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On Page 894, Fig. 1d is redundant in the original article and should be removed. On Page 895, in Section 2.2, the 4th paragraph, the figure number “Fig. 1d” in the last sentence is incorrect. It should be corrected into “Fig. 1c”. On Page 896, in Section 3.2, the 1st paragraph, the figure number “Fig. 1d” in the 2nd sentence is incorrect. It should be corrected into “Fig. 1c”.
Zheng-Lan Yang; Ting-Bin Zhang; Gui-Hua Yi; Jing-Ji Li; Yan-Bin Qin; Yang Chen. Erratum to: Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China. Journal of Mountain Science 2021, 18, 1710 -1710.
AMA StyleZheng-Lan Yang, Ting-Bin Zhang, Gui-Hua Yi, Jing-Ji Li, Yan-Bin Qin, Yang Chen. Erratum to: Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China. Journal of Mountain Science. 2021; 18 (6):1710-1710.
Chicago/Turabian StyleZheng-Lan Yang; Ting-Bin Zhang; Gui-Hua Yi; Jing-Ji Li; Yan-Bin Qin; Yang Chen. 2021. "Erratum to: Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China." Journal of Mountain Science 18, no. 6: 1710-1710.
The Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is an important indicator of the primary productivity of vegetation. FPAR is often used to estimate the assimilation of carbon dioxide in vegetation. Based on MOD15A2H/FPAR data product, the temporal and spatial variation characteristics and variation trend of FPAR in different vegetation types in 2001 to 2018 were analyzed in the Hengduan Mountains. The response of FPAR to climate change was investigated by using Pearson correlation analytical method and partial least squares regression analysis. Results showed that the FPAR in Hengduan Mountains presented an increasing trend with time. Spatially, it was high in the south and low in the north, and it also showed obvious vertical zonality by elevation gradient. The vegetation FPAR was found to be positively correlated with air temperature and sunshine duration but negatively correlated with precipitation. Partial least squares regression analysis showed that the influence of sunshine duration on vegetation FPAR in Hengduan Mountains was stronger than that of air temperature and precipitation.
Zheng-Ian Yang; Ting-Bin Zhang; Gui-Hua Yi; Jing-Ji Li; Yan-Bin Qin; Yang Chen. Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China. Journal of Mountain Science 2021, 18, 891 -906.
AMA StyleZheng-Ian Yang, Ting-Bin Zhang, Gui-Hua Yi, Jing-Ji Li, Yan-Bin Qin, Yang Chen. Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China. Journal of Mountain Science. 2021; 18 (4):891-906.
Chicago/Turabian StyleZheng-Ian Yang; Ting-Bin Zhang; Gui-Hua Yi; Jing-Ji Li; Yan-Bin Qin; Yang Chen. 2021. "Spatio-temporal variation of Fraction of Photosynthetically Active Radiation absorbed by vegetation in the Hengduan Mountains, China." Journal of Mountain Science 18, no. 4: 891-906.
