A case study of a precision fertilizer application task generation for wheat based on classified hyperspectral data from UAV combined with farm history data

2013 ◽  
Author(s):  
Jere Kaivosoja ◽  
Liisa Pesonen ◽  
Jouko Kleemola ◽  
Ilkka Pölönen ◽  
Heikki Salo ◽  
...  
Keyword(s):  
Fertilizer Application ◽  
Hyperspectral Data ◽  
History Data

scholarly journals Geospatial Serverless Computing: Architectures, Tools and Future Directions

2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey
Keyword(s):  
Big Data ◽  
Forest Cover ◽  
Mineral Resources ◽  
Hyperspectral Data ◽  
Real Time Analysis ◽  
First Case ◽  
Amazon Web Services ◽  
Aws Lambda ◽  
Physical Features

Several real-world applications involve the aggregation of physical features corresponding to different geographic and topographic phenomena. This information plays a crucial role in analyzing and predicting several events. The application areas, which often require a real-time analysis, include traffic flow, forest cover, disease monitoring and so on. Thus, most of the existing systems portray some limitations at various levels of processing and implementation. Some of the most commonly observed factors involve lack of reliability, scalability and exceeding computational costs. In this paper, we address different well-known scalable serverless frameworks i.e., Amazon Web Services (AWS) Lambda, Google Cloud Functions and Microsoft Azure Functions for the management of geospatial big data. We discuss some of the existing approaches that are popularly used in analyzing geospatial big data and indicate their limitations. We report the applicability of our proposed framework in context of Cloud Geographic Information System (GIS) platform. An account of some state-of-the-art technologies and tools relevant to our problem domain are discussed. We also visualize performance of the proposed framework in terms of reliability, scalability, speed and security parameters. Furthermore, we present the map overlay analysis, point-cluster analysis, the generated heatmap and clustering analysis. Some relevant statistical plots are also visualized. In this paper, we consider two application case-studies. The first case study was explored using the Mineral Resources Data System (MRDS) dataset, which refers to worldwide density of mineral resources in a country-wise fashion. The second case study was performed using the Fairfax Forecast Households dataset, which signifies the parcel-level household prediction for 30 consecutive years. The proposed model integrates a serverless framework to reduce timing constraints and it also improves the performance associated to geospatial data processing for high-dimensional hyperspectral data.

Trend of fertilizer application during the last three decades (Case study: America, Australia, Iran and Malaysia)

2016 ◽  
Vol 40 (4) ◽  
pp. 532-542 ◽  
Author(s):  
Babak Motesharezadeh ◽  
Keyvan Valizadeh-Rad ◽  
Arezoo Dadrasnia ◽  
Hormoz Amir-Mokri
Keyword(s):  
Fertilizer Application

scholarly journals Economics of a variable rate fertiliser strategy on a Whanganui hill country station

2017 ◽  
Vol 79 ◽  
pp. 125-129
Author(s):  
M.D. White ◽  
A.K. Metherell ◽  
A.H.C. Roberts ◽  
R.E. Meyer ◽  
T.A. Cushnahan
Keyword(s):  
Economic Benefit ◽  
Net Present Value ◽  
Hyperspectral Data ◽  
Variable Rate ◽  
Differential Gps ◽  
Hill Country ◽  
The Face ◽  
Gross Margins ◽  
Fertiliser Strategy

