Wetland mapping in East Asia by two-stage object-based Random Forest and hierarchical decision tree algorithms on Sentinel-1/2 images
Accurate information on wetland extent in East Asia is essential to assess progress towards
Sustainable Development Goals (SDGs) and the use of wetland resources, where wetlands …
Sustainable Development Goals (SDGs) and the use of wetland resources, where wetlands …
[HTML][HTML] From cropland to cropped field: A robust algorithm for national-scale mapping by fusing time series of Sentinel-1 and Sentinel-2
Detailed and updated maps of actively cropped fields on a national scale are vital for global
food security. Unfortunately, this information is not provided in existing land cover datasets …
food security. Unfortunately, this information is not provided in existing land cover datasets …
Delineation of orchard, vineyard, and olive trees based on phenology metrics derived from time series of Sentinel-2
MA Abubakar, A Chanzy, F Flamain, G Pouget… - Remote Sensing, 2023 - mdpi.com
This study aimed to propose an accurate and cost-effective analytical approach for the
delineation of fruit trees in orchards, vineyards, and olive groves in Southern France …
delineation of fruit trees in orchards, vineyards, and olive groves in Southern France …
Crop Type Identification Using High-Resolution Remote Sensing Images Based on an Improved DeepLabV3+ Network
Z Chang, H Li, D Chen, Y Liu, C Zou, J Chen, W Han… - Remote Sensing, 2023 - mdpi.com
Remote sensing technology has become a popular tool for crop classification, but it faces
challenges in accurately identifying crops in areas with fragmented land plots and complex …
challenges in accurately identifying crops in areas with fragmented land plots and complex …
A lightweight winter wheat planting area extraction model based on improved DeepLabv3+ and CBAM
Y Zhang, H Wang, J Liu, X Zhao, Y Lu, T Qu, H Tian… - Remote Sensing, 2023 - mdpi.com
This paper focuses on the problems of inaccurate extraction of winter wheat edges from high-
resolution images, misclassification and omission due to intraclass differences as well as the …
resolution images, misclassification and omission due to intraclass differences as well as the …
Interannual changes of urban wetlands in China's major cities from 1985 to 2022
With global climate change and accelerating urbanization, accurate and timely extent
information on urban wetlands is extremely important for sustainable urban development …
information on urban wetlands is extremely important for sustainable urban development …
Estimation of Winter Wheat Yield using multiple temporal vegetation indices derived from UAV-Based multispectral and hyperspectral imagery
Y Liu, L Sun, B Liu, Y Wu, J Ma, W Zhang, B Wang… - Remote Sensing, 2023 - mdpi.com
Winter wheat is a major food source for the inhabitants of North China. However, its yield is
affected by drought stress during the growing period. Hence, it is necessary to develop …
affected by drought stress during the growing period. Hence, it is necessary to develop …
A cost-effective and robust mapping method for diverse crop types using weakly supervised semantic segmentation with sparse point samples
Accurate and timely information on the spatial distribution and areas of crop types is critical
for yield estimation, agricultural management, and sustainable development. However …
for yield estimation, agricultural management, and sustainable development. However …
Deep learning with multi-scale temporal hybrid structure for robust crop mapping
P Tang, J Chanussot, S Guo, W Zhang, L Qie… - ISPRS Journal of …, 2024 - Elsevier
Large-scale crop mapping from dense time-series images is a difficult task and becomes
even more challenging with the cloud coverage. Current deep learning models frequently …
even more challenging with the cloud coverage. Current deep learning models frequently …
A Spatial Distribution Extraction Method for Winter Wheat Based on Improved U-Net
J Liu, H Wang, Y Zhang, X Zhao, T Qu, H Tian, Y Lu… - Remote Sensing, 2023 - mdpi.com
This paper focuses on the problems of omission, misclassification, and inter-adhesion due to
overly dense distribution, intraclass diversity, and interclass variability when extracting …
overly dense distribution, intraclass diversity, and interclass variability when extracting …