Snow depth distribution in the Qinghai-Tibetan plateau is important for atmospheric circulation and surface water resources. In-situ observations at meteorological stations and remote observation by passive microwave remote sensing technique are two main approaches for monitoring snow depth at regional or global levels. However, the meteorological stations are often scarce and unevenly distributed in mountainous regions because of inaccessibility, so are the in-situ snow depth measurements. Passive microwave remote sensing data can alleviate the unevenness issue, but accuracy and spatial (e.g., 25 km) and temporal resolutions are low; spatial heterogeneity in snow depth is thus hard to capture. On the other hand, optical sensors such as moderate resolution imaging spectroradiometer (MODIS) onboard Terra and Aqua satellites can monitor snow at moderate spatial resolution (1 km) and high temporal resolution (daily) but only snow area extent, not snow depth. Fusing passive microwave snow depth data with optical snow area extent data provides an unprecedented opportunity for generating snow depth data at moderate spatial resolution and high temporal resolution. In this article, a linear multivariate snow depth reconstruction (LMSDR) model was developed by fusing multisource snow depth data, optical snow area extent data, and environmental factors (e.g., spatial distribution, terrain features, and snow cover characteristics), to reconstruct daily snow depth data at moderate resolution (1 km) for 16 consecutive hydrological years, taking Qinghai-Tibetan Plateau (QTP) as a case study. We found that snow cover day (SCD) and environmental factors such as longitude, latitude, slope, surface roughness, and surface fluctuation have a significant impact on the variations of snow depth over the QTP. Relatively high accuracy (root mean square error (RMSE) = 2.26 cm) was observed in the reconstructed snow depth when compared with in-situ data. Compared with the passive microwave remote sensing snow depth product, constructing a nonlinear snow depletion curve product with an empirical formula and fusion snow depth product, the LMSDR model (RMSE = 2.28 cm, R2 = 0.63) demonstrated a significant improvement in accuracy of snow depth reconstruction. The overall spatial accuracy of the reconstructed snow depth was 92%. Compared with in-situ observations, the LMSDR product performed well regarding different snow depth intervals, land use, elevation intervals, slope intervals, and SCD and performed best, especially when the snow depth was less than 3 cm. At the same time, a long-time snow depth series reconstructed based on the LMSDR model reflected interannual variations of snow depth well over the QTP.
Pengtao Wei; Tingbin Zhang; Xiaobing Zhou; Guihua Yi; Jingji Li; Na Wang; Bo Wen. Reconstruction of Snow Depth Data at Moderate Spatial Resolution (1km) from Remotely Sensed Snow Data and Multiple Optimized Environmental Factors: A Case Study over the Qinghai-Tibetan Plateau. Remote Sensing 2021, 13, 657 .
AMA StylePengtao Wei, Tingbin Zhang, Xiaobing Zhou, Guihua Yi, Jingji Li, Na Wang, Bo Wen. Reconstruction of Snow Depth Data at Moderate Spatial Resolution (1km) from Remotely Sensed Snow Data and Multiple Optimized Environmental Factors: A Case Study over the Qinghai-Tibetan Plateau. Remote Sensing. 2021; 13 (4):657.
Chicago/Turabian StylePengtao Wei; Tingbin Zhang; Xiaobing Zhou; Guihua Yi; Jingji Li; Na Wang; Bo Wen. 2021. "Reconstruction of Snow Depth Data at Moderate Spatial Resolution (1km) from Remotely Sensed Snow Data and Multiple Optimized Environmental Factors: A Case Study over the Qinghai-Tibetan Plateau." Remote Sensing 13, no. 4: 657.
Yi Qin; Ting-Bin Zhang; Gui-Hua Yi; Peng-Tao Wei; Da Yang. Remote sensing monitoring and analysis of influencing factors of drought in Inner Mongolia growing season since 2000. JOURNAL OF NATURAL RESOURCES 2021, 36, 459 -475.
AMA StyleYi Qin, Ting-Bin Zhang, Gui-Hua Yi, Peng-Tao Wei, Da Yang. Remote sensing monitoring and analysis of influencing factors of drought in Inner Mongolia growing season since 2000. JOURNAL OF NATURAL RESOURCES. 2021; 36 (2):459-475.
Chicago/Turabian StyleYi Qin; Ting-Bin Zhang; Gui-Hua Yi; Peng-Tao Wei; Da Yang. 2021. "Remote sensing monitoring and analysis of influencing factors of drought in Inner Mongolia growing season since 2000." JOURNAL OF NATURAL RESOURCES 36, no. 2: 459-475.
The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of −0.13/10° E and −0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.
Xianglin Huang; Tingbin Zhang; Guihua Yi; Dong He; Xiaobing Zhou; Jingji Li; Xiaojuan Bie; Jiaqing Miao. Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change. International Journal of Environmental Research and Public Health 2019, 16, 3452 .
AMA StyleXianglin Huang, Tingbin Zhang, Guihua Yi, Dong He, Xiaobing Zhou, Jingji Li, Xiaojuan Bie, Jiaqing Miao. Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change. International Journal of Environmental Research and Public Health. 2019; 16 (18):3452.
