Article
Construction & Building Technology
Xue Zhong, Lihua Zhao, Jie Wang, Haichao Zheng, Junru Yan, Rong Jin, Peng Ren
Summary: This paper proposed a method to retrieve pixel-scale emissivity on the micro-scale by measuring reflectance spectra and emissivity spectra in the field using spectrometers. Empirical models characterizing correlations between the normalized difference vegetation index (NDVI) and emissivity were established and applied to low-altitude hyperspectral images from a drone. The accuracy of emissivity retrieval for different sensors was assessed, with the model based on the SRF of Aster found to be the most accurate.
BUILDING AND ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
Jean Moussa Kourouma, Emmanuel Eze, Emnet Negash, Darius Phiri, Royd Vinya, Atkilt Girma, Amanuel Zenebe
Summary: The study aimed to characterize agricultural drought in Ethiopia and understand its effects on crop yield using NDVI and VCI values. Results showed that VCI and NDVI data are useful for drought monitoring in Ethiopia, and that crops like maize, teff, and beans are more vulnerable to drought.
GEOMATICS NATURAL HAZARDS & RISK
(2021)
Article
Agronomy
Ewa Panek, Dariusz Gozdowski
Summary: This study analyzed the relationships between NDVI and grain yield in 20 European countries, finding strong correlations in Croatia, Czechia, Germany, Hungary, Latvia, Lithuania, Poland, and Slovakia, allowing for early yield prediction. Weak relationships were observed in France and Belgium.
Article
Plant Sciences
Weeberb J. Requia, Claudia Costa Saenger, Rejane Ennes Cicerelli, Lucijane Monteiro de Abreu, Vanessa R. N. Cruvinel
Summary: This study investigates the association between greenness and academic performance at the school-level in Brazil. The results show a positive correlation between green areas surrounding schools and math academic performance, suggesting that improving the environment around schools can promote public health.
URBAN FORESTRY & URBAN GREENING
(2022)
Article
Environmental Sciences
Ilknur Zeren Cetin, Tugrul Varol, Halil Baris Ozel, Hakan Sevik
Summary: Economic and industrial development have led to population concentration in cities, resulting in the urban heat island effect. This study analyzed the changes in the urban heat island effect in the central district of Bartin over the past 30 years and found increases in urban surfaces and land surface temperatures, as well as a decline in vegetation. The results emphasized the importance of increasing open and green areas to mitigate the negative effects of the urban heat island.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Forestry
Xisheng Hu, Chongmin Xu, Jin Chen, Yuying Lin, Sen Lin, Zhilong Wu, Rongzu Qiu
Summary: Urban vegetation plays a crucial role in regulating urban climate and improving the urban environment. This study proposes a synthetic vegetation quality index (VQI) to effectively and quickly assess urban vegetation quality and detects its changes over time. The results demonstrate the reliability and applicability of the VQI in evaluating urban vegetation quality and its impact on the urban thermal environment.
Article
Plant Sciences
Tiantian Chen, Qiang Wang, Yuxi Wang, Li Peng
Summary: Vegetation is crucial for the earth's surface system and its changes serve as an indicator of global climate change. This study used advanced methods to analyze the vegetation trends in China from 1982 to 2018. The results show that China experienced abrupt changes in vegetation growth in the 1990s and 2000s, with significant impacts on the entire country. Climate and human activities played important roles in driving these changes.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Environmental Sciences
Huoqing Li, Zonghui Liu, Ali Mamtimin, Junjian Liu, Yongqiang Liu, Chenxiang Ju, Hailiang Zhang, Zhibo Gao
Summary: The study proposes a new method for estimating broadband emissivity in arid regions using FTIR observations, MODIS emissivity, LAI, and reflectance products, which showed higher variations and finer distribution compared to global satellite and land model data. The proposed method accurately estimates broadband emissivity in arid regions and reveals a complex relationship between emissivity, land-use type, and soil moisture under an inhomogeneous surface. Future research will focus on testing the data in a land model.
Article
Environmental Sciences
Yuan Zou, Wei Chen, Siliang Li, Tiejun Wang, Le Yu, Min Xu, Ramesh P. Singh, Cong-Qiang Liu
Summary: This study conducted a detailed analysis of spatio-temporal vegetation patterns in the Beijing-Tianjin-Hebei region. The results show a slow upward trend in vegetation indices and leaf area indices, with variations observed among different vegetation types and regions. The study also reveals significant correlations between air temperature, precipitation, and net primary production, as well as negative impacts of urbanization on vegetation.
Article
Environmental Studies
Ruifeng Wang, Fengling Shi, Dawei Xu
Summary: This study developed a method for alfalfa mapping using remote sensing data by analyzing the time-series variation characteristics of different vegetation types. The results showed that the number of wave peaks and valleys in the normalized difference vegetation index curve could be used as criteria for alfalfa extraction. The method achieved promising results with high classification accuracy.
