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Frontiers of Earth Science

, Volume 12 Issue 2

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Trip-oriented travel time prediction (TOTTP) with historical vehicle trajectories
Tao XU, Xiang LI, Christophe CLARAMUNT
Front. Earth Sci.. 2018, 12 (2): 253-263.
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Accurate travel time prediction is undoubtedly of importance to both traffic managers and travelers. In highly-urbanized areas, trip-oriented travel time prediction (TOTTP) is valuable to travelers rather than traffic managers as the former usually expect to know the travel time of a trip which may cross over multiple road sections. There are two obstacles to the development of TOTTP, including traffic complexity and traffic data coverage. With large scale historical vehicle trajectory data and meteorology data, this research develops a BPNN-based approach through integrating multiple factors affecting trip travel time into a BPNN model to predict trip-oriented travel time for OD pairs in urban network. Results of experiments demonstrate that it helps discover the dominate trends of travel time changes daily and weekly, and the impact of weather conditions is non-trivial.

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Mapping of wind energy potential over the Gobi Desert in Northwest China based on multiple sources of data
Li LI, Xinyuan WANG, Lei LUO, Yanchuang ZHAO, Xin ZONG, Nabil BACHAGHA
Front. Earth Sci.. 2018, 12 (2): 264-279.
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In recent years, wind energy has been a fast-growing alternative source of electrical power due to its sustainability. In this paper, the wind energy potential over the Gobi Desert in Northwest China is assessed at the patch scale using geographic information systems (GIS). Data on land cover, topography, and administrative boundaries and 11 years (2000–2010) of wind speed measurements were collected and used to map and estimate the region’s wind energy potential. Based on the results, it was found that continuous regions of geographical potential (GeoP) are located in the middle of the research area (RA), with scattered areas of similar GeoP found in other regions. The results also show that the technical potential (TecP) levels are about 1.72–2.67 times (2.20 times on average) higher than the actual levels. It was found that the GeoP patches can be divided into four classes: unsuitable regions, suitable regions, more suitable regions, and the most suitable regions. The GeoP estimation shows that 0.41 billion kW of wind energy are potentially available in the RA. The suitable regions account for 25.49%, the more suitable regions 24.45%, and the most suitable regions for more than half of the RA. It is also shown that Xinjiang and Gansu are more suitable for wind power development than Ningxia.

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Data fusion in data scarce areas using a back-propagation artificial neural network model: a case study of the South China Sea
Zheng WANG, Zhihua MAO, Junshi XIA, Peijun DU, Liangliang SHI, Haiqing HUANG, Tianyu WANG, Fang GONG, Qiankun ZHU
Front. Earth Sci.. 2018, 12 (2): 280-298.
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The cloud cover for the South China Sea and its coastal area is relatively large throughout the year, which limits the potential application of optical remote sensing. A HJ-charge-coupled device (HJ-CCD) has the advantages of wide field, high temporal resolution, and short repeat cycle. However, this instrument suffers from its use of only four relatively low-quality bands which can’t adequately resolve the features of long wavelengths. The Landsat Enhanced Thematic Mapper-plus (ETM+) provides high-quality data, however, the Scan Line Corrector (SLC) stopped working and caused striping of remote sensed images, which dramatically reduced the coverage of the ETM+ data. In order to combine the advantages of the HJ-CCD and Landsat ETM+ data, we adopted a back-propagation artificial neural network (BP-ANN) to fuse these two data types for this study. The results showed that the fused output data not only have the advantage of data intactness for the HJ-CCD, but also have the advantages of the multi-spectral and high radiometric resolution of the ETM+ data. Moreover, the fused data were analyzed qualitatively, quantitatively and from a practical application point of view. Experimental studies indicated that the fused data have a full spatial distribution, multi-spectral bands, high radiometric resolution, a small difference between the observed and fused output data, and a high correlation between the observed and fused data. The excellent performance in its practical application is a further demonstration that the fused data are of high quality.

