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Chaobin Yang
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

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Journal article
Published: 09 August 2021 in Remote Sensing
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Urban parks have been proven to cool the surrounding environment, and can thus mitigate the urban heat island to an extent by forming a park cooling island. However, a comprehensive understanding of the mechanism of park cooling islands is still required. Therefore, we studied 32 urban parks in Jinan, China and proposed absolute and relative indicators to depict the detailed features of the park cooling island. High-spatial-resolution GF-2 images were used to obtain the land cover of parks, and Landsat 8 TIR images were used to examine the thermal environment by applying buffer analysis. Linear statistical models were developed to explore the relationships between park characteristics and the park cooling island. The results showed that the average land surface temperature (LST) of urban parks was approximately 3.6 °C lower than that of the study area, with the largest temperature difference of 7.84 °C occurring during summer daytime, while the average park cooling area was approximately 120.68 ha. The park cooling island could be classified into four categories—regular, declined, increased, and others—based on the changing features of the surrounding LSTs. Park area (PA), park perimeter (PP), water area proportion (WAP), and park shape index (PSI) were significantly negatively correlated with the park LST. We also found that WAP, PP, and greenness (characterized by the normalized difference vegetation index (NDVI)) were three important factors that determined the park cooling island. However, the relationship between PA and the park cooling island was complex, as the results indicated that only parks larger than a threshold size (20 ha in our study) would provide a larger cooling effect with the increase in park size. In this case, increasing the NDVI of the parks by planting more vegetation would be a more sustainable and effective solution to form a stronger park cooling island.

ACS Style

Wenhao Zhu; Jiabin Sun; Chaobin Yang; Min Liu; Xinliang Xu; Caoxiang Ji. How to Measure the Urban Park Cooling Island? A Perspective of Absolute and Relative Indicators Using Remote Sensing and Buffer Analysis. Remote Sensing 2021, 13, 3154 .

AMA Style

Wenhao Zhu, Jiabin Sun, Chaobin Yang, Min Liu, Xinliang Xu, Caoxiang Ji. How to Measure the Urban Park Cooling Island? A Perspective of Absolute and Relative Indicators Using Remote Sensing and Buffer Analysis. Remote Sensing. 2021; 13 (16):3154.

Chicago/Turabian Style

Wenhao Zhu; Jiabin Sun; Chaobin Yang; Min Liu; Xinliang Xu; Caoxiang Ji. 2021. "How to Measure the Urban Park Cooling Island? A Perspective of Absolute and Relative Indicators Using Remote Sensing and Buffer Analysis." Remote Sensing 13, no. 16: 3154.

Journal article
Published: 15 September 2020 in Remote Sensing
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Land surface temperature (LST) is a crucial parameter in surface urban heat island (SUHI) studies. A better understanding of the driving mechanisms, influencing variations in LST dynamics, is required for the sustainable development of a city. This study used Changchun, a city in northeast China, as an example, to investigate the seasonal effects of different dominant driving factors on the spatial patterns of LST. Twelve Landsat 8 images were used to retrieve monthly LST, to characterize the urban thermal environment, and spectral mixture analysis was employed to estimate the effect of the driving factors, and correlation and linear regression analyses were used to explore their relationships. Results indicate that, (1) the spatial pattern of LST has dramatic monthly and seasonal changes. August has the highest mean LST of 38.11 °C, whereas December has the lowest (−19.12 °C). The ranking of SUHI intensity is as follows: summer (4.89 °C) > winter with snow cover (1.94 °C) > spring (1.16 °C) > autumn (0.89 °C) > winter without snow cover (−1.24 °C). (2) The effects of driving factors also have seasonal variations. The proportion of impervious surface area (ISA) in summer (49.01%) is slightly lower than those in spring (56.64%) and autumn (50.85%). Almost half of the area is covered with snow (43.48%) in winter. (3) The dominant factors are quite different for different seasons. LST possesses a positive relationship with ISA for all seasons and has the highest Pearson coefficient for summer (r = 0.89). For winter, the effect of vegetation on LST is not obvious, and snow becomes the dominant driving factor. Despite its small area proportion, water has the strongest cooling effect from spring to autumn, and has a warming effect in winter. (4) Human activities, such as agricultural burning, harvest, and different choices of crop species, could also affect the spatial patterns of LST.

