A cloud-computing framework for downscaled global 300 m SIF retrieval from Sentinel-3 and TROPOSIF [0.03%]
基于Sentinel-3和TROPOSIF的全球300m尺度气导荧光数据降尺度反演云计算框架
Yuxin Zhang,Pablo Reyes-Muñoz,Jochem Verrelst
Yuxin Zhang
Sun-induced chlorophyll fluorescence (SIF) is a critical indicator of photosynthetic activity. Yet, existing satellite SIF products typically suffer from coarse spatial resolutions, generally coarser than 500 m, which limits their utility f...
Detecting gaps between urban expansion and lighting infrastructure growth using daytime and nighttime satellite imagery [0.03%]
基于昼夜间卫星遥感数据的城市扩张与照明设施增长差异检测研究
Tzu-Hsin Karen Chen,Wei Chen,Eleanor C Stokes et al.
Tzu-Hsin Karen Chen et al.
Characterizing the evolution of urban settlements is vital for informed urban planning that mitigates associated risks. Urban development has traditionally been examined in two dimensions using Earth observation: land cover change, monitore...
Predicting environmental suitability and future spread range of An. stephensi in the Greater Horn of Africa using remote sensing and ensemble modeling [0.03%]
基于遥感和集合模型预测非洲之角斯氏按蚊的生态适宜性和未来扩散范围
Jinyang Li,Ming-Chieh Lee,Ai-Ling Jiang et al.
Jinyang Li et al.
Malaria, a life-threatening disease, remains a major global health challenge, particularly in Africa. While Anopheles gambiae sensu lato has long been the primary vector in Africa, the recent invasion of Anopheles stephensi-an urban malaria...
How accurately does L band vegetation optical depth predict aboveground biomass? [0.03%]
L波段植被光学厚度对地上生物量的预测精度如何？
Yuan Zhang,Philippe Ciais,Jean-Pierre Wigneron et al.
Yuan Zhang et al.
L-band Vegetation Optical Depth (L-VOD) has emerged as a critical remote sensing proxy for monitoring global aboveground biomass (AGB) dynamics. Persistent methodological ambiguities, including the absence of standardized protocols for deri...
Geospatial impact evaluation of a low-cost agricultural intervention for enhancing environmental resilience [0.03%]
低成本的农业干预措施增强环境恢复力的空间影响评估
Pratap Khattri,Rachel Sayers,Kunwar K Singh et al.
Pratap Khattri et al.
Land degradation poses a significant threat to ecosystems and livelihoods, particularly in disaster-prone regions. In these settings, the promotion of certain agricultural practices with economic incentives, such as sugarcane (Saccharum off...
Optimizing the detection of emerging infections using mobility-based spatial sampling [0.03%]
基于流动性的空间抽样优化新兴感染的检测
Die Zhang,Yong Ge,Jianghao Wang et al.
Die Zhang et al.
Timely and precise detection of emerging infections is imperative for effective outbreak management and disease control. Human mobility significantly influences the spatial transmission dynamics of infectious diseases. Spatial sampling, int...
Unraveling near real-time spatial dynamics of population using geographical ensemble learning [0.03%]
基于地理集合学习的.population空间动态近实时解析
Yimeng Song,Shengbiao Wu,Bin Chen et al.
Yimeng Song et al.
Dynamic gridded population data are crucial in fields such as disaster reduction, public health, urban planning, and global change studies. Despite the use of multi-source geospatial data and advanced machine learning models, current framew...
The relationship between remotely-sensed spectral heterogeneity and bird diversity is modulated by landscape type [0.03%]
遥感光谱异质性与鸟类多样性关系受景观类型调节
Dominika Prajzlerová,Vojtěch Barták,Petr Keil et al.
Dominika Prajzlerová et al.
To identify areas of high biodiversity and prioritize conservation efforts, it is crucial to understand the drivers of species richness patterns and their scale dependence. While classified land cover products are commonly used to explain b...
Spatially explicit accuracy assessment of deep learning-based, fine-resolution built-up land data in the United States [0.03%]
基于深度学习的美国细分辨率建设用地数据的空间显式精度评价
Johannes H Uhl,Stefan Leyk
Johannes H Uhl
Geospatial datasets derived from remote sensing data by means of machine learning methods are often based on probabilistic outputs of abstract nature, which are difficult to translate into interpretable measures. For example, the Global Hum...
A deep learning approach for automatic identification of ancient agricultural water harvesting systems [0.03%]
一种用于自动识别古代农业集水系统的深度学习方法
Arti Tiwari,Micha Silver,Arnon Karnieli
Arti Tiwari
Despite the harsh climatic conditions in the Central Negev Desert, Israel, thousands of dry stonewalls were built across ephemeral streams between the fourth and seventh centuries CE to sustain productive agricultural activity. Since 640 CE...