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Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China
Zhixiong MEI, Hao WU, Shiyun LI
Front. Earth Sci.. 2018, 12 (2): 299-310.
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The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NE-logistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001–2009 and 2005–2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009–2020. Apparent differences also existed in the simulated change sizes and locations of each land-use type under different scenarios. The results not only demonstrate the validity of the improved model but also provide a valuable reference for relevant policy-makers.

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Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models
Bilaşco ŞTEFAN, Roşca SANDA, Fodorean IOAN, Vescan IULIU, Filip SORIN, Petrea DĂNUŢ
Front. Earth Sci.. 2018, 12 (2): 311-324.
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Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes – landslides and soil erosion – which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

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New insights into the origin of the bimodal volcanism in the middle Okinawa Trough: not a basalt-rhyolite differentiation process
Yuxiang ZHANG, Zhigang ZENG, Shuai CHEN, Xiaoyuan WANG, Xuebo YIN
Front. Earth Sci.. 2018, 12 (2): 325-338.
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In the middle Okinawa Trough (MOT), rhyolites have been typically considered as products of crystallization differentiation of basaltic magma as a feature of bimodal volcanism. However, the evidence is insufficient. This paper compared chemical trends of volcanic rocks from the MOT with fractional crystallization simulation models and experimental results and utilized trace element modeling combined with Rayleigh fractionation calculations to re-examine fractional crystallization processes in generating rhyolites. Both qualitative and quantitative studies indicate that andesites, rather than rhyolites, originate by fractional crystallization from basalts in the MOT. Furthermore, we established two batch-melting models for the MOT rhyolites and proposed that type 1 rhyolites are produced by remelting of andesites with amphiboles in the residue, while type 2 rhyolites are derived from remelting of andesites without residual amphiboles. It is difficult to produce melts with a SiO2 content ranging from 62% to 68% either by magmatic differentiation from basalts or by remelting of andesites, and this difficulty might help account for the compositional gap (Daly gap) for bimodal volcanism in the Okinawa Trough.

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Effect of reclamation on soil organic carbon pools in coastal areas of eastern China
Jianguo LI, Wenhui YANG, Qiang LI, Lijie PU, Yan XU, Zhongqi ZHANG, Lili LIU
Front. Earth Sci.. 2018, 12 (2): 339-348.
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The coastal wetlands of eastern China form one of the most important carbon sinks in the world. However, reclamation can significantly alter the soil carbon pool dynamics in these areas. In this study, a chronosequence was constructed for four reclamation zones in Rudong County, Jiangsu Province, eastern China (reclaimed in 1951, 1974, 1982, and 2007) and a reference salt marsh to identify both the process of soil organic carbon (SOC) evolution, as well as the effect of cropping and soil properties on SOC with time after reclamation. The results show that whereas soil nutrient elements and SOC increased after reclamation, the electrical conductivity of the saturated soil extract (ECe), pH, and bulk density decreased within 62 years following reclamation and agricultural amendment. In general, the soil’s chemical properties remarkably improved and SOC increased significantly for approximately 30 years after reclamation. Reclamation for agriculture (rice and cotton) significantly increased the soil organic carbon density (SOCD) in the top 60 cm, especially in the top 0–30 cm. However, whereas the highest concentration of SOCD in rice-growing areas was in the top 0–20 cm of the soil profile, it was greater at a 20–60 cm depth in cotton-growing areas. Reclamation also significantly increased heavy fraction organic carbon (HFOC) levels in the 0–30 cm layer, thereby enhancing the stability of the soil carbon pool. SOC can thus increase significantly over a long time period after coastal reclamation, especially in areas of cultivation, where coastal SOC pools in eastern China tend to be more stable.