ACS Style

Chaobin Yang; Fengqin Yan; Xuelei Lei; Xiuli Ding; Yue Zheng; Lifeng Liu; Shuwen Zhang. Investigating Seasonal Effects of Dominant Driving Factors on Urban Land Surface Temperature in a Snow-Climate City in China. Remote Sensing 2020, 12, 3006 .

AMA Style

Chaobin Yang, Fengqin Yan, Xuelei Lei, Xiuli Ding, Yue Zheng, Lifeng Liu, Shuwen Zhang. Investigating Seasonal Effects of Dominant Driving Factors on Urban Land Surface Temperature in a Snow-Climate City in China. Remote Sensing. 2020; 12 (18):3006.

Chicago/Turabian Style

Chaobin Yang; Fengqin Yan; Xuelei Lei; Xiuli Ding; Yue Zheng; Lifeng Liu; Shuwen Zhang. 2020. "Investigating Seasonal Effects of Dominant Driving Factors on Urban Land Surface Temperature in a Snow-Climate City in China." Remote Sensing 12, no. 18: 3006.

Journal article
Published: 09 April 2020 in Journal of Environmental Management
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The urban heat island (UHI) effect is an increasingly consequential problem that confronts cities. The accurate characterization and quantification of UHI are crucial for sustainable urban development. Few UHI studies, however, compare data source, spatio-temporal variations, and indicators for the same city in parallel. This study uses Changchun, a snow climate city in China, as an example and compares five different indicators of the UHI based on land surface temperature (LST) derived from Landsat 8 TIRS and hourly air temperature (AT) collected from 41 meteorological weather stations to conduct a more comprehensive comparative study of the UHI. The results show the following. (1) The relationships between LST and AT are all statistically significant, and the surface urban heat island (SUHI) intensity characterized by the LST is considerably stronger than that of AT both in summer and winter. (2) The SUHI intensity is significantly stronger in summer (6.83 °C) than in winter (1.55 °C) based on the morning LST, whereas the UHI intensity (0.27 °C in summer and 0.40 °C in winter) that is simultaneously quantified by the AT has an opposite result. The mean whole-day and daytime UHI intensity difference, which is quantified hourly by the AT between summer and winter, is not significant. The difference between nighttime and daytime UHI intensities is evident in both summer (1.26 °C) and winter (0.76 °C). Additionally, the high temperatures for both LST and AT have a more concentrated distribution in winter than in summer. (3) The values of UHI/SUHI intensity considerably vary based on different indicators. The different choices among land covers to represent “urban” and “rural” areas would significantly affect the values of UHI/SUHI intensity. The selection of appropriate indicators and data sources to quantify the UHI remains a problem that has to be resolved in future studies.

ACS Style

Chaobin Yang; Fengqin Yan; Shuwen Zhang. Comparison of land surface and air temperatures for quantifying summer and winter urban heat island in a snow climate city. Journal of Environmental Management 2020, 265, 110563 .

AMA Style

Chaobin Yang, Fengqin Yan, Shuwen Zhang. Comparison of land surface and air temperatures for quantifying summer and winter urban heat island in a snow climate city. Journal of Environmental Management. 2020; 265 ():110563.

Chicago/Turabian Style

Chaobin Yang; Fengqin Yan; Shuwen Zhang. 2020. "Comparison of land surface and air temperatures for quantifying summer and winter urban heat island in a snow climate city." Journal of Environmental Management 265, no. : 110563.

