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Forest and Crop Leaf Area Index Estimation Using Remote Sensing: Research Trends and Future Directions

Jin Xu, Lindi J. Quackenbush, Timothy A. Volk, Jungho Im
2020 Remote Sensing  
The ease of use of empirical models supports these as the preferred choice for forest and crop LAI estimation.  ...  estimate forest and crop LAI and explores uncertainty analysis in LAI estimation.  ...  these three products were closely related to LAI estimates from Sentinel-2 and Landsat 7/8 (R 2 ≈ 0.90, RMSE ≈ 0.50).  ... 
doi:10.3390/rs12182934 fatcat:wh3p2pgq35cizailwwv4wlaqje

Reviewing the Potential of Sentinel-2 in Assessing the Drought

Dani Varghese, Mirjana Radulović, Stefanija Stojković, Vladimir Crnojević
2021 Remote Sensing  
Considering the spatial, temporal, and spectral characteristics, the freely available Sentinel-2 data products are a promising option in this area of research, compared to Landsat and MODIS.  ...  Furthermore, this review also addresses and compares various data fusion methods and downscaling methods applied to Sentinel-2 for retrieving the major bio-geophysical variables used in the analysis of  ...  Acknowledgments: Authors would like to acknowledge Sanja Brdar and Oskar Marko for their constructive suggestions. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs13173355 fatcat:ntzknamhcvcwxb7lyzhxq3ywse

Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using Landsat-8 Multispectral Remote Sensing Data

Xianfeng Zhou, Jingcheng Zhang, Dongmei Chen, Yanbo Huang, Weiping Kong, Lin Yuan, Huichun Ye, Wenjiang Huang
2020 Remote Sensing  
Overall, our study suggest that Landsat-8 OLI data are suitable for crop LCC retrieval and could provide a basis for LCC estimation with similar multispectral datasets.  ...  For hybrid regression methods, the use of active learning (AL) techniques together with GPR for LCC modelling significantly increased the estimation accuracy, and the combination of entropy query by bagging  ...  The authors would also like to thank those who helped in the field campaigns with data collection, and we thank the anonymous reviewers for providing comments that helped with improving the quality of  ... 
doi:10.3390/rs12162574 fatcat:pdabnyna6zgibm5nebqgjr3lsq

Mapping Plantations in Myanmar by Fusing Landsat-8, Sentinel-2 and Sentinel-1 Data along with Systematic Error Quantification

Ate Poortinga, Karis Tenneson, Aurélie Shapiro, Quyen Nquyen, Khun San Aung, Farrukh Chishtie, David Saah
2019 Remote Sensing  
In this work, we have developed an innovative method to accurately map rubber and palm oil plantations using fusion of Landsat-8, Sentinel 1 and 2.  ...  These primitives were then used to create land cover and probability maps in a decision tree logic and Monte-Carlo simulations.  ...  BRDF correction and topographic correction were applied to Landsat 8. The atmospheric correction was done by applying the 6S radiative transfer model.  ... 
doi:10.3390/rs11070831 fatcat:axfatfyafbhtzfgpfsvdftbeiq

Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

Jochem Verrelst, Jordi Muñoz, Luis Alonso, Jesús Delegido, Juan Pablo Rivera, Gustavo Camps-Valls, José Moreno
2012 Remote Sensing of Environment  
ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high  ...  By using data from the ESA-led field campaign SPARC (Barrax, Spain) we have compared the utility of four state-of-the-art machine learning regression algorithms and four different S2 and S3 band settings  ...  This work was partially supported by projects AYA2008-05965-C04-03, AYA2010-21432-C02-01 and CSD2007-00018 funded by the Spanish Ministry of Science and Innovation.  ... 
doi:10.1016/j.rse.2011.11.002 fatcat:m2q4sjikmndmzphn6jloiv7obu

Remote sensing big data for water environment monitoring: current status, challenges, and future prospects

Jinyue Chen, Rao Fu, Shuisen Chen, Dan Li, Hao Jiang, Chongyang Wang, Yongshi Peng, Kai Jia
2022 Earth's Future  
, and machine learning-based methods; (c) state-of-the-art models for quantitative estimation of water quality, including empirical models, semi-empirical/semi-analytical models, and machine learning-based  ...  This study reviews the operating framework and methods of remote sensing big data for water environment monitoring, with emphasis on water extraction and quantitative estimation of water quality.  ...  In addition, by comparing the classification results of wetland vegetation using GF-1, GF-2, ZY-3, Sentinel-2A, and Landsat-8 OLI, M.  ... 
doi:10.1029/2021ef002289 fatcat:mkusa7mstnalvnxlhu5ybdsgdy

Assessing Durum Wheat Yield through Sentinel-2 Imagery: A Machine Learning Approach

Maria Bebie, Chris Cavalaris, Aris Kyparissis
2022 Remote Sensing  
In the second approach, the reflectance data of all Sentinel-2 bands for several dates during the growth periods were used as input parameters in three machine learning model algorithms, i.e., random forest  ...  Two modeling approaches for the estimation of durum wheat yield based on Sentinel-2 data are presented for 66 fields across three growing periods.  ...  to estimate crop productivity and the resulting final yield [11, 16, 17] .  ... 
doi:10.3390/rs14163880 fatcat:45s6zevx3faq3gy37bc7qiid3y

Improving the Performance of Index Insurance Using Crop Models and Phenological Monitoring