Article
Plant Sciences
Silvas Prince, Md Rokebul Anower, Christy M. Motes, Timothy D. Hernandez, Fuqi Liao, Laura Putman, Rob Mattson, Anand Seethepalli, Kushendra Shah, Michael Komp, Perdeep Mehta, Larry M. York, Carolyn Young, Maria J. Monteros
Summary: Drought stress has negative impacts on crop growth and profitability. This study compared two different alfalfa subspecies and identified key morphological and physiological traits for enhancing biomass yield under drought stress. Field surveys and root architecture analysis further validated the importance of these traits. Different drought-adaptive strategies were identified across subspecies populations, which will contribute to the development of alfalfa cultivars suitable for various growing conditions. Combining genes from both subspecies can lead to the development of drought-tolerant alfalfa with higher productivity under limited water availability.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Agriculture, Multidisciplinary
Yongqian Ding, Xueni Wu, Hongfeng Yu, Yizhuo Jiang, Zhuo Liu, Xianglin Dou
Summary: By introducing the standard whiteboard response ratio CW with constant value, a new method for calculating VIs was constructed, which showed strong adaptability to natural light intensity and measurement heights. The measured NDVI values were stable and more accurate compared to traditional methods.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Environmental Sciences
Amir Nejatian, Masoud Makian, Mohammad Gheibi, Amir M. Fathollahi-Fard
Summary: The study focuses on the impact of implementing green city concept in Mashhad, Iran on air pollution. The results show that the vegetation area is positively correlated to clean and healthy days, and negatively correlated to unhealthy days in the city. The increase in NDVI, EVI, and OSAVI is indicative of the positive effect of green space on air quality.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Geography, Physical
Shuxu Li, Zheng Zhou, Rongfei Ma, Shishi Liu, Qingfeng Guan
Summary: The normalized difference vegetation index (NDVI) is widely used to monitor vegetation vigor and cover. In heterogeneous urban areas, mixed pixels affect the accurate estimation of gross primary productivity (GPP). This study proposed a framework to extract subpixel vegetation NDVI (NDVIvege) and showed its potential for characterizing vegetation dynamics in heterogeneous areas.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Environmental Sciences
Honglei Jiang, Xia Xu, Tong Zhang, Haoyu Xia, Yiqin Huang, Shirong Qiao
Summary: This study analyzed the vegetation dynamics in coastal China and found that both greenification and degradation of vegetation were present with significant spatial heterogeneity. Human activities had a greater positive impact on vegetation compared to climate change, particularly in the northern and southern regions. The findings provide evidence for the designation of rational ecological conservation policies.
Article
Geochemistry & Geophysics
Feng Yang, Jie Cheng, Qi Zeng
Summary: This study validated a CBT-based SLCM at the global scale and achieved relatively high SLDR estimation accuracy for Terra and Aqua satellites, but with slightly worse random RMSE compared to CERES products.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Remote Sensing
Jie Cheng, Qi Zeng, Jiancheng Shi
Summary: This paper proposes a direct algorithm for estimating the surface longwave net radiation (SLNR) using satellite radiances and water vapor data. The relationships were established using multivariate regression and extreme gradient boosting, showing that the direct algorithm performs better than the conventional method. Results indicate that there is a weak nonlinearity between clear-sky SLNR and predictors.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Agronomy
Junming Yang, Yunjun Yao, Changliang Shao, Yufu Li, Joshua B. Fisher, Jie Cheng, Jiquan Chen, Kun Jia, Xiaotong Zhang, Ke Shang, Ruiyang Yu, Xiaozheng Guo, Zijing Xie, Lu Liu, Jing Ning, Lilin Zhang
Summary: A novel method for daily LE estimation using all-weather LST was proposed and validated in mainland China, demonstrating its accuracy at regional scale.
AGRICULTURAL AND FOREST METEOROLOGY
(2022)
Article
Multidisciplinary Sciences
Hui Liang, Bo Jiang, Shunlin Liang, Jianghai Peng, Shaopeng Li, Jiakun Han, Xiuwan Yin, Jie Cheng, Kun Jia, Qiang Liu, Yunjun Yao, Xiang Zhao, Xiaotong Zhang
Summary: A new long-term global daily net radiation product for the ocean surface was generated in this study, addressing the shortcomings of existing datasets. By fusing multiple datasets and comparing with in-situ measurements, estimates and growth rates of global ocean surface net radiation were obtained, providing valuable data for oceanic and climatic studies.
