Diversified Land Research Articles

Quantification and analysis study for the morphological characteristics of urban waterbodies: Evidences from 42 cases in China

Influenced by the water design principle of Chinese classical garden, the design of urban waterbodies (lakes, ponds and wetlands) in China typically exhibits natural-like morphological characteristics, but what similarities and differences among these characteristics remain unclear. Also, the morphology of urban waterbodies is mostly designed with beauty and lacks quantitative research and methodological support, which is not favourable to the exploration of the correlation between waterbody morphology and ecology. In this study, 11 quantifiable morphological indicators are selected from water surface, shoreline complexity and water-land spatial morphology. A Grasshopper-based model for waterbody morphology quantification and analysis was constructed and applied to 42 cases in China. Combined with frequency, correlation and PCA analysis, the cases and indicators with higher composite scores generally showed more natural water surface morphology, island distribution, and diversified land and water spaces. The thresholds for the more representative indicators are 0.10–0.60 for the circularity ratio (C), 1.01–1.15 for the shoreline fractal dimension (D0), 1.58–29.42 for the island nearest-neighbour index (NN), 1.20–2.50 for the shoreline development index (SDI), 0.20–0.55 for the compactness ratio (Rc) and 0.30–0.85 for the unit water surface morphological difference ratio (ΔB). Focusing on these indicators, along with ΔB and I which describe spatial inclusiveness and island distribution, their regression equations and threshold ranges provide a primary basis for developing waterbody morphology designs and generative algorithms. This methodology has been experimentally applied in the design of a case waterbody in Suqian City Park. Overall, this study constructs and validates the feasibility of a Grasshopper-based algorithm for the quantitative analysis and morphogenetic design of waterbody morphology. It demonstrates the potential of this method for understanding complex waterbody morphology and water-land spaces, and supports a new digital methodology for the optimisation of waterscape design.

A Study based on Agricultural Marketing Strategies

Agriculture is the core part of Indian traditional practice. India is a country of diverse culture and Nature; verities of crops and fruits are grown in different parts of the country. The gift of Nature and the efficiency and business attitudes blend with agriculture open a new preface. ’Agro-based product businesses. Agro based product business can viable and truly possible where Nature supports. In case of India, the God gifted nature, diversified land form, water resources all are eventually support the agriculture and majority of population spend their livelihood by farming. Agro based business indicates the commercialization of agriculture in a systematic meaningful way. The farmers sell some commercial crops to some business house and the business house process the agricultural raw material as per the industry need. Rural people are highly associated with cultivation for their livelihood, but they are not getting high economic benefits from farming. This paper will highlight the need of proper agricultural marketing. This research paper will focus on the marketing strategies of agr0-based products. This paper will highlight the significance of efficient marketing strategies in agro based products to capture the market and gaining profit from market. (Key words: Agriculture, marketing strategies, digital, agricultural product)

Destigmatizing urban villages by examining their attractiveness: Quantification evidence from Shenzhen

While existing social and political research has qualitatively discussed the stigmatization of urban villages (UVs), there's a lack of quantitative support. This study innovatively attempts to provide quantitative evidence, employing a spatial perspective for the destigmatization of UVs. We integrated population trajectory, GDP data, employment and residential points of interest, and developed a spatial gravity model to derive the spatial attractiveness index. Concurrently, we selected environmental, spatial structure, and housing economic indicators to construct a regression analysis. Our findings revealed that urban villagers exhibit a preference for shorter daily commutes, underscoring the positive role of UVs in promoting job-housing balance and providing diverse services. The high-frequency mobility of villagers accelerates the categorization of UVs and enhances intra-area circulation. We further discussed the interaction between UV renewal and its destigmatization. To counter spatial stigmatization, enhancing the spatial quality and infrastructure of UVs, as well as promoting diversified land use can reduce the public's stereotypical impressions. Moreover, prioritizing affordable housing and equitable distribution of facilities, along with fostering synergies between urban capital and UVs, can facilitate the destigmatization process. Stigmatization in informal settlements is a widespread issue. Our quantitative approaches, as well as targeted renovation and policy recommendations, can serve as a blueprint for addressing similar challenges in informal settlements globally.

