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Retrieval of High Spatiotemporal Resolution Leaf Area Index with Gaussian Processes, Wireless Sensor Network, and Satellite Data Fusion

Gaofei Yin, Aleixandre Verger, Yonghua Qu, Wei Zhao, Baodong Xu, Yelu Zeng, Ke Liu, Jing Li, Qinhuo Liu
2019 Remote Sensing  
Many applications, including crop growth and yield monitoring, require accurate long-term time series of leaf area index (LAI) at high spatiotemporal resolution with a quantification of the associated  ...  Then, the CACAO approach generates synchronous reflectance data at high spatiotemporal resolution (30-m and 8-day) from the fusion of multitemporal MODIS and high spatial resolution Landsat satellite imagery  ...  To our knowledge, this is the first work combining wireless sensor network, data blending, and machine learning technologies for retrieving LAI and its uncertainty at high spatiotemporal resolution.  ... 
doi:10.3390/rs11030244 fatcat:h4ossdd67vfypkh2quwndkmnpi

2014 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 7

2014 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., and Foerster, S  ...  ., +, JSTARS Nov. 2014 4422-4431 Crop Leaf Area Index Observations With a Wireless Sensor Network and Its Potential for Validating Remote Sensing Products.  ...  ., +, JSTARS Sept. 2014 3683-3684 + Check author entry for coauthors Meta data Neural networks A Neural Network Retrieval Technique for High-Resolution Profiling of Cloudy Atmospheres. Blackwell, W.  ... 
doi:10.1109/jstars.2015.2397347 fatcat:ib3tjwsjsnd6ri6kkklq5ov37a

Continuous Daily Evapotranspiration Estimation at the Field-Scale over Heterogeneous Agricultural Areas by Fusing ASTER and MODIS Data

Zhenyan Yi, Hongli Zhao, Yunzhong Jiang
2018 Remote Sensing  
Through combination with a linear unmixing-based method, the spatial and temporal adaptive reflectance fusion model (STARFM) is modified to generate high-resolution ET estimates for heterogeneous areas  ...  Here, an integrated framework for daily ET, with the required spatiotemporal resolution, is described.  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/rs10111694 fatcat:5paa6h6lzbgtba6ivyfj4fqcra

Interoperability, XML Schema [chapter]

2017 Encyclopedia of GIS  
, Hilbert R-Tree, Spatial Indexing, Multimedia Indexing  ...  Cross-References Cross-References Geospatial Semantic Integration Geospatial Semantic Web Geospatial Semantic Web: Applications Geospatial Semantic Web, Interoperability Geospatial Semantic Web: Personalization Indexing  ...  Future Directions Wireless Networks, Location Tracking and Sensors With wireless network access becoming increasingly pervasive, there will be growing use of this technology in geospatial applications  ... 
doi:10.1007/978-3-319-17885-1_100625 fatcat:bgxdhdxa4bewzcggrogz56rdpi

An overview of MATISSE-v2.0

Luc Labarre, Karine Caillault, Sandrine Fauqueux, Claire Malherbe, Antoine Roblin, Bernard Rosier, Pierre Simoneau, Karin Stein, John D. Gonglewski
2010 Optics in Atmospheric Propagation and Adaptive Systems XIII  
Co-Sponsoring Organisations Delivered with the support of Scottish Enterprise Cooperating Organisations 3A  ...  The symposium, like our other conferences and activities, would not be possible without the dedicated contribution of our participants and members.  ...  SLN were prepared with cetyl palmitate and glyceryl stearate as solid lipids and for NLC, a mixture of the same solid lipids and grape seed oil has been used.  ... 
doi:10.1117/12.868183 fatcat:5anlqspzzzcftfufaxvlr45zve

GIS Mashups [chapter]

Ilya Zaslavsky
2017 Encyclopedia of GIS  
Definition Gaussian processes (GPs) are local approximation techniques that model spatial data by placing (and updating) priors on the covariance structures underlying the data.  ...  ., ozone concentrations) over 2D spatial fields as realizations of a stochastic process. Sacks et al. (1989) described the use of kriging to model (deterministic) computer experiments.  ...  Sensor networks consist of a large number of small computing devices with attached sensor boards, and equipped with batteries and wireless communication.  ... 
doi:10.1007/978-3-319-17885-1_530 fatcat:rrr5buo3zrevpigdtjwhewipvm

Reanalysis in Earth System Science: Towards Terrestrial Ecosystem Reanalysis

R. Baatz, H.J. Hendricks Franssen, E. Euskirchen, D. Sihi, M. Dietze, S. Ciavatta, K. Fennel, H. Beck, G. De Lannoy, V.R.N. Pauwels, A. Raiho, C. Montzka (+15 others)
2021 Reviews of Geophysics  
High computational costs for modeled processes and assimilation algorithms has led to Earth system specific reanalysis products for the atmosphere, the ocean and the land separately.  ...  A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation.  ...  The land surface model used to build the reanalysis is forced with the regional high resolution atmospheric reanalysis COSMO-REA6 (Bollmeyer et al., 2015) and annually variable leaf area index.  ... 
doi:10.1029/2020rg000715 fatcat:oggekyqenvf7jiune2doi2doc4

