Article
Engineering, Environmental
Qingrui Wang, Ruimin Liu, Feng Zhou, Jing Huang, Lijun Jiao, Lin Li, Yifan Wang, Leiping Cao, Xinghui Xia
Summary: This study predicts a decreasing trend in future cropland N2O emissions in China using high-precision land use data, with a reduction in total emissions and cropland area. However, some cities in China are projected to emit more than current levels, and different land use and climate change scenarios will have significant impacts on cropland N2O emissions. The implementation of environmental projects, like the Grain for Green Plan, could effectively control emissions by about 12%.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Remote Sensing
Philippe Rufin, Adia Bey, Michelle Picoli, Patrick Meyfroidt
Summary: This study presents a mapping framework using Google Earth Engine and PlanetScope data to identify active cropland and short-term fallows in smallholder landscapes in Northern Mozambique. The research reveals that existing global and regional land cover products tend to underestimate or overestimate the extent of active cropland. Short-term fallows account for 28.9% of the cropland.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Sciences
Jennifer Kennedy, George C. Hurtt, Xin-Zhong Liang, Louise Chini, Lei Ma
Summary: Climate change is impacting global crop productivity and agricultural land suitability, leading to changes in land use and potentially significant environmental and socioeconomic effects. This study analyzes the correspondence between changes in cropland and climate variables, revealing that higher temperatures and increased drought severity are associated with greater cropland loss. These patterns vary across regions and countries due to different socioeconomic factors and adaptation strategies. This global-scale analysis complements regional studies and provides context for locally-observed phenomena.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Tyler J. Lark, Ian H. Schelly, Holly K. Gibbs
Summary: The study comprehensively characterized the performance of the CDL across space and time using state- and land cover class-specific accuracy statistics from the USDA. It found that the CDL provides highly accurate annual measures of crops and cropland areas, showing good performance in identifying specific crops.
Article
Agriculture, Multidisciplinary
Xuan Zhao, Taixia Wu, Shudong Wang, Kai Liu, Jingyu Yang
Summary: We developed the PCRRSBS-CV model by combining the phenology-based cropland retirement remote sensing (PCRRS) model with the coefficient of variation (CV) and tilled soil fraction (BS) to accurately map cropland abandonment on a large scale. Our method successfully incorporated crop phenology information with MODIS time-series images, while reducing interference from mixed pixels using the BS as a weighting coefficient for the PCRRS model. By dividing the research area into regional units, spatial heterogeneity was reduced. The accuracy of our algorithm was verified in the Loess Plateau of China and central Europe, achieving an overall accuracy of 82.2% and extracting cropland abandonment information as little as 20% of a pixel.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Environmental Sciences
Abdelaziz Htitiou, Abdelghani Boudhar, Abdelghani Chehbouni, Tarik Benabdelouahab
Summary: This study automated the extraction of cropland phenological metrics on GEE and used them with machine-learning models to produce high-resolution cropland and crop field-probabilities maps in Morocco. The classification product showed an overall accuracy of 97.86% for the nominal year 2019-2020, and the cropland probabilities maps accurately estimated sub-national SAU areas with an R-value of 0.9.
Article
Geosciences, Multidisciplinary
Bo Liu, Wei Song
Summary: In light of the COVID-19 pandemic and ongoing armed conflicts, the world is facing an unparalleled food crisis. Reclaiming abandoned cropland with potential for food production could rapidly increase global food supply and ensure food security. Utilizing within-year Sentinel-2 time series, a change-detection method was developed to identify and extract abandoned cropland in Linxia County, China, from 2018 to 2021. The method proved effective in accurately detecting and differentiating various types of abandoned cropland, providing valuable insights for future land use change research.