Chicago/Turabian StyleXianglin Huang; Tingbin Zhang; Guihua Yi; Dong He; Xiaobing Zhou; Jingji Li; Xiaojuan Bie; Jiaqing Miao. 2019. "Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change." International Journal of Environmental Research and Public Health 16, no. 18: 3452.
This paper focuses on the suitability of urban expansion in mountain areas against the background of accelerated urban development. Urbanization is accompanied by conflict and intense transformations of various landscapes, and is accompanied by social, economic, and ecological impacts. Evaluating the suitability of urban expansion (UE) and determining an appropriate scale is vital to solving urban environmental issues and realizing sustainable urban development. In mountain areas, the natural and social environments are different from those in the plains; the former is characterized by fragile ecology and proneness to geological disasters. Therefore, when evaluating the expansion of a mountain city, more factors need to be considered. Moreover, we need to follow the principle of harmony between nature and society according to the characteristics of mountain cities. Thus, when we evaluate the expansion of a mountain city, the key procedure is to establish a scientific evaluation system and explore the relationship between each evaluation factor and the urban expansion process. Taking Leshan (LS), China—a typical mountain city in the upper Yangtze River which has undergone rapid growth—as a case study, the logic minimum cumulative resistance (LMCR) model was applied to evaluate the suitability of UE and to simulate its direction and scale. The results revealed that: An evaluation system of resistance factors (ESRFs) was established according to the principle of natural and social harmony; the logic resistance surface (LRS) scientifically integrated multiple resistance factors based on the ESRF and a logic regression analysis. LRS objectively and effectively reflected the contribution and impact of each resistance factor to urban expansion. We found that landscape, geological hazards and GDP have had a great impact on urban expansion in LS. The expansion space of the mountain city is limited; the area of suitable expansion is only 23.5%, while the area which is unsuitable for expansion is 39.3%. In addition, it was found that setting up ecological barriers is an effective way to control unreasonable urban expansion in mountain cities. There is an obvious scale (grid size) effect in the evaluation of urban expansion in mountain cities; an evaluation of the suitable scale yielded the result of 90 m × 90 m. On this scale, taking the central district as the center, the urban expansion process will extend to the neighboring towns of Mianzhu, Suji, Juzi and Mouzi. Urban expansion should be controlled in terms of scale, especially in mountain cities. The most suitable urban size of LS is 132 km2.This would allow for high connectivity of urban-rural areas with the occupation of relatively few green spaces.
Haijun Wang; Peihao Peng; Xiangdong Kong; Tingbin Zhang; Guihua Yi. Evaluating the Suitability of Urban Expansion Based on the Logic Minimum Cumulative Resistance Model: A Case Study from Leshan, China. ISPRS International Journal of Geo-Information 2019, 8, 291 .
AMA StyleHaijun Wang, Peihao Peng, Xiangdong Kong, Tingbin Zhang, Guihua Yi. Evaluating the Suitability of Urban Expansion Based on the Logic Minimum Cumulative Resistance Model: A Case Study from Leshan, China. ISPRS International Journal of Geo-Information. 2019; 8 (7):291.
Chicago/Turabian StyleHaijun Wang; Peihao Peng; Xiangdong Kong; Tingbin Zhang; Guihua Yi. 2019. "Evaluating the Suitability of Urban Expansion Based on the Logic Minimum Cumulative Resistance Model: A Case Study from Leshan, China." ISPRS International Journal of Geo-Information 8, no. 7: 291.
Accurate measurements of the associated vegetation phenological dynamics are crucial for understanding the relationship between climate change and terrestrial ecosystems. However, at present, most vegetation phenological calculations are based on a single algorithm or method. Because of the spatial, temporal, and ecological complexity of the vegetation growth processes, a single algorithm or method for monitoring all these processes has been indicated to be elusive. Therefore, in this study, from the perspective of plant growth characteristics, we established a method to remotely determine the start of the growth season (SOG) and the end of the growth season (EOG), in which the maximum relative change rate of the normalized difference vegetation index (NDVI) corresponds to the SOG, and the next minimum absolute change rate of the NDVI corresponds to the EOG. Taking the Three-River Headwaters Region in 2000–2013 as an example, we ascertained the spatiotemporal and vertical characteristics of its vegetation phenological changes. Then, in contrast to the actual air temperature data, observed data and other related studies, we found that the SOG and EOG calculated by the proposed method is closer to the time corresponding to the air temperature, and the trends of the SOG and EOG calculated by the proposed method are in good agreement with other relevant studies. Meantime, the error of the SOG between the calculated and observed in this study is smaller than that in other studies.
