4.7 Article

Evaluation of Sentinel-2 time-series for mapping floodplain grassland plant communities

期刊

REMOTE SENSING OF ENVIRONMENT
卷 223, 期 -, 页码 115-129

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2019.01.018

关键词

Vegetation; Wetlands; Natural habitats; Phytosociology; EUNIS

资金

  1. French Ministry of Ecology, Sustainable Development and Energy - CarHAB program [2101606295]
  2. French National Research Center (CNRS) -Zone Atelier program

向作者/读者索取更多资源

Monitoring grassland plant communities is crucial for understanding and managing biodiversity. Previous studies indicate that mapping these natural habitats from single-date remotely sensed imagery remains challenging because some communities have similar physiognomy. The recently launched Sentinel-2 satellites are a promising opportunity for monitoring vegetation. This article assesses the advantages of Sentinel-2 time-series for discriminating plant communities in wet grasslands. An annual Sentinel-2 time-series was compared respectively to single-date and single-band datasets derived from this time-series for mapping grassland plant communities in a temperate floodplain located near Mont-Saint-Michel Bay, which is included in the long-term ecological research network ZA Armorique (France). At this 475 ha site, 123 vegetation releves were collected and assigned to seven plant communities to calibrate and validate the Sentinel-2 data. Satellite images were classified using support vector machine (SVM) and random forest (RF) classifiers. Results show that the SVM classifier performs slightly better than the RF classifier (overall accuracy 0.78 and 0.71, respectively). They highlight that accuracy is lower when using single-date (0.67) or single-band images (0.70). The results also reveal that discrimination of plant communities is more sensitive to temporal resolution (Delta = 0.34 in overall accuracy) than spectral resolution (Delta = 0.12 in overall accuracy).

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Environmental Sciences

Comparison of Hyperspectral Techniques for Urban Tree Diversity Classification

Charlotte Brabant, Emilien Alvarez-Vanhard, Achour Laribi, Gwenael Morin, Kim Thanh Nguyen, Alban Thomas, Thomas Houet

REMOTE SENSING (2019)

Article Geography, Physical

Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data

Sebastien Rapinel, Clemence Rozo, Pauline Delbosc, Damien Arvor, Alban Thomas, Jan-Bernard Bouzille, Frederic Bioret, Laurence Hubert-Moy

GISCIENCE & REMOTE SENSING (2020)

Article Multidisciplinary Sciences

Past landscape structure drives the functional assemblages of plants and birds

Lucie Lecoq, Aude Ernoult, Cendrine Mony

Summary: The study demonstrates that both current and past landscape structure have significant impacts on plant and bird assemblages, with a potential delay in biodiversity response. Simple landscapes are associated with lower species richness for both plants and birds, as well as higher functional variance in plant traits. Changes in landscape structure may result in delayed biodiversity response.

SCIENTIFIC REPORTS (2021)

Article Plant Sciences

Investigating the effect of habitat amount and landscape heterogeneity on the gamma functional diversity of grassland and hedgerow plants

Lucie Lecoq, Cendrine Mony, Hugo Saiz, Myriam Marsot, Aude Ernoult

Summary: Landscape structure affects functional diversity of plants and selects specific trait syndromes related to plant dispersal, phenology, and competitiveness. These results are important for better understanding the impact of land management and effectively preserving associated ecosystem functioning.

JOURNAL OF ECOLOGY (2022)

Article Ornithology

Phenotypic variation of Forest Thrushes Turdus lherminieri in Guadeloupe: evidence for geographic differentiation at fine spatial scale

Emilie Arnoux, Cyril Eraud, Alban Thomas, Francois Cavallo, Stephane Garnier, Bruno Faivre

JOURNAL OF ORNITHOLOGY (2013)

Article Environmental Sciences

Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy

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

Evaluating the spatial patterns of US urban NOx emissions using TROPOMI NO2

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

Wide-swath and high-resolution whisk-broom imaging and on-orbit performance of SDGSAT-1 thermal infrared spectrometer

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

Simulation of urban thermal anisotropy at remote sensing pixel scales: Evaluating three schemes using GUTA-T over Toulouse city

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

Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar

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

Spatially constrained atmosphere and surface retrieval for imaging spectroscopy

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

A vehicle imaging approach to acquire ground truth data for upscaling to satellite data: A case study for estimating harvesting dates

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

Low-amplitude brittle deformations revealed by UAV surveys in alluvial fans along the northwest coast of Lake Baikal: Neotectonic significance and geological hazards

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

Global retrieval of the spectrum of terrestrial chlorophyll fluorescence: First results with TROPOMI

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

Choosing a sample size allocation to strata based on trade-offs in precision when estimating accuracy and area of a rare class from a stratified sample

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

Use of a new Tibetan Plateau network for permafrost to characterize satellite-based products errors: An application to soil moisture and freeze/ thaw

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)