Quantitatively determine the dominant driving factors of the spatial—temporal changes of vegetation NPP in the Hengduan Mountain area during 2000–2015

Chen, Shu-Ting; Guo, Bing; Zhang, Rui; Zang, Wenqian; Wei, Cuixia; Wu, Hongwei; Yang, Xiaofan; Zhen, Xiaoyan; Li, Xing; Zhang, Dafu; Han, Baomin; Zhang, Hailing

doi:10.1007/s11629-020-6404-9

Cited by 68 publications

(28 citation statements)

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“…Moreover, the monitoring index of rocky desertification based on feature space had better applicability in zones with moderate and severe rocky desertification, while that of zones with slight rocky desertification was lower (Table 2 and Figure 5). The reason was that the mixed pixels composed of rock, vegetation, and bare land in zones of slight rocky desertification had contributed to the misclassified and missed pixels (Chen et al, 2021;Han et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

“…All these factors could aggravate the process of rocky desertification. In the northern and eastern parts, the rocky desertification was slighter because the Program of Conversion From Cropland to Forest and Grassland had been applied to restore the vegetation ecosystem since 2005 (Chen et al, 2021). In addition, during the past 20 years, the vegetation coverage had been greatly improved (Guo et al, 2020a(Guo et al, , 2020b.…”

Section: Discussionmentioning

confidence: 99%

“…Remote sensing since the 1970s become an increasingly convenient approach for monitoring and investigating spatiotemporal patterns of rocky desertification. Many past studies have applied single indices, comprehensive index evaluation, or image classification to identify the spatial distributions of rocky desertification (Chen et al, 2021). Tong (2003) proposed a rock bare index using the nearinfrared band and swir1 band of Landsat images as an indicator of rocky desertification in a karst mountain area in Southwest China.…”

Section: Introductionmentioning

confidence: 99%

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A novel‐optimal monitoring model of rocky desertification based on feature space models with typical surface parameters derived from LANDSAT_8 OLI

Guo

Zhang

et al. 2021

Land Degrad Dev

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Previous studies monitoring the spatial distribution of rocky desertification have used single indices, a comprehensive index, or image classification. However, these approaches could not distinguish between the degrees of rocky desertification as they did not consider various influencing factors and their interactions. To avoid the above shortcomings, this study used the feature space model and seven typical land surface parameters to establish two categories of rocky desertification model: (1) a point-to-point model; and (2) a point-to-line model. A novel model for the optimal monitoring of rocky desertification was then proposed, which could take the comprehensive impacts of the human-nature system on the process of rocky desertification.The results showed that: (1) the feature space models provided a novel approach to large-scale monitoring of rocky desertification; (2) the point-to-line model incorporating the rock bare index (RBI)-dryness index feature space showed the optimal applicability for monitoring of rocky desertification, with a precision of 93.4%; and (3) the RBI performed the best in indicating the process of rocky desertification, with an average precision of 88.5%. The results of this study can act as a reference within the investigation of the spatiotemporal evolution of rocky desertification for karst mountain areas.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel‐optimal monitoring model of rocky desertification based on feature space models with typical surface parameters derived from LANDSAT_8 OLI

Guo

Zhang

et al. 2021

Land Degrad Dev

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“…Multiple studies have identified different natural environmental and socioeconomic factors that function as the driving forces of land-use transition, and have carried out analyses of the driving mechanisms [20][21][22]. Among these factors, urbanization, as an important force promoting social and economic development, has a profound impact on the change of land-use morphology.…”

Section: Introductionmentioning

confidence: 99%

The Evolution of the Interactive Relationship between Urbanization and Land-Use Transition: A Case Study of the Yangtze River Delta

Niu

Yan

et al. 2021

Land

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In recent years, the impact of land-use systems on global climate change has become increasingly significant, and land-use change has become a hot issue of concern to academics, both within China and abroad. Urbanization, as an important socioeconomic factor, plays a vital role in promoting land-use transition, which also shows a significant spatial dependence on urbanization. This paper constructs a theoretical framework for the interaction relationship between urbanization and land-use transition, taking the Yangtze River Delta as an example, and measures the level of urbanization from the perspective of population urbanization, economic urbanization and social urbanization, while also evaluating the level of land-use morphologies from the perspective of dominant and recessive morphologies of land-use. We construct a PVAR model and coupled coordination model based on the calculated indexes for empirical analysis. The results show that the relationship between urbanization and land-use transition is not a simple linear relationship, but tends to be complex with the process of urbanization, and reasonable urbanization and land-use morphologies will promote further benign coupling in the system. By analyzing the interaction relationship between urbanization and land-use transition, this study enriches the study of land-use change and provides new pathways for thinking about how to promote high-quality urbanization.

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“…Several studies demonstrated that time-series SAR can efficiently extract rice-planting areas and achieve good results. Compared with singletime phase, multi-time phase [13][14][15][16] can better reflect the polarization backscattering strength of rice in the growing period and its changes so as to better separate other ground objects.…”

Section: Introductionmentioning

confidence: 99%

Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions

et al. 2021

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The use of remote sensing technology to monitor farmland is currently the mainstream method for crop research. However, in cloudy and misty regions, the use of optical remote sensing image is limited. Synthetic aperture radar (SAR) technology has many advantages, including high resolution, multi-mode, and multi-polarization. Moreover, it can penetrate clouds and mists, can be used for all-weather and all-time Earth observation, and is sensitive to the shape of ground objects. Therefore, it is widely used in agricultural monitoring. In this study, the polarization backscattering coefficient on time-series SAR images during the rice-growing period was analyzed. The rice identification results and accuracy of InSAR technology were compared with those of three schemes (single-time-phase SAR, multi-time-phase SAR, and combination of multi-time-phase SAR and InSAR). Results show that VV and VH polarization coherence coefficients can well distinguish artificial buildings. In particular, VV polarization coherence coefficients can well distinguish rice from water and vegetation in August and September, whereas VH polarization coherence coefficients can well distinguish rice from water and vegetation in August and October. The rice identification accuracy of single-time series Sentinel-1 SAR image (78%) is lower than that of multi-time series SAR image combined with InSAR technology (81%). In this study, Guanghan City, a cloudy region, was used as the study site, and a good verification result was obtained.

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Quantitatively determine the dominant driving factors of the spatial—temporal changes of vegetation NPP in the Hengduan Mountain area during 2000–2015

Cited by 68 publications

References 50 publications

A novel‐optimal monitoring model of rocky desertification based on feature space models with typical surface parameters derived from LANDSAT_8 OLI

A novel‐optimal monitoring model of rocky desertification based on feature space models with typical surface parameters derived from LANDSAT_8 OLI

The Evolution of the Interactive Relationship between Urbanization and Land-Use Transition: A Case Study of the Yangtze River Delta

Combined Multi-Time Series SAR Imagery and InSAR Technology for Rice Identification in Cloudy Regions

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