Zobrazeno 1 - 10
of 524
pro vyhledávání: '"high-resolution remote sensing images"'
Publikováno v:
Geo-spatial Information Science, Pp 1-18 (2024)
Accurate and complete road network extraction plays a critical role in urban planning, street navigation, and emergency response. At present, narrow roads are a main feature in most public road datasets. However, the continuity and boundary completen
Externí odkaz:
https://doaj.org/article/efc6796467c84c3e9b2566fd97bc5d19
Autor:
Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Detecting farmland parcels in high-resolution remote sensing images is challenging in smallholder farming systems in China, characterized by fragmented plots, irregular shapes, and varying scales. To improve detection accuracy in these contexts, this
Externí odkaz:
https://doaj.org/article/0fa2882da8bf4c65a594e2e6786488df
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 135, Iss , Pp 104241- (2024)
The heterogeneity and complexity of multimodal data in high-resolution remote sensing images significantly challenges existing cross-modal networks in fusing the complementary information of high-resolution optical and synthetic aperture radar (SAR)
Externí odkaz:
https://doaj.org/article/4d1acf6a071f44018b48ac968220ba00
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Ephemeral gully headcut erosion contributes significantly to global land degradation and increased sediment yields, but the underlying driving factors and prediction models remain poorly understood. We conduct a comprehensive quantitative analysis of
Externí odkaz:
https://doaj.org/article/c3e127b37f214483b9d7624c59af4856
Publikováno v:
Zhejiang Daxue xuebao. Lixue ban, Vol 51, Iss 2, Pp 131-142 (2024)
High spatial resolution remote sensing images contain rich information, it is therefore very important to study their semantic segmentation. Traditional machine learning methods appear low accuracy and efficiency when used for segmenting high-resolut
Externí odkaz:
https://doaj.org/article/91a8827f7d9541ddbf34b7b47ff39e0f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 6514-6528 (2024)
Extracting building heights from single-view remote sensing images greatly enhances the application of remote sensing data. While methods for extracting building height from single-view shadow images have been widely studied, it remains a challenging
Externí odkaz:
https://doaj.org/article/b46436f217e2466ab7a079d5cde60833
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3664-3673 (2024)
Semantic segmentation is a basic task in the interpretation of remote sensing images. Mainstream deep-learning-based semantic segmentation algorithms typically process images with small sizes. However, remote sensing images typically involve large ar
Externí odkaz:
https://doaj.org/article/3f08fd084f7f4a86bcb16f2ccdbdb8f3
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 2489-2500 (2024)
This article addresses the problem of building segmentation for rural areas with high-resolution remote sensing images. Due to the irregular spatial distribution of rural buildings, it is often challenging to perform pixel-wise dense prediction to en
Externí odkaz:
https://doaj.org/article/4f8cb010b0694790b2700a781830091f
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1638-1655 (2024)
Rapid and reliable gully erosion (GE) extraction from high-resolution remote sensing (HRRS) images is crucial for the development of land protection measures. For this task, semantic segmentation methods are widely considered the state-of-the-art sol
Externí odkaz:
https://doaj.org/article/76f68b8326c44cd896fcf9b8fccd4c47
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 323-339 (2024)
Existing zero-watermarking algorithms for remote sensing images heavily rely on traditional feature extraction techniques, which are vulnerable to targeted attacks and lack discriminability for images captured by different sensors or at different tim
Externí odkaz:
https://doaj.org/article/23bb2a27515440dbac1fedfec1aa0a53