Dynamics of dissolved inorganic carbon (DIC) and stable C isotope ratios (δ13CDIC) in a tropical watershed with diversified land use in São Paulo State, Brazil

The fluvial transport of dissolved inorganic carbon (DIC) is an important component of the global carbon cycle. Herein, we assessed the dynamics of DIC and the C stable isotopic composition (δ13CDIC) in a watershed with diversified land use in São Paulo State (Brazil), more specifically in the Sorocaba River basin (SRB) and considered the temporal and spatial scales. For this purpose, twelve fluvial samples at each sampling point (e.g., S1, S2, S3, S4 and S5) were collected in the SRB, from June 2009 to May 2010, which represented one complete hydrological cycle that included the extremes of the rainfall and discharge regimes. In addition, the δ13CDIC values were also characterized in the wet and dry season at all sampling points to verify their seasonal variability. The results reflected the seasonal variation in discharges, water temperatures, and electrical conductivities. Most of the DIC was transported in the wet season at all sampling points, where the less negative δ13CDIC values were characterized. The natural sources of DIC are associated with atmospheric/soil CO2 consumption. The anthropogenic impacts on both [DIC] and δ13CDIC are linked to untreated urban sewage that is discharged directly into the Sorocaba River, as well as to aquatic photosynthesis in the Itupararanga Reservoir. From 1970 to 2020, the modeling proposed in this study indicated that the annual flux of DIC (Friver) varied from 9.0 to 78.7 t km−2 a−1, confirming that the El Niño Southern Oscillation (ENSO) controlled Friver in the SRB, with higher and lower Friver values occurring during strong El Niño (EN) and La Niña (LN) years. The average Friver value was 20 t km−2 a−1, which is higher than those obtained in natural several temperate and tropical watersheds due to the influences of urban areas on [DIC] in the SRB.

Commercial timber plantations and community livelihoods: Insights from comparative case studies in southern Laos

The social impacts of industrial wood plantations (IWP) in Southeast Asia are extensively contested. Whilst productive, well-managed IWPs can offer a range of benefits to broader societies, they have also been criticised as driving community displacement and economic marginalisation. There is benefit to comparative case studies that identify the conditions whereby IWPs can support improved rural well-being. This paper assesses changes in resource tenure and livelihoods following plantation establishment in three selected case communities in southern Laos, using a rural appraisal approach. The study finds that IWPs can contribute positively to local livelihoods in Laos, under conditions. These occur when sufficient land is reserved for diversified land uses; local people secure plantation employment; there is adequate compensation for formal and informal land claims; and there are tangible contributions to village infrastructure and development. The availability plantation wage labour alone was found to be inadequate for driving broad livelihood improvement. Fieldwork identified the lingering negative social impacts of uncompensated land dispossession. Assessments of realised community benefits of plantation schemes should be considered in relation to the increasing underlying value of forest-lands in Laos. The paper provides updated policy options for an improved balance between stakeholder interests in Laos' strategic plantation sector.

Climate change information tailored to the agricultural sector in Central Europe, exemplified on the region of Lower Franconia

There is a growing societal, economic, and political demand to translate available data on regional climate change into sector-specific, practice-oriented, and user-friendly information. The study presents a demand-driven approach to specify the impacts of regional climate change on agriculture, viticulture, and fruit and vegetable growing in Lower Franconia, southern Germany, a region with heterogeneous topography, diversified land use patterns, and intense activities in the sectors specified above. The approach is based on an ensemble of high-resolution regional climate model projections, a bias correction tool, and a large spectrum of meteorological (extreme) indicators that are crucial to the agricultural sector in Central Europe, as inferred from a stakeholder survey.For several decades, Lower Franconia represents a hotspot region of climate change with enhanced heat waves, prolonged droughts, and intermittent local flooding by heavy rainfall events. Results of the high-resolution regional climate model projections indicate an increase of hot days and tropical nights by a factor of 5 and 12, respectively, if greenhouse gas emissions continue to grow until 2100 according to the RCP8.5 emission scenario. At the same time, droughts will occur more frequently and last longer while rainfall intensity enhances. A longer growing period starting more than 40 days earlier (compared to the reference period 1970 to 1999) implies a higher risk of late frost damage for crops, fruits, grapes, and even some tree species. In contrast, the thermal prerequisites for viticulture will be satisfied across the entire region, even at higher-elevation sites. These facets of regional climate change are made accessible to users and the public via an interactive field-resolving web portal. Altogether, they gravely challenge the historically developed land use systems in Lower Franconia and require timely adaptation and mitigation strategies.