Tian-Tian Chen; Gui-Hua Yi; Ting-Bin Zhang; Qiang Wang; Xiao-Juan Bie. A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China. Journal of Mountain Science 2019, 16, 2001 -2014.
AMA StyleTian-Tian Chen, Gui-Hua Yi, Ting-Bin Zhang, Qiang Wang, Xiao-Juan Bie. A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China. Journal of Mountain Science. 2019; 16 (9):2001-2014.
Chicago/Turabian StyleTian-Tian Chen; Gui-Hua Yi; Ting-Bin Zhang; Qiang Wang; Xiao-Juan Bie. 2019. "A method for determining vegetation growth process using remote sensing data: A case study in the Three-River Headwaters Region, China." Journal of Mountain Science 16, no. 9: 2001-2014.
The Inner Mongolia Autonomous Region (IMAR) is a major source of rivers, catchment areas, and ecological barriers in the northeast of China, related to the nation’s ecological security and improvement of the ecological environment. Therefore, studying the response of vegetation to climate change has become an important part of current global change research. Since existing studies lack detailed descriptions of the response of vegetation to different climatic factors using the method of grey correlation analysis based on pixel, the temporal and spatial patterns and trends of enhanced vegetation index (EVI) are analyzed in the growing season in IMAR from 2000 to 2015 based on moderate resolution imaging spectroradiometer (MODIS) EVI data. Combined with the data of air temperature, relative humidity, and precipitation in the study area, the grey relational analysis (GRA) method is used to study the time lag of EVI to climate change, and the study area is finally zoned into different parts according to the driving climatic factors for EVI on the basis of lag analysis. The driving zones quantitatively show the characteristics of temporal and spatial differences in response to different climatic factors for EVI. The results show that: (1) The value of EVI generally features in spatial distribution, increasing from the west to the east and the south to the north. The rate of change is 0.22/10°E from the west to the east, 0.28/10°N from the south to the north; (2) During 2000–2015, the EVI in IMAR showed a slightly upward trend with a growth rate of 0.021/10a. Among them, the areas with slight and significant improvement accounted for 21.1% and 7.5% of the total area respectively, ones with slight and significant degradation being 24.6% and 4.3%; (3) The time lag analysis of climatic factors for EVI indicates that vegetation growth in the study area lags behind air temperature by 1–2 months, relative humidity by 1–2 months, and precipitation by one month respectively; (4) During the growing season, the EVI of precipitation driving zone (21.8%) in IMAR is much larger than that in the air temperature driving zone (8%) and the relative humidity driving zone (11.6%). The growth of vegetation in IMAR generally has the closest relationship with precipitation. The growth of vegetation does not depend on the change of a single climatic factor. Instead, it is the result of the combined action of multiple climatic factors and human activities.
Dong He; Guihua Yi; Tingbin Zhang; Jiaqing Miao; Jingji Li; Xiaojuan Bie. Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China. Remote Sensing 2018, 10, 961 .
AMA StyleDong He, Guihua Yi, Tingbin Zhang, Jiaqing Miao, Jingji Li, Xiaojuan Bie. Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China. Remote Sensing. 2018; 10 (6):961.
Chicago/Turabian StyleDong He; Guihua Yi; Tingbin Zhang; Jiaqing Miao; Jingji Li; Xiaojuan Bie. 2018. "Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China." Remote Sensing 10, no. 6: 961.
