Prof. Zhihao Qin Profile

Prof. Zhihao Qin

at Chinese Academy of Agricultural Sciences

SPIE Involvement:

Author

Publications (21)

Proceedings Article | 4 November 2010 Paper

Estimates of carbon fluxes from Poyang Lake wetlands vegetation in the growing season

Hongxiu Wan, Zhihao Qin, Yuanbo Liu, Yongming Xu

Proceedings Volume 7858, 78581B (2010) https://doi.org/10.1117/12.869540

KEYWORDS: Vegetation, Carbon dioxide, Carbon, Magnesium, Satellites, Methane, Satellite imaging, Earth observing sensors, Temperature metrology, Soil science

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Proceedings Article | 14 October 2010 Paper

Temporal and spatial characteristics of atmospheric methane in the Yangtze River basin and the analysis of the main environmental impact factors

Hongxiu Wan, Zhihao Qin, Yuanbo Liu, Yongming Xu, Xiuying Zhang

Proceedings Volume 7827, 782711 (2010) https://doi.org/10.1117/12.864907

KEYWORDS: Methane, Temperature metrology, Climatology, Climate change, Meteorology, Carbon dioxide, Atmospheric particles, Earth's atmosphere, Spatial resolution, Oxygen

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Proceedings Article | 13 October 2008 Paper

Retrieving spatial-temporal variation of land surface temperature in Tibetan Plateau for the years 2005-2006 from MODIS satellite data

Maofang Gao, Zhihao Qin, Jianjun Qiu, Sanchao Liu, Bin Xu, Wenjuan Li, Xiuchun Yang

Proceedings Volume 7110, 71101A (2008) https://doi.org/10.1117/12.800098

KEYWORDS: MODIS, Transmittance, Vegetation, Climatology, Remote sensing, Temperature metrology, Clouds, Satellites, Sensors, Atmospheric sensing

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Proceedings Article | 13 October 2008 Paper

Integration of remote sensing with GIS for grassland snow cover monitoring and snow disaster evaluating in Tibet

Maofang Gao, Sanchao Liu, Zhihao Qin, Jianjun Qiu, Bin Xu, Wenjuan Li, Xiuchun Yang, Jingjing Li

Proceedings Volume 7110, 71100O (2008) https://doi.org/10.1117/12.800047

KEYWORDS: Snow cover, MODIS, Clouds, Geographic information systems, Remote sensing, Climatology, Algorithm development, Reflectivity, Satellites, Statistical analysis

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Proceedings Article | 2 October 2008 Paper

Mapping irrigation area of winter wheat farmland in North China Plain using MODIS remote sensing data

Lu Lin, Zhihao Qin, Jingjing Li

Proceedings Volume 7104, 71040P (2008) https://doi.org/10.1117/12.800167

KEYWORDS: MODIS, Vegetation, Agriculture, Remote sensing, Associative arrays, Soil science, Image processing, Landsat, Data acquisition, Earth observing sensors

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Proceedings Article | 2 October 2008 Paper

Snow mapping for water resource management using MODIS satellite data in northern Xinjiang, China

Huan Pei, Zhihao Qin, Shifeng Fang, Zhihui Liu

Proceedings Volume 7104, 710414 (2008) https://doi.org/10.1117/12.800203

KEYWORDS: Snow cover, MODIS, Associative arrays, Reflectivity, Satellites, Algorithm development, Data modeling, Ecosystems, Vegetation, Image analysis

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Snow is the most important freshwater resource in northern Xinjiang, which is a typical inland arid ecosystem in western China. Snow mapping can provide useful information for water resource management in this arid ecosystem. An applicable approach for snow mapping in Northern Xinjiang Basin using MODIS data was proposed in this paper. The approach of linear spectral mixture analysis (LSMA) was used to calculate snow cover fractions within a pixel, which was used to establish a regression function with NDSI at a 250-meter grid resolution. Field campaigns were conducted to examine whether NDSI can be used to extend the utility of the snow mapping approach to obtain sub-pixel estimates of snow cover. In addition, snow depths at 80 sampling sites were collected in the study region. The correlation between image reflectivity and snow depth as well as the comparison between measured snow spectra and image spectra were analyzed. An algorithm was developed on the basis of the correlation for snow depth mapping in the region. Validation for another dataset with 50 sampling sites showed an RMSE of 1.63, indicating that the algorithm was able to provide an estimation of snow depth at an accuracy of 1.63cm. The results indicated that snow cover area can reach 81% and average snow depth was 13.8 cm in north Xinjiang in January 2005. Generally speaking, the snow cover and depth had a trend of gradually decreasing from north to south and from the surroundings to the center. Temporally, the cover reached a maximum in early January, and the depth reached a maximum was ten days later. Snow duration was so different in different regions with the Aletai region having the longest and the Bole having the shortest. In the period of snow melting, snow depth decreased earlier, afterward snow cover dwindled. Our study showed that the spatial and temporal variation of snow cover was very critical for water resource management in the arid inland region and MODIS satellite data provide an alternative for snow mapping through dedicated development of mapping algorithms suitable for local application.