Do shared E-bikes reduce urban carbon emissions?

Under the threat of climate change, many global cities nowadays are promoting shared commuting modes to reduce greenhouse gas emissions. Shared electric bikes (e-bikes) are emerging modes that compete with bikes, cars, or public transit. However, there is a lack of empirical evidence for the net effect of shared e-bikes on carbon emissions, as shared e-bikes can substitute for both higher carbon emissions modes and cleaner commuting modes. Using a large collection of spatio-temporal trajectory data of shared e-bike trips in two provincial cities (Chengdu and Kunming) in China, this study develops a travel mode substitution model to identify the changes in travel modes due to the introduction of shared e-bike systems and to quantify the corresponding impact on net carbon emissions. We find that, on average, shared e-bikes decrease carbon emissions by 108–120 g per kilometre. More interestingly, the reduction effect is much stronger in underdeveloped non-central areas with lower density, less diversified land use, lower accessibility, and lower economic level. Although the actual carbon reduction benefits of shared e-bike schemes are far from clear, this study bears important policy implications for exploring this emerging micro-mobility mode to achieve carbon reduction impacts.

Forecast of policy-driven land use change and its impact on ecosystem services in China: A case study of the Yangtze River Economic Belt.

Land use change is an important factor affecting the performance of ecosystem services (ESs). Therefore, understanding the impact of land use change on ESs is of great significance for promoting the coordination of regional human-land relationships. In this study, random forest and cellular automata were used to simulate and predict the characteristics of land use change in the Yangtze River Economic Belt, and diversified land use evolution patterns were formed in combination with China's strategic development needs. The effects of habitat suitability on ESs were analyzed by using a multiscenario land use change model. The results demonstrated that the driving factors selected in this article had a good induction effect on the law of land use evolution, and the simulated land use change had high credibility. Under the mode of ecological protection and cultivated land protection, the expansion of construction land was greatly affected and was not conducive to social and economic development. Under the natural evolution mode, farmland was greatly encroached upon, and food security was greatly threatened. The regional coordination model had relative advantages, and all kinds of land use needs were met to a certain extent. The water production function of ESs was strong, but the carbon storage function was weak. The relationship between the habitat suitability index and ES changes under land use change revealed that there were significant differences in ES changes caused by ecological quality changes in mountainous and plain areas. This study provides a reference for promoting social and economic development and ecosystem integrity. Integr Environ Assess Manag 2023;19:1473-1484. © 2023 SETAC.

Evaluation on the performance of tree view factor in a high-density subtropical city: A case study in Hong Kong

Outdoor thermal comfort is a primary concern when designing urban environments suitable for pedestrian activities. In previous research, urban greenery had been considered as an effective strategy to mitigate the deterioration of the street-level thermal environment. Tree view factor (TVF), a parameter that can estimate the amount of tree cover visible in the overlying hemisphere, was applied in recent thermal environment assessment studies. However, a detailed understanding of TVF's suitability and application in a subtropical high-rise compact metropolis with diversified land uses is still lacking. To fill the knowledge gap, this study used Hong Kong as a study case and conducted ENVI-met simulations to analyse the human thermal comfort at two levels of TVF sites and two weather conditions. Results showed that high TVF (Htvf) sites had a pronounced reduction in mean radiant temperature (TMRT) of at least 15 °C after 12:00 under both typical and extreme weather scenarios. A lower mean physiological equivalent temperature (PET) of below 30 °C and 35 °C remained in the daytime of typical and extreme weather scenarios, respectively. It was also found that low TVF sites inside parks received more solar radiation, while Htvf sites inside parks exhibited a more substantial cooling potential than that inside street canyons. Htvf sites could maintain better pedestrian thermal comfort due to the shading effect. This study also proved that TVF is more suitable than green coverage ratio (GCR) in urban thermal environment assessments and urban green infrastructure design to create a thermally comfortable high-rise and high-density metropolis.

