Vegetation change of giant panda habitats in Qionglai Mountains through dense Landsat Data

doi:10.17521/cjpe.2020.0226

Abstract

Abstract:

Aims Understanding the processes and drivers of vegetation change in giant panda habitats plays an important role in their conservation and management.

Methods Based on the long-term normalized difference vegetation index (NDVI) time series that was constructed by all available Landsat TM/ETM/OLI images from 1986 to 2018, we employed the BFAST (Breaks For Additive Seasonal and Trend) method and harmonic model to monitor the vegetation change during the period of 1986-2018. Three types of NDVI changes (i.e. vegetation accumulated abrupt change, accumulated gradual change, and total change) were built to reveal the spatial distribution characteristics of vegetation change. The effects of different factors (i.e. mean annual precipitation, mean annual air temperature, elevation, slope, aspect, distance to rivers, soil type, land cover type, distance to roads and distance to engineering disturbance area) on the spatial distribution of the three types of vegetation change were evaluated by Geodetector.

Important findings 1) A total of 9.13% of vegetation abrupt change in the study area was detected, which was mainly distributed around the eastern boundary of the habitats, and the largest abrupt change areas occurred in 2011 and 2013. 2) The proportion of vegetation accumulated abrupt change showing degradation accounted for 40.17% of the vegetation accumulated abrupt change area, and the accumulated gradual change and total change which presented increasing trends accounted for 94.58% and 97.02% of the study area, respectively. 3) The spatial distribution of vegetation changes was mainly affected by four factors: mean annual precipitation, mean annual air temperature, elevation, and soil type. The strongest explanatory factors of vegetation accumulated abrupt change, accumulated gradual change, and total change were mean annual precipitation, elevation, and soil type, respectively. The interactions between driving factors were mutually enhanced and nonlinearly enhanced.

Key words: Breaks For Additive Seasonal and Trend (BFAST), Geodetector, vegetation change, normalized difference vegetation index (NDVI), giant panda habitat

ZHOU Ming-Xing, LI Deng-Qiu, ZOU Jian-Jun. Vegetation change of giant panda habitats in Qionglai Mountains through dense Landsat Data[J]. Chin J Plant Ecol, 2021, 45(4): 355-369.

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Figures/Tables 11

References 58

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因子类型 Factor type	因子 Factor	空间分辨率 Spatial resolution (m)	预处理(重采样) Preprocessing (resampling)
气候 Climate	年降水量 Mean annual precipitation (X1)	1 000	双线性内插法 Bilinear interpolation
气候 Climate	年平均气温 Mean annual air temperature (X2)	1 000	双线性内插法 Bilinear interpolation
地形 Topography	高程 Elevation (X3)	30	-
	坡度 Slope (X4)	30	-
	坡向 Aspect (X5)	30	-
河流 River	与河流距离 Distance to rivers (X6)	30	-
土壤类型 Soil type	土壤类型 Soil type (X7)	1 000	最邻近内插法 Nearest interpolation
人类活动 Human activity	土地覆盖类型 Land cover type (X8)	30	-
	与道路距离 Distance to roads (X9)	30	-
	与工程扰动区距离 Distance to engineering disturbance area (X10)	30	-

因子类型 Factor type	因子 Factor	空间分辨率 Spatial resolution (m)	预处理(重采样) Preprocessing (resampling)
气候 Climate	年降水量 Mean annual precipitation (X1)	1 000	双线性内插法 Bilinear interpolation
气候 Climate	年平均气温 Mean annual air temperature (X2)	1 000	双线性内插法 Bilinear interpolation
地形 Topography	高程 Elevation (X3)	30	-
	坡度 Slope (X4)	30	-
	坡向 Aspect (X5)	30	-
河流 River	与河流距离 Distance to rivers (X6)	30	-
土壤类型 Soil type	土壤类型 Soil type (X7)	1 000	最邻近内插法 Nearest interpolation
人类活动 Human activity	土地覆盖类型 Land cover type (X8)	30	-
	与道路距离 Distance to roads (X9)	30	-
	与工程扰动区距离 Distance to engineering disturbance area (X10)	30	-

突变次数 Number of abrupt change	占研究区比例 Proportion of study area (%)		占突变区域比例 Proportion of abrupt change area (%)
突变次数 Number of abrupt change	栖息地 Habitat	外围区域 Peripheral area	栖息地 Habitat	外围区域 Peripheral area
0	58.09	32.78	-	-
1	5.74	2.92	62.87	31.98
2	0.24	0.21	2.63	2.30
3	0.01	0.01	0.11	0.11
4	0.00	0.00	0.00	0.00
≥1	5.99	3.14	65.61	34.39

突变次数 Number of abrupt change	占研究区比例 Proportion of study area (%)		占突变区域比例 Proportion of abrupt change area (%)
突变次数 Number of abrupt change	栖息地 Habitat	外围区域 Peripheral area	栖息地 Habitat	外围区域 Peripheral area
0	58.09	32.78	-	-
1	5.74	2.92	62.87	31.98
2	0.24	0.21	2.63	2.30
3	0.01	0.01	0.11	0.11
4	0.00	0.00	0.00	0.00
≥1	5.99	3.14	65.61	34.39

因子 Factor	植被累积突变 Vegetation accumulated abrupt change			植被累积渐变 Vegetation accumulated gradual change			植被总变化 Vegetation total change
因子 Factor	q	p(sig)	q排序 Sequence of q	q	p(sig)	q排序 Sequence of q	q	p(sig)	q排序 Sequence of q
X1	0.048 1	2.78E-10	1	0.031 5	6.49E-11	4	0.068 1	6.44E-10	5
X2	0.021 3	2.89E-10	2	0.037 6	6.14E-12	2	0.089 1	2.69E-11	3
X3	0.018 9	1.56E-10	3	0.037 7	5.38E-10	1	0.089 6	8.18E-10	2
X4	0.001 1	5.61E-11	10	0.000 3	2.78E-10	10	0.001 5	5.49E-10	10
X5	0.001 4	5.03E-10	9	0.001 6	2.10E-10	9	0.005 8	1.87E-10	9
X6	0.011 7	4.07E-11	5	0.012 3	6.59E-10	6	0.028 2	3.72E-10	6
X7	0.013 6	3.11E-11	4	0.037 5	1.95E-10	3	0.097 4	6.81E-10	1
X8	0.005 9	5.49E-10	7	0.023 8	4.22E-10	5	0.079 7	3.07E-10	4
X9	0.010 6	2.98E-10	6	0.008 0	6.97E-11	7	0.018 3	9.47E-10	7
X10	0.002 5	2.20E-11	8	0.003 1	6.36E-10	8	0.010 3	2.07E-10	8