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Spatial and temporal correlation between beach and wave processes: implications for bar–berm sediment transition
Front. Earth Sci.. 2018, 12 (2): 349-360.
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Investigation of a beach and its wave conditions is highly requisite for understanding the physical processes in a coast. This study composes spatial and temporal correlation between beach and nearshore processes along the extensive sandy beach of Nagapattinam coast, southeast peninsular India. The data collection includes beach profile, wave data, and intertidal sediment samples for 2 years from January 2011 to January 2013. The field data revealed significant variability in beach and wave morphology during the northeast (NE) and southwest (SW) monsoon. However, the beach has been stabilized by the reworking of sediment distribution during the calm period. The changes in grain sorting and longshore sediment transport serve as a clear evidence of the sediment migration that persevered between foreshore and nearshore regions. The Empirical Orthogonal Function (EOF) analysis and Canonical Correlation Analysis (CCA) were utilized to investigate the spatial and temporal linkages between beach and nearshore criterions. The outcome of the multivariate analysis unveiled that the seasonal variations in the wave climate tends to influence the bar – berm sediment transition that is discerned in the coast.

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Exploring the heavy air pollution in Beijing in the fourth quarter of 2015: assessment of environmental benefits for red alerts
Teng NIE, Lei NIE, Zhen ZHOU, Zhanshan WANG, Yifeng XUE, Jiajia GAO, Xiaoqing WU, Shoubin FAN, Linglong CHENG
Front. Earth Sci.. 2018, 12 (2): 361-372.
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In recent years, Beijing has experienced severe air pollution which has caused widespread public concern. Compared to the same period in 2014, the first three quarters of 2015 exhibited significantly improved air quality. However, the air quality sharply declined in the fourth quarter of 2015, especially in November and December. During that time, Beijing issued the first red alert for severe air pollution in history. In total, 2 red alerts, 3 orange alerts, 3 yellow alerts, and 3 blue alerts were issued based on the adoption of relatively temporary emergency control measures to mitigate air pollution. This study explored the reasons for these variations in air quality and assessed the effectiveness of emergency alerts in addressing severe air pollution. A synthetic analysis of emission variations and meteorological conditions was performed to better understand these extreme air pollution episodes in the fourth quarter of 2015. The results showed that compared to those in the same period in 2014, the daily average emissions of air pollutants decreased in the fourth quarter of 2015. However, the emission levels of primary pollutants were still relatively high, which was the main intrinsic cause of haze episodes, and unfavorable meteorological conditions represented important external factors. Emergency control measures for heavy air pollution were implemented during this red alert period, decreasing the emissions of primary air pollutants by approximately 36% and the PM2.5 concentration by 11%?21%.

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On the classification of mixed floating pollutants on the Yellow Sea of China by using a quad-polarized SAR image
Xiaochen WANG, Yun SHAO, Wei TIAN, Kun LI
Front. Earth Sci.. 2018, 12 (2): 373-380.
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This study explored different methodologies using a C-band RADARSAT-2 quad-polarized Synthetic Aperture Radar (SAR) image located over China’s Yellow Sea to investigate polarization decomposition parameters for identifying mixed floating pollutants from a complex ocean background. It was found that solitary polarization decomposition did not meet the demand for detecting and classifying multiple floating pollutants, even after applying a polarized SAR image. Furthermore, considering that Yamaguchi decomposition is sensitive to vegetation and the algal variety Enteromorpha prolifera, while H/A/alpha decomposition is sensitive to oil spills, a combination of parameters which was deduced from these two decompositions was proposed for marine environmental monitoring of mixed floating sea surface pollutants. A combination of volume scattering, surface scattering, and scattering entropy was the best indicator for classifying mixed floating pollutants from a complex ocean background. The Kappa coefficients for Enteromorpha prolifera and oil spills were 0.7514 and 0.8470, respectively, evidence that the composite polarized parameters based on quad-polarized SAR imagery proposed in this research is an effective monitoring method for complex marine pollution.