Mehdi H. Afshar, Timothy Foster, Thomas P. Higginbottom, Ben Parkes, Koen Hufkens, Sanjay Mansabdar, Francisco Ceballos, Berber Kramer
2021 Remote Sensing  
Using a biophysical process-based crop model (Agricultural Production System sIMulator (APSIM)) applied for rice producers in Odisha, India, we simulate a synthetic yield dataset to train non-parametric  ...  We analyse to what extent the use of crop simulation models and crop phenology monitoring can reduce basis risk in index insurance.  ...  Acknowledgments: We gratefully acknowledge Tharakeswar Ganta, Senthil Kumar and Shashank Bhushan Dash from Dvara E-Registry for their dedication to the ground data collection.  ... 
doi:10.3390/rs13050924 doaj:6dbb5d3018f34db4a6a817d2e7c03719 fatcat:s2shftxbozakflfu2ngsffmfci

The Role of Earth Observation in Achieving Sustainable Agricultural Production in Arid and Semi-Arid Regions of the World

Sarchil Hama Qader, Jadu Dash, Victor A. Alegana, Nabaz R. Khwarahm, Andrew J. Tatem, Peter M. Atkinson
2021 Remote Sensing  
We also discuss the future challenges associated with maintaining food security in ASA regions and explore some recent advances in RS that can be used to monitor cropland and forecast crop production and  ...  Finally, existing approaches used in these applications are evaluated, and the challenges associated with their use and possible future improvements are discussed.  ...  Data extracted from Sentinel imagery, such as from Sentinel-2 and 3, can be used in isolation or combined, or both can be combined with MODIS and Landsat 8 through data fusion techniques.  ... 
doi:10.3390/rs13173382 fatcat:gva463nkdjbark4odzswvqg7l4

Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine

Pablo Reyes-Muñoz, Luca Pipia, Matías Salinero-Delgado, Santiago Belda, Katja Berger, José Estévez, Miguel Morata, Juan Pablo Rivera-Caicedo, Jochem Verrelst
2022 Remote Sensing  
The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SCOPE and the atmospheric  ...  Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping  ...  In this regard, observations at higher scale resolution, coming from instruments such as Sentinel-2 or Landsat-8 ETM+ may contribute to homogeneity estimations.  ... 
doi:10.3390/rs14061347 fatcat:3uimmzg26rayhnxszx5nx2q6cq

Assessment of Workflow Feature Selection on Forest LAI Prediction with Sentinel-2A MSI, Landsat 7 ETM+ and Landsat 8 OLI

Benjamin Brede, Jochem Verrelst, Jean-Philippe Gastellu-Etchegorry, Jan G. P. W. Clevers, Leo Goudzwaard, Jan den Ouden, Jan Verbesselt, Martin Herold
2020 Remote Sensing  
Hybrid retrieval workflows combining non-parametric Machine Learning Regression Algorithms (MLRAs) and vegetation Radiative Transfer Models (RTMs) were proposed as fast and accurate methods to infer biophysical  ...  Administration (NASA)/United States Geological Survey (USGS) Landsat 7 (L7) and Landsat 8 (L8) missions.  ...  Considering these developments together-decametric observations from Sentinel-2 and Landsat, fast mapping with MLRA algorithms and fast radiative transfer modelling with emulators-a decametric LAI product  ... 
doi:10.3390/rs12060915 fatcat:ad2i3odyqzgjvhcz5zfxhwkzfm

2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14

2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Application of Landsat ETM+ and OLI Data for Foliage Fuel Load Monitoring Using Radiative Transfer Model and Machine Learning Method.  ... 
doi:10.1109/jstars.2022.3143012 fatcat:dnetkulbyvdyne7zxlblmek2qy

Advances in remote sensing of vegetation function and traits

Rasmus Houborg, Joshua B. Fisher, Andrew K. Skidmore
2015 International Journal of Applied Earth Observation and Geoinformation  
This editorial provides 1) a background on major advances in the remote sensing of vegetation, 2) a detailed timeline and description of relevant historical and planned satellite missions, and 3) an outline  ...  Remote sensing of vegetation function and traits has advanced significantly over the past half-century in the capacity to retrieve useful plant biochemical, physiological and structural quantities across  ...  JBF contributed from the Jet Propulsion Laboratory (JPL), California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA); government sponsorship acknowledged  ... 
doi:10.1016/j.jag.2015.06.001 fatcat:jmq3tyb6p5aixefy7o4fgehsry

Assessment of Sentinel-2 MSI Spectral Band Reflectances for Estimating Fractional Vegetation Cover

Bing Wang, Kun Jia, Shunlin Liang, Xianhong Xie, Xiangqin Wei, Xiang Zhao, Yunjun Yao, Xiaotong Zhang
2018 Remote Sensing  
The samples, including the Sentinel-2 MSI canopy reflectances and corresponding FVC values, were simulated using the PROSPECT + SAIL radiative transfer model under different conditions, and random forest  ...  The Sentinel-2 missions carrying multi-spectral instrument (MSI) sensors with 13 multispectral bands are potentially useful for estimating FVC.  ...  Sentinel-2 data were downloaded from the ESA's Copernicus Open Access Hub. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs10121927 fatcat:cfu2qzqnjza27h4k2ww2m4yjbq

Comparison of Machine Learning Regression Algorithms for Cotton Leaf Area Index Retrieval Using Sentinel-2 Spectral Bands

Huihui Mao, Jihua Meng, Fujiang Ji, Qiankun Zhang, Huiting Fang
2019 Applied Sciences  
gradient boosting regression tree (GBRT), have been used in the retrieval of cotton LAI with Sentinel-2 spectral bands.  ...  crop fields management and agricultural production decisions.  ...  the global LAI products.  ... 
doi:10.3390/app9071459 fatcat:dfl3v7zkszgnpoqdduminlownq
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