Vegetation type classification and fractional vegetation coverage estimation for an open elm (<i>Ulmus pumila</i>) woodland ecosystem during a growing season based on an unmanned aerial vehicle platform coupled with decision tree algorithms

Dong, 韩东 Han; Wang, Haozhou; Bangyou, 郑邦友 Zheng; Feng, 王锋 Wang

doi:10.5846/stxb201803300694

Cited by 2 publications

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“…The use of highly accurate aerial images to monitor vegetation coverage, biomass, soil patches, rat holes, the species diversity of vegetation, and livestock grazing is becoming a popular approach in the application of low-altitude remote sensing to ecology and biodiversity [14][15][16][17][18][19][20][21]. The UAV monitoring platform and decision tree algorithm could be used to construct an automatic tool to quickly, accurately, and automatically determine vegetation types at the landscape scale [22]. A model for estimating the FVC (Fractional Vegetation Cover) in the Gannan steppe based on large quadrat data obtained by a small UAV and an enhanced vegetation index had a high accuracy (R 2 = 0.88) [23].…”

Section: Introductionmentioning

confidence: 99%

Using UAV Visible Images to Estimate the Soil Moisture of Steppe

Sun

Hou

2020

Water

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Although unmanned aerial vehicles (UAVs) have been utilized in many aspects of steppe management, they have not been commonly used to monitor the soil moisture of steppes. To explore the technology of detecting soil moisture by UAV in a typical steppe, we conducted a watered test in the Loess Plateau of China, quantitatively revealing the relationship between the surface soil moisture and the visible images captured using a UAV. The results showed that the surface soil moisture was significantly correlated with the brightness of UAV visible images, and the surface soil moisture could be estimated based on the brightness of the visible images of the UAV combined with vegetation coverage. This study addresses the problem of soil moisture measurement in flat regions of arid and semi-arid steppes at the mesoscale, and contributes to the popularization of the use of UAVs in steppe ecological research.

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Section: Introductionmentioning

confidence: 99%

Using UAV Visible Images to Estimate the Soil Moisture of Steppe

Sun

Hou

2020

Water

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Extraction of fractional vegetation cover in arid desert area based on Chinese GF-6 satellite

et al. 2021

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The red edge band is considered as one of the diagnosable characteristics of green plants, but the large-scale remote sensing retrieval of fractional vegetation coverage (FVC) based on the red edge band is still rare. To explore the application of the red edge band in the remote sensing estimation of FVC, this study proposed a new vegetation index (normalized difference red edge index, RENDVI) based on the two red edge bands of Chinese GaoFen-6 satellite (GF-6). The FVC estimated by using three vegetation indices (NDVI, RENDVI1, and RENDVI2) were evaluated based on the field survey FVC obtained in Minqin Basin of Gansu Province. The results showed that there was a good linear correlation between the FVC estimated by GF-6 WFV data and the FVC investigated in the field, and the most reasonable estimation of FVC was obtained based on RENDVI2 model (R 2 = 0.97611 and RMSE = 0.07075). Meanwhile, the impact of three confidence levels (1, 2, and 5%) on FVC was also analyzed in this study. FVC obtained from NDVI and RENDVI2 has the highest accuracy at 2% confidence, while FVC based on RENDVI1 achieved the best accuracy at 5% confidence. It could be concluded that it is feasible and reliable to estimate FVC based on red edge bands, and the GF-6 Wide Field View (WFV) data with high temporal and spatial resolution provide a new data source for remote sensing estimation of FVC.

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Vegetation type classification and fractional vegetation coverage estimation for an open elm (Ulmus pumila) woodland ecosystem during a growing season based on an unmanned aerial vehicle platform coupled with decision tree algorithms

Cited by 2 publications

References 0 publications

Using UAV Visible Images to Estimate the Soil Moisture of Steppe

Using UAV Visible Images to Estimate the Soil Moisture of Steppe

Extraction of fractional vegetation cover in arid desert area based on Chinese GF-6 satellite

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