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The geography of human activity and land use: A big data approach
جغرافیای فعالیت های انسانی و استفاده از زمین: یک رویکرد داده های بزرگ-2020 The application of location-based social media big data in urban contexts offers new and alternative strategies
for understanding city liveliness in developing countries where traditional census data are poor. This paper
demonstrates how the spatial-temporal distribution of Chinas Tencent social media usage intensities can be
effectively used as a proxy for modelling the geographic patterns of human activity at fine scales. Our results
suggest that the spatially-temporally contextualized nature of human activity is dependent upon land use mixing
characteristics. With billions of social media data being collected in the virtual world, findings of this study
suggest that land use policies to delineating the density, orderly or disorderly geographic patterns of human
activity are important for city liveliness. Keywords: Big data | Human activity | Land use |
مقاله انگلیسی |
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A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach
یک مدل برای زیرساخت های داده های بزرگ فضایی روستایی در ترکیه: رویکرد حسگر محور و یکپارچه-2020 A Spatial Data Infrastructure (SDI) enables the effective spatial data flow between providers and users for their
prospective land use analyses. The need for an SDI providing soil and land use inventories is crucial in order to
optimize sustainable management of agricultural, meadow and forest lands. In an SDI where datasets are static,
it is not possible to make quick decisions about land use. Therefore, SDIs must be enhanced with online data flow
and the capabilities to store big volumes of data. This necessity brings the concepts of the Internet of Things (IoT)
and Big Data (BD) into the discussion.
Turkey needs to establish an SDI to monitor and manage its rural lands. Even though Turkish decision-makers
and scientists have constructed a solid national SDI standardization, a conceptual model for rural areas has not
been developed yet. In accordance with the international agreements, this model should adopt the INSPIRE
Directive and Land Parcel Identification System (LPIS) standards. In order to manage rural lands in Turkey, there
are several legislations which characterize the land use planning, land classification and restrictions. Especially,
the Soil Protection and Land Use Law (SPLUL) enforces to use a lot and a variety of land use parameters that
should be available in a big rural SDI. Moreover, this model should be enhanced with IoT, which enables to use
of smart sensors to collect data for monitoring natural occurrences and other parameters that may help to classify
lands.
This study focuses on a conceptual model of a Turkish big rural SDI design that combines the sensor usage and
attribute datasets for all sorts of rural lands. The article initially reviews Turkish rural reforms, current enterprises
to a national SDI and sensor-driven agricultural monitoring. The suggested model integrates rural land
use types, such as agricultural lands, meadowlands and forest lands. During the design process, available data
sets and current legislation for Turkish rural lands are taken into consideration. This schema is associated with
food security databases (organic and good farming practices), non-agricultural land use applications and local/
European subsidies in order to monitor the agricultural parcels on which these practices are implemented. To
provide a standard visualization of this conceptual schema, the Unified Modeling Language (UML) class diagrams
are used and a supplementary data dictionary is prepared to make clear definitions of the attributes, data
types and code lists used in the model.
This conceptual model supports the LPIS, ISO 19156 International Standard (Geographic Information:
Observations and Measurements) catalogue and INSPIRE data theme specifications due to the fact that Turkey is
negotiating the accession to EU; however, it also provides a local understanding that enables to manage rural
lands holistically for sustainable development goals. It suggests an expansion for the sensor variety of Turkish
agricultural monitoring project (TARBIL) and it specifies a rural theme for Turkish National SDI (TUCBS). Keywords: Spatial data infrastructures | Big data | Internet of things | Rural land use | INSPIRE | LPIS |
مقاله انگلیسی |
3 |
Identifying regionalized co-variate driving factors to assess spatial distributions of saturated soil hydraulic conductivity using multivariate and state-space analyses
شناسایی عوامل محرک متغیر منطقه ای برای ارزیابی توزیع مکانی هدایت هیدرولیکی خاک اشباع شده با استفاده از تجزیه و تحلیل چند متغیره فضای دولت-2020 Saturated soil hydraulic conductivity (Ksat) is a key factor in hydrological management projects and its variability
along the landscape hinders its correct use in the formulation of such projects. Ksat varies under different
climatic and hydrological conditions at spatial scales as reported in several studies. However, co-regionalization
of Ksat remains a challenging aspect with regard to identifying supportive co-variates and suitable spatial
models. The objectives of this study were to (i) identify factors that relate Ksat with soil and topographic attributes
and land-use systems along a 15-km transect using principal component analysis, and (ii) describe the
spatial continuum of Ksat across the transect through co-regionalization with autoregressive state-space models.
