Article
Environmental Sciences
Kai Wu, Jiahao Chen, Han Yang, Yue Yang, Zhongmin Hu
Summary: This study examines the temporal variability of vegetation sensitivity to climate factors on the Qinghai-Tibet Plateau (QTP) using various vegetation indicators. The results show that temperature has a positive impact on forests, grasslands, and barren areas, but the sensitivity of all land-cover types to temperature variability has decreased. Solar radiation has a positive impact on forests, but a negative impact on grasslands and barren areas. Water availability has a positive impact on grasslands and barren areas, while its impact on forests is unclear. Overall, temperature is the most important climate factor affecting vegetation sensitivity on the QTP.
Article
Environmental Sciences
Haibo Feng, Jianwei Zhou, Aiguo Zhou, Hengli Xu, Danhui Su, Xu Han
Summary: This study proposes three indicators to characterize vegetation landscape stability and processes, which were applied to detect landscape changes and stability through spatio-temporal analysis. The results of the study align with on-site conditions, indicating the effectiveness of the indicators in identifying the stability and dynamic trend of grassland landscape.
LAND DEGRADATION & DEVELOPMENT
(2022)
Article
Ecology
Alison K. Post, Kristin P. Davis, Jillian LaRoe, David L. Hoover, Alan K. Knapp
Summary: The frequency and intensity of deluges are increasing globally as the climate warms. Semiarid grasslands are particularly sensitive to the timing and size of deluges, with postdeluge canopy greenness usually increasing linearly with larger deluge size. Grazing regimes did not significantly alter the responses to deluges in this study.
Article
Remote Sensing
Kamel Soudani, Nicolas Delpierre, Daniel Berveiller, Gabriel Hmimina, Gaelle Vincent, Alexandre Morfin, Eric Dufrene
Summary: The study uses the annual time-series data of two C-band SAR satellites, Sentinel-1A and 1B, to characterize the phenological cycle of a temperate deciduous forest over five years. Various phenological metrics were derived from the backscattering data and compared to ground-based observations, showing discrepancies in budburst and leaf senescence. The study demonstrates the potential of using Sentinel-1 SAR C-band time-series for forest phenology detection and the limitations of optical remote sensing in cloud-covered areas.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Maninder Singh Dhillon, Thorsten Dahms, Carina Kuebert-Flock, Ingolf Steffan-Dewenter, Jie Zhang, Tobias Ullmann
Summary: The increasing availability and variety of global satellite products provide new levels of data with different spatial, temporal, and spectral resolutions. However, determining the most suitable resolution for a specific application is becoming more time-consuming and complicated. Cloud coverage in the region affects the trade-off between spatial and temporal resolution, and different pixel sizes of remote sensing data can hinder accurate monitoring of various land cover classes.
Article
Environmental Sciences
Yujiao Wei, Lin Zhu, Yun Chen, Xinyu Cao, Huilin Yu
Summary: This study combined different resolution vegetation index data to investigate the spatiotemporal characteristics of vegetation and drought in Inner Mongolia over the past 38 years. The results showed that grasslands had a stronger response to drought compared to forests.
