Innovative Analysis Ready Data (ARD) product and process requirements, software system design, algorithms and implementation at the midstream as
            <i>necessary-but-not-sufficient</i>
            precondition of the downstream in a new notion of Space Economy 4.0 - Part 2: Software developments

Baraldi, A.; Sapia, Luca D.; Tiede, Dirk; Sudmanns, Martin; Augustin, Hannah; Lang, Stefan

doi:10.1080/20964471.2021.2017582

Cited by 5 publications

(1 citation statement)

References 169 publications

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“…The design of software systems, algorithms, and midstream implementation as downstream prerequisites will all be covered in later study by experts in the field of software development. They will also talk about product requirements and Innovative Analysis Ready Data (ARD) methods [12].…”

Section: Introductionmentioning

confidence: 99%

Identification of Risk Factors in the Software Design Stage Using the C4.5 Algorithm

Azkiya,

Maulita,

Jumanto

2024

ITJRD

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A strong design phase is necessary for good software. However, design errors in software can cause serious issues with its creation and use. Therefore, the goal of this study is to find risk variables that could have an early impact on software development. In this study, a machine learning technique called technique C4.5 is employed to create decision tree models. 100 respondents with software design experience participated in the online surveys and questionnaires that collected the data for this study in 2022. The C4.5 Algorithm was used in this study to analyze the data and determine the risk variables that affect the success of software design. The study's findings show that the C4.5 Algorithm-based model has a high level of accuracy (93.33%), which means that the data can offer crucial insights into understanding potential risks that may arise during the software design stage, enabling software developers to take the necessary precautions to lessen or eliminate these risks. In order to enhance the caliber and effectiveness of software design, this research is anticipated to provide a significant contribution to practitioners and academics in the field of software development.

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Section: Introductionmentioning

confidence: 99%

Identification of Risk Factors in the Software Design Stage Using the C4.5 Algorithm

Azkiya,

Maulita,

Jumanto

2024

ITJRD

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Uncovering Early Traces of Bark Beetle Induced Forest Stress via Semantically Enriched Sentinel-2 Data and Spectral Indices

Mandl

Lang

2023

PFG

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Forest ecosystems are shaped by both abiotic and biotic disturbances. Unlike sudden disturbance agents, such as wind, avalanches and fire, bark beetle infestation progresses gradually. By the time infestation is observable by the human eye, trees are already in the final stages of infestation—the red- and grey-attack. In the relevant phase—the green-attack—biochemical and biophysical processes take place, which, however, are not or hardly visible. In this study, we applied a time series analysis based on semantically enriched Sentinel-2 data and spectral vegetation indices (SVIs) to detect early traces of bark beetle infestation in the Berchtesgaden National Park, Germany. Our approach used a stratified and hierarchical hybrid remote sensing image understanding system for pre-selecting candidate pixels, followed by the use of SVIs to confirm or refute the initial selection, heading towards a 'convergence of evidence approach’. Our results revealed that the near-infrared (NIR) and short-wave-infrared (SWIR) parts of the electromagnetic spectrum provided the best separability between pixels classified as healthy and early infested. Referring to vegetation indices, we found that those related to water stress have proven to be most sensitive. Compared to a SVI-only model that did not incorporate the concept of candidate pixels, our approach achieved distinctively higher producer’s accuracy (76% vs. 63%) and user’s accuracy (61% vs. 42%). The temporal accuracy of our method depends on the availability of satellite data and varies up to 3 weeks before or after the first ground-based detection in the field. Nonetheless, our method offers valuable early detection capabilities that can aid in implementing timely interventions to address bark beetle infestations in the early stage.

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Innovative Analysis Ready Data (ARD) product and process requirements, software system design, algorithms and implementation at the midstream as necessary-but-not-sufficient precondition of the downstream in a new notion of Space Economy 4.0 - Part 1: Problem background in Artificial General Intelligence (AGI)

Baraldi¹,

Sapia²,

Tiede

et al. 2022

Big Earth Data

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Innovative Analysis Ready Data (ARD) product and process requirements, software system design, algorithms and implementation at the midstream as necessary-but-not-sufficient precondition of the downstream in a new notion of Space Economy 4.0 - Part 2: Software developments

Cited by 5 publications

References 169 publications

Identification of Risk Factors in the Software Design Stage Using the C4.5 Algorithm

Identification of Risk Factors in the Software Design Stage Using the C4.5 Algorithm

Uncovering Early Traces of Bark Beetle Induced Forest Stress via Semantically Enriched Sentinel-2 Data and Spectral Indices

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