Deep learning on edge: Extracting field boundaries from satellite images with a convolutional neural network

F Waldner, FI Diakogiannis - Remote sensing of environment, 2020 - Elsevier
Applications of digital agricultural services often require either farmers or their advisers to
provide digital records of their field boundaries. Automatic extraction of field boundaries from …

Mapping agricultural land abandonment from spatial and temporal segmentation of Landsat time series

H Yin, AV Prishchepov, T Kuemmerle, B Bleyhl… - Remote sensing of …, 2018 - Elsevier
Agricultural land abandonment is a common land-use change, making the accurate
mapping of both location and timing when agricultural land abandonment occurred …

Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery

L Wang, WP Sousa, P Gong - International journal of remote …, 2004 - Taylor & Francis
IKONOS 1-m panchromatic and 4-m multispectral images were used to map mangroves in a
study site located at Punta Galeta on the Caribbean coast of Panama. We hypothesized that …

Comparison of pixel‐based and object‐oriented image classification approaches—a case study in a coal fire area, Wuda, Inner Mongolia, China

G Yan, JF Mas, BHP Maathuis, Z Xiangmin… - … journal of remote …, 2006 - Taylor & Francis
Pixel‐based and object‐oriented classifications were tested for land‐cover mapping in a
coal fire area. In pixel‐based classification a supervised Maximum Likelihood Classification …

Multi-resolution segmentation parameters optimization and evaluation for VHR remote sensing image based on meanNSQI and discrepancy measure

Y Chen, Q Chen, C Jing - Journal of Spatial Science, 2021 - Taylor & Francis
ABSTRACT Multi-Resolution Segmentation (MRS) is known to be a general segmentation
algorithm for very-high-resolution (VHR) remote sensing applications. The critical problems …

[HTML][HTML] Automated delineation of agricultural field boundaries from Sentinel-2 images using recurrent residual U-Net

H Zhang, M Liu, Y Wang, J Shang, X Liu, B Li… - International Journal of …, 2021 - Elsevier
Delineation of agricultural fields is desirable for operational monitoring of agricultural
production and is essential to support food security. Due to large within-class variance of …

A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas

AK Shackelford, CH Davis - IEEE Transactions on GeoScience …, 2003 - ieeexplore.ieee.org
In this paper, we present an object-based approach for urban land cover classification from
high-resolution multispectral image data that builds upon a pixel-based fuzzy classification …

[HTML][HTML] Automated crop field extraction from multi-temporal Web Enabled Landsat Data

L Yan, DP Roy - Remote Sensing of Environment, 2014 - Elsevier
An automated computational methodology to extract agricultural crop fields from 30 m Web
Enabled Landsat data (WELD) time series is presented. The results for three 150× 150 km …

The comparison index: A tool for assessing the accuracy of image segmentation

M Möller, L Lymburner, M Volk - … Journal of Applied Earth Observation and …, 2007 - Elsevier
Segmentation algorithms applied to remote sensing data provide valuable information about
the size, distribution and context of landscape objects at a range of scales. However, there is …

Classifying multilevel imagery from SAR and optical sensors by decision fusion

B Waske, S van der Linden - IEEE Transactions on Geoscience …, 2008 - ieeexplore.ieee.org
A strategy for the joint classification of multiple segmentation levels from multisensor
imagery is introduced by using synthetic aperture radar and optical data. At first, the two data …