Article
Forestry
Yating Li, Zhenzi Wu, Xiao Xu, Hui Fan, Xiaojia Tong, Jiang Liu
Summary: This study utilized satellite imagery and advanced algorithms to monitor forest disturbances in the Hengduan Mountains Region, revealing that fire was the primary disturbance agent and that the annual disturbance area significantly decreased after 2000. The findings suggest that China's logging bans in natural forests, combined with other forest sustainability programs, have effectively curbed forest disturbances in the HDMR.
Article
Environmental Sciences
Atupelye W. Komba, Teiji Watanabe, Masami Kaneko, Mohan Bahadur Chand
Summary: This study utilized satellite data to examine vegetation disturbance history in the Ruaha-Rungwa landscape of Tanzania, revealing that 36% of vegetation was significantly disturbed with varying trends, severity, and patterns depending on management approaches.
Article
Environmental Sciences
Paulo J. Murillo-Sandoval, Lola Fatoyinbo, Marc Simard
Summary: Awareness of the significant benefits of mangroves has increased recently. However, there is still uncertainty about their change trajectories at national scales. This study used satellite imagery to track the historical mangrove conversion in Colombia from 1984-2020. The findings show a gradual reduction of mangrove extent along the Pacific coast and declines in the Caribbean. The drivers of mangrove change were found to be hydroclimatic events, dredging activities, sediment loads, agricultural expansion, and road construction.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Engineering, Geological
Sheng Fu, Steven M. M. de Jong, Axel Deijns, Marten Geertsema, Tjalling de Haas
Summary: This study proposes a novel landslide dating technique called Segmented WAvelet-DEnoising and stepwise linear fitting (SWADE), which utilizes the Landsat archive to identify temporal changes in normalized difference vegetation index (NDVI) caused by landslides. SWADE detects sudden changes in NDVI values and estimates the most probable date ranges for landslide occurrences. The evaluation in a specific area revealed that SWADE can detect a significant percentage of landslides with maximum errors of 1 or 2 years, outperforming other dating methods. SWADE provides a promising fully automatic method for dating landslides in remote areas.
Article
Environmental Sciences
Katsuto Shimizu, Wataru Murakami, Takahisa Furuichi, Ronald C. Estoque
Summary: In this study, the applicability of Landsat time series temporal segmentation and random forest classifiers for mapping LULCC and forest disturbances in Vietnam was examined. The results showed that although there were some accuracy issues, this method is still useful for consistently mapping LULCC and forest disturbances.
Article
Environmental Sciences
Lei Tian, Longtao Liao, Yu Tao, Xiaocan Wu, Mingyang Li
Summary: In this study, a forest age mapping method with a 30 m resolution was proposed, considering forest disturbance. Landsat time-series stacks data and the LandTrendr algorithm were utilized to detect the age of disturbed forests. Non-disturbed forest age was extracted based on forest canopy height data and the empirical relationship between age and height. The proposed method showed high accuracy in detecting disturbance years and had reliable results in determining the age of non-disturbed forests, contributing to the understanding of carbon budget studies in forest ecosystems.
Article
Environmental Sciences
P. J. Gelabert, M. Rodrigues, J. de la Riva, A. Ameztegui, M. T. Sebasti, C. Vega-Garcia
Summary: This study models and monitors the spatial evolution of secondary succession in semi-natural grassland communities in the Pyrenees in Spain over 36 years. Results show that approximately 66% of the area is affected by secondary succession, with significant expansion of woodlands.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Hao Ni, Peng Gong, Xuecao Li
Summary: The study discusses how to use time-series image data and machine learning algorithms to identify old towns. By combining field surveys with time-series image data and machine learning algorithms, higher accuracy is achieved, and the final results can serve as references for future urban development planning.
Article
Biodiversity Conservation
Yuanyuan Meng, Xiangnan Liu, Zheng Wang, Chao Ding, Lihong Zhu
Summary: This study used LandTrendr algorithm and NBR-based spatial structural metrics time series to analyze forest disturbance and recovery, finding that texture metrics can effectively enhance the accuracy of recovery detection and depict changes in forest composition and landscape patches.
ECOLOGICAL INDICATORS
(2021)
Article
Environmental Sciences
Lili Xu, Martin Herold, Nandin-Erdene Tsendbazar, Dainius Masiliunas, Linlin Li, Myroslava Lesiv, Steffen Fritz, Jan Verbesselt
Summary: This study compares the performance of three satellite sensors (PROBA-V, Landsat 8 OLI, and Sentinel-2 MSI) in global land cover change (LCC) monitoring and evaluates their potential and limitations. The results show that Landsat 8 OLI slightly outperforms Sentinel-2 in global LCC monitoring, while PROBA-V performs the worst. The performance differences among the sensors remain consistent despite variations in data availability and spectral observation regions.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Ecology
Lu Ye, Meiling Liu, Xiangnan Liu, Lihong Zhu
Summary: This study aimed to establish a vegetation index for monitoring changes in order to determine the long-term gradual change processes of forest ecosystems in red soil areas. The DSVI was found to be a suitable index for forest change detection due to its stronger sensitivity and excellent change detection ability for various gradual changes.