CEU-Net: ensemble semantic segmentation of hyperspectral images using clustering

Most semantic segmentation approaches of big data hyperspectral images use and require preprocessing steps in the form of patching to accurately classify diversified land cover in remotely sensed images. These approaches use patching to incorporate the rich spatial neighborhood information in images and exploit the simplicity and segmentability of the most common datasets. In contrast, most landmasses in the world consist of overlapping and diffused classes, making neighborhood information weaker than what is seen in common datasets. To combat this common issue and generalize the segmentation models to more complex and diverse hyperspectral datasets, in this work, we propose a novel flagship model: Clustering Ensemble U-Net. Our model uses the ensemble method to combine spectral information extracted from convolutional neural network training on a cluster of landscape pixels. Our model outperforms existing state-of-the-art hyperspectral semantic segmentation methods and gets competitive performance with and without patching when compared to baseline models. We highlight our model’s high performance across six popular hyperspectral datasets including Kennedy Space Center, Houston, and Indian Pines, then compare them to current top-performing models.

Carbon dynamics in old-growth forests of the Central Hardwoods Region, USA

Managing old-growth forests and promoting old-growth complexity in aging forests for carbon emissions mitigation has become an important component of diversified land management strategies. In the midwestern US, the Central Hardwoods Region (CHR) is the largest continuous deciduous forested area and includes a diverse range of species compositions, forest structures, and topoedaphic environments. Understanding carbon storage potential in old-growth forests across the CHR is important for evaluating climate-adaptive management strategies to increase carbon sequestration in the region’s aging forests. We assessed forest carbon in two time periods (the early 1990s and the 2010s) in ten old-growth forests across a 770 km east-west productivity gradient from Indiana to Missouri. Further, we related anomalies in carbon pools between the two sampling periods to documented or observable disturbances. As expected, old-growth forests on more productive sites in the eastern portion of the study range stored more aboveground carbon (120–177 Mg C ha−1) than less productive sites to the west (93–117 Mg C ha−1). Over the twenty-year period, old-growth forests accumulated 9.2 ± 1.5 (mean ± SE) Mg C ha−1 or a 7 % increase in total aboveground carbon. Further, downed dead wood carbon increased 5 % (0.4 ± 0.7 Mg C ha−1), standing dead increased 7 % (0.3 ± 0.7 Mg C ha−1), live roots increased 4 % (1.0 ± 0.3), and dead roots increased by 68 % (0.3 ± 0.1 Mg C ha−1). However, stochastic disturbances can positively or negatively impact total carbon and carbon pools. Documenting carbon trends and disturbance effects in old-growth forests provides guidance to enhance the representation of structurally complex, late successional forests using active forest management. Old-growth forests are currently rare in the CHR landscape, but the abundance of aging forests in the region provides immense potential to store carbon, particularly when combined with strategies that optimize early- and late-successional habitats for carbon sequestration along with other ecological goods and services.

