Artificial Intelligence and Objective‐Function Methods Can Identify Bankfull River Channel Extents
Abstract Bankfull channel extents are of fundamental importance in fluvial geomorphology, to describe the geomorphic character of a river, and to provide a boundary for further processing of morphologic and hydraulic attributes. With ever‐increasing availability of high‐resolution spatial data (e.g., lidar, aerial photography), manual delineation of ...
Jonathan Garber +5 more
wiley +1 more source
Detecting Invasive Alien Plant Species Using Remote Sensing, Machine Learning and Deep Learning
Invasive alien plants (IAPs) are nonnative species that pose significant threats to the environment by outcompeting native vegetation and disrupting ecosystem functions. Efforts to monitor and eradicate IAPs have been limited due to the challenges in accurately identifying these plants using traditional remote sensing (RS) methods.
Perry B. Rakgoale +2 more
wiley +1 more source
Contrast plays an important role in the visual interpretation of imagery. To mimic visual interpretation and using contrast in a Geographic Object Based Image Analysis (GEOBIA) environment, it is useful to consider an analysis for single pixel objects ...
Roeland de Kok
doaj +1 more source
The conflict between environmental conservation and agricultural production highlights the need for precise land use and land cover (LULC) mapping to support agro-environmental-related policies.
Michel E. D. Chaves +7 more
doaj +1 more source
Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa [PDF]
CITATION: Munch, Z., et al. 2017. Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa. Geosciences, 7(1):7, doi:10.3390/geosciences7010007.The original publication is available at http://www.mdpi ...
Brown +22 more
core +3 more sources
Fuzzy segmentation for geographic object-based image analysis [PDF]
Image segmentation partitions remote sensing images into image objects before assigning them to categorical land cover classes. Current segmentation methods require users to invest considerable time and effort in the search for meaningful image objects ...
Elsner, Paul, Lizarazo, Ivan
core +1 more source
The advent of very high resolution (VHR) satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA) have led to many new opportunities for fine-scale land cover mapping, especially in urban areas.
Brian A. Johnson, Shahab E. Jozdani
doaj +1 more source
Assessing land cover changes in the French Pyrenees since the 1940s A semi‐automatic GEOBIA approach using aerial photographs [PDF]
International audienceAgro-pastoral landscapes of the Pyrenees are subject to fast spontaneous reforestation. The objective of this work is to assess the spatial patterns of land cover changes during the last 70 years in three study sites of the Pyrenees,
Houet, Thomas +5 more
core +1 more source
OBIA for combining LiDAR and multispectral data to characterize forested areas and land cover in a tropical region [PDF]
International audiencePrioritizing and designing forest restoration strategies requires an adequate survey to inform on the status (degraded or not) of forest types and the human disturbances over a territory. Very High Spatial Resolution (VHSR) remotely
Dupuy, S., Laine, G., Tormos, T.
core +1 more source
Assessment of Nigeriasat-1 satellite data for urban land use / land cover analysis using Object Based Image Analysis in Abuja, Nigeria [PDF]
This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods.
Blackett, Matthew +2 more
core +1 more source