Journal article
Published: 01 March 2018 in Remote Sensing
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Over the last six decades, paddy fields on the Sanjiang Plain have experienced rapid expansion and aggregation. In our study, land use and land cover changes related to paddy fields were studied based on information acquired from topographic maps and remote-sensing images. Paddy field expansion and aggregation were investigated through landscape indices and trajectory codes. Furthermore, the possible causes of paddy field expansion and aggregation were explored. Results indicated that such fields have increased by approximately 42,704 ha·y−1 over the past six decades. Approximately 98% of paddy fields in 2015 were converted from other land use types. In general, the gravity center moved 254.51 km toward the northeast, at a rate of approximately 4.17 km·y−1. The cohesion index increased from 96.8208 in 1954 to 99.5656 in 2015, and the aggregation index grew from 91.3533 in 1954 to 93.4448 in 2015, indicating the apparent aggregation of paddy fields on the Sanjiang Plain. Trajectory analyses showed that the transformations from marsh as well as from grassland to dry farmland and then into paddy fields were predominant. Climate warming provided a favorable environment for rice planting. Meanwhile, population growth, technological progress, and government policies drove paddy field expansion and aggregation during the study period.

ACS Style

Fengqin Yan; Lingxue Yu; Chaobin Yang; Shuwen Zhang. Paddy Field Expansion and Aggregation Since the Mid-1950s in a Cold Region and Its Possible Causes. Remote Sensing 2018, 10, 384 .

AMA Style

Fengqin Yan, Lingxue Yu, Chaobin Yang, Shuwen Zhang. Paddy Field Expansion and Aggregation Since the Mid-1950s in a Cold Region and Its Possible Causes. Remote Sensing. 2018; 10 (3):384.

Chicago/Turabian Style

Fengqin Yan; Lingxue Yu; Chaobin Yang; Shuwen Zhang. 2018. "Paddy Field Expansion and Aggregation Since the Mid-1950s in a Cold Region and Its Possible Causes." Remote Sensing 10, no. 3: 384.

Journal article
Published: 19 October 2017 in Remote Sensing
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Urban parks have been shown to form park cool islands (PCIs), which can effectively alleviate the negative influences of urban heat islands (UHI). However, few studies have examined the detailed characteristics of PCIs, the effect of urban park features on their individual temperatures, and monthly variation in PCIs. Land surface temperature (LST) retrieved from Landsat 8 TIR images between May and October were used to represent the thermal environment. Urban park characteristics were extracted from high-resolution GF-2 images. Using these datasets, the relationships between urban park characteristics and PCIs were explored in this study using Changchun, which has a snow climate, as a case study. The results showed the following: (1) the urban parks exhibited a cooling island effect, and the PCIs showed significant monthly variations with the highest intensities in the hot months; (2) the effects of composition (e.g., park size and the percentage of water area) on LSTs and PCIs showed significant monthly variability and were stronger than the configuration effects. Furthermore, an unexpected, negative correlation between PCIs and the area of park grass was also found; and (3) larger parks tended to have stronger PCI intensities and extents of influence. For parks larger than 30 ha, the cooling effects extended approximately 480 m from the park edge between June and August. For all of parks during the study duration, the rate of temperature increase was highest within 60 m from the park edge. The PCI we employ specifically in this study is characterized by LST.

ACS Style

Chaobin Yang; Xingyuan He; Lingxue Yu; Jiuchun Yang; Fengqin Yan; Kun Bu; Liping Chang; Shuwen Zhang. The Cooling Effect of Urban Parks and Its Monthly Variations in a Snow Climate City. Remote Sensing 2017, 9, 1066 .

AMA Style

Chaobin Yang, Xingyuan He, Lingxue Yu, Jiuchun Yang, Fengqin Yan, Kun Bu, Liping Chang, Shuwen Zhang. The Cooling Effect of Urban Parks and Its Monthly Variations in a Snow Climate City. Remote Sensing. 2017; 9 (10):1066.

Chicago/Turabian Style

Chaobin Yang; Xingyuan He; Lingxue Yu; Jiuchun Yang; Fengqin Yan; Kun Bu; Liping Chang; Shuwen Zhang. 2017. "The Cooling Effect of Urban Parks and Its Monthly Variations in a Snow Climate City." Remote Sensing 9, no. 10: 1066.