A new rice identification algorithm under complex terrain combining multi-characteristic parameters and homogeneous objects based on time series dual-polarization synthetic aperture radar

Accurate mapping of rice-growing areas is essential to ascertain the spatial distribution of rice fields, and ensure food security. It is a challenging task to timely and accurate identify rice under the complex terrain due to its diversified land cover, small- or middle-sized rice fields with fragmented distribution. In this paper, the time series VV and VH backscatter coefficient datasets were first constructed based on 411 sentinel-1 synthetic aperture radar (SAR) images in Chongqing city with complex terrain. Then, the rice multi-characteristic parameters, including SAR backscatter features, composite features, rice phenological parameters, texture features and topographic features, were generated. On this basis, the homogeneous image objects were produced. Furthermore, a rice identification algorithm combining multi-characteristic parameters and homogeneous objects based on time series dual-polarization SAR (MPHO-DPSAR) was established. The research demonstrated that the MPHO-DPSAR algorithm can achieve accurate mapping of small and medium-sized and fragmented rice fields in regions under complex terrain according to the accuracy evaluation at three levels and the comparison with other three classical rice identification methods. The suitability and limitations of proposed MPHO-DPSAR algorithm were also discussed from the aspects of SAR data temporal and spatial resolution, rice phenology, and surface landscape complexity.

Diversified land conversion deepens understanding of impacts of rapid rubber plantation expansion on plant diversity in the tropics

Understanding the status and changes of plant diversity in rubber (Hevea brasiliensis) plantations is essential for sustainable plantation management in the context of rapid rubber expansion in the tropics, but remains very limited at the continental scale. In this study, we investigated plant diversity from 10-meter quadrats in 240 different rubber plantations in the six countries of the Great Mekong Subregion (GMS)—where nearly half of the world's rubber plantations are located—and analyzed the influence of original land cover types and stand age on plant diversity using Landsat and Sentinel-2 satellite imagery since the late 1980s. The results indicate that the average plant species richness of rubber plantations is 28.69 ± 7.35 (1061 species in total, of which 11.22 % are invasive), approximating half the species richness of tropical forests but roughly double that of the intensively managed croplands. Time-series satellite imagery analysis revealed that rubber plantations were primarily established in place of cropland (RPC, 37.72 %), old rubber plantations (RPORP, 27.63 %), and tropical forests (RPTF, 24.12 %). Plant species richness in RPTF (34.02 ± 7.62) was significantly (p < 0.001) higher than that in RPORP (26.41 ± 7.02) and RPC (26.34 ± 5.37). More importantly, species richness can be maintained for the duration of the 30-year economic cycle, and the number of invasive species decreases as the stand ages. Given diverse land conversions and changes in stand age, the total loss of species richness due to rapid rubber expansion in the GMS was 7.29 %, which is far below the traditional estimates that only consider tropical forest conversion. In general, maintaining higher species richness at the earliest stages of cultivation has significant implications for biodiversity conservation in rubber plantations.

Land cover diversity: Reshaping the socioeconomic value of land

The land is a vital resource to support economic growth. Previous studies have mainly taken urban and agricultural areas as the major factors of economic boost. However, the supporting role of diversified land in sustainable economy has not been fully valued. This study analyzed the relationship between land cover diversity and socioeconomic outputs from 1992 to 2019 on up to 2086 counties in China. The results showed the regional disparity in the eastern and western counties. In the western counties, land cover diversity was positively correlated with per area socioeconomic indicators throughout the period. In the eastern counties, the correlation with per area indicators has gradually changed from negative to positive. The correlation with per capita indicators was more significant in the east than west. The regional disparity and temporal trends may come from the influence of water resources, demographic pressure and other constraints in different regions. The refreshed land value can help to achieve sustainable development and improve human well-being in the long term.

A Spatial PWV Retrieval Model Over Land for GCOM-W/AMSR2 Using Neural Network Method: A Case in the Western United States

Precipitable water vapor (PWV) is an important and active part of the atmosphere. As known, microwave PWV retrieval is well applied for the ocean but challenging over land. In this article, we creatively established a microwave PWV retrieval spatial model over land using the back-propagation (BP) neural network to combine the high precision ground-based Global Navigation Satellite System (GNSS) data and high spatial continuity satellite-borne data. Three-year data from 167 GNSS stations located in western America were utilized for training the network, and 40 untrained sites were selected as the test set. Root-mean-square error (RMSE) of the test set can reach 3.90 mm and 3.88 mm in the ascending (As) and descending (De) orbits. Then, we analyzed the influence of land cover types on the model over land. As a result, we found that stations located in the area with a single large-scale continuous land cover type had higher retrieval accuracy. In contrast, stations with diversified land cover types had lower precision. Furthermore, after fully considering the impact of land cover type, we performed an improved model with 61 stations on the single large-scale continuous grasslands, and the results of 8 stations as the test set showed that the RMSE could reach 3.41 and 3.31 mm in the As and De orbits. Compared with the spatial model established previously, the accuracy had been improved by about 13%. We think this is due to the stable physical properties (such as microwave emissivity) of the single large-scale continuous land cover type.