Geospatial Artificial Intelligence (GeoAI) in the Integrated Hydrological and Fluvial Systems Modeling: Review of Current Applications and Trends

Carlos Gonzales-Inca, Mikel Calle, Danny Croghan, Ali Torabi Haghighi, Hannu Marttila, Jari Silander, Petteri Alho
2022 Water  
GeoAI effectively harnesses the vast amount of spatial and non-spatial data collected with the new automatic technologies.  ...  GeoAI has shown advantages in non-linear modeling, computational efficiency, integration of multiple data sources, high accurate prediction capability, and the unraveling of new hydrological patterns and  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/w14142211 fatcat:tjiod5qz45f67kbmkm3f6kuv7i

Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations

Lei Fan, Qing Xiao, Jianguang Wen, Qiang Liu, Rui Jin, Dongqing You, Xiaowen Li
2015 Remote Sensing  
High spatial resolution soil moisture (SM) data are crucial in agricultural applications, river-basin management, and understanding hydrological processes.  ...  Merging multi-resource observations is one of the ways to improve the accuracy of high spatial resolution SM data in the heterogeneous cropland.  ...  Acknowledgments This work was jointly supported by the Natural Science Foundation of China under Grant 91125003 and National High Technology Research and Development Program of China (2013AA12A301).  ... 
doi:10.3390/rs71013273 fatcat:d2dc5dbtare4fg4ezjq2okhnne

Integrating a Trimble Recon X 400 MHz Intel PXA255 Xscale CPU® Mobile Field Data Collection System Using Differentially Corrected Global Positioning System Technology and a Real-Time Bidirectional Actionable Platform within an ArcGIS Cyberenvironment for Implementing Mosquito Control

Benjamin G. Jacob, Robert J. Novak
2014 Advances in Remote Sensing  
Secondly, these canopy-shaded characteristics must be successfully measured using high spectral resolution remote-sensing data.  ...  The outcome of the model inversion procedure was influenced by the timing and availability of remote sensing data, the spectral resolution of the data, the types of models implemented, and the choice of  ...  Leaf Area Index (LAI) is a dimensionless quantity that characterizes plant canopies which is defined as the one-sided green leaf area per unit ground surface area (LAI = leaf area/ground area, m 2 /m 2  ... 
doi:10.4236/ars.2014.33012 fatcat:sg5srenclnatlilciuy3pv3nx4

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  
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  ...  They need to be sufficiently diverse to cover the major target areas of satellite images under varying imaging conditions and across all seasons.  ...  a comprehensive network system of data management and sharing for the Scientific Investigation over the South China Sea.  ... 
doi:10.5281/zenodo.3941573 fatcat:zzifwgljifck5bpjnboetsftfu

Urban Computing

Yu Zheng, Licia Capra, Ouri Wolfson, Hai Yang
2014 ACM Transactions on Intelligent Systems and Technology  
Urban computing connects urban sensing, data management, data analytics, and service providing into a recurrent process for an unobtrusive and continuous improvement of people's lives, city operation systems  ...  Additionally, we usually need to harness a diversity of data sources in a single task. For instance, the aforementioned anomaly detection uses human mobility data, road networks, and social media.  ...  Silvia et al. [2008] assess environmental noise pollution in urban areas by using wireless sensor networks.  ... 
doi:10.1145/2629592 fatcat:no5gcshbmrdfphv6ewm6wdoewq

A Review of the Challenges of Using Deep Learning Algorithms to Support Decision-Making in Agricultural Activities

Khadijeh Alibabaei, Pedro D. Gaspar, Tânia M. Lima, Rebeca M. Campos, Inês Girão, Jorge Monteiro, Carlos M. Lopes
2022 Remote Sensing  
The vast amount of data received from sensors in smart farms makes it possible to use deep learning as a model for decision-making in this field.  ...  Deep Learning has been successfully applied to image recognition, speech recognition, and natural language processing in recent years.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14030638 fatcat:blr6s47dzvff3maj3rv3t3leyq

Spatiotemporal enabled Content-based Image Retrieval

Mariana Belgiu, Martin Sudmanns, Tiede Dirk, Andrea Baraldi, Stefan Lang
2016 International Conference on GIScience Short Paper Proceedings  
Wireless Sensor Networks (WSNs) are widely used for monitoring and observation of dynamic phenomena.  ...  This is because raster representations are constrained by their spatial resolution, and their regular shapes result in redundant data for unoccupied areas.  ...  Government for the development of a fine-resolution model of urban-energy systems' water footprint in river networks; Oak Ridge National Laboratory's Laboratory Directed Research and Development (LDRD)  ... 
doi:10.21433/b311729295dw fatcat:fulw4pw3kfh5nmfzcsy3pkisvm

Cross-Covariance Models [chapter]

2017 Encyclopedia of GIS  
Cross-References Indexing, Hilbert R-tree, Spatial Indexing, Multimedia Indexing The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the automated discovery  ...  The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns.  ...  As shown in Fig. 3 , using the R-tree in Fig. 1a , suppose objects C , E, D, and F are indexed by an R-tree with two leaf nodes A and B.  ... 
doi:10.1007/978-3-319-17885-1_100240 fatcat:2ojzb7es7rhofinw4abol6dgc4
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