Article
Environmental Sciences
Chengxiu Li, Matt Kandel, Daniela Anghileri, Francis Oloo, Oscar Kambombe, Tendai Polite Chibarabada, Cosmo Ngongondo, Justin Sheffield, Jadunandan Dash
Summary: The study found evidence of unsustainable cropland use in Malawi, characterized by rapid expansion of cropland, limited potential for future expansion, reduced cropland productivity, and increased soil erosion. Urgent measures are needed to promote sustainable cropland use, including protecting current cropland from further degradation and improving cropland use planning.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Jianghao Wang, Junjie Zhang, Peng Zhang
Summary: The increasing demand for calories and protein, alongside urbanization, presents significant challenges to China's food security. This study examines the impact of temperature on land use in China using high-resolution satellite data and daily weather data from 1980 to 2010. The findings suggest that extremely hot weather has a long-lasting effect on reducing cropland in China, and climate change is predicted to further decrease China's cropland area by the end of this century.
ENVIRONMENTAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Xueliang Feng, Shen Tan, Yun Dong, Xin Zhang, Jiaming Xu, Liheng Zhong, Le Yu
Summary: Bamboo forest is a unique forest landscape mainly composed of herbal plants. It has a stronger capability to increase terrestrial carbon sinks than woody forests, playing a special role in absorbing atmospheric CO2. Accurate and timely bamboo forest maps are necessary for understanding and quantifying their contribution to the carbon and hydrological cycles.
Article
Environmental Sciences
Liming Ye, Johan De Grave, Eric Van Ranst, Lijun Xu
Summary: In recent years, satellite remote sensing has played an increasingly important role in monitoring global environmental changes. However, the calibration of satellite land surface phenology (LSP) observations using standardized procedures has received less attention. In this study, a new approach using a climotransfer function (CTF) based on a polynomial regression was proposed to calibrate satellite LSP products. A case study of the cropland growing season in Northeast China (NEC) from 2001 to 2010 was conducted to illustrate the model development and evaluation process. The results showed that calibration was necessary to accurately characterize the spatiotemporal patterns of the cropland growing season.
Article
Food Science & Technology
Ziyang Yu, Zhenzhen Li, Haoxuan Yang, Yihao Wang, Yang Cui, Guoping Lei, Shuai Ye
Summary: Understanding the relationship between climate change and cropland spatiotemporal patterns is crucial for government policy and agricultural adaptation. The study used land use data to analyze cropland expansion and contraction, as well as calculate cropland landscape indices. The impact of climatic factors on cropland patterns was quantified and the accuracy of models indicated the intensity of this influence.
Article
Plant Sciences
Eline Lorer, Kris Verheyen, Haben Blondeel, Karen De Pauw, Pieter Sanczuk, Pieter De Frenne, Dries Landuyt
Summary: Species are adjusting their phenology in response to warming temperatures. This study focuses on understory plants in forests, which experience different light and temperature conditions compared to open environments due to tree canopy shading. The researchers recorded the flowering patterns of 10 temperate forest understory plant species in mesocosm experiments to understand how phenology is influenced by sub-canopy warming and illumination. They found that flowering onset is advanced by an average of 7.1 days per 1 degree Celsius warming, with warm-adapted species showing greater advances. The study suggests that considering sub-canopy temperature and light availability is crucial for understanding future phenological responses of understory plants.
Article
Environmental Sciences
Christopher Mulverhill, Nicholas C. Coops, Txomin Hermosilla, Joanne C. White, Michael A. Wulder
Summary: The study evaluated the agreement between two broad-scale forest canopy height products across different ecological gradients. Overall, the two datasets showed high correspondence, but there were variations in agreement in different ecozones. The study also found that the modeled heights based on optical satellite data had a less generalized distribution than heights from ICESat-2.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Jiarui Zhang, Zhiyi Fu, Yilin Zhu, Bin Wang, Keran Sun, Feng Zhang
Summary: Land cover mapping is crucial for global resource monitoring, sustainable development research, and effective management. However, the complexity and computational requirements often cause delays in data processing and product publication, posing challenges for creating large-area products for monitoring dynamic land cover. This study proposes the HALF framework to automate and improve the efficiency of land cover mapping processes.
