Uav-Based Hyperspectral Data Analysis for Urban Area Mapping

Suran, N. A.; Shafri, H. Z. M.; Shaharum, Nur Shafira Nisa; Radzali, N. A. W. M.; Kumar, Vipin

doi:10.5194/isprs-archives-xlii-4-w16-621-2019

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…However, there are existing gaps in satellite imagery that limit its effectiveness in capturing the fine-scale details and monitoring dynamic urban environments. These gaps include limitations in the spatial resolution, temporal coverage, and cloud cover interference [40,41]. These limitations hinder accurately assessing and monitoring climate-related phenomena in urban areas.…”

Section: Uavs and Data Capabilitiesmentioning

confidence: 99%

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Bayomi,

Fernandez

2023

Drones

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This paper reviews the diverse applications of drone technologies in the built environment and their role in climate change research. Drones, or unmanned aerial vehicles (UAVs), have emerged as valuable tools for environmental scientists, offering new possibilities for data collection, monitoring, and analysis in the urban environment. The paper begins by providing an overview of the different types of drones used in the built environment, including quadcopters, fixed-wing drones, and hybrid models. It explores their capabilities and features, such as high-resolution cameras, LiDAR sensors, and thermal imaging, which enable detailed data acquisition for studying climate change impacts in urban areas. The paper then examines the specific applications of drones in the built environment and their contribution to climate change research. These applications include mapping urban heat islands, assessing the energy efficiency of buildings, monitoring air quality, and identifying sources of greenhouse gas emissions. UAVs enable researchers to collect spatially and temporally rich data, allowing for a detailed analysis and identifying trends and patterns. Furthermore, the paper discusses integrating UAVs with artificial intelligence (AI) to derive insights and develop predictive models for climate change mitigation and adaptation in urban environments. Finally, the paper addresses drone technologies’ challenges and the future directions in the built environment. These challenges encompass regulatory frameworks, privacy concerns, data management, and the need for an interdisciplinary collaboration. By harnessing the potential of drones, environmental scientists can enhance their understanding of climate change impacts in urban areas and contribute to developing sustainable strategies for resilient cities.

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Section: Uavs and Data Capabilitiesmentioning

confidence: 99%

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Bayomi,

Fernandez

2023

Drones

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“…The authors of [76] reported an OA of 87.75% for RF, 83.31% for CNN, and 80.29% for SVM due to mapping using the Random Forest (RF), CNN, and SVM models. In [77], the classification of urban areas was evaluated using ANN, SVM, ML, and SAM, and the overall accuracies obtained were 92.33%, 85.86%, 83.41%, and 46.55%, with Kappa coefficients of 0.91, 0.83, 0.80, and 0.38, respectively. The ANN method was reported to be effective.…”

Section: Assessment Of Classification Techniquesmentioning

confidence: 99%

A Study on Wetland Cover Map Formulation and Evaluation Using Unmanned Aerial Vehicle High-Resolution Images

Lim,

Kim,

Kim

et al. 2023

Drones

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Wetlands possess significant ecological value and play a crucial role in the environment. Recent advancements in remote exploration technology have enabled a quantitative analysis of wetlands through surveys on the type of cover present. However, the classification of complex cover types as land cover types in wetlands remains challenging, leading to ongoing studies aimed at addressing this issue. With the advent of high-resolution sensors in unmanned aerial vehicles (UAVs), researchers can now obtain detailed data and utilize them for their investigations. In this paper, we sought to establish an effective method for classifying centimeter-scale images using multispectral and hyperspectral techniques. Since there are numerous classes of land cover types, it is important to build and extract effective training data for each type. In addition, computer vision-based methods, especially those that combine deep learning and machine learning, are attracting considerable attention as high-accuracy methods. Collecting training data before classifying by cover type is an important factor that which requires effective data sampling. To obtain accurate detection results, a few data sampling techniques must be tested. In this study, we employed two data sampling methods (endmember and pixel sampling) to acquire data, after which their accuracy and detection outcomes were compared through classification using spectral angle mapper (SAM), support vector machine (SVM), and artificial neural network (ANN) approaches. Our findings confirmed the effectiveness of the pixel-based sampling method, demonstrating a notable difference of 38.62% compared to the endmember sampling method. Moreover, among the classification methods employed, the SAM technique exhibited the highest effectiveness, with approximately 10% disparity observed in multispectral data and 7.15% in hyperspectral data compared to the other models. Our findings provide insights into the accuracy and classification outcomes of different models based on the sampling method employed in spectral imagery.

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Use of drones in archaeology and conservation as a tool for monitoring and documentation of bark beetle calamity on the example of the Vysočina Region

Macků¹

2022

ZPP

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Uav-Based Hyperspectral Data Analysis for Urban Area Mapping

Cited by 3 publications

References 9 publications

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

A Study on Wetland Cover Map Formulation and Evaluation Using Unmanned Aerial Vehicle High-Resolution Images

Use of drones in archaeology and conservation as a tool for monitoring and documentation of bark beetle calamity on the example of the Vysočina Region

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