One of the most important characteristics of porphyry copper deposits (PCDs) is the type and distribution pattern of alteration zones which can be used for screening and recognizing these deposits. Hydrothermal alteration minerals with diagnostic spectral absorption properties in the visible and near-infrared (VNIR) through the shortwave infrared (SWIR) regions can be identified by multispectral and hyperspectral remote sensing data. Six Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands in SWIR have been shown to be effective in the mapping of Al-OH, Fe-OH, Mg-OH group minerals. The five VNIR bands of Landsat-8 (L8) Operational Land Imager (OLI) are useful for discriminating ferric iron alteration minerals. In the absence of complete hyperspectral coverage area, an opportunity, however, exists to integrate ASTER and L8-OLI (AO) to compensate each other’s shortcomings in covering area for mineral mapping. This study examines the potential of AO data in mineral mapping in an arid area of the Duolong porphyry Cu-Au deposit(Tibetan Plateau in China) by using spectral analysis techniques. Results show the following conclusions: (1) Combination of ASTER and L8-OLI data (AO) has more mineral information content than either alone; (2) The Duolong PCD alteration zones of phyllic, argillic and propylitic zones are mapped using ASTER SWIR bands and the iron-bearing mineral information is best mapped using AO VNIR bands; (3) The multispectral integration data of AO can provide a compensatory data of ASTER VNIR bands for iron-bearing mineral mapping in the arid and semi-arid areas.
Tingbin Zhang; Guihua Yi; Hongmei Li; Ziyi Wang; Juxing Tang; Kanghui Zhong; Yubin Li; Qin Wang; Xiaojuan Bie. Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China. Remote Sensing 2016, 8, 890 .
AMA StyleTingbin Zhang, Guihua Yi, Hongmei Li, Ziyi Wang, Juxing Tang, Kanghui Zhong, Yubin Li, Qin Wang, Xiaojuan Bie. Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China. Remote Sensing. 2016; 8 (11):890.
Chicago/Turabian StyleTingbin Zhang; Guihua Yi; Hongmei Li; Ziyi Wang; Juxing Tang; Kanghui Zhong; Yubin Li; Qin Wang; Xiaojuan Bie. 2016. "Integrating Data of ASTER and Landsat-8 OLI (AO) for Hydrothermal Alteration Mineral Mapping in Duolong Porphyry Cu-Au Deposit, Tibetan Plateau, China." Remote Sensing 8, no. 11: 890.
The Tibetan Plateau is a key area for research on global environmental changes. During the past 50 years, the climate in the Siling Co lake area has become continuously warmer and wetter, which may have further caused the increase in Siling Co lake area. Based on the Siling Co lake area (2003 to 2013) and climate data acquired from the Xainza and Baingoin meteorological stations (covering 1966 to 2013), we analyzed the delayed responses of lake area changes to climate changes through grey relational analysis. The following results were obtained: (1) The Siling Co lake area exhibited a rapid expansion trend from 2003 to 2013. The lake area increased to 2318 km2, with a growth ratio of 14.6% and an annual growth rate of 26.84 km2·year−1; (2) The rate of air temperature increase was different in the different seasons. The rate in the cold season was about 0.41 °C per ten years and 0.32 °C in hot season. Precipitation evidently increased, with a change rate of 17.70 mm per ten years in the hot season and a slight increase with a change rate of 2.36 mm per ten years in the cold season. Pan evaporation exhibited evidently decreasing trends in both the hot and cold seasons, with rates of −33.35 and −14.84 mm per ten years, respectively; (3) An evident delayed response of lake area change to climate change is observed, with a delay time of approximately one to two years.
Guihua Yi; Tingbin Zhang. Delayed Response of Lake Area Change to Climate Change in Siling Co Lake, Tibetan Plateau, from 2003 to 2013. International Journal of Environmental Research and Public Health 2015, 12, 13886 -13900.
AMA StyleGuihua Yi, Tingbin Zhang. Delayed Response of Lake Area Change to Climate Change in Siling Co Lake, Tibetan Plateau, from 2003 to 2013. International Journal of Environmental Research and Public Health. 2015; 12 (11):13886-13900.
