Figure 1

Schematic figures showing the methods of phenological detection. (a) Defining the NDVI threshold according to the NDVI relative change (NDVI(t + 1) - NDVI(t)) (Method 1). (b) Defining the NDVI threshold according to the NDVI relative change ratio ((NDVI(t + 1) - NDVI(t)) / NDVI(t)) (Method 2) in the NDVI seasonal cycle fitted by HANTS (with the same temporal resolution as the raw data), and then determining SGS by applying the NDVI threshold in each year’s NDVI seasonal cycle fitted by HANTS (with a temporal resolution of 1 d). (c) Determining the maximum and minimum NDVI values based on the smoothed data with the same temporal resolution as the raw data, and then normalizing all the NDVI values using (NDVImax - NDVImin) based on the smoothed data with a temporal resolution of 1 d and determining SGS by applying the NDVI ratio threshold (Method 3). (d) Based on the three-points-smooth data, modeling by the four-parameter logistic function, and then calculating the rate of change of the curvature and defining SGS as the time when RCC reached its first local maximum value (Method 4). For (a), (b) and (d), the change lines are shown in gray, while the smooth data are shown in black."

Figure 2

Spatial distribution of the vegetation SGS estimated from GIMMS NDVI data by the four methods described in the text. (a) Method 1; (b) Method 2; (c) Method 3; (d) Method 4; (e) Average of the four methods; and (f) SD of the four methods. The name of the physiographical regions are as follows: IB1 Golog-Nagqu high-cold shrub-meadow zone; IC1 Southern Qinghai high-cold meadow steppe zone; IC2 Qangtang high-cold steppe zone; ID1 Kunlun high-cold desert zone; IIAB1 Western Sichuan-eastern Tibet montane coniferous forest zone; IIC1 Southern Tibet montane shrub-steppe zone; IIC2 Eastern Qinghai-Qilian montane steppe zone; IID1 Ngari montane desert-steppe and desert zone; IID2 Qaidam montane desert zone; IID3 Northern slopes of Kunlun montane desert zone; OA1 Southern slopes of Himalaya montane evergreen broad-leaved forest zone (Zheng, 1996)."

Figure 3

Spatial distribution of the vegetation SGS estimated from SPOT NDVI data by the four methods described in the text. (a) Method 1; (b) Method 2; (c) Method 3; (d) Method 4; (e) Average of the four methods; and (f) SD of the four methods. The others same as Figure 2."

Figure 4

Histograms of the SDs of vegetation SGS values, for different vegetation types"

Figure 5

Histograms of SGS values for different vegetation types, as determined by four methods"

Figure 6

Inter-annual variations of vegetation SGS on the TP from 1982 to 2012; GIMMS data are shown in black and SPOT data are shown in gray"

Figure 7

Comparison between SGS estimated by the four methods described in the text (using GIMMS data) and the observed SGS data from 19 agro-meteorological stations on the TP"

Figure 8

Comparison between SGS estimated by the four methods described in the text (using SPOT data) and the observed SGS data from 19 agro-meteorological stations on the TP"

Figure 9

Vegetation growth curves at two sample sites in 2006 (Qilian and Qingshuihe) based on GIMMS data. The blue and red straight lines show the extracted vegetation phenological information based on the raw and smoothed data, respectively. The NDVI values were averaged within a circular area, with an 8-km radius, centered at each site. The phenological information is calculated using Methods 1, 2 and 3."

Figure 10

Schematic diagram indicating different yearly NDVI curves (GIMMS) in different years, which probably biases the derived SGS"

Figure 11

Vegetation growth curves in regions with different NDVI grades (a, b), and on the southern slopes of the Himalaya montane evergreen broad-leaved forest zone (c), based on the mean NDVI, over many years, of the GIMSS (1982-2006) and SPOT-VGT (1999-2012) data"