Jian Wang

ORCID: 0000-0003-0813-5965
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About
Contact & Profiles
Research Areas
  • Remote Sensing in Agriculture
  • Plant Water Relations and Carbon Dynamics
  • Climate change and permafrost
  • Cryospheric studies and observations
  • Land Use and Ecosystem Services
  • Climate variability and models
  • Remote Sensing and LiDAR Applications
  • Species Distribution and Climate Change
  • Remote Sensing and Land Use
  • Tree-ring climate responses
  • Forest, Soil, and Plant Ecology in China
  • Environmental Changes in China
  • Remote-Sensing Image Classification
  • Underwater Vehicles and Communication Systems
  • Geological Studies and Exploration
  • Environmental and Agricultural Sciences
  • Soil Carbon and Nitrogen Dynamics
  • Landslides and related hazards
  • Smart Agriculture and AI
  • Geology and Paleoclimatology Research
  • Wetland Management and Conservation
  • Microbial Community Ecology and Physiology
  • Leaf Properties and Growth Measurement
  • Peatlands and Wetlands Ecology
  • Plant responses to elevated CO2

University of Chinese Academy of Sciences
2008-2025

Chinese Academy of Sciences
2011-2025

Institute of Geographic Sciences and Natural Resources Research
2024-2025

The Ohio State University
2020-2024

Shenyang Institute of Automation
2014-2024

Henan Agricultural University
2019-2024

China Geological Survey
2024

Nanjing Normal University
2013-2023

Shandong Institute of Automation
2021-2023

Beijing Academy of Artificial Intelligence
2023

Timely and accurate mapping of winter crop planting areas in China is important for food security assessment at a national level. Time-series vegetation indices, such as the normalized difference index (NDVI), are widely used mapping, they can characterize growth cycle crops. However, with moderate spatial resolution optical imagery acquired by Landsat Sentinel-2, it difficult to obtain complete time-series curves indices due influence revisit satellite weather conditions. Therefore, this...

10.3390/rs11070820 article EN cc-by Remote Sensing 2019-04-05

Garlic and winter wheat are major economic grain crops in China, their boundaries have increased substantially recent decades. Updated accurate garlic maps critical for assessing impacts on society the environment. Remote sensing imagery can be used to monitor spatial temporal changes croplands such as maize. However, our knowledge, few studies focusing area mapping. Here, we proposed a method coupling active passive satellite identification of both Northern China. First, (Sentinel-2...

10.3390/rs12213539 article EN cc-by Remote Sensing 2020-10-28

The expanding world population is expected to double the worldwide demand for food by 2050. Eighty-eight percent of countries currently face a serious burden malnutrition, especially in Africa and south southeast Asia. About 95% energy needs humans are fulfilled just 30 species, which wheat, maize, rice provide majority calories. Therefore, diversify stabilize global supply, enhance agricultural productivity, tackle greater use neglected or underutilized local plants (so-called orphan crops,...

10.1093/gigascience/giy152 article EN cc-by GigaScience 2018-12-07

To realize highly precise and automatic cloud detection from multi-sensors, this paper proposes a algorithm-generating (CDAG) method for remote sensing data visible to short-wave infrared (SWIR) bands. Hyperspectral with high spatial resolution were collected used as pixel dataset of cloudy clear skies. In paper, multi-temporal AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) 224 bands at SWIR wavelengths 20 m the dataset. Based on dataset, pixels different types clouds land cover...

10.1016/j.isprsjprs.2016.12.005 article EN cc-by-nc-nd ISPRS Journal of Photogrammetry and Remote Sensing 2016-12-31

Wetlands are one of the world’s most important ecosystems, playing an role in regulating climate and protecting environment. However, human activities have changed land cover wetlands, leading to direct destruction If wetlands be protected, their must classified changes it monitored using remote sensing technology. The random forest (RF) machine learning algorithm, which offers clear advantages (e.g., processing feature data without selection preferable classification result) for high...

10.3390/rs11161927 article EN cc-by Remote Sensing 2019-08-17

Significance Decline in winds over past decades were observed high northern latitudes (>50°), yet its influence on the date of autumn leaf senescence (DFS) remains unknown. Using ground observations, flux measurements, and remote sensing imagery, here we show that decline significantly extended DFS at a magnitude comparable with temperature precipitation effects. We found reduces evapotranspiration, causes fewer damaging effects, also results decreased cooling effect. Our therefore are...

