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In-Season Mapping of Crop Type with Optical and X-Band SAR Data: A Classification Tree Approach Using Synoptic Seasonal Features

Paolo Villa, Daniela Stroppiana, Giacomo Fontanelli, Ramin Azar, Pietro Brivio
2015 Remote Sensing  
The work focuses on developing a classification tree approach for in-season crop mapping during early summer, by integrating optical (Landsat 8 OLI) and X-band SAR (COSMO-SkyMed) data acquired over a test  ...  The approach is based on a classification tree scheme fed with a set of synoptic seasonal features (minimum, maximum and average, computed over the multi-temporal datasets) derived from vegetation and  ...  the crop type reference data.  ... 
doi:10.3390/rs71012859 fatcat:p65v7sbyobfb7gbvox3apqjc64

Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches

Brian Barrett, Ingmar Nitze, Stuart Green, Fiona Cawkwell
2014 Remote Sensing of Environment  
variability (i.e. grasslands) were the most 557 difficult to reliably classify as grasslands form a continuum of types and there is confusion between band SAR data with a RF classifier.  ...  and multi-frequency 597 multi-temporal SAR and ancillary data are capable of providing high classification accuracies in the 598 absence of optical data. 599 6.  ...  Fusion of active and passive microwave observations to create an Essential Climate Variable  ... 
doi:10.1016/j.rse.2014.05.018 fatcat:cfgq4maigncdbmncwtqopsyl2i


B. K. Kenduiywo, D. Bargiel, U. Soergel
2016 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Our ensemble technique is compared to standard approach of stacking all images as bands for classification using Maximum Likelihood Classifier (MLC) and standard CRFs.  ...  However, government, insurers, agricultural market traders and other stakeholders are interested in the quantity of a certain crop in a season.  ...  ACKNOWLEDGEMENTS The project is funded by the German Federal Ministry of Education and Research (Project 50EE1326) and images provided by DLR.  ... 
doi:10.5194/isprs-annals-iii-7-59-2016 fatcat:dmkztfd47bhbxm2wsh4yd5vhl4

Satellite remote sensing of grasslands: from observation to management

Iftikhar Ali, Fiona Cawkwell, Edward Dwyer, Brian Barrett, Stuart Green
2016 Journal of Plant Ecology  
With the growth in availability of spaceborne remote sensing data it is therefore important to revisit the relevant methods and applications that can exploit this imagery.  ...  In this article we have reviewed the (1) current status of grassland monitoring/observation methods and applications based on satellite remote sensing data, (2) the technological and methodological developments  ...  Wang et al. (2013) compared satellite imagery from three different SAR (X, C and L-band) sensors and showed that X-band SAR data has the highest correlation with the vegetation indices.  ... 
doi:10.1093/jpe/rtw005 fatcat:vua3i7f5ovaujnnkm4z3v55uei

Mapping Urban Impervious Surface by Fusing Optical and SAR Data at the Decision Level

Zhenfeng Shao, Huyan Fu, Peng Fu, Li Yin
2016 Remote Sensing  
Results showed that impervious surfaces estimated from the combined use of original images and features yielded a higher accuracy than those from the original optical or SAR data.  ...  It has a tropical monsoon (humid) climate with abundant rainfall and four distinctive seasons.  ...  The integration of feature information with optical (or SAR data) enhanced the overall classification accuracy by 2.64% (or 5.90%).  ... 
doi:10.3390/rs8110945 fatcat:3seiit55nfbtnhfdfonshzy4eq


Akshay Dhande, Rahul Malik
2021 Information Technology in Industry  
Because of this background we studied various remote sensing methods like crop classification, crop tracking and yield assessment.  ...  We discovered that almost all of the remote sensing methods have been exploratory investigations, examined on a nearby scale with direct dependence on ground data.  ...  The initial phase of remote sensing research in agricultural applications was concerned with the use of remote sensing data for crop types and the classification of ground cover types.  ... 
doi:10.17762/itii.v9i1.142 fatcat:63iopwgoqfey7nroqdshgcg4re

Change Detection Techniques Based on Multispectral Images for Investigating Land Cover Dynamics

Dyah R. Panuju, David J. Paull, Amy L. Griffin
2020 Remote Sensing  
In addition, it reviews some CD techniques used for synthetic aperture radar (SAR). The importance of data selection and preprocessing for CD provides a starting point for the discussion.  ...  This article reviews advances in bitemporal and multitemporal two-dimensional CD with a focus on multispectral images.  ...  Acknowledgments: The authors would like to thank the Australian Department of Foreign Affairs and Trade for the opportunity to pursue a PhD research program.  ... 
doi:10.3390/rs12111781 fatcat:gyxuwlxzwbhzjez5lqg44f7h4i

Soil Salinity Mapping Using SAR Sentinel-1 Data and Advanced Machine Learning Algorithms: A Case Study at Ben Tre Province of the Mekong River Delta (Vietnam)

Pham Hoa, Nguyen Giang, Nguyen Binh, Le Hai, Tien-Dat Pham, Mahdi Hasanlou, Dieu Tien Bui
2019 Remote Sensing  
crop types in the context of climate change.  ...  The main objective of this work is to map soil salinity intrusion in Ben Tre province located on the Mekong River Delta of Vietnam using the Sentinel-1 Synthetic Aperture Radar (SAR) C-band data combined  ...  Funding: This research was funded by Vietnam Academy of Science and Technology through the project "Studying, Assessing, and Zoning Soil Salinity Intrusion by using Multi-temporal Satellite Imagery-A case  ... 
doi:10.3390/rs11020128 fatcat:jwd5efmmzjeulppwuxcf43bkny

Agriculture and Wetland Applications [chapter]

