Mapping the albedo of the active surface at different stages of the growing season using data from various sources

Bartmiński, Piotr; Siłuch, Marcin

doi:10.1016/j.rsase.2022.100818

Cited by 3 publications

(3 citation statements)

References 60 publications

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“…We examined if there is a way to combine these two sensors for better prediction of ET. Similar to other remote sensing integration applications [52,54,55], our spatial integration result shows that the Landsat ET can be used in synergy with UAV ET. We found that the RMSE, MAE, and bias values are significantly reduced in all crops by the application of the integration factor by at least 35.75% (Table 10).…”

Section: Integration Of Etsupporting

confidence: 74%

“…Besides, Landsat ET is normally over-predicted around bare land areas and under-predicted around the dense vegetation areas compared to UAV ET (Figure 4). The reason for this difference is due to the varying sensing time and pixel resolution as the various landscapes exhibit varying temperature and ET results are influenced by the aggregation [44,45,52]. As ET mapped using UAVbased imagery was done at higher spatial resolution, the variability in ET captured using UAV imagery is higher compared to Landsat imagery.…”

Section: Spatial Integration Of Etmentioning

confidence: 99%

“…Further, we used the same equations for the broadband albedo estimation from the narrow band without considering the crop growth stage. However, as pointed out by Bartmi ński and Siłuch [52], the surface albedo equation needs adjustment for crop growth stage. Besides, the current study was performed on working fields (not experimental plots) allowing the farmers to use their own management practice, irrigation application, and crop rotation.…”

Section: Integration Of Etmentioning

confidence: 99%

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Integration of Unmanned Aerial Vehicle Imagery with Landsat Imagery for Better Watershed Scale ET Prediction

Khanal

Barber

2023

Hydrology

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Evapotranspiration (ET) is a critical component of the water cycle, and an accurate prediction of ET is essential for water resource management, irrigation scheduling, and agricultural productivity. Traditionally, ET has been estimated using satellite-based remote sensing, which provides synoptic coverage but can be limited in spatial resolution and accuracy. Unmanned aerial vehicles (UAVs) offer improved ET prediction by providing high-resolution imagery of the Earth’s surface but are limited to a small area. Therefore, UAV and satellite images provide complementary data, but the integration of these two data for ET prediction has received limited attention. This paper presents a method that integrates UAV and satellite imagery for improved ET prediction and applies it to five crops (corn, rye grass, wheat, and alfalfa) from agricultural fields in the Walla Walla of eastern Washington State. We collected UAV and satellite data for five crops and used the combination of remote sensing models and statistical techniques to estimate ET. We show that UAV-based ET can be integrated with the Landsat-based ET with the application of integration factors. Our result shows that the Root Mean Square Error (RMSE) of daily ET for corn (Zea mays), rye grass (Lolium perenne), wheat (Triticum aestivum), peas (Pisum sativum), and alfalfa (Medicago sativa) can be improved by the application of the integration factor to the Landsat based ET in the range of (35.75–65.52%). We also explore the variability and effect of partial cloud on UAV-based ET estimation. Our findings have implications for the use of UAVs in water resource management and highlight the importance of considering multiple sources of data in ET prediction.

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Section: Integration Of Etsupporting

confidence: 74%

Section: Spatial Integration Of Etmentioning

confidence: 99%

Section: Integration Of Etmentioning

confidence: 99%

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Integration of Unmanned Aerial Vehicle Imagery with Landsat Imagery for Better Watershed Scale ET Prediction

Khanal

Barber

2023

Hydrology

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Advancing the local climate zones framework: a critical review of methodological progress, persisting challenges, and future research prospects

Han,

Mo,

Cai

et al. 2024

Humanit Soc Sci Commun

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The local climate zones (LCZs) classification system has emerged as a more refined method for assessing the urban heat island (UHI) effect. However, few researchers have conducted systematic critical reviews and summaries of the research on LCZs, particularly regarding significant advancements of this field in recent years. This paper aims to bridge this gap in scientific research by systematically reviewing the evolution, current status, and future trends of LCZs framework research. Additionally, it critically assesses the impact of the LCZs classification system on climate-responsive urban planning and design. The findings of this study highlight several key points. First, the challenge of large-scale, efficient, and accurate LCZs mapping persists as a significant issue in LCZs research. Despite this challenge, the universality, simplicity, and objectivity of the LCZs framework make it a promising tool for a wide range of applications in the future, especially in the realm of climate-responsive urban planning and design. In conclusion, this study makes a substantial contribution to the advancement of LCZs research and advocates for the broader adoption of this framework to foster sustainable urban development. Furthermore, it offers valuable insights for researchers and practitioners engaged in this field.

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The Effect of Environmental Albedo on the Energy Use of a Selected House in Amman-Jordan

Alrwashdeh

2023

AIMSES

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<abstract> <p>I explore the effect that albedo has on the amount of solar energy collected as well as the effectiveness of various building materials used in Jordan's varied construction industry. Albedo, which is the reflection of incoming radiation by surfaces, is of crucial relevance in minimizing the damage that solar radiation may do to building components like windows. The construction sector in Jordan is a substantial contributor to the overall level of energy consumption in the country because of the wide variety of building types, purposes and technologies found there. The findings of this research show that substances with greater albedo values produce the best results in terms of energy gains. These findings are supported by in-depth albedo value analyses and provide useful insights that may be used to improve building design and construction methods in Jordan, which will eventually lead to increased energy efficiency and sustainability within the construction sector.</p> </abstract>

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Mapping the albedo of the active surface at different stages of the growing season using data from various sources

Cited by 3 publications

References 60 publications

Integration of Unmanned Aerial Vehicle Imagery with Landsat Imagery for Better Watershed Scale ET Prediction

Integration of Unmanned Aerial Vehicle Imagery with Landsat Imagery for Better Watershed Scale ET Prediction

Advancing the local climate zones framework: a critical review of methodological progress, persisting challenges, and future research prospects

The Effect of Environmental Albedo on the Energy Use of a Selected House in Amman-Jordan

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