[HTML][HTML] A deep-learning-based tree species classification for natural secondary forests using unmanned aerial vehicle hyperspectral images and LiDAR

Y Ma, Y Zhao, J Im, Y Zhao, Z Zhen - Ecological Indicators, 2024 - Elsevier
Accurate tree species classification is essential for forest resource management and
biodiversity assessment. However, classifying tree species becomes challenging in natural …

[HTML][HTML] Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review

M Gašparović, I Pilaš, D Radočaj, D Dobrinić - Applied Sciences, 2024 - mdpi.com
Monitoring and predicting land surface phenology (LSP) are essential for understanding
ecosystem dynamics, climate change impacts, and forest and agricultural productivity …

Experimental evaluation of remote sensing–based climate change prediction using enhanced deep learning strategy

M Madhavi, R Kolikipogu, S Prabakar… - Remote Sensing in …, 2024 - Springer
Climate change is one of the most pressing global challenges of our time, with far-reaching
impacts on ecosystems, economies, and human societies. Accurate prediction of climate …

[HTML][HTML] Deep learning bird song recognition based on MFF-ScSEnet

S Hu, Y Chu, Z Wen, G Zhou, Y Sun, A Chen - Ecological Indicators, 2023 - Elsevier
Bird diversity plays an important role in ecological balance, and bird song identification is of
great practical significance. The spectrum generated by feature extraction shows good …

Assessing the spatial occupation and ecological impact of human activities in Chengguan district, Lhasa city, Tibetan Plateau

L Xu, Y Xu, J Duan, Y Wang, H Yang - Scientific Reports, 2024 - nature.com
In this study, the ecological impact of human activities and the space occupied by
construction and arable land on the Tibetan Plateau were examined, focusing on changes in …

[HTML][HTML] Accurate map** of rapeseed fields in the initial flowering stage using Sentinel-2 satellite images and convolutional neural networks

Y Sun, Z Hao, H Chang, J Yang, G Ding, Z Guo, X He… - Ecological …, 2024 - Elsevier
In high-intensity farming, swiftly and accurately adjusting the proportion of artificially reared
pollinators according to the flowering phenology of crops is vital. This adjustment is essential …

[HTML][HTML] Time-series simulation of alpine grassland cover using transferable stacking deep learning and multisource remote sensing data in the Google Earth Engine

X Lin, J Chen, T Wu, S Yi, J Chen, X Han - International Journal of Applied …, 2024 - Elsevier
The growth of vegetation on the Qinghai Tibet Plateau (QTP) is experiencing significant
changes due to climate change. There is still a lack of high-precision simulation methods for …

The 30 m vegetation maps from 1990 to 2020 in the Tibetan Plateau

F Wu, H Ren, G Zhou - Scientific Data, 2024 - nature.com
Abstract The Tibetan Plateau (TP) is crucial for global climate change and China's
ecological security. Given recent drastic changes in vegetation from climate change and …

[HTML][HTML] Recent decade expansion of aquatic vegetation covering in china's lakes

Z Cao, Y Zhang, Z Liu, B Guan, L Lai, Q Yang… - Ecological Indicators, 2024 - Elsevier
Often characterized as “sentinels of lake aquatic ecosystems”, different life-form aquatic
vegetation covering dynamics reflects both short-and long-term climate fluctuations and …

[HTML][HTML] Effects of Climate Variability and Human Activities on Vegetation Dynamics across the Qinghai–Tibet Plateau from 1982 to 2020

Y Liu, Y **e, Z Guo, G ** - Remote Sensing, 2023 - mdpi.com
In recent years, vegetation on the Qinghai–Tibet Plateau (QTP) has undergone significant
greening. However, the causal factors underpinning this phenomenon, whether attributable …