Abstract
Grazing intensity (GI) is an important indicator for grazing situations in pastoral areas. However, it has been difficult to be observed directly in the field, due to the randomness and dynamics of the grazing behavior of livestock. Consequently, the lack of actual GI information has become a common issue in studies on quantitatively estimating GI. In this paper, a novel quantitative estimation method is proposed based on the Space-Air-Ground integrated monitoring technology. It systematically integrates GPS tracking technology, Unmanned Aerial Vehicle (UAV) observation technology, and satellite remote sensing technology. Taking Xiangdong Village on the Zoige Plateau as a study area, the trajectory data and UAV images were acquired by the GPS tracking experiments and UAV observation experiments, respectively. The GI at paddock scale (PGI) was then generated with the Kernel Density Estimation (KDE) algorithm and the above data. Taking the generated PGI as training data, an estimation model of GI at region scale (RGI) was constructed by using the time-series satellite remote sensing images and random forest regression algorithm. Finally, the time-series RGI data with a spatial resolution of 10 m in Xiangdong Village were produced by the above model. The accuracy assessment demonstrated that the generated time-series RGI data could reflect the spatial-temporal heterogeneity of actual GI, with a mean absolute error of 0.9301 and r2 of 0. 8573. The proposed method provides a new idea for generating the actual GI on the ground and the time-series RGI data. This study also highlights the feasibility and potential of using the Space-Air-Ground integrated monitoring technology to generate time-series RGI data with high spatial resolution. The generated time-series RGI data would provide data support for the formulation of policies and plans related to the sustainable development of animal husbandry.
Highlights
Animal husbandry is the pillar industry in pastoral areas
This study proposes a new method for the estimation of the time-series Grazing intensity (GI) with a finer spatial resolution based on the Space-Air-Ground integrated monitoring technology
A novel estimation method for GI on the Zoige Plateau is proposed in this paper based on the Space-Air-Ground integrated monitoring technology
Summary
Animal husbandry is the pillar industry in pastoral areas. The benign and healthy development of animal husbandry is of considerable significance to the sustainable development of society and economy in these areas. GI at paddock scale (PGI) might be quantitatively estimated based on these trajectory data recorded by GPS collars. The livestock inventory of each paddock and its changes in the monitoring period are the critical coefficients of the PGI estimation model based on trajectory data. Study Arspeeacific objectives of this research are to (1) generate actual GI data at paddock scale (PGI) with spatial-temporal heterogeneity based on GPS tracking technology and UAV observation technology; Xiangd(2o) nbugilVd ialnlaegsteim, Zatoioingme oCdoeluonf tGyI,altorceagitoendaloscnalteh(eRGeIa)sutseinrng tmheagregnienratoefdtPhGeI Qdaitna ganhdasia-Tteilbliteetan Plateau (Figure 1), wreamsosteesleencstiendg taeschanostlougdyy; aandre(a3). After a series of preprocessing steps, including geometric rectification and image mosaicking, UAV images of each monitored paddock were generated
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