10.1073/pnas.2015821118 article EN cc-by-nc-nd Proceedings of the National Academy of Sciences 2021-04-12

Abstract Spring vegetation phenology (green‐up onset date, GUD) exhibits notable sensitivity to climate change, serving as a critical indicator of ecosystem dynamics. However, long‐term changes and drivers GUD remain unclear. Here we showed that satellite‐derived averaged over China forests grasslands advanced by −1.3 ± 0.4 (mean SD) days decade −1 during 1982–2022, but with contrasting trends between (−5.0 0.6 ) (2.8 ), despite similarly increasing temperature precipitation. Such were...

10.1029/2024ef005379 article EN cc-by-nc-nd Earth s Future 2025-03-01

Global climate change substantially influences vegetation spring phenology, that is, green-up date (GUD), in the northern permafrost region. Changes GUD regulate ecosystem carbon uptake, further feeding back to local and regional systems. Extant studies mainly focused on direct effects of factors, such as temperature, precipitation, insolation; however, responses degradation caused by warming (i.e., indirect effects) remain elusive yet. In this study, we examined impacts analyzing long-term...

10.1111/gcb.16011 article EN Global Change Biology 2021-12-02

Vegetation in the Mongolian Plateau is very sensitive to climate change, which has a significant impact on regulation of terrestrial carbon cycle.We analyzed spatio-temporal changes both growing season and seasonal Normalized Difference Index (NDVI) using simple linear trend analysis. Besides, correlation analysis was applied explore factors' effects vegetation growth at temporal spatial scale. Potential human factors were also explored by residual analysis.The results indicated that showed...

10.7717/peerj.7735 article EN cc-by PeerJ 2019-09-30

Agriculture is increasingly facing major challenges such as climate change, scarcity of natural resources, and changing societal demands. To tackle these challenges, there a pressing need to evolve towards more sustainable agricultural practices. As result, sustainability stands among the most relevant topics in research worldwide, countries along Belt Road (B&R) route are no exception. This paper selected 25 indicators from five subsystems population, society, economy, environment,...

10.3390/su11072004 article EN Sustainability 2019-04-04

Microbial communities play critical roles in soil nitrogen (N) cycle; however, we have limited understanding of the distribution N-cycling microbial groups deeper horizons. In this study, used quantitative PCR to characterize changes populations (16S rRNA and 18S rRNA) five key gene abundances involved N fixation (nifH), ammonia oxidation (amoA) by ammonia-oxidizing bacteria (AOB) archaea (AOA), nitrite reduction (nirS nirK) along profiles (0–100 cm depth) different paddy soils from three...

10.1371/journal.pone.0189506 article EN cc-by PLoS ONE 2017-12-28

High-yield rice cultivation is an effective way to address the increasing food demand worldwide. Correct classification of high-yield a key step breeding. However, manual measurements within breeding programs are time consuming and have high cost low throughput, which limit application in large-scale field phenotyping. In this study, we developed accurate approach presented potential usage hyperspectral data for yield measurement using XGBoost algorithm speed up process many breeders. total,...

10.34133/2021/9765952 article EN Plant Phenomics 2021-01-01

Abstract The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998–2012) due to ocean energy redistribution. However, lack of studies about natural cooling effects hampers our understanding vegetation responses climate change. Using 15,125 ground phenological time series at 3,620 sites since 1950s and 31-year satellite greenness observations (1982–2012) covering period, we show a stronger response leaf onset date (LOD) than warming, i.e....

10.1093/pnasnexus/pgad308 article EN cc-by PNAS Nexus 2023-09-01

China has experienced an unprecedented increase in nitrogen deposition over recent decades, threatening ecosystem structure, functioning, and resilience. However, the impact of elevated on date foliar senescence remains widely unexplored. Using 22,780 situ observations long-term satellite-based measures for woody species across China, we find that increased generally delays senescence, with strong causal evidence observed at site-to-region scales. Changes climate conditions levels jointly...

10.1038/s41467-025-59000-0 article EN cc-by-nc-nd Nature Communications 2025-04-17
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