Article
Ecology
Eduarda M. O. Silveira, Volker C. Radeloff, Guillermo J. Martinez Pastur, Sebastian Martinuzzi, Natalia Politi, Leonidas Lizarraga, Luis O. Rivera, Gregorio Gavier-Pizarro, He Yin, Yamina M. Rosas, Noelia C. Calamari, Maria F. Navarro, Yanina Sica, Ashley M. Olah, Julieta Bono, Anna M. Pidgeon
Summary: The paper presents a method for mapping and characterizing forests using remote sensing phenology measures and climate data. The authors applied this method in Argentina and identified 54 forest phenoclusters with unique combinations of vegetation phenology and climate characteristics.
ECOLOGICAL APPLICATIONS
(2022)
Article
Environmental Sciences
Teresa De Marzo, Nestor Ignacio Gasparri, Eric F. Lambin, Tobias Kuemmerle
Summary: This study attributes forest disturbances in the Argentine Dry Chaco based on Landsat image time series, revealing that partial clearing is the most widespread type of disturbance. Results show that partial clearing is becoming more prevalent over time, while fires are declining. Factors such as roads and fields are associated with the spatial patterns of disturbances.
Article
Green & Sustainable Science & Technology
Franz Schug, David Frantz, Dominik Wiedenhofer, Helmut Haberl, Doris Virag, Sebastian van der Linden, Patrick Hostert
Summary: This study assessed the dynamics of material stock and its relation to population in Germany using Landsat imagery and a spatial resolution of 30 m. The results showed that material stock and population in Germany grew by 13% and 4% respectively, with highly variable spatial patterns. The reunification of East and West Germany in 1990 led to a rapid growth of material stock per capita in East Germany, despite a decline in population. Possible over- or underestimations of stock growth due to methodological assumptions require further research.
JOURNAL OF INDUSTRIAL ECOLOGY
(2023)
Article
Biodiversity Conservation
Spencer R. Keyser, Daniel Fink, David Gudex-Cross, Volker C. Radeloff, Jonathan N. Pauli, Benjamin Zuckerberg
Summary: Snow cover dynamics have significant impacts on the distribution and abundance patterns of overwintering bird species. This study utilized observations from eBird to investigate the effects of snow cover dynamics on 150 bird species across the United States. The results demonstrate the importance of snow cover dynamics as environmental predictors in species distribution models.
Article
Forestry
Neda K. Kasraee, Todd J. Hawbaker, Volker C. Radeloff
Summary: This study evaluates the use of convolutional neural networks (CNNs) for identifying buildings and mapping the wildland-urban interface (WUI) areas. The CNNs show moderate accuracy in detecting individual buildings post-fire, but are inaccurate for damage assessments or building counts in the WUI, especially when buildings are occluded by trees.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2023)
Article
Environmental Sciences
Eduarda M. O. Silveira, Volker C. Radeloff, Sebastian Martinuzzi, Guillermo J. Martinez Pastur, Julieta Bono, Natalia Politi, Leonidas Lizarraga, Luis O. Rivera, Lucia Ciuffoli, Yamina M. Rosas, Ashley M. Olah, Gregorio Gavier-Pizarro, Anna M. Pidgeon
Summary: Detailed mapping of forest structure attributes is crucial for sustainable forest management, conservation, and forest ecosystem science at the landscape level. This study explores the integration of field inventory plots with SAR and optical remote sensing data to map forest structure attributes across a large area of native forests in Argentina. The models developed using Sentinel-1 and Sentinel-2 data, combined with geographic coordinates, accurately predicted forest structure attributes with relatively low root mean square errors.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Qiongyu Huang, Brooke L. Bateman, Nicole L. Michel, Anna M. Pidgeon, Volker C. Radeloff, Patricia Heglund, Andrew J. Allstadt, A. Justin Nowakowski, Jesse Wong, John R. Sauer
Summary: As climate change affects species distributions, understanding the relationship between climate suitability shifts and species distributions is crucial. This study examined the observed and modeled shifts of 250 bird species in the United States from 1969 to 2011, finding large differences between the two. However, temperate migrants and habitat generalist species showed higher observed shifting velocities.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Biodiversity Conservation
Katarzyna Ewa Lewinska, Anthony R. Ives, Clay J. Morrow, Natalia Rogova, He Yin, Paul R. Elsen, Kirsten de Beurs, Patrick Hostert, Volker C. Radeloff
Summary: Grassland ecosystems cover a large portion of global land area, and monitoring their long-term changes is crucial for various purposes. Existing remote sensing-based monitoring methods often fail to consider temporal and spatial autocorrelation, leading to inaccurate identification of trends. In this study, we analyzed trends in Eurasian grasslands using a new statistical approach that accounts for autocorrelation. The results showed significant changes in Eurasian grasslands over the past two decades, with an increase in non-photosynthetic vegetation and local changes in green vegetation and soil cover. Environmental variables significantly affected these trends, but their effects varied across regions.