Journal article
Published: 01 July 2017 in Ecological Engineering
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ACS Style

Fengqin Yan; Shuwen Zhang; Xingtu Liu; Lingxue Yu; Dan Chen; Jiuchun Yang; Chaobin Yang; Kun Bu; Liping Chang. Monitoring spatiotemporal changes of marshes in the Sanjiang Plain, China. Ecological Engineering 2017, 104, 184 -194.

AMA Style

Fengqin Yan, Shuwen Zhang, Xingtu Liu, Lingxue Yu, Dan Chen, Jiuchun Yang, Chaobin Yang, Kun Bu, Liping Chang. Monitoring spatiotemporal changes of marshes in the Sanjiang Plain, China. Ecological Engineering. 2017; 104 ():184-194.

Chicago/Turabian Style

Fengqin Yan; Shuwen Zhang; Xingtu Liu; Lingxue Yu; Dan Chen; Jiuchun Yang; Chaobin Yang; Kun Bu; Liping Chang. 2017. "Monitoring spatiotemporal changes of marshes in the Sanjiang Plain, China." Ecological Engineering 104, no. : 184-194.

Article
Published: 25 June 2017 in Chinese Geographical Science
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Wetland databases can provide the basic data that necessary for the protection and management of wetlands. A large number of wetland databases have been established in the world as well as in China. In this paper, we review China’s wetland databases based on remote sensing (RS) technology after introducing the background theory to the application of RS technology in wetland surveys. A key conclusion is that China’s wetland databases are far from sufficient in fulfilling protection and management needs. Our recommendations focus on the use of the hyper-spectral imagery, microwave data, multi-temporal images, and automatic classifications in order to improve the accuracy and efficiency of wetland inventory. Further, attention should also be paid to detect major biophysical features of wetlands and build wetland databases in years after the 1980s in China. Considering that great gap exists between RS experts and wetland experts, further cooperation between wetland scientists and RS scientists are needed to promote the application of RS in the foundation of wetland databases.

ACS Style

Fengqin Yan; Xingtu Liu; Jing Chen; Lingxue Yu; Chaobin Yang; Liping Chang; Jiuchun Yang; Shuwen Zhang. China’s wetland databases based on remote sensing technology. Chinese Geographical Science 2017, 27, 374 -388.

AMA Style

Fengqin Yan, Xingtu Liu, Jing Chen, Lingxue Yu, Chaobin Yang, Liping Chang, Jiuchun Yang, Shuwen Zhang. China’s wetland databases based on remote sensing technology. Chinese Geographical Science. 2017; 27 (3):374-388.

Chicago/Turabian Style

Fengqin Yan; Xingtu Liu; Jing Chen; Lingxue Yu; Chaobin Yang; Liping Chang; Jiuchun Yang; Shuwen Zhang. 2017. "China’s wetland databases based on remote sensing technology." Chinese Geographical Science 27, no. 3: 374-388.

Journal article
Published: 02 May 2017 in Forests
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Urban green spaces have been shown to decrease land surface temperature (LST) significantly. However, few studies have explored the relationships between urban green spaces and LST across different seasons at different spatial scales. In this study, using Changchun, China as a case study, landscape ecology and comparative approaches were employed quantitatively to investigate the effects of the composition and configuration of urban green spaces on the urban thermal environments. LST maps were retrieved from Landsat 8 Thermal Infrared Sensor (TIRS) data acquired on four dates that represented four different seasons, and detailed information of urban green spaces was extracted from high resolution imagery GF-1. Normalized differential vegetation index (NDVI) and six landscape metrics at patch, class, and landscape level were used to characterize the spatial patterns of urban green spaces. The results showed that urban green spaces did have significant cooling effects in all seasons, except for winter, but the effects varied considerably across the different seasons and green types, and seemed to depend on the NDVI and size of urban green spaces. Compared to shape metrics, the negative relationships between the LST and the area and the NDVI of urban green spaces were more significant. Both the composition and configuration of urban green spaces can affect the distribution of LST. Based on findings with one city, given a fixed area of urban green spaces, the number of green patches can positively or negatively affect the LST, depending on if the number is larger than a threshold or not, and the threshold varies according to the given area. These findings provide new perspectives, and further research is also suggested, to generate a better understanding of how urban green spaces affect the urban thermal environment.