The transect was established in the Fragata River Watershed (FRW), Southern Brazil. One hundred soil sampling
points were distributed along the transect at equal distances (150 m). Clay and sand fractions, soil organic
carbon content, soil bulk density, soil macroporosity, Ksat, and the soil water retention curve were determined
for the 0–20 cm layer at each point. Topographic attributes were derived from the digital elevation model and a
land-use map was derived from satellite images. The highest and lowest spatial variabilities were exhibited by
Ksat and soil organic carbon content, respectively. Applying the state-space approach, spatial relationships
among Ksat and soil and topographic attributes, and land-use systems along the transect, could be found.
Principal component analysis used jointly with state-space showed that macroporosity could be used as a proxy
to estimate the spatial variation of Ksat in the FRW watershed, assessing surface and subsurface runoff potentials
at areas of different land-use. Further studies should be carried out to investigate the use of the type of land-use
system as a soil structural predictor of the spatial variations of Ksat at the watershed scale since it is nowadays an
“easy-to-measure” variable from satellite images. Keywords: Ksat | Soil and topographic attributes | Spatial variability | Land-use system |
مقاله انگلیسی |
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Maize production and environmental costs: Resource evaluation and strategic land use planning for food security in northern Ghana by means of coupled emergy and data envelopment analysis
تولید ذرت و هزینه های زیست محیطی: ارزیابی منابع و برنامه ریزی استراتژیک کاربری اراضی برای امنیت غذایی در شمال غنا با استفاده از تجزیه و تحلیل آمیخته و پوشش داده ها-2020 This paper applies an integrated methodology which is constituted of the following: (i) the Emergy-Data
Envelopment Analysis (EM-DEA), (ii) environmental Cost-Benefit Analysis (CBA), (iii) Value Chain Analysis
(VCA), and (iv) Sustainability Balanced Scorecard (SBSC) approaches, -to support multicriteria decision analysis
(MCDA) for strategic agricultural land use planning, which could contribute to improve food security in northern
Ghana. Five scenarios of land use and resource management practices for maize production were modelled. The
business-as-usual scenario was based on primary data, which were collected using semi-structured questionnaires administered to 56 small-scale maize farmers through personal interviews. The dominant land use was
characterised by an external input ≤12 kg/ha/yr inorganic fertilizer with/without the addition of manure in
rainfed maize systems. The project scenarios were based on APSIM simulations of maize yield response to 0, 20,
50 and 100 kg/ha/yr urea dosages, with/without supplemental irrigation. The scenarios were dubbed as follows:
(1) no/low input systems were denoted by Extensive0, Extensive12, and Intercrop20, and (2) moderate/high input
systems were denoted by Intensive50, and Intensive100. The EM-DEA approach was used to assess the resource
use efficiency (RUE) and sustainability in maize production systems, Ghana. The measured RUE and sustainability were used as a proxy for further analyses by applying the environmental CBA and VCA approaches to
calculate: (a) the environmental costs of producing maize, i.e. resource use measured as total emergy (U), and (b)
benefits from the yielded maize, i.e. (b i) food provision from grain measured in kcal/yr, and (b ii) potential
electricity (bioenergy) which could be generated from residue measured in MWh/yr. The information which was
derived from the applications of the EM-DEA, CBA and VCA approaches was aggregated by applying the SBSC
approach to do a sustainability appraisal of the scenarios. The results show that, when labour and services are
included in the assessment of RUE and sustainability, Intercrop20 and Intensive50 achieved greater marginal
yield, better RUE, sustainability and appraisal score. The same scenarios caused lesser impacts in terms of expansion of area cultivated compared to Extensive0 and Extensive12. Meanwhile the impacts of Intercrop20 and
Intensive50 in terms of ecotoxicity, emissions, and demand for resources (energy, materials, labour and services)
were lesser compared to Intensive100. The implications of the various scenarios are discussed. The environmental
performance of the scenarios are compared to maize production systems in other developing regions in order to
put this study within a broader context. We conclude that, the EM-DEA approach is useful for assessing RUE and
sustainability of agricultural production systems at farm and regional scales, as well as in connecting the
