Predicting the Distribution of Oxytropis ochrocephala Bunge in the Source Region of the Yellow River (China) Based on UAV Sampling Data and Species Distribution Model

Zhang, Xinyu; Yin, Yuan; Zhu, Zhengtao; Ma, Qingshan; Yu, Hongyan; Li, Meng; Ma, Jin; Yi, Shuai; He, Xiong Zhao; Sun, Yi

doi:10.3390/rs13245129

Cited by 7 publications

(4 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The spatial distribution of grassland biomass in 2019–2021 was obtained by inversion. To better predict the effects of pika distribution in alpine grasslands on grassland degradation, BIOMOD (BIOdiversity MODelling) was combined with remote sensing technology to determine grassland spatial distribution and explore the factors limiting that distribution ( Zhang et al, 2021 ). At the eastern margin of the Qinghai-Tibet Plateau, the Biome-BGC carbon cycle model and the SHAW surface model were coupled to predict the interaction between an alpine meadow ecosystem and the atmosphere and to explore the effects of environmental factors on the flux of the alpine meadow ( Wang et al, 2014 ).…”

Section: Resultsmentioning

confidence: 99%

A bibliometric analysis of research trends and hotspots in alpine grassland degradation on the Qinghai-Tibet Plateau

Xu,

Li,

Zhang

2023

PeerJ

View full text Add to dashboard Cite

A bibliometric analysis of current research, hotspots, and development trends was used to develop an overall framework of mechanisms of alpine grassland degradation on the Qinghai-Tibet Plateau. This investigation includes data from 1,330 articles on alpine grassland degradation on the Qinghai-Tibet Plateau, acquired from the Chinese Science Citation Database (CSCD) and Web of Science Core Collection (WOS). Research was divided into three themes: spatial scope and management of typical grassland degradation problems, dynamic mechanisms of grassland degradation and effects of ecological engineering, and grassland degradation risk based on remote sensing technology. The results of the analysis showed that the research can be summarized into three aspects: typical grassland degradation identification, dynamic mechanism analysis of grassland degradation, and grassland ecosystem stability strategy. The main findings can summarized, as follows: (1) Ecological analyses using the river source as a typical region defined the formation of “black soil beach” type degraded grasslands in the region, and promoted the ecological environment management and protection of the alpine grassland by discussing the causes of regional ecological environment changes; (2) Dynamic mechanism analyses of climate change and characteristics analyses of grassland vegetation-soil degradation revealed that alpine grassland degradation is the result of multiple main factors; and (3) Risk prediction methods for grassland degradation, methods of grassland management and sustainable countermeasures for agriculture and animal husbandry development, and the development of a comprehensive index of influencing factors on grassland degradation all indicate that selecting the right grassland restoration measures is the key to grassland restoration. Remote sensing monitoring and high-throughput sequencing technology should be used in future research on grassland ecosystems. In addition, multiscale, multidimensional, and multidisciplinary systematic research methods and long-term series data mining could help identify the characteristics and causes of alpine grassland system degradation. These findings can help identify a more effective coordination of landscape, water, lake, field, forest, grass, and sand management for the prevention of alpine grassland degradation.

show abstract

Section: Resultsmentioning

confidence: 99%

A bibliometric analysis of research trends and hotspots in alpine grassland degradation on the Qinghai-Tibet Plateau

Xu,

Li,

Zhang

2023

PeerJ

View full text Add to dashboard Cite

show abstract

“…Climate change could induce upward shifting of this medicinal plant from the middle to high altitudes in Isfahan province. Therefore, The development of computer programs and approaches of species distribution models, especially the ensemble model, have enabled the conservation and management prioritization of medicinal plants under present climate conditions and the formulation of conservation plans to address the impacts of future climate change on these medicinal plants’ habitats 61 – 63 .…”

Section: Discussionmentioning

confidence: 99%

Climate change impacts on optimal habitat of Stachys inflata medicinal plant in central Iran