ACS Style

Chaobin Yang; Xingyuan He; Ranghu Wang; Fengqin Yan; Lingxue Yu; Kun Bu; Jiuchun Yang; Liping Chang; Shuwen Zhang. The Effect of Urban Green Spaces on the Urban Thermal Environment and Its Seasonal Variations. Forests 2017, 8, 153 .

AMA Style

Chaobin Yang, Xingyuan He, Ranghu Wang, Fengqin Yan, Lingxue Yu, Kun Bu, Jiuchun Yang, Liping Chang, Shuwen Zhang. The Effect of Urban Green Spaces on the Urban Thermal Environment and Its Seasonal Variations. Forests. 2017; 8 (5):153.

Chicago/Turabian Style

Chaobin Yang; Xingyuan He; Ranghu Wang; Fengqin Yan; Lingxue Yu; Kun Bu; Jiuchun Yang; Liping Chang; Shuwen Zhang. 2017. "The Effect of Urban Green Spaces on the Urban Thermal Environment and Its Seasonal Variations." Forests 8, no. 5: 153.

Journal article
Published: 20 February 2017 in Sustainability
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The spatio-temporal patterns of land use/land cover changes (LUCC) can significantly affect the distribution and intensity of the urban heat island (UHI) effect. However, few studies have mapped a clear picture of the influence of LUCC on UHI. In this study, both qualitative and quantitative models are employed to explore the effect of LUCC on UHI. UHI and LUCC maps were retrieved from Landsat data acquired from 1984, 1992, 2000, 2007, and 2014 to show their spatiotemporal patterns. The results showed that: (1) both the patterns of LUCC and UHI have had dramatic changes in the past 30 years. The urban area of Changchun increased more than four times, from 143.15 km2 in 1984 to 577.45 km2 in 2014, and the proportion of UHI regions has increased from 15.27% in 1984 to 29.62% in 2014; (2) the spatiotemporal changes in thermal environment were consistent with the process of urbanization. The average LST of the study area has been continuously increasing as many other land use types have been transformed to urban regions. The mean temperatures were higher in urban regions than rural areas over all of the periods, but the UHI intensity varied based on different measurements; and (3) the thermal environment inside the city varied widely even within a small area. The LST possesses a very strong positive relationship with impervious surface area (ISA), and the relationship has become stronger in recent years. The UHI we employ, specifically in this study, is SUHI (surface urban heat island).

ACS Style

Chaobin Yang; Xingyuan He; Fengqin Yan; Lingxue Yu; Kun Bu; Jiuchun Yang; Liping Chang; Shuwen Zhang. Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China. Sustainability 2017, 9, 312 .

AMA Style

Chaobin Yang, Xingyuan He, Fengqin Yan, Lingxue Yu, Kun Bu, Jiuchun Yang, Liping Chang, Shuwen Zhang. Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China. Sustainability. 2017; 9 (2):312.

Chicago/Turabian Style

Chaobin Yang; Xingyuan He; Fengqin Yan; Lingxue Yu; Kun Bu; Jiuchun Yang; Liping Chang; Shuwen Zhang. 2017. "Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China." Sustainability 9, no. 2: 312.

