Remote Sensing Monitoring of Vegetation Phonological Features in Songnen Plain of Northeast China during 1999-2013

doi:10.11849/zrzyxb.20160239

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JOURNAL OF NATURAL RESOURCES ›› 2017, Vol. 32 ›› Issue (2) : 321-328. DOI: 10.11849/zrzyxb.20160239

Resource Evaluation

Remote Sensing Monitoring of Vegetation Phonological Features in Songnen Plain of Northeast China during 1999-2013

LI Xiao-dong^{1, 2}, ZENG Fa-liang³, JIANG Qi-gang¹, YAN Shou-gang²

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Abstract

With the rapid development of 3S technology, there are vast volume of satellite image data can be used in monitoring the surface vegetation coverage, moreover, the extraction of the implied information in the images, mainly referred to the vegetation ecological features such as the annual semi-variance of surface vegetation growth and the duration length of the vegetation-growing season, are often heavy work and time-consuming. A new extraction method using the variation function is proposed to quickly and accurately extract vegetation ecological features and study the vegetation change in the growing season. The method uses normalized difference vegetation index (NDVI) dataset, and builds the relational function of the time span and the semi-variance of each point pair based on the NDVI dataset. The Songnen Plain is selected as the experimental zone, where the surface vegetation is analyzed to extract the duration and the semi-variance of the vegetation growing season. The extracted data were statistically analyzed and verified. Eventually, the calculated result was compared to the actual local phonology. The results are as follows: 1) The largest differences (the maximum of semi-variance function) of the surface vegetation growth status appeared at the time-interval of 150 d. 2) The duration of the rain-fed crops in the growing season is 107-126 d, while the deviation of the crops between the fitted values and the measured values of the duration in the growing season is less than 5 d. Similarly, for grassland the range is 120-139 d (deviation, 5-10 d), for marsh vegetation it is 160-170 d (deviation, 10 d). So the results resembled the ecological state of the surface vegetation.

Key words

remote sensing monitoring / the semi-variance function / the vegetation growing season / vegetation growth

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LI Xiao-dong, ZENG Fa-liang, JIANG Qi-gang, YAN Shou-gang. Remote Sensing Monitoring of Vegetation Phonological Features in Songnen Plain of Northeast China during 1999-2013[J]. JOURNAL OF NATURAL RESOURCES, 2017, 32(2): 321-328 https://doi.org/10.11849/zrzyxb.20160239

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Funding

Natural Science Foundation of Jilin Provincial Science and Technology Department, No. 20140101211JC; Fund Project of China Geological Survey, No. 12120115063701. ]