Shaban

Ardestani

Ebrahimi‬

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Stachys inflata Benth. is a perennial shrub plant, with powerful natural antioxidant agents, which is recognized as a famous medicinal plant that is widely applied to treat Infection, Asthma, and Rheumatism. Iran is renowned as a center of diversity for Stachys, however, the ideal habitats of S. inflata in this nation remain unknown. The potential and future distribution of suitable habitats for S. inflata were projected using an ensembles ecological niche model in Isfahan province, Iran. We used occurrence data (using GPS), bioclimatic and topographic variables from the Chelsa and WorldClim databases to model the current and future potential distribution of this valuable species. The results showed that: (i) S. inflata is mainly distributed in the south, southwest, center, and west of the Isfahan province, and the excellent habitats of S. inflata accounted for 14.34% of the 107,000 km2 study area; (ii) mean annual temperature, mean daily temperature of wettest quarter, annual precipitation, and elevation were the four most important variables that affect the distribution of S. inflata, with a cumulative contribution of 56.55%; and (iii) about the half (− 42.36%) of the currently excellent habitats of S. inflata show a tendency to decrease from now to the 2080s, while often the area of other S. inflata habitats increases (the area of unsuitable habitat: 5.83%, the area of low habitat suitability: 24.68%, the area of moderate habitat suitability: 2.66%, and the area of high habitat suitability: 2.88%). The increase in the area of other S. inflata habitats is different and they are less favorable than the excellent habitat. The results help establishing a framework for long-term in-situ and ex-situ conservation and management practices in habitats of S. inflata in rangeland and agricultural ecosystems.

show abstract

“…Zhang et al [150] proposed a method to observe and estimate the distribution of the harmful plant Oxytropis ochrocephala Bunge based on UAV remote sensing image. Lan et al [151] proposed two neural network models, MobileNetv2-UNet and FFB-BiseNetV2, to monitor weeds in farmland.…”

Section: Weed Detectionmentioning

confidence: 99%

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

Zhang

Zhu

2023

Drones

View full text Add to dashboard Cite

In recent years, UAV remote sensing has gradually attracted the attention of scientific researchers and industry, due to its broad application prospects. It has been widely used in agriculture, forestry, mining, and other industries. UAVs can be flexibly equipped with various sensors, such as optical, infrared, and LIDAR, and become an essential remote sensing observation platform. Based on UAV remote sensing, researchers can obtain many high-resolution images, with each pixel being a centimeter or millimeter. The purpose of this paper is to investigate the current applications of UAV remote sensing, as well as the aircraft platforms, data types, and elements used in each application category; the data processing methods, etc.; and to study the advantages of the current application of UAV remote sensing technology, the limitations, and promising directions that still lack applications. By reviewing the papers published in this field in recent years, we found that the current application research of UAV remote sensing research can be classified into four categories according to the application field: (1) Precision agriculture, including crop disease observation, crop yield estimation, and crop environmental observation; (2) Forestry remote sensing, including forest disease identification, forest disaster observation, etc.; (3) Remote sensing of power systems; (4) Artificial facilities and the natural environment. We found that in the papers published in recent years, image data (RGB, multi-spectral, hyper-spectral) processing mainly used neural network methods; in crop disease monitoring, multi-spectral data are the most studied type of data; for LIDAR data, current applications still lack an end-to-end neural network processing method; this review examines UAV platforms, sensors, and data processing methods, and according to the development process of certain application fields and current implementation limitations, some predictions are made about possible future development directions.

show abstract

Predicting the Distribution of Oxytropis ochrocephala Bunge in the Source Region of the Yellow River (China) Based on UAV Sampling Data and Species Distribution Model

Cited by 7 publications

References 46 publications

A bibliometric analysis of research trends and hotspots in alpine grassland degradation on the Qinghai-Tibet Plateau

A bibliometric analysis of research trends and hotspots in alpine grassland degradation on the Qinghai-Tibet Plateau

Climate change impacts on optimal habitat of Stachys inflata medicinal plant in central Iran

A Review on Unmanned Aerial Vehicle Remote Sensing: Platforms, Sensors, Data Processing Methods, and Applications

Contact Info

Product

Resources

About