Abstract Automated flow control coupled to differential GPS guidance systems in aerial topdressing aircraft will allow variable rate (VR) fertiliser strategies to be applied on hill country farms. The effectiveness of these strategies will be enhanced with the use of remotely sensed hyperspectral data to categorise and quantify the farm landscape in greater detail. The economic benefit of a variable rate fertiliser strategy in comparison to a single rate (blanket) strategy was evaluated for a case study Whanganui hill country station. The analysis illustrates the robustness of a VR strategy in the face of volatile returns in that it produced a higher 10 year cumulative net present value (NPV) and remained at a positive advantage at three different stock gross margins, in comparison to a blanket approach. The effectiveness of hyperspectral imagery for defining effective pasture areas to assist development of more precise variable rate fertiliser applications, compared to the current visual classification from farm photography is discussed. Keywords: economic benefit, variable rate fertiliser, hyperspectral data

scholarly journals BATHYMETRY MAPPING USING HYPERSPECTRAL DATA: A CASE STUDY OF YAMADA BAY, NORTHEAST JAPAN

2016 ◽  
Vol XLI-B7 ◽  
pp. 61-64
Author(s):  
E. Ariyasu ◽  
S. Kakuta ◽  
T. Takeda
Keyword(s):  
Water Depth ◽  
Hyperspectral Image ◽  
Hyperspectral Data ◽  
Inversion Method ◽  
Main Island ◽  
Inherent Optical Properties ◽  
Ground Survey ◽  
Iwate Prefecture ◽  
Sand Bottom

This study aims to examine if the inversion method using hyperspectral data is applicable in Japan. Nowadays, overseas researchers are mainly applied an inversion method for accurately estimating water depth. It is able to gain not only water depth, but also benthic spectral reflection and inherent optical properties (IOPs) at the same time, based on physics-based radiative transfer theory for hyperspectral data. It is highly significant to understand the possibility to develop the application in future for coastal zone of main island, which is a common water quality in Japan, but there is not any case study applied this method in Japan. The study site of Yamada bay in Iwate Prefecture is located in northeast of Japan. An existed analytical model was optimized for mapping water depth in Yamada bay using airborne hyperspectral image and ground survey data which were simultaneously acquired in December, 2015. The retrieved remote-sensing reflectance (R<sub>rs</sub>) is basically qualitatively appropriate result. However, when compared with all ground survey points, the retrieved water depth showed low correlation, even though ground points which are selected sand bottom indicates high relationship. Overall, we could understand the inversion method is applicable in Japan. However, it needs to challenge to improve solving error-caused problems.

scholarly journals Accommodating individual travel history, global mobility, and unsampled diversity in phylogeography: a SARS-CoV-2 case study

2020 ◽  
Author(s):  
Philippe Lemey ◽  
Samuel Hong ◽  
Verity Hill ◽  
Guy Baele ◽  
Chiara Poletto ◽  
...  
Keyword(s):  
Sequence Divergence ◽  
Sampling Bias ◽  
Global Scale ◽  
Ancestral Reconstruction ◽  
Travel History ◽  
History Data ◽  
Current Sampling ◽  
Alternative Routes ◽  
The Impact

AbstractSpatiotemporal bias in genome sequence sampling can severely confound phylogeographic inference based on discrete trait ancestral reconstruction. This has impeded our ability to accurately track the emergence and spread of SARS-CoV-2, the virus responsible for the COVID-19 pandemic. Despite the availability of unprecedented numbers of SARS-CoV-2 genomes on a global scale, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history. When confronted with these issues, incorporating additional contextual data may critically inform phylodynamic reconstructions. Here, we present a new approach to integrate individual travel history data in Bayesian phylogeographic inference and apply it to the early spread of SARS-CoV-2, while also including global air transportation data. We demonstrate that including travel history data for each SARS-CoV-2 genome yields more realistic reconstructions of virus spread, particularly when travelers from undersampled locations are included to mitigate sampling bias. We further explore methods to ameliorate the impact of sampling bias by augmenting the phylogeographic analysis with lineages from undersampled locations in the analyses. Our reconstructions reinforce specific transmission hypotheses suggested by the inclusion of travel history data, but also suggest alternative routes of virus migration that are plausible within the epidemiological context but are not apparent with current sampling efforts. Although further research is needed to fully examine the performance of our travel-aware phylogeographic analyses with unsampled diversity and to further improve them, they represent multiple new avenues for directly addressing the colossal issue of sample bias in phylogeographic inference.

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