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Analysis of three echo-trainings of a rainstorm in the South China warm region
Zhiying DING, Lei QIAN, Xiangjun ZHAO, Fan XIA
Front. Earth Sci.. 2018, 12 (2): 381-396.
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A rainstorm which occurred between May 22 and 23, 2014 in Guangdong Province of the South China warm region was simulated by using the ARW-WRF model. Three “echo-trainings” over the rainstorm center were analyzed and the results of both the simulation and observational analysis showed that this rainstorm process was composed of three stages. In the first stage, gravity waves triggered the simultaneous but relatively independent formation of linear convection and convective cells, which moved toward the northeast through the rain center, thus creating the echo-training. In the second stage, with the formation of cold outflow, new convective cells were continuously created in the southwest and northwest of the rain area and then gradually moved to merge into the northeast rain area, thus forming a new echo-training. In the third stage, multiple rain bands above the rain area moved southeastward and passed through the strongest precipitation center, thus creating the third echo-training. The model simulation showed that a substantial warming appeared at 900 hPa before the convective initiation, leading to the formation of a stable layer below 900 hPa, which was the primary cause for the gravity waves that triggered the multiple convective cells. The multiple convective cells formed the convective line, following which new convection was formed from the cold outflow in its southwest and northwest directions. The new convection in the southwest maintained the rain band; however, the new convection in the northwest, combined with the rain band of the north, formed a large radar reflectivity area and consequently, a larger MCS.

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Speciation, sources, and risk assessment of heavy metals in suburban vegetable garden soil in Xianyang City, Northwest China
Lijun WANG, Wendong TAO, Richard C. SMARDON, Xue XU, Xinwei LU
Front. Earth Sci.. 2018, 12 (2): 397-407.
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Intensive anthropogenic activities can lead to soil heavy metal contamination resulting in potential risks to the environment and to human health. To reveal the concentrations, speciation, sources, pollution level, and ecological risk of heavy metals in vegetable garden soil, a total of 136 soil samples were collected from three vegetable production fields in the suburbs of Xianyang City, Northwest China. These samples were analyzed by inductively coupled plasma- atomic emission spectrometry and atomic fluorescence spectrometry. The results showed that the mean concentrations of Cd, Co, Cu, Mn, Pb, Zn, and Hg in vegetable garden soil were higher than the corresponding soil element background values of Shaanxi Province. The heavy metals studied in vegetable garden soil were primarily found in the residual fraction, averaging from 31.26% (Pb) to 90.23% (Cr). Considering the non-residual fractions, the mobility or potential risk was in the order of Pb (68.74%)>Co (60.54%)>Mn (59.28%)>Cd (53.54%)>>Ni (23.36%)>Zn (22.73%)>Cu (14.93%)>V (11.81%)>Cr (9.78%). Cr, Mn, Ni, V, and As in the studied soil were related to soil-forming parent materials, while Cu, Hg, Zn, Cd, Co, and Pb were associated with the application of plastic films, fertilizers, and pesticides, as well as traffic emissions and industrial fumes. Cr, Ni, V, and As presented low contamination levels, whereas Co, Cu, Mn, Pb, and Zn levels were moderate, and Cd and Hg were high. Ecological risk was low for Co, Cr, Cu, Mn, Pb, Zn, and As, with high risk observed for Cd and Hg. The overall pollution level and ecological risk of these heavy metals were high.

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Diverse effects of crop distribution and climate change on crop production in the agro-pastoral transitional zone of China
Jianmin QIAO, Deyong YU, Qianfeng WANG, Yupeng LIU
Front. Earth Sci.. 2018, 12 (2): 408-419.
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Both crop distribution and climate change are important drivers for crop production and can affect food security, which is an important requirement for sustainable development. However, their effects on crop production are confounded and warrant detailed investigation. As a key area for food production that is sensitive to climate change, the agro-pastoral transitional zone (APTZ) plays a significant role in regional food security. To investigate the respective effects of crop distribution and climate change on crop production, the well-established GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted with different scenario designs in this study. From 1980 to 2010, the crop distribution for wheat, maize, and rice witnessed a dramatic change due to agricultural policy adjustments and ecological engineering-related construction in the APTZ. At the same time, notable climate change was observed. The simulation results indicated that the climate change had a positive impact on the crop production of wheat, maize, and rice, while the crop distribution change led to an increase in the production of maize and rice, but a decrease in the wheat production. Comparatively, crop distribution change had a larger impact on wheat (−1.71 × 106 t) and maize (8.53 × 106 t) production, whereas climate change exerted a greater effect on rice production (0.58 × 106 t), during the period from 1980 to 2010 in the APTZ. This study is helpful to understand the mechanism of the effects of crop distribution and climate change on crop production, and aid policy makers in reducing the threat of future food insecurity.