Proceedings Article | 2 October 2008 Paper

Mapping vegetation cover of grassland ecosystem for desertification monitoring in Hulun Buir of Inner Mongolia, China

Zhihao Qin, Yuxia Zhu, Wenjuan Li, Bin Xu

Proceedings Volume 7104, 71040C (2008) https://doi.org/10.1117/12.800190

KEYWORDS: Vegetation, Ecosystems, MODIS, Associative arrays, Remote sensing, Reflectivity, Composites, Agriculture, Climatology, Earth observing sensors

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Grassland ecosystem degradation and desertification has been highly concerned in China for years because such degradation is perceived to directly relate with the occurrence of sandstorms invading into north China. In this study we intend to map the spatial-temporal variation of vegetation cover density from remote sensing data in Hulun Buir, a typical grassland ecosystem with the highest biomass productivity in Inner Mongolia of China. Since NDVI is a good indicator of vegetation, a practical approach had been developed in the study to map the spatial-temporal variation of the vegetation cover. The MODIS satellite data were used for the mapping. Results from our study indicated that the vegetation cover rate had been steadily decreasing in recent years, with relatively high spatial and temporal variation. Our study reveals that the rate on average has a trend of steadily decreasing in recent years. In 2000 the rate was above 80.6% on average, while it decreased to below 76.5% in 2006. Generally the west part of the region had much lower vegetation cover rate than the east part, probably due to the fact that the east part was dominated with forest ecosystem while the west part with fragile grassland. The counties of Xinbaerhuyou Banner and Manzhouli in the west part had the lowest vegetation cover rate among the 13 counties. As to the grassland types, lowland meadow had the highest vegetation cover rate while the temperate meadow and steppe had the lowest, indicating that ecosystem degradation was very serious in the temperate meadow and steppe, which were mainly distributed in the west part of the region. Though many factors might contribute to the decrease of vegetation cover, annual precipitation vibration had very good correspondence with the up-and-down change of vegetation cover in the region. In addition, overgrazing also played an important role in accelerating the degradation under the drought year. Therefore, we were able to conclude that the grassland ecosystem in Hulun Buir was under a very serious situation of degradation and desertification. Our study suggested that the change of vegetation cover rate could be an applicable indicator for grassland ecosystem monitoring required urgently to combat grassland degradation and desertification in arid and semiarid region.

Proceedings Article | 2 October 2008 Paper

Evaluating health of paddy rice field ecosystem with remote sensing and GIS in Lower Yangtze River Plain, China

Jingjing Li, Zhihao Qin, Wenjuan Li, Lu Lin

Proceedings Volume 7104, 710412 (2008) https://doi.org/10.1117/12.800183

KEYWORDS: Ecosystems, Remote sensing, MODIS, Vegetation, Geographic information systems, Agriculture, Environmental sensing, Microorganisms, Lithium, Composites

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A paddy rice ecosystem is a farming system composed of paddy, animals, microbes and other environmental factors in specific time and space, with particular temporal and spatial dynamics. Since paddy rice is a main grain crop to feed above half of population in China, the performance of paddy rice ecosystem is highly concerned to yield level of paddy and food supply safety in China. Therefore, monitoring the performance of paddy rice ecosystem is very important to obtain the required information for evaluation of ecosystem health. In the study we intend to develop an approach to monitor the ecosystem performance spatially and dynamically in a regional scale using MODIS remote sensing data and GIS spatial mapping. On the basis of key factors governing the paddy rice ecosystem, we accordingly develop the following three indicators for the evaluation: Crop growing index (CGI), environmental Index (EI), and pests-diseases index (PDI). Then, we integrated the three indicators into a model with different weight coefficients to calculate Comprehensive ecosystem health index (CEHI) to evaluate the performance and functioning of paddy rice ecosystem in a regional scale. CGI indicates the health status of paddy rice calculated from the normalizing enhanced vegetation Index (EVI) retrieved from MODIS data. EI is estimated from temperature Index (TI) and precipitation Index (PI) indicating heat and water stress on the rice field. PDI reflects the damage brought by pests and diseases, which can be estimated using the information obtained from governmental websites. Applying the approach to Lower Yangtze River Plain, we monitor and evaluate the performance of paddy rice ecosystem in various stages of rice growing period in 2006. The results indicated that the performance of the ecosystem was generally very encouraging. During booting stage and heading and blooming stage, the health level was the highest in Anhui province, which is the main paddy rice producer in the region. During stage of yellow ripeness, Jiangsu province had the lowest level of performance. Yield level of paddy rice in 2006 confirms that the applicability of the proposed approach for a rapid evaluation and monitoring of agricultural ecosystem performance in Lower Yangtze River Plain. As a result, the new approach could supply scientific basis for relevant departments taking policies and measures to make sure stable development of paddy yield.

Proceedings Article | 12 November 2007 Paper

Landscape pattern and process of modern oasis in Xinjiang, China

Junfang Huang, Ranghui Wang, Liping Lu, Zhihao Qin, Yi Lin, Shuang Dong, Huizhi Zhang

Proceedings Volume 6749, 67491V (2007) https://doi.org/10.1117/12.737009

KEYWORDS: Ecosystems, Ecology, Agriculture, Geographic information systems, Vegetation, Charge-coupled devices, Data conversion, Remote sensing, Analytical research, Lithium

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