A review of change detection in multitemporal hyperspectral images: Current techniques, applications, and challenges
We review both widely used methods and new techniques proposed in the recent literature.
The basic concepts, categories, open issues, and challenges related to CD in HS images …
The basic concepts, categories, open issues, and challenges related to CD in HS images …
A review of multi-class change detection for satellite remote sensing imagery
Q Zhu, X Guo, Z Li, D Li - Geo-spatial Information Science, 2024 - Taylor & Francis
Change Detection (CD) provides a research basis for environmental monitoring, urban
expansion and reconstruction as well as disaster assessment, by identifying the changes of …
expansion and reconstruction as well as disaster assessment, by identifying the changes of …
Temporal difference-guided network for hyperspectral image change detection
Recently, the research area of hyperspectral (HS) image change detection (CD) is popular
with convolutional neural networks (CNNs) based methods. However, conventional CNNs …
with convolutional neural networks (CNNs) based methods. However, conventional CNNs …
UTRNet: An unsupervised time-distance-guided convolutional recurrent network for change detection in irregularly collected images
Change detection in time series is among the most critical problems in Earth monitoring and
attracts extensive attention in the remote sensing community. The task is, however, nontrivial …
attracts extensive attention in the remote sensing community. The task is, however, nontrivial …
A novel framework for the design of change-detection systems for very-high-resolution remote sensing images
This paper addresses change detection in multitemporal remote sensing images. After a
review of the main techniques developed in remote sensing for the analysis of multitemporal …
review of the main techniques developed in remote sensing for the analysis of multitemporal …
Accuracy, bias, and improvements in map** crops and cropland across the United States using the USDA cropland data layer
The US Department of Agriculture's (USDA) Cropland Data Layer (CDL) is a 30 m resolution
crop-specific land cover map produced annually to assess crops and cropland area across …
crop-specific land cover map produced annually to assess crops and cropland area across …
Hyperspectral image classification with capsule network using limited training samples
Deep learning techniques have boosted the performance of hyperspectral image (HSI)
classification. In particular, convolutional neural networks (CNNs) have shown superior …
classification. In particular, convolutional neural networks (CNNs) have shown superior …
Unsupervised change detection from heterogeneous data based on image translation
ZG Liu, ZW Zhang, Q Pan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
It is quite an important and challenging problem for change detection (CD) from
heterogeneous remote sensing images. The images obtained from different sensors (ie …
heterogeneous remote sensing images. The images obtained from different sensors (ie …
An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support
Y Hu, Y Dong - ISPRS journal of photogrammetry and remote sensing, 2018 - Elsevier
Land-use/land-cover information is the basis of global-change research and regional
governmental management. Automatic approaches are always required to update land …
governmental management. Automatic approaches are always required to update land …
Annual large-scale urban land map** based on Landsat time series in Google Earth Engine and OpenStreetMap data: A case study in the middle Yangtze River …
Long time series (eg 30 years) urban land observations from remote sensing images are
important for urban growth modeling as well as for the goal of sustainable urban …
important for urban growth modeling as well as for the goal of sustainable urban …