Article
Environmental Sciences
Yuanxin Ye, Chao Yang, Bai Zhu, Liang Zhou, Youquan He, Huarong Jia
Summary: Co-registering Sentinel-1 SAR and Sentinel-2 optical images is crucial for remote sensing applications, but misregistration shifts are common. This paper proposes a fast and effective registration method using block-based interest points extraction and similarity-based feature detection for accurate co-registration. Experimental results demonstrate that the third-order polynomial model achieves the best registration accuracy among the tested geometric transformation models.
Article
Environmental Sciences
Jakob Sigurdsson, Sveinn E. Armannsson, Magnus O. Ulfarsson, Johannes R. Sveinsson
Summary: In this study, we combined S2 and L8 data and modified the S2 sharpening method (S2Sharp) to sharpen all bands (S2 and L8) to the highest resolution of 10 m. The method was evaluated using both real and simulated data.
Article
Environmental Sciences
Rohit Mukherjee, Desheng Liu
Summary: In this study, a conditional generative adversarial network (CGAN) is developed to translate observations from Landsat 8 OLI (L8) to Sentinel-2 MSI (S2) imagery, improving data availability for earth monitoring. Two translation methodologies-direct single-step translation and indirect multistep translation-are employed, and the results show that the multistep approach achieves higher spectral fidelity and spatial correlation compared to the original L8 bands. This research validates the effectiveness of CGANs for cross-sensor domain adaptation and provides a reusable computational framework for satellite image translation.
Article
Environmental Sciences
Hongye Cao, Ling Han, Liangzhi Li
Summary: This study evaluates the potential of integrating surface reflectance data from Landsat-7, Landsat-8, and Sentinel-2. A cross-sensor conversion model is proposed to adjust the Sentinel-2 reflectance values to match Landsat-7 or Landsat-8, reducing the discrepancy in surface reflectance. The study suggests that it is feasible to integrate these datasets by applying a linear regression correction between the bands.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Yunfei Li, Qian Shi, Lin He, Runlin Cai, Liangli Meng, Jun Li, Antonio Plaza
Summary: This article proposes a pixel-wise local normalization-based fusion method (LN-FM) for fusing Sentinel-2 and Landsat-8 images, and compares it with other methods through experiments. The experimental results demonstrate that LN-FM exhibits excellent qualitative and quantitative performance, and remarkable spatial, spectral, and pixel distribution fidelity.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Remote Sensing
Xiuhua Zhang, Zhaoxin Qiu, Cong Peng, Peng Ye
Summary: This paper proposes a method that integrates GEE data and a multi-level feature connected CNN to remove clouds in Sentinel-2 imagery using Sentinel-1 Synthetic Aperture Radar imagery as auxiliary data. The results show that the method can generate results comparable to a classic deep Sentinel-2 cloud removal method.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Environmental Sciences
Chang Fan, Jilin Yang, Guosong Zhao, Junhu Dai, Mengyao Zhu, Jinwei Dong, Ruoqi Liu, Geli Zhang
Summary: This study compared ground and satellite observations and found that the 30m Landsat/Sentinel-2 data was more consistent with ground observations in wetland vegetation phenology, indicating its advantage over the 500m MODIS data. The study also highlighted the complexity of wetland phenology and its role in global climate change.
Article
Environmental Sciences
Lorena N. Lacerda, Yafit Cohen, John Snider, Hanna Huryna, Vasileios Liakos, George Vellidis
Summary: Remotely sensed-based surface temperature is important for crop monitoring and irrigation management, but current thermal satellite platforms lack the fine spatial resolution needed to identify crop water status patterns at the field scale. The TsHARP method provides a technique for downscaling coarse thermal images to match the finer resolution of visible and near infrared images. This study shows that using the TsHARP method can improve irrigation management efficiency.
Article
Remote Sensing
Jingan Wu, Liupeng Lin, Tongwen Li, Qing Cheng, Chi Zhang, Huanfeng Shen
Summary: In this study, a degradation-term constrained spatiotemporal fusion network (DSTFN) is proposed for time-series imagery, which can generate high-resolution dense time-series imagery and shows strong robustness and generalization ability.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Environmental Sciences
Xiaojing Tang, Kelsee H. Bratley, Kangjoon Cho, Eric L. Bullock, Pontus Olofsson, Curtis E. Woodcock
Summary: The frequency of usable satellite observations is crucial for rapid detection of forest disturbance. Combining optical and SAR data provides the most usable observations in the tropics and enables more timely detection of forest disturbance. A new algorithm called Fusion Near Real-Time (FNRT) has been developed to monitor tropical forest disturbance by combining Landsat, Sentinel-2, and Sentinel-1 data, achieving high accuracy in detecting forest disturbances within short time frames.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Angela Tsao, Ikenna Nzewi, Ayodeji Jayeoba, Uzoma Ayogu, David B. Lobell
Summary: This study evaluated the performance of existing global canopy height map (CHM) products and a locally trained model using GEDI and optical satellite data in oil palm plantations in Nigeria. It found that existing CHMs performed poorly in the region, but the locally trained model performed well and reduced errors for short trees.
