IKONOS Image-Based Extraction of the Distribution Area of Stellera chamaejasme L. in Qilian County of Qinghai Province, China

Li, Jingzhong; Liu, Yongmei; Mo, Chonghui; Wang, Lei; Pang, Guowei; Cao, Mingming

doi:10.3390/rs8020148

Cited by 12 publications

(9 citation statements)

References 51 publications

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“…was successfully (84% overall accuracy) mapped by Forsyth et al (2014) in mountainous regions of the Western Cape, using SPOT-6 imagery. Other studies that have reported an improved discrimination of vegetation types using high spatial resolution multispectral sensors include Oumar (2016), Peerbhay et al (2016b), Li et al (2016), Gómez-Casero et al (2010), and Lawrence et al (2006a). The strategically positioned bands in high spatial resolution multispectral sensors have significantly improved their performance in discrimination of vegetation types as compared to low spatial resolution multispectral sensors.…”

Section: Multispectral Remote Sensing Of Alien Invasionmentioning

confidence: 99%

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Royimani

Mutanga

Odindi

et al. 2019

Physics and Chemistry of the Earth, Parts A/B/C

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Detecting and mapping the occurrence, spatial distribution and abundance of Alien Invasive Plants (AIPs) have recently gained substantial attention, globally. This work, therefore, provides an overview of advancements in satellite remote sensing for mapping and monitoring of AIPs and associated challenges and opportunities. Satellite remote sensing techniques have been successful in detecting and mapping the spatial and temporal distribution of AIPs in rangeland ecosystems. Also, the launch of high spatial resolution and hyperspectral remote sensing sensors marked a major breakthrough to precise characterization of earth surface feature as well as optimal resource monitoring. Although essential, the improvements in spatial and spectral properties of remote sensing sensors presented a number of challenges including the excessive acquisition and limited temporal resolution. Therefore, the use of high spatial and hyperspectral datasets is not a plausible alternative to continued and operational scale earth observation, especially in financially constrained countries. On the other hand, literature shows that image classification algorithms have been instrumental in compensating the poor spatial and spectral resolution of remote sensing sensors. Furthermore, the emergence of robust and advanced nonparametric image classification algorithms have been a major development in image classification algorithms. Therefore, to address the inevitable challenges arising with satellite sensor development technology it is necessary to explore the use of robust and advanced non-parametric image classifiers with data provided by the new generation of multispectral sensors with improved spatial and spectral resolutions. This will promote longterm and large scale mapping of AIPs, especially in financially constrained countries.

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Section: Multispectral Remote Sensing Of Alien Invasionmentioning

confidence: 99%

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Royimani

Mutanga

Odindi

et al. 2019

Physics and Chemistry of the Earth, Parts A/B/C

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“…The vertical changes of climate, soil and vegetation are obvious, and the temperature decreases with the gradual increase of altitude. The annual average temperature is—1.8– 1.0 °C, and the annual precipitation of 406.7 mm 35 . Total grassland area is 1.12 × 10 6 hm 2 , accounting for 75.74% of the total area of the county.…”

Section: Methodsmentioning

confidence: 99%

Impacts of climate change and human activities on different degraded grassland based on NDVI