J. M. Lopez-Sanchez, J. D. Ballester-Berman, F. Vicente-Guijalba, S. R. Cloude, H. McNairn, J. Shang, H. Skriver, T. Jagdhuber, I. Hajnsek, E. Pottier, C. Marechal, L. Hubert-Moy (+7 others)
2021 Remote Sensing and Digital Image Processing  
For crop type mapping, supervised or partially unsupervised classification schemes are used.  ...  Concerning agriculture, crop type mapping, soil moisture estimation and phenology estimation are reviewed, as they are ones with a clear benefit of full polarimetry over dual or single polarimetry.  ...  can be approached in a similar way to crop type mapping.  ... 
doi:10.1007/978-3-030-56504-6_3 fatcat:zmamsy4vfbfjdomtypqgvcf4se

Copernicus User Uptake: From Data to Applications

Lorenza Apicella, Monica De Martino, Alfonso Quarati
2022 ISPRS International Journal of Geo-Information  
the use of Copernicus resources towards a wider audience of end-users boosting the development of new EO applications along with some advice to data providers to improve their publication practices.  ...  As part of the activities performed in the EO-UPTAKE project, we illustrate a set of application scenario workflows exemplifying usage practices of the data and tools available in the Copernicus ecosystem  ...  A special thanks go to Loris Vescovo of Fondazione Edmund Mach, and the Highlander Project (, accessed on 10 November 2021), who strongly supported us in identifying the AS3  ... 
doi:10.3390/ijgi11020121 fatcat:l4mjxt5sxrcv5d5rtwpffbol3e

A Complete Procedure for Crop Phenology Estimation With PolSAR Data Based on the Complex Wishart Classifier

Lucio Mascolo, Juan M. Lopez-Sanchez, Fernando Vicente-Guijalba, Ferdinando Nunziata, Maurizio Migliaccio, Giuseppe Mazzarella
2016 IEEE Transactions on Geoscience and Remote Sensing  
Consequently, the computation of PolSAR features, which is the main step of state-of-the-art methods, is no longer needed, and the proposed approach can be applied in the same way to any crop type.  ...  A new methodology to estimate the growth stages of agricultural crops using the time series of polarimetric synthetic aperture radar (PolSAR) images is proposed.  ...  In the second step, hierarchical trees and/or simple decision planes are defined by thresholding manually the evolution of the selected features and then used for the final phenology classification.  ... 
doi:10.1109/tgrs.2016.2585744 fatcat:gabaazubz5akrinfmpcegzxejy

Flood Mapping in Vegetated Areas Using an Unsupervised Clustering Approach on Sentinel-1 and -2 Imagery

Lisa Landuyt, Niko E. C. Verhoest, Frieke M. B. Van Coillie
2020 Remote Sensing  
Based on a SAR image pair, the region of interest is segmented into objects, which are converted to a SAR-optical feature space and clustered using K-means.  ...  In this paper, we present an unsupervised object-based clustering framework capable of mapping flooding in the presence and absence of flooded vegetation based on freely and globally available data only  ...  Based on X-band data, Pierdicca et al. [50] presented an object-based region-growing approach capable of detecting flooded narrow-leaf crops, while Grimaldi et al.  ... 
doi:10.3390/rs12213611 fatcat:qx4o66ysxregheefrqkzjwkogm

Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

Donato Amitrano, Gerardo Di Martino, Raffaella Guida, Pasquale Iervolino, Antonio Iodice, Maria Nicolina Papa, Daniele Riccio, Giuseppe Ruello
2021 Remote Sensing  
The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market.  ...  The purpose is to highlight the main issues and limitations preventing the diffusion of synthetic aperture radar data in both industrial and multidisciplinary research contexts and the possible solutions  ...  Data Availability Statement: Not applicable. Acknowledgments: The authors sincerely thank Airbus Defense and Space UK and Catapult SA for providing NovaSAR data from the commissioning phase.  ... 
doi:10.3390/rs13040604 fatcat:zgqmk5chjbc7hio5l6serraeym

Knowledge Extracted from Copernicus Satellite Data

Dumitru Octavian, Schwarz Gottfried, Eltoft Torbjørn, Kræmer Thomas, Wagner Penelope, Hughes Nick, Arthus David, Fleming Andrew, Koubarakis Manolis, Datcu Mihai
2019 Zenodo  
In this publication, we focus on the Polar case which requires the selection of validation areas, the generation of a training dataset, the development and testing of deep learning algorithms, and the  ...  ExtremeEarth is a European H2020 project; it aims at developing analytics techniques and technologies that combine Copernicus satellite data with information and knowledge extraction, and exploiting them  ...  The use of multi-or hyperspectral remote sensing data into soil monitoring and digital mapping can provide a large-scale survey, comprehensive and effective sites' monitoring and assess topsoil variables  ... 
doi:10.5281/zenodo.3941573 fatcat:zzifwgljifck5bpjnboetsftfu

Review of the use of remote sensing for biomass estimation to support renewable energy generation

Lalit Kumar, Priyakant Sinha, Subhashni Taylor, Abdullah F. Alqurashi
2015 Journal of Applied Remote Sensing  
The quantification, mapping and monitoring of biomass are now central issues due to the importance of biomass as a renewable energy source in many countries of the world.  ...  The estimation of biomass is a challenging task, especially in areas with complex stands and varying environmental conditions, and requires accurate and consistent measurement methods.  ...  Use of Optical Remote Sensing Optical remote sensing data, with a variety of spatial and temporal resolutions, have been widely used for forest biomass estimation using different types of image processing  ... 
doi:10.1117/1.jrs.9.097696 fatcat:vb6fitx52rbyxprbf2c6c7nu3i
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