Article
Environmental Sciences
Martina Perez, Marcello Vitale
Summary: Vegetation dynamics and phenology in the Mediterranean area can indicate changes in land use and cover as well as the impact of climate change. Remote sensing using satellite images, such as Landsat and Sentinel, has been crucial in studying these changes. This study aims to analyze long-time-series pixel values and compare different satellite sensors to improve the accuracy of reflectance data.
Article
Environmental Sciences
Sean P. Kearney, Lauren M. Porensky, David J. Augustine, Rowan Gaffney, Justin D. Derner
Summary: This study developed a model to accurately predict daily herbaceous biomass under varying seasonal and annual conditions, and found that including plant community composition information from a high-spatial resolution map improved model performance.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Multidisciplinary Sciences
Cesar Aybar, Luis Ysuhuaylas, Jhomira Loja, Karen Gonzales, Fernando Herrera, Lesly Bautista, Roy Yali, Angie Flores, Lissette Diaz, Nicole Cuenca, Wendy Espinoza, Fernando Prudencio, Valeria Llactayo, David Montero, Martin Sudmanns, Dirk Tiede, Gonzalo Mateo-Garcia, Luis Gomez-Chova
Summary: This article addresses the importance of accurately characterizing clouds and their shadows in Earth Observation and introduces a new global dataset, CloudSEN12, to facilitate research in cloud and cloud shadow detection.
Article
Environmental Sciences
Jie Xue, Martha C. Anderson, Feng Gao, Christopher Hain, Yun Yang, Kyle R. Knipper, William P. Kustas, Yang Yang
Summary: This study evaluates the potential value of using a combination of the HLS dataset with sharpened VIIRS TIR imagery as a thermal proxy source, in conjunction with Landsat data, to achieve 30m ET mapping every 2-3 days. The results suggest that VIIRS-S2 ET retrievals show high accuracy against flux tower observations, but with decreasing performance at large VIIRS view angles.
Article
Biodiversity Conservation
W. Turner, C. Rondinini, N. Pettorelli, B. Mora, A. K. Leidner, Z. Szantoi, G. Buchanan, S. Dech, J. Dwyer, M. Herold, L. P. Koh, P. Leimgruber, H. Taubenboeck, M. Wegmann, M. Wikelski, C. Woodcock
BIOLOGICAL CONSERVATION
(2015)
Article
Geography, Physical
Karen Schleeweis, Samuel N. Goward, Chengquan Huang, John L. Dwyer, Jennifer L. Dungan, Mary A. Lindsey, Andrew Michaelis, Khaldoun Rishmawi, Jeffery G. Masek
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2016)
Article
Environmental Sciences
Adam Lewis, Simon Oliver, Leo Lymburner, Ben Evans, Lesley Wyborn, Norman Mueller, Gregory Raevksi, Jeremy Hooke, Rob Woodcock, Joshua Sixsmith, Wenjun Wu, Peter Tan, Fuqin Li, Brian Killough, Stuart Minchin, Dale Roberts, Damien Ayers, Biswajit Bala, John Dwyer, Arnold Dekker, Trevor Dhu, Andrew Hicks, Alex Ip, Matt Purss, Clare Richards, Stephen Sagar, Claire Trenham, Peter Wang, Lan-Wei Wang
REMOTE SENSING OF ENVIRONMENT
(2017)
Article
Environmental Sciences
Todd J. Hawbaker, Melanie K. Vanderhoof, Yen-Ju Beal, Joshua D. Takacs, Gail L. Schmidt, Jeff T. Falgout, Brad Williams, Nicole M. Fairaux, Megan K. Caldwell, Joshua J. Picotte, Stephen M. Howard, Susan Stitt, John L. Dwyer
REMOTE SENSING OF ENVIRONMENT
(2017)
Article
Environmental Sciences
Steve Foga, Pat L. Scaramuzza, Song Guo, Zhe Zhu, Ronald D. Dilley, Tim Beckmann, Gail L. Schmidt, John L. Dwyer, M. Joseph Hughes, Brady Laue
REMOTE SENSING OF ENVIRONMENT
(2017)
Article
Environmental Sciences
Kevin Gallo, Greg Stensaas, John Dwyer, Ryan Longhenry
Article
Geochemistry & Geophysics
Pasquale L. Scaramuzza, Michelle A. Bouchard, John L. Dwyer
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2012)
Article
Environmental Sciences
James R. Irons, John L. Dwyer, Julia A. Barsi
REMOTE SENSING OF ENVIRONMENT
(2012)
Article
Environmental Sciences
T. K. Maiersperger, P. L. Scaramuzza, L. Leigh, S. Shrestha, K. P. Gallo, C. B. Jenkerson, J. L. Dwyer
REMOTE SENSING OF ENVIRONMENT
(2013)
Article
Environmental Sciences
James Storey, Michael Choate, Donald Moe
Article
Environmental Sciences
James Storey, Michael Choate, Kenton Lee
Article
Environmental Sciences
James C. Storey, Rajagopalan Rengarajan, Michael J. Choate
Article
Environmental Sciences
John L. Dwyer, David P. Roy, Brian Sauer, Calli B. Jenkerson, Hankui K. Zhang, Leo Lymburner
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)