management planning level and regional development considerations. Keywords: Food security | Sustainable agriculture | Strategic land use planning | Emergy-Data envelopment analysis | Environment-biomass-food-energy nexus | Sub-Saharan Africa |
مقاله انگلیسی |
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Assessment of urban land use efficiency in China: A perspective of scaling law
ارزیابی راندمان استفاده از اراضی شهری در چین: چشم انداز قانون مقیاس بندی-2020 In the context of urbanization and sustainable development, efficient urban land use is essential, especially in China, the world’s most populous country. Within this context, the law of urban scaling reveals the nonlinear scale relationship between urban indicators and urban population, which can be applied to adjust the bias of the raw or the per capita indices used in the measurement of local urban performance at different scales. However, the manner in which the urban scaling law applies to China and how it can be used to assess urban land use efficiency (ULUE) is still unclear. In this study, we employ scale-adjusted metropolitan indicators (SAMIs) to assess ULUE in Chinese cities. We first considered the urban population to calculate the land input performance (LIP) and land output performance (LOP), then we quantify ULUE and identify four related patterns. We further investigate the temporal and spatial variations of ULUE and explore the characteristics and policy implications of ULUE values. Results from our study indicate that ULUE assessments from the perspective of the urban scaling law can effectively correct the bias caused by the urban size, thereby allowing for an objective understanding of performance of cities in different sizes. From 2012 to 2016, ULUE of Chinese cities showed a steadily rising trend. The ULUE patterns of most cities remained unchanged and showed significant “path dependence.” However, the disparity in ULUE between regions is widening. Specifically, the cities in the south are better than those in the north, and the cities in the northeast have significantly deteriorated ULUEs. Some cities showed a high ULUE, especially Shenzhen, Hangzhou, and Wuhan. Spatial autocorrelation analysis suggests that geographically neighboring cities are likely to perform similarly regarding ULUE. In terms of policy implications, our work can provide a clear direction for development of cities in urban size and urban efficiency. Keywords: Urban scaling law | Land use efficiency | Land use | Urbanization | Urban | China |
مقاله انگلیسی |
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Projecting land use change impacts on nutrients, sediment and runoff in multiple spatial scales: Business-as-usual vs. stakeholder-informed scenarios
پیش بینی اثرات تغییر کاربری اراضی روی مواد مغذی ، رسوب و رواناب در مقیاس های مکانی مختلف: تجارت معمول در مقابل سناریوهای آگاه از ذینفعان-2020 While the impact of land use/land cover (LULC) change on watersheds has been extensively studied, little
attention has been given to the variability of this impact with respect to the projected LULC scenarios at a
range of spatial scales. Here, a spatial LULC change model was coupled with the Chesapeake Bay
Watershed Model to investigate LULC change impact on nutrients (nitrogen and phosphorous) and
sediment loads and runoff volume in northwestern Virginia, U.S. Using 2011 as the baseline scenario, we
examined four stakeholder-informed future (50 years hence) LULC scenarios, which differed in projection
of population growth and planning strategy, along with a ‘business-as-usual’ (BAU) scenario, which
projected historical LULC trends into the future. Four LULCsdDeveloped, Forest, Grasses and
Cropsdwere dynamically transitioned. The difference in projected nutrient and sediment loads and
runoff volume between the LULC scenarios was greater at finer spatial scales, where planning decisions
are most commonly made. The LULC change scenario with reactive planning and high population growth
resulted in the largest increase in runoff volume, while the scenario with reactive planning and low
population growth showed the largest increase in modeled nutrient and sediment loads. These results
suggested that planning strategy plays a more critical role than population growth in watershed
management. Keywords: Land use/land cover change | Watershed modeling | Nutrient and sediment pollution | Surface runoff |
مقاله انگلیسی |
7 |
Soil quality should be accurate evaluated at the beginning of lifecycle after land consolidation for eco-sustainable development on the Loess Plateau
ارزیابی کیفیت خاک در ابتدای چرخه حیات پس از ادغام اراضی برای توسعه سازگار با محیط زیست در فلات لس -2020 Evaluating farmland soil quality and zoning the obstacle factors regions were essential to enhance the
productiveness of cultivated land and adopt sustainable management practices after land reclamation.