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ICESat/GLAS-derived changes in the water level of Hulun Lake, Inner Mongolia, from 2003 to 2009
Chunlan LI, Jun WANG, Richa HU, Shan YIN, Yuhai BAO, Yuwei LI
Front. Earth Sci.. 2018, 12 (2): 420-430.
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Hulun Lake is the largest freshwater lake in northern Inner Mongolia and even minor changes in its level may have major effects on the ecology of the lake and the surrounding area. In this study, we used high-precision elevation data for the interval from 2003–2009 measured by the Geoscience Laser Altimetry System (GLAS) on board the Ice, Cloud, and land Elevation Satellite (ICESat) to assess annual and seasonal water level variations of Hulun Lake. The altimetry data of 32 satellite tracks were processed using the RANdom SAmple Consensus algorithm (RANSAC) to eliminate elevation outliers, and subsequently the Normalized Difference Water Index (NDWI) was used to delineate the area of the lake. From 2003–2009, the shoreline of Hulun Lake retreated westwards, which was especially notable in the southern part of the lake. There was only a small decrease in water level, from 530.72 m to 529.22 m during 2003–2009, an average rate of 0.08 m/yr. The area of the lake decreased at a rate of 49.52 km2/yr, which was mainly the result of the shallow bathymetry in the southern part of the basin. The decrease in area was initially rapid, then much slower, and finally rapid again. Generally, the lake extent and water level decreased due to higher temperatures, intense evaporation, low precipitation, and decreasing runoff. And their fluctuations were caused by a decrease in intra-annual temperature, evaporation, and a slight increase in precipitation. Overall, a combination of factors related to climate change were responsible for the variations of the water level of Hulun Lake during the study interval. The results improve our understanding of the impact of climate change on Hulun Lake and may facilitate the formulation of response strategies.

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Scale characters analysis for gully structure in the watersheds of loess landforms based on digital elevation models
Hongchun ZHU, Yipeng ZHAO, Haiying LIU
Front. Earth Sci.. 2018, 12 (2): 431-443.
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Scale is the basic attribute for expressing and describing spatial entity and phenomena. It offers theoretical significance in the study of gully structure information, variable characteristics of watershed morphology, and development evolution at different scales. This research selected five different areas in China’s Loess Plateau as the experimental region and used DEM data at different scales as the experimental data. First, the change rule of the characteristic parameters of the data at different scales was analyzed. The watershed structure information did not change along with a change in the data scale. This condition was proven by selecting indices of gully bifurcation ratio and fractal dimension as characteristic parameters of watershed structure information. Then, the change rule of the characteristic parameters of gully structure with different analysis scales was analyzed by setting the scale sequence of analysis at the extraction gully. The gully structure of the watershed changed with variations in the analysis scale, and the change rule was obvious when the gully level changed. Finally, the change rule of the characteristic parameters of the gully structure at different areas was analyzed. The gully fractal dimension showed a significant numerical difference in different areas, whereas the variation of the gully branch ratio was small. The change rule indicated that the development degree of the gully obviously varied in different regions, but the morphological?structure was basically similar.

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Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta
Jicai NING, Zhiqiang GAO, Ran MENG, Fuxiang XU, Meng GAO
Front. Earth Sci.. 2018, 12 (2): 444-456.
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This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

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