Hou

Yang

et al. 2022

Sci Rep

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Grassland degradation has emerged as a serious socio-economic and ecological problem, endangering both long-term usage and the regional biogeochemical cycle. Climate change and human activities are the two leading factors leading to grassland degradation. However, it is unclear what the degradation level caused by these two factors is. Using the normalized difference vegetation index (NDVI) and coefficient of variation of NDVI (CVNDVI), the spatial distribution features of grassland degradation or restoration were analyzed in Qilian County in the northeast of the Qinghai–Tibet Plateau. The dominant climate variables affecting NDVI variation were selected through the combination of random forest model and stepwise regression method to improve the residual trend analysis, and on this basis, twelve possible scenarios were established to evaluate the driving factors of different degraded grasslands. Finally, used the Hurst index to forecast the trend of grassland degradation or restoration. The results showed that approximately 55.0% of the grassland had been degraded between 2000 and 2019, and the area of slight degradation (NDVIslope > 0; CVNDVI (slope) > 0; NDVIvalue > 0.2) accounted for 48.6%. These regions were centered in the northwest of Qilian County. Climate and human activities had a joint impact on grassland restoration or degradation. Human activities played a leading role in grassland restoration, while climate change was primarily a driver of grassland degradation. The regions with slight degradation or re-growing (NDVIslope > 0; CVNDVI (slope) > 0), moderate degradation (NDVIslope < 0; CVNDVI (slope) > 0), and severe degradation or desertification (NDVIslope < 0; CVNDVI (slope) < 0) were dominated by the joint effects of climate and anthropogenic activity accounted for 34.3%, 3.3%, and 1.3%, respectively, of the total grassland area. Grasslands in most areas of Qilian County are forecasted to continue to degrade, including the previously degraded areas, with continuous degradation areas accounting for 54.78%. Accurately identifying the driving factors of different degraded grassland and predicting the dynamic change trend of grassland in the future is the key to understand the mechanism of grassland degradation and prevent grassland degradation. The findings offer a reference for accurately identifying the driving forces in grassland degradation, as well as providing a scientific basis for the policy-making of grassland ecological management.

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“…Such interspecific differentiation in the acquisition of soil resources alleviates competition and permits co-existence with heterospecific plants F I G U R E 1 Global distribution of S. chamaejasme based on previously published records (Liu, Long, & Yao, 2004;Wang, 2004;Wang & Gilbert, 2007;Zhang, Volis, & Sun, 2010;, primarily including southern Russia, North Korea, Mongolia, Nepal, and northern and southwestern China (Fargione & Tilman, 2006;Ryel, 2010;Xin et al, 2012). Nevertheless, perennial toxic weeds are usually tall and thus superior competitors for light resources relative to shorter plant species (Craine & Dybzinski, 2013;Hautier, Niklaus, & Hector, 2009;Li et al, 2016). In addition, individuals often aggregate to form patches that facilitate intraspecific cooperation, enhance their competitive ability, and promote their expansion Ren et al, 2015;Sun, Ren, & He, 2011).…”

Section: Interspecific Relationshipsmentioning

confidence: 99%

Don’t judge toxic weeds on whether they are native but on their ecological effects

Zhang

Sun

Liu

et al. 2020

Ecology and Evolution

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The sharp rise in anthropogenic activities and climate change has caused the extensive degradation of grasslands worldwide, jeopardizing ecosystem function, and threatening human well‐being. Toxic weeds have been constantly spreading in recent decades; indeed, their occurrence is considered to provide an early sign of land degeneration. Policymakers and scientific researchers often focus on the negative effects of toxic weeds, such as how they inhibit forage growth, kill livestock, and cause economic losses. However, toxic weeds can have several potentially positive ecological impacts on grasslands, such as promoting soil and water conservation, improving nutrient cycling and biodiversity conservation, and protecting pastures from excessive damage by livestock. We reviewed the literature to detail the adaptive mechanisms underlying toxic weeds and to provide new insight into their roles in degraded grassland ecosystems. The findings highlight that the establishment of toxic weeds may provide a self‐protective strategy of degenerated pastures that do not require special interventions. Consequently, policymakers, managers, and other personnel responsible for managing grasslands need to take appropriate actions to assess the long‐term trade‐offs between the development of animal husbandry and the maintenance of ecological services provided by grasslands.

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IKONOS Image-Based Extraction of the Distribution Area of Stellera chamaejasme L. in Qilian County of Qinghai Province, China

Cited by 12 publications

References 51 publications

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Advancements in satellite remote sensing for mapping and monitoring of alien invasive plant species (AIPs)

Impacts of climate change and human activities on different degraded grassland based on NDVI

Don’t judge toxic weeds on whether they are native but on their ecological effects

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