High-Resolution Remote Sensing Image Change Detection by Statistical-Object-Based Method

We implemented a change detection method based on a multitemporal object using a chi-square method and iterative trimming to find the changed object in the past. Trapping in the sample data does not obey Gaussian distribution, and the detection result is not ideal. To fix this problem, we proposed a method based on the law of cosines with a box-whisker plot. First, using the incremental segmentation method to segment the image and selecting the optimum combination of spatial, spectral, and contextual features by the Optimum Index Factor method, we constructed the feature space of different time images. Then, the law of cosines was used to calculate the change index of every object. Finally, we identified changed objects by analyzing the change index using the box-whisker plot. High-resolution remote sensing images of GF-1 were used as the experimental data. The experimental results show that the correct detection accuracy and omissions rate accuracy are much better than the results of the traditional multitemporal-object-based change detection.

• Publication year

  2018

• Venue

  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

• Publication date

  2018-04-11

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/JSTARS.2018.2817121
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Exploratory data analysis

  2018influential reference
• and cover changed object detection in remote sensing data with edium spatial resolution

  2015cited by this paper
• Microblog Hot Topic Detection Based on Box-plot

  2014cited by this paper
• Plant leaf identification method based on cosine theorem and K-means

  2014cited by this paper
• Object-based change detection

  2012cited by this paper
• HEAT-HOME ENERGY ASSESSMENT TECHNOLOGIES : RESIDENTIAL WASTE HEAT-MONITORING WITH HIGH-RESOLUTION AIRBORNE THERMAL IMAGERY

  2010cited by this paper
• Supporting large-area, sample-based forest inventories with very high spatial resolution satellite imagery

  2009cited by this paper
• Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

  2009cited by this paper
• A Matching Algorithm for Detecting Land Use Changes Using Case-Based Reasoning

  2009cited by this paper
• Analysis of co‐occurrence and discrete wavelet transform textures for differentiation of forest and non‐forest vegetation in very‐high‐resolution optical‐sensor imagery

  2008cited by this paper
• An object-based change detection method accounting for temporal dependences in time series with medium to coarse spatial resolution

  2008cited by this paper
• Image objects and geographic objects

  2008cited by this paper
• Object‐based change detection using correlation image analysis and image segmentation

  2008cited by this paper
• Object-oriented urban dynamic monitoring — A case study of Haidian District of Beijing

  2007cited by this paper
• Forest change detection by statistical object-based method

  2006cited by this paper
• Objects based change detection in a pair of gray-level images

  2005cited by this paper
• Remote sensing: land cover

  2004cited by this paper
• Change detection techniques

  2004cited by this paper
• Review ArticleDigital change detection methods in ecosystem monitoring: a review

  2004cited by this paper
• Preliminary evaluation of eCognition object-based software for cut block delineation and feature extraction

  2003cited by this paper
• Evaluation functions in aerial image segmentation

  2002cited by this paper
• Digital change detection in forest ecosystems with remote sensing imagery

  1996cited by this paper
• Textural Features for Image Classification

  1973cited by this paper

• Deep-Learning-Based Semantic Change Detection for Urban Greenery and Comprehensive Urban Areas

  2025cites this paper
• A global downstream approach to mapping surface urban heat islands using open data and collaborative technology

  2025cites this paper
• Optimization of NIRS-based models for predicting quality and gas production traits of fresh alfalfa silage via machine learning.

  2025cites this paper
• VG-Net: a Mamba-based U-shaped network for remote sensing change detection

  2025cites this paper
• Accuracy Assessment of GEDI and ICESat-2 Canopy Height Products by Excluding Geolocation Error Based on Virtual Sampling Units

  2025cites this paper
• Integrating isolation forest and deep learning for reliability check of land vector patch types

  2025cites this paper
• Building Change Detection Using Deep-SiamCNN Network Through Two-Stream Triplet Attention Mechanism

  2024cites this paper
• GateFormer: Gate Attention UNet With Transformer for Change Detection of Remote Sensing Images

  2024cites this paper
• AMCA: Attention-Guided Multiscale Context Aggregation Network for Remote Sensing Image Change Detection

  2023cites this paper
• A Siamese Multiscale Attention Decoding Network for Building Change Detection on High-Resolution Remote Sensing Images

  2023cites this paper
• Crossed Siamese Vision Graph Neural Network for Remote-Sensing Image Change Detection

  2023cites this paper
• Two-phase methods to segment man-made objects around reservoirs

  2023cites this paper
• Adaptive Fusion NestedUNet for Change Detection Using Optical Remote Sensing Images

  2023cites this paper
• TCIANet: Transformer-Based Context Information Aggregation Network for Remote Sensing Image Change Detection

  2023cites this paper
• Change Detection for High-Resolution Remote Sensing Images Based on a Multi-Scale Attention Siamese Network

  2022cites this paper
• MAFF-Net: Multi-Attention Guided Feature Fusion Network for Change Detection in Remote Sensing Images

  2022cites this paper
• Robust Change Detection using Channel-Wise Co-Attention-Based Twin Network with Contrastive Loss Function

  2022cites this paper
• HMCNet: Hybrid Efficient Remote Sensing Images Change Detection Network Based on Cross-Axis Attention MLP and CNN

  2022cites this paper
• SARAS-Net: Scale and Relation Aware Siamese Network for Change Detection

  2022cites this paper
• MRA-SNet: Siamese Networks of Multiscale Residual and Attention for Change Detection in High-Resolution Remote Sensing Images

  2021cites this paper
• CANet: A Combined Attention Network for Remote Sensing Image Change Detection

  2021cites this paper
• Identification and Evaluation of Urban Construction Waste with VHR Remote Sensing Using Multi-Feature Analysis and a Hierarchical Segmentation Method

  2021cites this paper
• Object-Oriented Key Point Vector Distance for Binary Land Cover Change Detection Using VHR Remote Sensing Images

  2020cites this paper
• DASNet: Dual Attentive Fully Convolutional Siamese Networks for Change Detection in High-Resolution Satellite Images

  2020cites this paper
• Extraction of Yardang Characteristics Using Object-Based Image Analysis and Canny Edge Detection Methods

  2020cites this paper
• Optimal Segmentation Scale Selection for Object-Based Change Detection in Remote Sensing Images Using Kullback–Leibler Divergence

  2020cites this paper
• Transformer

  2020cites this paper
• Early Detection System for Abnormalities by Analyzing Blood Flow Sound during Dialysis

  2020cites this paper
• Change detection method based on vector data and isolation forest algorithm

  2020cites this paper
• A novel density-based super-pixel aggregation for automatic segmentation of remote sensing images in urban areas

  2019cites this paper
• Intersensor Remote Sensing Image Registration Using Multispectral Semantic Embeddings

  2019cites this paper
• A Novel Joint Change Detection Approach Based on Weight-Clustering Sparse Autoencoders

  2019cites this paper
• Estimating Change Percentage in Texture Developed by the Water Turndown of Bolivia's Lake Poopo

  2018cites this paper