Chicago/Turabian StyleGuihua Yi; Tingbin Zhang. 2015. "Delayed Response of Lake Area Change to Climate Change in Siling Co Lake, Tibetan Plateau, from 2003 to 2013." International Journal of Environmental Research and Public Health 12, no. 11: 13886-13900.
Changes in the lake areas of Xainza basin in the past 33 years (1976 to 2008) were studied using Landsat data from Multispectral Scanners (1973–1977), Thematic Mapper (1989–1992, 2007–2009), and Enhanced Thematic Mapper Plus (1999–2002). The results indicated that lakes in the study area evidently expanded from 1976 to 2008, with total expansion of 1512.64 km2. The mean annual air temperature presented an upward trend with certain fluctuations from 1966 to 2008. The air temperature rise rates in the cold season (0.31°C/10a) were higher than those in the hot season (0.24°C/10a), in the Xainza station example. Precipitation exhibited evident seasonal differences. Mean annual precipitation in hot season is 281.48 mm and cold season is 32.66 mm from 1966 to 2008 in study area. Precipitation in the hot season was the major contributor to the increase in annual precipitation. Grey relational analysis (GRA) was used to study the response of lake areas to climatic factors. The mean air temperature and precipitation were selected as compared series, and the lake areas were regarded as the reference series. The grey relational grade (GRG) between compared series and reference series were calculated through GRA. The results indicated that changes in lake areas were mainly affected by climatic factors in the hot season. Lakes in this region were classified into three grades, namely, Grades I, II, and III according to the recharge source and elevation. The GRGs of each series varied for different grade lakes: the area of Grade III lakes were the most relevant to the hot season factors, the GRGs of precipitation and air temperature were 0.7570 and 0.6606; followed by the Grade II lakes; Grade I lakes were more sensitive to the air temperature.
Gui-Hua Yi; Wei Deng; Ai-Nong Li; Ting-Bin Zhang. Response of lakes to climate change in Xainza basin Tibetan Plateau using multi-mission satellite data from 1976 to 2008. Journal of Mountain Science 2015, 12, 604 -613.
AMA StyleGui-Hua Yi, Wei Deng, Ai-Nong Li, Ting-Bin Zhang. Response of lakes to climate change in Xainza basin Tibetan Plateau using multi-mission satellite data from 1976 to 2008. Journal of Mountain Science. 2015; 12 (3):604-613.
Chicago/Turabian StyleGui-Hua Yi; Wei Deng; Ai-Nong Li; Ting-Bin Zhang. 2015. "Response of lakes to climate change in Xainza basin Tibetan Plateau using multi-mission satellite data from 1976 to 2008." Journal of Mountain Science 12, no. 3: 604-613.
Dexin Pb-Zn mining area is located in Zexu Township, Xietongmen County, Shigatse, Tibet. This research adopts the multisource remote sensing technique to interpret the wall rock alternation and the structural information in the study area to acquire more prospecting information.
Guo Na; Juxing Tang; Maozhi Wang; Tingbin Zhang; Xiaojuan Bie. The application of multisource remote sensing techniques to the mineral exploration of Dexin Pb-Zn mining area in Zexu Township, Xietongmen County, Shigaste, Tibet. 2012 IEEE International Geoscience and Remote Sensing Symposium 2012, 2729 -2732.
AMA StyleGuo Na, Juxing Tang, Maozhi Wang, Tingbin Zhang, Xiaojuan Bie. The application of multisource remote sensing techniques to the mineral exploration of Dexin Pb-Zn mining area in Zexu Township, Xietongmen County, Shigaste, Tibet. 2012 IEEE International Geoscience and Remote Sensing Symposium. 2012; ():2729-2732.
Chicago/Turabian StyleGuo Na; Juxing Tang; Maozhi Wang; Tingbin Zhang; Xiaojuan Bie. 2012. "The application of multisource remote sensing techniques to the mineral exploration of Dexin Pb-Zn mining area in Zexu Township, Xietongmen County, Shigaste, Tibet." 2012 IEEE International Geoscience and Remote Sensing Symposium , no. : 2729-2732.