The land consolidation project was initiated to reclaim gullies of the Loess Plateau and return them to
farmland. However, soil quality and eco-sustainable improvement strategies of the reclaimed farmland
were still unknown. The primary objective of this research was to assess soil quality, select a suitable
evaluation method and provide precise amendment recommendations for this regions, selecting the
reclaimed farmland of Yan’an city as a case. Indictor values of SOM, CEC, nitrogen, phosphorus, avail -Mn
and -Zn on reclaimed farmland were considered at low level and soil quality was generally poor. A
minimum data set evaluation method selecting by the Norm values is recommended for delineating poor
quality farmland, with the threshold values of soil quality at 0.92. The main limiting factors for reclaimed
farmland were identified as SOM, CEC, nitrogen, NaHCO3-P, and enzyme activities. SOM and nitrogen
content, CEC and clay percentage, and NaHCO3-P concentration were the main limiting factors of soil
quality on the all Yan’an regions, northern and southern areas, respectively, indicating the soil texture
should be improved in the arid areas while the phosphate fertilizer should be accurately applied in the
semi-arid regions. Those approaches will identify areas needing more intense management and improve
utilization of applied amendments. We emphasize the spatial distribution of limiting factors was uneven
on the Loess Plateau regions and the particular attention should be paid on specialized soil quality
evaluation of targeted regions for precise amendment and utilization. The results of this study are
important at the practices for avoiding the traditional unsustainable and inaccurately fertilization
strategy. Keywords: Land consolidation | Soil quality index | Land use | Life cycle assessment | Loess plateau |
مقاله انگلیسی |
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Ecological and environmental consequences of ecological projects in the Beijing–Tianjin sand source region
پیامدهای محیطی و زیست محیطی از پروژه های زیست محیطی در منطقه منبع شن و ماسه پکن - تیانجین-2020 Evaluation of influences of the Beijing–Tianjin Sand Source Control Project on soil wind erosion and ecosystem
services is imperative for mastering the benefits and drawbacks of the program, as well as for distinguishing
more reasonable estimations to evaluate regional sustainable development. Within the Beijing–Tianjin Sand
Source Region, we quantified the spatiotemporal patterns of land use/cover changes (LUCCs), soil wind erosion
modulus (SWEM), and essential ecosystem services throughout 2000–2015 by utilizing field investigations,
remotely sensed data, meteorological data, and modeling. The influences of ecological projects on wind erosion
and ecosystem services has been subsequently assessed by using those modifications brought on via the LUCCs
(e.g., conversion from cropland to grassland/woodland) during the ecological construction. The results indicated
that the SWEM showed a decline and ecosystem services which included carbon storage, water retention, and air
quality regulation exhibited growth driven by using both local climate exchanges and human activities such as
ecological projects. Excluding the effects of climate factors, the LUCCs stemming from ecological projects caused
a total SWEM decrease of 3.77 million tons during 2000–2015, of which approximately 70% was prompted by
the way of the transition from desert to sparse grassland. And from this transition, ecosystem services including
both water retention and aboveground net primary productivity manifest a general increase. The sub-regions of
desert grassland in Bayannur, Ordos Sandy Land, and Otindag Sandy Land were hot spots for wind erosion
declines and ecosystem service enhancements induced by the ecological projects. We recommend that endeavors
be coordinated toward the scientific management of the degraded lands and distribution of the local populace, as
well as the implementation of diverse measures in the expected hotter and drier future. Keywords: Wind erosion Ecosystem services | Sustainability | Spatiotemporal pattern | Land use/cover change | Ecological project |
مقاله انگلیسی |
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Mapping spatio-temporal patterns and detecting the factors of traffic congestion with multi-source data fusion and mining techniques
نقشه برداری از الگوهای مکانی-زمانی و تشخیص عوامل ازدحام ترافیک با تکنیک های تلفیق داده ها و استخراج داده های چند منبع-2019 The study focuses on mapping spatiotemporal patterns and detecting the potential drivers of traffic congestion