Article
Environmental Sciences
Jiaxin Zhang, Tao Yang, Mingjiang Deng, Huiping Huang, Yuping Han, Huanhuan Xu
Summary: This study explores the spatiotemporal evolution characteristics and driving mechanisms of vegetation in the Northwest China using NDVI data. The results show an overall improvement trend in vegetation, but also identified areas with deterioration tendencies. Key parameters influencing vegetation distribution include precipitation, vegetation type, land use type, and soil type. Both climate variations and human activities have been recognized as significant factors affecting vegetation growth, with human activities playing a more influential role.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
Guojin Pang, Deliang Chen, Xuejia Wang, Hui-Wen Lai
Summary: Land surface albedo on the Tibetan Plateau (TP) showed significant spatial and temporal variations from 1982 to 2015, influenced by factors such as snow cover, vegetation, and soil moisture. The average albedo exhibited a clear seasonal cycle with a peak in winter and a minimum value in summer, with a weakly downward trend in annual average albedo. Interannual variation of albedo was more responsive to changes in snow cover and vegetation cover in different regions on the TP.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Ecology
Guangshuai Li, Lingxue Yu, Tingxiang Liu, Yulong Bao, Jiaxin Yu, Bingxia Xin, Lun Bao, Xuan Li, Xinyue Chang, Shuwen Zhang
Summary: Based on MODIS NDVI data and growth season meteorological data, this study investigated the spatial and temporal variation characteristics of grassland vegetation on the Mongolian Plateau, as well as the dual response of NDVI changes to climate and human activities. The results showed that the average NDVI of grassland vegetation increased gradually from southwest to northeast during the growing season, with a significant overall increase from 2000 to 2018. Precipitation, average air temperature, and downward surface shortwave radiation all played a role in influencing the NDVI variations, with Inner Mongolia experiencing higher precipitation rates and lower air temperature and surface shortwave radiation rates compared to Mongolia. The study emphasized the importance of ecological engineering and agricultural production activities for vegetation recovery in the region. The findings contribute to our understanding of surface-atmosphere interactions in arid and semi-arid regions in the context of global climate change.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2023)
Article
Environmental Sciences
Libo Wang, Guoqiang Wang, Baolin Xue, A. Yinglan, Qingqing Fang, Sangam Shrestha
Summary: This study evaluates the changes in evapotranspiration (ET) in the Hailar River Basin using a distributed hydrological model. The results show an increasing trend in ET over the past 40 years, with significant spatial heterogeneity. Climate warming, precipitation, and vegetation dynamics are identified as the main factors influencing ET.
ENVIRONMENTAL RESEARCH
(2022)
Article
Environmental Sciences
Jiaxin Shang, Yang Zhang, Yu Peng, Yihang Huang, Lu Zhu, Zhuoyi Wu, Jing Wang, Yixin Cui
Summary: The study found that vegetation in Northwest China experienced greening from 2000 to 2015, mainly influenced by precipitation and temperature, with population being the major factor under low precipitation gradients. Climate change was identified as the primary driver of vegetation change.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Agronomy
Wei Cheng, Beibei Shen, Xiaoping Xin, Qian Gu, Tao Guo
Summary: This study investigates the spatiotemporal variations of grassland ecosystem service value (ESV) and its influencing factors in Inner Mongolia. The results show that the ESV is higher in the northeast and gradually increases over time. The normalized vegetation index (NDVI) and precipitation are found to be the main factors affecting the distribution of ESV. These findings can provide valuable insights for policymaking in natural resource conservation or restoration.
Article
Robotics
Hui Yang, Siqi Zhang, Yan Lu, Paul Witherell, Soundar Kumara
Summary: This paper presents a stochastic modeling framework for monitoring melt-pool variations in the metal-based additive manufacturing process. Experimental results show the effectiveness of tensor decomposition for spatiotemporal monitoring of melt-pool variations.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Environmental Sciences
Abdelraouf M. Ali, Igor Savin, Anton Poddubskiy, Mohamed Abouelghar, Nasser Saleh, Khaled Abutaleb, Mohammed El-Shirbeny, Peter Dokukin
Summary: This study successfully mapped the rice cultivated areas in Kafr El-Sheikh governorate using Sentinel-2 satellite data and a remote sensing-based classification method, providing an effective estimate for the expected yield. The methodology showed high accuracy and correlation between the measured and predicted parameters, demonstrating its potential application in estimating rice area and yield in the northern Nile delta before harvest.
EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES
(2021)
Article
Environmental Sciences
Chin-Yu Hsu, Hong-Xin Xie, Pei-Yi Wong, Yu-Cheng Chen, Pau-Chung Chen, Chih-Da Wu
Summary: This study is the first to predict spatial-temporal variations in benzene concentrations for the entirety of Taiwan using a mixed spatial prediction model and multiple machine learning algorithms. The results show the value of the proposed ensemble-based model for estimating spatiotemporal variation in benzene exposure.