GLOBAL CHANGE BIOLOGY
(2023)
Article
Forestry
Colleen M. Sutheimer, Jed Meunier, Igor Drobyshev, Michael C. Stambaugh, Sara C. Hotchkiss, Eric Rebitzke, Volker C. Radeloff
Summary: By analyzing an extensive fire-scar network in the upper Great Lakes Region, this study evaluated the historical fire regimes over the past 350 years. The findings revealed the significant influence of climate factors on fire frequency and seasonality in the region, and highlighted the importance of recurrent fires in shaping and maintaining forest resilience.
INTERNATIONAL JOURNAL OF WILDLAND FIRE
(2023)
Article
Ecology
Ariel Mordechai Meroz, He Yin, Noam Levin
Summary: It is challenging to determine the extent to which changes in vegetation cover are caused by human actions or climate variability. Through remote sensing and satellite imagery, this study found that differences in land use on either side of the border had a significant impact on vegetation cover.
JOURNAL OF ARID ENVIRONMENTS
(2023)
Editorial Material
Multidisciplinary Sciences
Stephen M. Bell, Samuel J. Raymond, He Yin, Wenzhe Jiao, Daniel S. Goll, Philippe Ciais, Elsa Olivetti, Victor O. Leshyk, Cesar Terrer
Summary: Despite being prevalent worldwide, post-agricultural landscapes are the least constrained human-induced land carbon sinks. To understand their role in rebuilding the natural carbon stocks through ecosystem restoration, it is important to gain a better understanding of their spatial and temporal legacies.
NATURE COMMUNICATIONS
(2023)
Article
Ecology
Todd J. Hawbaker, Paul D. Henne, Melanie K. Vanderhoof, Amanda R. Carlson, Miranda H. Mockrin, Volker C. Radeloff
Summary: Since the 1990s, wildfires and housing development have increased significantly, leading to unique challenges for wildfire management. This study used a random forests model to predict burn probabilities and assess the risk to homes in the Southern Rocky Mountains ecoregion. The results showed that the observed burned area and exposure to homes have sharply increased, primarily due to warmer and drier weather conditions as well as housing growth. The modeling approach provides critical information to guide decision-making in mitigating wildfire risks.
Article
Multidisciplinary Sciences
Franz Schug, Dominik Wiedenhofer, Helmut Haberl, David Frantz, Doris Virag, Sebastian van der Linden, Patrick Hostert
Summary: This study provides high-resolution maps of material stocks in buildings and infrastructures in Austria, showing a 33-year time series. These data are important for studies on societal resource use, transport studies, and land system science.
Article
Environmental Sciences
Q. J. Antonio Guzman, Jesus N. Pinto-Ledezma, David Frantz, Philip A. Townsend, Jennifer Juzwik, Jeannine Cavender-Bares
Summary: This study proposes a new workflow for monitoring oak wilt disease using satellite observations. By analyzing the temporal changes in pigments and photosynthetic activity of oak trees affected by the pathogenic fungus, the disease progression can be tracked using land surface phenology metrics. The results show that it is feasible to accurately differentiate between healthy, symptomatic, and dead oak trees using satellite observations, providing valuable information for disease monitoring and treatment decision-making.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)