with multi-source data. First, based on real-time traffic data retrieved from an online map, the k-means clustering
algorithm was applied to classify the spatiotemporal distribution of congested roads. Then, we applied a
geographical detector (Geo-detector) to mine the potential factors for each spatiotemporal pattern. The results
showed six congestion patterns for intra-regional roads and inter-regional roads on weekdays. On both intraregional
and inter-regional roads, congestion density reflected by building height was the strongest indicator
during the morning peak period. Public facilities such as hospitals, tourist sites and green spaces located near
areas of employment or residential areas contributed to congestion during and off-peak hours. On intra-regional
roads, the sparse road network and greater distance from the city center contribute to congestion during peak
hours. On inter-regional roads, the number of bus stops contributed most to the early evening peak congestion,
while the design of the entrances to large buildings in mixed business areas and public service areas increased
the level of congestion. The results suggest that land use should be more mixed in high-density areas as this
would reduce the number of trips made to the city center. However, mixed land-use planning should also be
combined with a detailed design of the microenvironment to improve accessibility for different travel modes in
order to increase the efficiency of traffic and reduce congestion. The innovative approach can be potentially
applied in traffic congestion and land use planning studies elsewhere based on real-time multi-source data. Keywords: Traffic congestion | Land use | Spatiotemporal pattern | Multi-source data |
مقاله انگلیسی |
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Mapping sugarcane in complex landscapes by integrating multi-temporal Sentinel-2 images and machine learning algorithms
نقشه برداری نیشکر در مناظر پیچیده با ادغام تصاویر چند زمانه Sentinel-2 و الگوریتم های یادگیری ماشین-2019 Sugarcane is an important type of cash crop and plays a crucial role in global sugar production. Clarifying the
magnitude of sugarcane planting will likely provide very evident supports for local land use management and
policy-making. However, sugarcane growth environment in complex landscapes with frequent rainy weather
conditions poses many challenges for its rapid mapping. This study thus tried and used 10-m Sentinel-2 images
as well as crop phenology information to map sugarcane in Longzhou county of China in 2018. To minimize the
influences of cloudy and rainy conditions, this study firstly fused all available images in each phenology stage to
obtain cloud-free remote sensing images of three phenology stage (seedling, elongation and harvest) with the
help of Google Earth Engine platform. Then, the study used the fused images to compute the normalized difference
vegetation index (NDVI) of each stage. A three-band NDVI dataset along with 4000 training samples and
2000 random validation samples was finally used for sugarcane mapping. To assess the robustness of the threeband
NDVI dataset with phenological characteristics for sugarcane mapping, this study employed five classifiers
based on machine learning algorithms, including two support vector machine classifiers (Polynomial-SVM and
RBF-SVM), a random forest classifier (RF), an artificial neural network classifier (ANN) and a decision tree
classifier (CART-DT). Results showed that except for ANN classifier, Polynomial-SVM, RBF-SVM, RF and CARTDT
classifiers displayed high accuracy sugarcane resultant maps with producer’s and user’s accuracies of greater
than 91%. The ANN classifier tended to overestimate area of sugarcane and underestimate area of forests.
Overall performances of five classifiers suggest Polynomial-SVM has the best potential to improve sugarcane
mapping at the regional scale. Also, this study observed that most sugarcane (more than 75% of entire study
area) tends to grow in flat regions with slope of less than 10°. This study emphasizes the importance of considering
phenology in rapid sugarcane mapping, and suggests the potential of fine-resolution Sentinel-2 images
and machine learning approaches in high-accuracy land use management and decision-making. Keywords: Crop phenology | Sentinel-2 images | Machine learning approach | Sugarcane mapping | Land use |
مقاله انگلیسی |