Remote Sensing Monitoring of Grasslands Based on Adaptive Feature Fusion with Multi-Source Data

Article Environmental Sciences

Changes in soil carbon and nitrogen stocks following degradation of alpine grasslands on the Qinghai-Tibetan Plateau: A meta-analysis

Xiang Liu et al.

Summary: The study revealed that grassland degradation on the Qinghai-Tibetan Plateau led to reductions in SOC and STN stocks, with the most significant decreases observed at extreme degradation stages. The dynamics of vegetation coverage were positively correlated with changes in SOC and STN stocks, indicating its potential as an indicator of grassland degradation and soil quality changes. Preventing the degradation succession of alpine grasslands is crucial for maintaining or promoting SOC and STN levels in this region.

LAND DEGRADATION & DEVELOPMENT (2021)

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Review Computer Science, Artificial Intelligence

A review of deep learning methods for semantic segmentation of remote sensing imagery

Xiaohui Yuan et al.

Summary: This paper reviews the application of deep learning methods for semantic segmentation of remote sensing imagery and identifies challenges in handling non-traditional data as well as small datasets. Researchers are still facing difficulties in developing and evaluating new deep learning methods for remote sensing analysis.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Environmental Sciences

Land Use Land Cover Classification with U-Net: Advantages of Combining Sentinel-1 and Sentinel-2 Imagery

Jonathan V. Solorzano et al.

Summary: The study compared the performance of different algorithms for LULC mapping using U-net with SAR and MS image inputs. The results demonstrated that the MS + SAR U-net achieved higher accuracy and F1-scores, especially in distinguishing old-growth forests from secondary forests.

REMOTE SENSING (2021)

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Article Computer Science, Artificial Intelligence