Journal article
Published: 04 November 2016 in ISPRS International Journal of Geo-Information
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This research is focused on gully erosion mapping and monitoring at multiple spatial scales using multi-source remote sensing data of the Sancha River catchment in Northeast China, where gullies extend over a vast area. A high resolution satellite image (Pleiades 1A, 0.7 m) was used to obtain the spatial distribution of the gullies of the overall basin. Image visual interpretation with field verification was employed to map the geometric gully features and evaluate gully erosion as well as the topographic differentiation characteristics. Unmanned Aerial Vehicle (UAV) remote sensing data and the 3D photo-reconstruction method were employed for detailed gully mapping at a site scale. The results showed that: (1) the sub-meter image showed a strong ability in the recognition of various gully types and obtained satisfactory results, and the topographic factors of elevation, slope and slope aspects exerted significant influence on the gully spatial distribution at the catchment scale; and (2) at a more detailed site scale, UAV imagery combined with 3D photo-reconstruction provided a Digital Surface Model (DSM) and ortho-image at the centimeter level as well as a detailed 3D model. The resulting products revealed the area of agricultural utilization and its shaping by human agricultural activities and water erosion in detail, and also provided the gully volume. The present study indicates that using multi-source remote sensing data, including satellite and UAV imagery simultaneously, results in an effective assessment of gully erosion over multiple spatial scales. The combined approach should be continued to regularly monitor gully erosion to understand the erosion process and its relationship with the environment from a comprehensive perspective.

ACS Style

Ranghu Wang; Shuwen Zhang; Luoman Pu; Jiuchun Yang; Chaobin Yang; Jing Chen; Cong Guan; Qing Wang; Dan Chen; Bolin Fu; Xuejia Sang. Gully Erosion Mapping and Monitoring at Multiple Scales Based on Multi-Source Remote Sensing Data of the Sancha River Catchment, Northeast China. ISPRS International Journal of Geo-Information 2016, 5, 200 .

AMA Style

Ranghu Wang, Shuwen Zhang, Luoman Pu, Jiuchun Yang, Chaobin Yang, Jing Chen, Cong Guan, Qing Wang, Dan Chen, Bolin Fu, Xuejia Sang. Gully Erosion Mapping and Monitoring at Multiple Scales Based on Multi-Source Remote Sensing Data of the Sancha River Catchment, Northeast China. ISPRS International Journal of Geo-Information. 2016; 5 (11):200.

Chicago/Turabian Style

Ranghu Wang; Shuwen Zhang; Luoman Pu; Jiuchun Yang; Chaobin Yang; Jing Chen; Cong Guan; Qing Wang; Dan Chen; Bolin Fu; Xuejia Sang. 2016. "Gully Erosion Mapping and Monitoring at Multiple Scales Based on Multi-Source Remote Sensing Data of the Sancha River Catchment, Northeast China." ISPRS International Journal of Geo-Information 5, no. 11: 200.

Journal article
Published: 22 October 2016 in Sustainability
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Understanding the historical change of agricultural landscape patterns is the basis for promoting the sustainable development of cultivated land, as well as appropriate decision-making. In order to analyze spatio-temporal changes of cultivated land in Sanjiang Plain, from 1985–2015, Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) were used to reconstruct satellite data of land use and land cover. Additionally, twelve landscape indices were selected to analyze landscape pattern changes and to compare the differences of cultivated landscape changes between the agricultural region and the reclamation region. Studies suggested that during the past 30 years, cultivated land in the study area grew rapidly, with a rapid growth of paddy fields and a slow reduction of dry farmland. This trend was more obvious in the reclamation region than it was in the agricultural region, where both dry farmland and paddy fields showed a growth trend in the past 30 years. Our study showed that paddies have become the dominant agricultural landscape and that fragmentation of paddy fields has decreased, while dry farmland has increased over the past 30 years, within the entire study area. Different management modes have caused major differences between the agricultural region and the reclamation region.

ACS Style

Fengqin Yan; Shuwen Zhang; Wenhui Kuang; Guoming Du; Jing Chen; Xingtu Liu; Lingxue Yu; Chaobin Yang. Comparison of Cultivated Landscape Changes under Different Management Modes: A Case Study in Sanjiang Plain. Sustainability 2016, 8, 1071 .

