. The approach is applied to five dune fields in the Ili‐Balkhash region in Kazakhstan. Comparing bedform orientations with the modern wind regime, we find (1) better alignment considering only strong ...
Maike Nowatzki, Kathryn E. Fitzsimmons, Hartwig Harder, Hans‐Joachim Rosner   +3 more
wiley   +1 more source

Performance Comparison of Deep Learning (DL)-Based Tabular Models for Building Mapping Using High-Resolution Red, Green, and Blue Imagery and the Geographic Object-Based Image Analysis Framework

Remote Sensing
Identifying urban buildings in high-resolution RGB images presents challenges, mainly due to the absence of near-infrared bands in UAVs and Google Earth imagery and the diversity in building attributes.
Mohammad D. Hossain, Dongmei Chen
doaj   +1 more source

Determination of the Olive Trees with Object Based Classification of Pleiades Satellite Image

International Journal of Environment and Geoinformatics, 2018
Identification of fruit trees and determination of their spatial distribution is an important task for several agricultural activities including fruit yield estimation, irrigation planning, disease management and supporting agricultural policies.
Uğur Algancı, Elif Sertel, Şinasi Kaya   +2 more
doaj   +1 more source

Spectral Patterns of Pixels and Objects of the Forest Phytophysiognomies in the Anauá National Forest, Roraima State, Brazil

Ecologies, 2023
Forest phytophysiognomies have specific spatial patterns that can be mapped or translated into spectral patterns of vegetation. Regions of spectral similarity can be classified by reference to color, tonality or intensity of brightness, reflectance ...
Tiago Monteiro Condé, Niro Higuchi, Adriano José Nogueira Lima, Moacir Alberto Assis Campos, Jackelin Dias Condé, André Camargo de Oliveira, Dirceu Lucio Carneiro de Miranda   +6 more
doaj   +1 more source