ECOLOGICAL INFORMATICS
(2021)
Article
Remote Sensing
Mitchell T. Bonney, Yuhong He
Summary: Satellite-derived vegetation proxies and tree-rings can provide temporal records of forest productivity change, but different forest types show variations in response to climate and growth. Recent advances in Landsat time-series allow for expanded research on forest change, but a better understanding of factors influencing relationship strength is needed.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Remote Sensing
Alba Viana-Soto, Mariano Garcia, Inmaculada Aguado, Javier Salas
Summary: Understanding post-fire recovery dynamics is crucial for effective management and enhancing fire resilience in Mediterranean pine forests. In this research, LiDAR and Landsat imagery were combined to analyze forest structure recovery over a 30-year period, revealing different responses in tree cover and height after fire.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Sciences
Jennifer N. Hird, Jahan Kariyeva, Gregory J. McDermid
Summary: Contemporary forest-health initiatives require technologies and workflows that can efficiently monitor forest degradation and recovery over large areas. By analyzing spectral trajectories in satellite time series, this study tracked spectral recovery across more than 57,000 forest harvest areas in Alberta, Canada using Landsat archive and Google Earth Engine (GEE). The research found that on average, forest harvest areas in Alberta recovered 59.9% of their pre-harvest NBR after five years, with significant variability in recovery rates influenced by regional and local factors.
Article
Environmental Sciences
Jining Yan, Haixu He, Lizhe Wang, Hao Zhang, Dong Liang, Junqiang Zhang
Summary: This study provides a benchmark dataset, CUG-FFireMCD1, for forest fire disturbance detection and validates four commonly used time series change detection models. The BFAST model performs the best in detecting forest fire disturbances from MOD13A2 time series. The results also suggest that the CCDC and LandTrendR models can be used for data support in labeling work. However, some model adaptation is recommended for perfect application in MOD13A2 time series change detection.
Article
Biodiversity Conservation
Teresa J. Lorenz, Kerri T. Vierling, Jody Vogeler, Jeffrey Lonneker, Jocelyn Aycrigg
JOURNAL OF FISH AND WILDLIFE MANAGEMENT
(2015)
Article
Ecology
Jeffrey D. Kline, Mark E. Harmon, Thomas A. Spies, Anita T. Morzillo, Robert J. Pabst, Brenda C. McComb, Frank Schnekenburger, Keith A. Olsen, Blair Csuti, Jody C. Vogeler
ECOLOGICAL APPLICATIONS
(2016)
Article
Ecology
Jody C. Vogeler, Zhiqiang Yang, Warren B. Cohen
Article
Environmental Sciences
Jody C. Vogeler, Zhiqiang Yang, Warren B. Cohen
REMOTE SENSING OF ENVIRONMENT
(2016)
Article
Environmental Sciences
Soyeon Bae, Joerg Mueller, Dowon Lee, Kerri T. Vierling, Jody C. Vogeler, Lee A. Vierling, Andrew T. Hudak, Hooman Latifi, Simon Thorn
REMOTE SENSING OF ENVIRONMENT
(2018)
Article
Ornithology
Jody C. Vogeler, Andrew T. Hudak, Lee A. Vierling, Kerri T. Vierling
Article
Environmental Sciences
Jody C. Vogeler, Andrew T. Hudak, Lee A. Vierling, Jeffrey Evans, Patricia Green, Kern I. T. Vierling
REMOTE SENSING OF ENVIRONMENT
(2014)
Article
Remote Sensing
Kerri T. Vierling, Charles E. Swift, Andrew T. Hudak, Jody C. Vogeler, Lee A. Vierling
REMOTE SENSING LETTERS
(2014)
Article
Ecology
Damon B. Lesmeister, Stan G. Sovern, Raymond J. Davis, David M. Bell, Matthew J. Gregory, Jody C. Vogeler
Article
Environmental Sciences
Steven K. Filippelli, Michael J. Falkowski, Andrew T. Hudak, Patrick A. Fekety, Jody C. Vogeler, Azad Henareh Khalyani, Benjamin M. Rau, Eva K. Strand
ENVIRONMENTAL RESEARCH LETTERS
(2020)
Article
Forestry
Jody C. Vogeler, Robert A. Slesak, Patrick A. Fekety, Michael J. Falkowski
Article
Environmental Sciences
Neal C. Swayze, Wade T. Tinkham, Matthew B. Creasy, Jody C. Vogeler, Chad M. Hoffman, Andrew T. Hudak
Summary: This study evaluates the influence of unmanned aerial vehicle (UAV) altitude and flight speed on the predictions of area-based aboveground forest biomass models. The results show that as the flight altitude increases, the accuracy of UAV predictions outperforms commercial airborne LiDAR strategies.
Review
Remote Sensing
J. C. Vogeler, W. B. Cohen
REVISTA DE TELEDETECCION
(2016)
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)