AMA Style

Fengqin Yan, Shuwen Zhang, Wenhui Kuang, Guoming Du, Jing Chen, Xingtu Liu, Lingxue Yu, Chaobin Yang. Comparison of Cultivated Landscape Changes under Different Management Modes: A Case Study in Sanjiang Plain. Sustainability. 2016; 8 (10):1071.

Chicago/Turabian Style

Fengqin Yan; Shuwen Zhang; Wenhui Kuang; Guoming Du; Jing Chen; Xingtu Liu; Lingxue Yu; Chaobin Yang. 2016. "Comparison of Cultivated Landscape Changes under Different Management Modes: A Case Study in Sanjiang Plain." Sustainability 8, no. 10: 1071.

Journal article
Published: 30 March 2016 in Sustainability
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The black soil region of Northeast China has suffered from severe soil erosion by water. Hillslope and gully erosion are the main erosion types. The objective of this research was to integrate the assessment of hillslope and gully erosion and explore spatial coupling relations between them in the Mushi River sub-catchment using geographical conditions monitoring (GCM) including remote sensing (RS) and geographic information system (GIS) techniques. The revised universal soil loss equation (RUSLE) model and visual satellite image interpretation were used to evaluate hillslope and gully erosion, respectively. The results showed that (1) the study area as a whole had slight erosion due to rill and sheet erosion, but suffered more serious gully erosion, which mainly occurs in cultivated land; (2) GCM contributed to the overall improvement of soil erosion assessment, but the RUSLE model likely overestimates the erosion rate in dry land; (3) the hillslope and gully erosion were stronger on sunny slopes than on shady slopes, and mainly occurred at middle elevations. When the slope was greater than 15 degrees, the slope was not the main factor restricting the erosion, while at steeper slopes, the dominant forest land significantly reduced the soil loss; (4) trends of gully erosion intensity and density were not consistent with the change in soil erosion intensity. To our knowledge, this study was one of the first that attempted to integrate gully erosion and hillslope erosion on a watershed scale. The findings of this study promote a better understanding of the spatial coupling relationships between hillslope and gully erosion and similarly indicate that GCM, RS, and GIS can be used efficiently in the hilly black soil region of Northeast China to assess hillslope and gully erosion.

ACS Style

Ranghu Wang; Shuwen Zhang; Jiuchun Yang; Luoman Pu; Chaobin Yang; Lingxue Yu; Liping Chang; Kun Bu. Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China. Sustainability 2016, 8, 317 .

AMA Style

Ranghu Wang, Shuwen Zhang, Jiuchun Yang, Luoman Pu, Chaobin Yang, Lingxue Yu, Liping Chang, Kun Bu. Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China. Sustainability. 2016; 8 (4):317.

Chicago/Turabian Style

Ranghu Wang; Shuwen Zhang; Jiuchun Yang; Luoman Pu; Chaobin Yang; Lingxue Yu; Liping Chang; Kun Bu. 2016. "Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China." Sustainability 8, no. 4: 317.

Journal article
Published: 01 September 2014 in Ying yong sheng tai xue bao = The journal of applied ecology
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ACS Style

Ling-Xue Yu; Shu-Wen Zhang; Cong Guan; Feng-Qin Yan; Chaobin Yang; Kun Bu; Jiu-Chun Yang; Li-Ping Chang. [Monitoring on spatial and temporal changes of snow cover in the Heilongjiang Basin based on remote sensing]. Ying yong sheng tai xue bao = The journal of applied ecology 2014, 25, 1 .

AMA Style

Ling-Xue Yu, Shu-Wen Zhang, Cong Guan, Feng-Qin Yan, Chaobin Yang, Kun Bu, Jiu-Chun Yang, Li-Ping Chang. [Monitoring on spatial and temporal changes of snow cover in the Heilongjiang Basin based on remote sensing]. Ying yong sheng tai xue bao = The journal of applied ecology. 2014; 25 (9):1.

