Article
Plant Sciences
Fei-Xue Zhang, Chun-Jing Wang, Ji-Zhong Wan
Summary: Invasive tree species pose a threat to ecosystems, natural resources, and managed land worldwide. Consensus land cover data can be an effective tool for predicting the distribution of these species. Open water and evergreen broadleaf trees have a strong explanatory power for the distribution of invasive tree species. These species are primarily found near equatorial, tropical, and subtropical areas. Implementing strong measures to prevent their further expansion is crucial for protecting global biodiversity, human life, safety, and the economy.
Article
Remote Sensing
Ling Zhu, Guangshuai Jin, Xiaohong Zhang, Ruoming Shi, Yixuan La, Cunwen Li
Summary: Accurate and detailed information on land cover products is essential for studying global climate change and sustainable development. The integration method based on fuzzy theory and combining multiple 30 m resolution LC products can improve the accuracy of research in this field.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Environmental Sciences
Yuhao Wu, Claude R. Duguay, Linlin Xu
Summary: This research evaluated the capability of four machine learning classifiers for mapping lake ice cover, water and cloud cover using MODIS satellite data. Random forest (RF) and gradient boosting trees (GBT) offered the most robust spatial transferability over 17 lakes and consistently performed well across ice seasons. RF was relatively insensitive to the choice of hyperparameters compared to the other three classifiers.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Multidisciplinary Sciences
Jonathan Pando Ocon, Thomas Ibanez, Janet Franklin, Stephanie Pau, Gunnar Keppel, Gonzalo Rivas-Torres, Michael Edward Shin, Thomas Welch Gillespie
Summary: There is a debate about the definition and extent of tropical dry forest biome and vegetation type globally. Using the FAO definition and CHELSA climate dataset provides an accurate, standard, and repeatable way to assess tropical dry forest cover and change globally.
Article
Environmental Sciences
Yoshie Ishii, Koki Iwao, Tsuguki Kinoshita
Summary: The study aimed to create a land cover map validation dataset with added spatial uniformity information using satellite images and DCP points, addressing the issue of using DCP points for accuracy assessment of global land cover maps. The new method devised in the study can guarantee the spatial uniformity of DCP validation data points at any resolution semi-automatically with a user's accuracy of 0.954, leading to differences in accuracy assessment trends across classes and regions for existing global land cover maps.
Article
Geosciences, Multidisciplinary
Mengmeng Cao, Kebiao Mao, Yibo Yan, Jiancheng Shi, Han Wang, Tongren Xu, Shu Fang, Zijin Yuan
Summary: This study addressed the issues with existing sea surface temperature (SST) products by developing temperature correction and spatial reconstruction models, effectively improving the accuracy and applicability of SST data. The unique global SST product generated shows significant improvements in handling cloud, rainfall, and land interference, indicating promising applications for analyses of mesoscale ocean phenomena.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Engineering, Environmental
Zhou Zang, Yue Zhang, Chen Zuo, Jiayi Chen, Bin He, Nana Luo, Junxiao Zou, Wenji Zhao, Wenzhong Shi, Xing Yan
Summary: This study proposes a new deep learning model (SCAM) for retrieving global land coarse-mode aerosol optical depths (cAOD). Compared to traditional models, SCAM considers the impact of spatiotemporal feature interactions and can describe both linear and nonlinear relationships, resulting in significantly improved accuracy and coverage of the retrieval results.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Environmental Sciences
Xing Yan, Zhou Zang, Chen Liang, Nana Luo, Rongmin Ren, Maureen Cribb, Zhanqing Li
Summary: This study generated and analyzed a 10-year global FMF product using satellite data, revealing global patterns and interannual/seasonal variations. Different countries showed different linear trends in FMF, with a particularly strong upward trend in Australia since 2008.
ENVIRONMENTAL POLLUTION
(2021)
Article
Remote Sensing
Xiongxin Xiao, Tao He, Shunlin Liang, Xinyan Liu, Yichuan Ma, Shuang Liang, Xiaona Chen
Summary: This study aimed to develop a robust and enhanced algorithm for estimating fractional snow cover (FSC) in vegetated areas. By integrating multiple sub-models and incorporating various variables, the FSC retrieval models showed improved accuracy and robustness. Canopy correction method also enhanced the accuracy of FSC prediction.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Agronomy
Xiao-Peng Song, Haijun Li, Peter Potapov, Matthew C. Hansen
Summary: This study combines long-term satellite and climate data, municipality-level crop yield statistics, and machine learning models to map soybean yield in Brazil. The models achieved good performance with a high-resolution yield map for 2020, demonstrating their predictive capability for future operational yield mapping.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Environmental Sciences
Dorothy K. Hall, Donal S. O'Leary, Nicolo E. DiGirolamo, Woodruff Miller, Do Hyuk Kang
Summary: The Great Salt Lake in Utah has been shrinking since the middle of the 19th Century, with decreased area and volume and increased salinity. Satellite data shows that the main reasons for this decline since 2000 are earlier snowmelt, rising temperatures leading to less snowfall, increased evaporation, and decreasing snow depth.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Tong Heng, Xinlin He, Lili Yang, Jiawen Yu, Yulin Yang, Miaoling Li
Summary: The analysis of the climatic warming in the Tianshan mountains showed a greater nighttime warming rate and a decrease in snow cover percentage. The asymmetrical warming trend has an impact on snow cover activity, which is expected to accelerate in the future.
Article
Environmental Sciences
Kalle Hirvonen, Elia A. Machado, Andrew M. Simons, Vis Taraz
Summary: Over one billion people globally receive cash or in-kind transfers from social protection programs. In low-income countries, these transfers often require participation in labor-intensive public works to rehabilitate local infrastructure or natural resources. However, the environmental impacts of these programs remain largely unknown. This study quantifies the impact of Ethiopia's Productive Safety Net Program (PSNP), one of the largest and longest-running public works programs, on tree cover using satellite-based data and statistical methodologies. The findings suggest that the PSNP has increased tree cover by 3.8%, particularly in less populated areas and steep-sloped terrain, indicating a potential win-win situation for social safety net programs with an environmental focus.
GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS
(2022)
Article
Environmental Sciences
Qingxue Wang, Yonggang Ma, Junli Li
Summary: Using Earth observation to accurately extract snow phenology changes is important for understanding Xinjiang's ecological environment, hydrological process, agricultural and animal husbandry production, and social economy development. This study developed a method to extract key phenological parameters in Xinjiang using MODIS product data and calculated the parameters from 2001 to 2020. The results showed that snow phenology varied with altitude, land use types, and topography. The snow cover area was mainly distributed in the Altai Mountains, Junggar Basin, Tianshan Mountains, and Kunlun Mountains. The variation trend of snow cover phenological parameters in most regions of Xinjiang was non-significant.
Article
Remote Sensing
Yuanyuan Wang, Guicai Li
Summary: This paper reports the production of a global land cover classification map using MERSI-II data. By utilizing various image compositing techniques and supervised learning algorithms, the study achieved high accuracy in LC classification and conducted comparisons with other widely used LC products.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)