Enhancing conceptual and practical understandings of small-scale farming resilience in the metropolitan countryside of Rio de Janeiro, Brazil

Rural-urban complexity can be seen across the Rio de Janeiro Metropolitan Region where land use, and economic and environmental policies have generated conflicts. In this context, agriculture has become juxtaposed with other functions and interests, which has resulted in a mosaic of diversified land use. These rural-urban interactions also provide opportunities to develop different types of knowledge that allow communities to develop resilience in an environment of spatial changes. The aim of this article is to analyse rural change and farming resilience in the Eastern Rio Metropolis, based on primary research undertaken in 2017 and 2018. The results provide useful insights for understanding the nature of rural-urban interactions in a metropolitan countryside that could, in turn, inform policies for promoting local and regional quality food systems and small-scale farming strategies.

Identifying regions of excess injury risks associated with distracted driving: A case study in Central Ohio, USA

This study examines the latent influence of spatial locations on the relative risks of crash injuries associated with distracted driving (DD) and identifies regions of excess risks for policy intervention. Using a sample of aggregated injury and fatal DD crash records for the period 2015–2019 across 1,024 census block groups in Central Ohio (i.e., the Columbus Metropolitan Area) in the United States, we investigate the role of latent effects along with several covariates such as land-use mix, sociodemographic features, and the built environment. To this end, we specifically leverage a full Bayesian hierarchical formulation with conditional autoregressive priors to account for uncertainty (i.e., spatially structured random effects) stemming from adjacent census block groups. Furthermore, we consider uncorrelated random effects from upper-level administrative units within which each block group is nested (i.e., census tracts and counties). Our analysis reveals that (1) addressing spatial correlation improves the model's performance, (2) block-group-level variability substantially explains the residual random fluctuation, and (3) intersection density appears negatively associated with the relative risks of crash injuries, while more diversified land use can increase injury risk. Based on these findings, we present spatial clusters with twice the relative risks compared to other block groups, suggesting that policies be devised to mitigate severe injuries due to DD and therefore enhance public health.

Impact of Aboveground Vegetation on Abundance, Diversity, and Biomass of Earthworms in Selected Land Use Systems as a Model of Synchrony between Aboveground and Belowground Habitats in Mid-Himalaya, India

The population status and biomass of earthworms were studied in three different land use systems of pasture (Pa), silvopasture (SP), and mixed evergreen forest (MEF) from 2019–2020 in the Solan district of Himachal Pradesh, India. The aim of this study was to assess the population status of earthworms and investigate how different land use systems influence their abundance, diversity, and biomass. Earthworms and soil were sampled using the Tropical Soil Biology and Fertility (TSBF) method in all seasons (winter, spring, summer, monsoon, and autumn). The physicochemical properties of the soil were analyzed to evaluate their effects on the diversity, biomass, and density of animals. The diversity status parameters, such as the Shannon diversity index (H′), Margalef richness index (R), evenness (J′), and dominance index (D), were computed. A total of seven earthworm species, belonging to four families, namely, Amynthas corticis, Aporrectodea rosea, Drawida japonica, Eisenia fetida, Metaphire birmanica, Metaphire houlleti, and Lennogaster pusillus, were identified from all three land use systems. The lowest Shannon diversity index (H′), Margalef index (R), and evenness (J′) index values were registered in MEF (H′ = 0.661, R = 0.762, J′ = 0.369) compared to those in Pa (H′ = 1.25, R = 1.165, J′ = 0.696) and SP (H′ = 0.99, R = 0.883, J′ = 0.552), implying that MEF is the least diversified land system. In contrast, the highest dominance index (D) value was registered in MEF (Pa = 0.39, SP = 0.53, MEF = 0.67), which again showed that MEF is the least diversified land system. The highest values of abundance and biomass were recorded in MEF (754.15 individuals m−2 and 156.02 g m−2), followed by SP (306.13 individuals m−2 and 124.84 g m−2) and Pa (77.87 individuals m−2 and 31.82 g m−2). Both the density and biomass of earthworms increased from Pa to MEF (Pa &lt; SP &lt; MEF). This study is novel because it revealed that the diversity and productivity (biomass and abundance) values of earthworms were negatively correlated (as diversity increased, productivity decreased; as diversity decreased, productivity increased). The total values of abundance and biomass of earthworms in the three land use systems indicated perfect synchrony between aboveground and belowground habitats, whereas the diversity values revealed that MEF was dominated by one or two species and the least diversified. Therefore, for sustainable belowground productivity, aboveground conservation is recommended, and vice versa, regardless of diversity.