Chicago/Turabian Style

Ling-Xue Yu; Shu-Wen Zhang; Cong Guan; Feng-Qin Yan; Chaobin Yang; Kun Bu; Jiu-Chun Yang; Li-Ping Chang. 2014. "[Monitoring on spatial and temporal changes of snow cover in the Heilongjiang Basin based on remote sensing]." Ying yong sheng tai xue bao = The journal of applied ecology 25, no. 9: 1.

Journal article
Published: 03 July 2014 in Theoretical and Applied Climatology
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Land cover change, as one of the most important driving forces to climate change, has become the research focus of the global environmental change research and global land project. More researchers studied on the global influence of Land-Use and Land-Cover Change and proved that land use change occurred at different temperature zones may produce different climate effects. For example, deforestation in tropical areas would lead to higher temperatures as the decreasing of evapotranspiration caused by the reduction of roughness and the decreasing of drag coefficient and leaf area index while, in boreal areas, similar deforestation would cause lower temperature as the increasing of albedo particularly during winter with the snow cover. However, the impact of deforestation in the temperate regions on the climate still existed uncertainty and the impacts of deforestation at different humidity conditions on climate has not explored yet. From this perspective, this article used Weather Research and Forecasting model to simulate the impact of deforestation on the temperature of Northeastern China. In this study, we designed two scenarios in July and December, respectively: One was simulated without human intervention, and the second one was simulated with the current forest covers. The results showed that the temperature in both summer and winter showed a decreasing trend when the conversion of forest to farmland occurred in northeastern China. In order to further explore the humidity impacts on the temperature, we performed sample analysis on humid, sub-humid, and semi-arid regions. According to the results, the maximum variation of temperature was found in humid areas, especially in December when the temperature decreased around 4–5 °C, while the change in semi-arid and sub-humid areas is relatively small.

ACS Style

Lingxue Yu; Shuwen Zhang; Junmei Tang; Tingxiang Liu; Kun Bu; Fengqin Yan; Chaobin Yang; Jiuchun Yang. The effect of deforestation on the regional temperature in Northeastern China. Theoretical and Applied Climatology 2014, 120, 761 -771.

AMA Style

Lingxue Yu, Shuwen Zhang, Junmei Tang, Tingxiang Liu, Kun Bu, Fengqin Yan, Chaobin Yang, Jiuchun Yang. The effect of deforestation on the regional temperature in Northeastern China. Theoretical and Applied Climatology. 2014; 120 (3-4):761-771.

Chicago/Turabian Style

Lingxue Yu; Shuwen Zhang; Junmei Tang; Tingxiang Liu; Kun Bu; Fengqin Yan; Chaobin Yang; Jiuchun Yang. 2014. "The effect of deforestation on the regional temperature in Northeastern China." Theoretical and Applied Climatology 120, no. 3-4: 761-771.

Journal article
Published: 01 January 2014 in Journal of Applied Remote Sensing
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ACS Style

Lingxue Yu; Tingxiang Liu; Hongyan Cai; Junmei Tang; Kun Bu; Fengqin Yan; Chaobin Yang; Jiuchun Yang; Shuwen Zhang. Estimating land surface radiation balance using MODIS in northeastern China. Journal of Applied Remote Sensing 2014, 8, 83523 .

AMA Style

Lingxue Yu, Tingxiang Liu, Hongyan Cai, Junmei Tang, Kun Bu, Fengqin Yan, Chaobin Yang, Jiuchun Yang, Shuwen Zhang. Estimating land surface radiation balance using MODIS in northeastern China. Journal of Applied Remote Sensing. 2014; 8 (1):83523.

Chicago/Turabian Style

Lingxue Yu; Tingxiang Liu; Hongyan Cai; Junmei Tang; Kun Bu; Fengqin Yan; Chaobin Yang; Jiuchun Yang; Shuwen Zhang. 2014. "Estimating land surface radiation balance using MODIS in northeastern China." Journal of Applied Remote Sensing 8, no. 1: 83523.