Article
Geography, Physical
Shaopeng Li, Bo Jiang, Shunlin Liang, Jianghai Peng, Hui Liang, Jiakun Han, Xiuwan Yin, Yunjun Yao, Xiaotong Zhang, Jie Cheng, Xiang Zhao, Qiang Liu, Kun Jia
Summary: Based on a comprehensive evaluation of different machine learning and deep learning methods, this study found that deep learning methods perform better in estimating all-wave net radiation, particularly the ResNet model showed robustness in different conditions. However, deep learning methods have disadvantages in terms of implementation environment configurability and computational efficiency.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2022)
Article
Environmental Sciences
Shengyue Dong, Jie Cheng, Jiancheng Shi, Chunxiang Shi, Shuai Sun, Weihan Liu
Summary: This paper proposes a data fusion method for generating hourly seamless land surface temperature (LST) from Himawari-8 Advanced Himawari Imager (AHI) data. The method involves retrieving high-quality LST from AHI data, calibrating it with the China Land Data Assimilation System (CLDAS) LST, and combining the two using the multiresolution Kalman filter (MKF) algorithm. The validation results show that the fused LST is comparable in accuracy to other methods and provides consistent LST images at different spatial scales.
Article
Green & Sustainable Science & Technology
Tingting Bai, Jie Cheng, Zihao Zheng, Qifei Zhang, Zihao Li, Dong Xu
Summary: In the past 18 years, the ecoenvironmental quality in more than 60% of China has improved, with natural factors and human activities jointly dominating 58% of the EEQ change. Climate water deficit is the most important natural factor. Human activities such as population, gross domestic product, and electricity consumption have significantly increased in the past 18 years, simultaneously dominating the EEQ change in about 18% of China's areas. Therefore, rational development of human activities is crucial for China's ecoenvironmental quality in the context of global climate change.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Environmental Sciences
Qi Zeng, Jie Cheng, Mengfei Guo
Summary: This study comprehensively evaluates the accuracy of mainstream surface longwave (LW) radiation products (GLASS, CERES SYN and ERA5) in terms of surface longwave upward radiation (SLUR) and surface longwave downward radiation (SLDR). The GLASS product shows the best accuracy under clear-sky conditions, while ERA5 has the best overall accuracy. The global annual mean values of SLUR and SLDR are quantified, along with their temporal variations from 2003 to 2020. This evaluation and trend analysis contribute to understanding global energy balance and climate change.
Article
Engineering, Electrical & Electronic
Xiangchen Meng, Weihan Liu, Jie Cheng, Hao Guo, Beibei Yao
Summary: This article extends the current land surface temperature retrieval algorithms by incorporating a daily land surface emissivity database for high-temporal-resolution retrieval. The validation results show that using the daily land surface emissivity obtained from Feng Yun-4A/Advanced Geostationary Radiation Imager data can improve the accuracy of land surface temperature retrieval.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Shugui Zhou, Jie Cheng
Summary: Surface longwave upwelling radiation (SLUR) is an important parameter for studying water-energy balance. A new hybrid method was proposed to estimate SLUR using MODIS data. The method utilizes a physical four-channel algorithm to estimate atmospheric terms and a linear model to relate SLUR to MODIS radiance. Validation results showed that the new method outperformed the original method and was slightly better than the classical hybrid method. The new method can accurately estimate SLUR and has the potential to provide long-term high-resolution environmental data.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Weihan Liu, Jie Cheng, Qiao Wang
Summary: This study proposes an effective method to estimate hourly all-weather land surface temperature (LST) using Advanced Geosynchronous Radiation Imager (AGRI) data. The method involves an improved temperature and emissivity separation algorithm to obtain high-quality clear-sky LST and a unique approach to solve the temperature difference between cloudy-sky LST and hypothetical clear-sky LST caused by cloud radiative effects. The estimated all-weather LST shows promising results in capturing diurnal variations and can be upscaled temporally.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Remote Sensing
Xiangchen Meng, Weihan Liu, Jie Cheng, Hao Guo
Summary: The adapted enterprise algorithm was used to retrieve land surface temperature from FY-4A thermal infrared data, and it was found that using the daily composite of emissivity data resulted in better accuracy. This study demonstrates the effectiveness of the algorithm.
REMOTE SENSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Shugui Zhou, Jie Cheng, Jiancheng Shi
Summary: In this study, a physical-based framework for generating high-frequency all-weather land surface temperature (LST) data was developed by synchronizing geostationary satellite thermal-infrared observations and land surface model simulations. The framework consisted of three parts: retrieval of clear-sky LST, assimilation of observations into the land surface model, and fusion of retrieved LST and assimilated LST using an ensemble Kalman filter algorithm. The proposed framework was shown to be capable of obtaining accurate high-frequency all-weather LST data.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Xiangchen Meng, Jie Cheng, Hao Guo, Yahui Guo, Beibei Yao
Summary: This article evaluates the performance of the Landsat 9 land surface temperature (LST) product and compares it with the LST products from Landsat 7/8. The results show that the Landsat 9 LST product performs well and is similar to other products. The evaluation results also validate the consistency of the Landsat 9 LST product, indicating its usability in multiple applications.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Xiangchen Meng, Hao Guo, Jie Cheng, Beibei Yao
Summary: This study investigates the performance of the ERA5 reanalysis product in atmospheric correction of Landsat series TIR data. The ERA5 product outperforms other datasets in Asia and Europe, but performs poorly in the Americas and Africa.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