Ecological correlates related to adolescent movement behaviors: A latent class analysis.

The ecological model has been widely used to help researchers understand the multiple influences in the physical activity (PA) and in the sedentary behaviors in isolated forms. To date, few correlates concerning the behavioral groupings of PA and sedentary behaviors have been studied. In this context, this study aimed to identify movement behaviors’ latent classes related to the different adolescents’ PA and sedentary time expressions, as well as their associations with individual, sociodemographic, family, and environmental correlates. This is a cross-sectional study with 309 students aged between 14 and 16. Latent Class Analysis was used to identify movement behavior classes based on light PA, moderate to vigorous PA, number of steps, sedentary time, and screen time (ST). An accelerometer was used to evaluate movement behaviors. The individual, sociodemographic, family, and environmental correlates were assessed by questionnaires. Three classes were identified: Class 1, "Active and Non-Sedentary" (8.10% of the sample), Class 2, "Active and Sedentary" (28.5%), and Class 3, "Inactive and Sedentary" (63.4%). Those with low fruit intake, low aerobic fitness, stressed and whose head of the family obtained an ‘elementary school’ level education were, respectively, 7.17, 3.59, 3.56, and 4.40 times more likely to belong to class 3 than class 1. Those with medium and high socioeconomic status were 82% and 83% less likely to belong to class 1 than classes 2 and 3, respectively. Adolescents who perceived the neighborhoods with the best access to diversified land use, street connectivity, walking/pedaling ease, and traffic safety attributes, were 84%, 85%, 82%, and 82%, respectively less likely to belong to class 1 than class 2. It is concluded that distinct correlates can be associated with the movement behaviors classes.

Land Use Multi-Functionality and Zoning Governance Strategy of Densely Populated Areas in the Upper Reaches of the Yellow River: A Case Study of the Lanzhou–Xining Region, China

With rapid urbanization, the interactions between human and land are becoming more and more intense, which leads to increasingly diversified land use and intensifies the conflicts among land use functions (LUFs). However, land use multi-functionality (LUMF) of densely populated areas (DPAs) in less developed regions has not been studied in depth. The objective of our study is to build a multi-functional conceptual framework for land use, and establish a comprehensive evaluation indicator system to assess LUMF. We took the Lanzhou–Xining Region (LXR) as a case area, which is a DPA in the upper reaches of the Yellow River. We established 36 indicators from the dimensions of status and trend of agricultural, economic, social, and ecological functions, to perform analysis on the LUMF using the entropy weight method (EWM) and the coupling degree method (CDM). The results show that land use in the LXR is multi-functional, that LUFs are developing in an uneven manner, and that the spatial distribution of LUFs differs greatly. We find that the multi-functional level of land use in the LXR is low. There are no dominant functions in 12 counties and districts. There are spatial conflicts among LUFs. To maintain sustainable land use, we proposed a functional zoning scheme and put forward corresponding governance strategies.