Spatio-Temporal Pattern Analysis of Vegetation NPP in Yunnan Province Based on Improved CASA Model

doi:10.13466/j.cnki.lczyyj.2023.06.015

Abstract

Abstract:

Vegetation net primary productivity (NPP)is one of the indicators to measure the level of ecosystem productivity,it is of great significance to estimate it by using the combination of ecology and remote sensing.In this study,we applied the improved CASA model;based on the MODIS vegetation index product,meteorological data,and land cover data;estimated the vegetation NPP in Yunnan Province in 2000,2005,2010,2015,and 2020,and explored its spatial distribution characteristics using the Moran's I index,Getis-Ord Gi^* hotspot analysis,and overlaying analysis with China's ecologically Functional Protected Areas in China were superimposed and analyzed.The results showed that:1)the vegetation NPP in Yunnan Province in the past 20 years showed a trend of decreasing and then increasing trend,with an average value of 822.98 gc/(m² a);the monthly vegetation NPP reached the highest in summer and the lowest in winter;and among the different vegetation types,the evergreen broadleaf forests had the highest NPP values.2)The spatial distribution of vegetation NPP decreased from south to north in each year,and the global spatial autocorrelation Moran 's I index was greater than 0.7.The NPP hot spots were mainly located in the southwestern border of Yunnan,and the cold spots were located in the northwestern and central urbanization areas of Yunnan.3)NPP hotspot areas superimposed with ecological function reserve intersected in Xishuangbanna Ecological Function Reserve and Southwest Karst Ecological Function Reserve,and the superimposed area accounted for 23%~26% of the total area of hotspot areas in each year.The study shows that NPP in Yunnan Province has shown a fluctuating upward trend in the past 20 years,and the results can provide scientific references for vegetation monitoring and ecological environmental protection in Yunnan Province.

Key words: net primary productivity of vegetation, spatial and temporal variability, spatial autocorrelation, cold hotspot analysis, ecological function zones

CLC Number:

S718.5

QIAN Hui, ZHANG Chao, FAN Jinming, DENG Zaichun, ZHU Xiali, LI Chengrong. Spatio-Temporal Pattern Analysis of Vegetation NPP in Yunnan Province Based on Improved CASA Model[J]. Forest and Grassland Resources Research, 2023, (6): 120-128.

Figures/Tables 8

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地级行政区	2000年	2005年	2010年	2015年	2020年	均值/ [gc/(m²·a)]	年均增量/ [gc/(m²·a)]	年均增长率/ %
迪庆州	436.5	481.2	442.6	540.9	595.4	499.3	7.95	1.56
怒江州	507.9	511.8	458.3	586.3	648.2	542.5	7.02	1.23
文山州	827.5	770.9	781.4	1 041.3	989.5	882.1	8.10	0.90
曲靖市	662.9	640.9	597.1	839.0	748.5	697.7	4.28	0.61
临沧市	858.0	829.5	846.8	990.8	1015.2	908.1	7.86	0.84
昆明市	757.0	644.8	568.5	803.1	788.5	712.4	1.58	0.20
楚雄市	708.7	705.4	613.5	813.3	753.6	718.9	2.25	0.31
德宏州	1 060.4	1 172.5	1 000.2	1 226.9	1 143.0	1 120.6	4.13	0.38
保山市	840.0	896.9	815.8	945.1	918.9	883.3	3.95	0.45
普洱市	1 014.6	988.9	982.3	1 172.0	1 095.1	1 050.6	4.03	0.38
丽江市	640.6	661.3	569.6	695.6	670.7	647.6	1.51	0.23
大理州	726.3	718.0	616.8	741.5	752.1	710.9	1.29	0.17
西双版纳州	1 294.3	1 286.6	1 144.6	1 386.0	1 308.1	1 283.9	0.69	0.53
红河州	903.9	742.6	779.4	966.9	894.9	857.5	-0.45	-0.50
玉溪市	749.8	654.1	676.3	814.9	751.9	729.4	0.11	0.14
昭通市	883.5	862.8	681.8	960.7	798.5	837.5	-4.70	-0.50

统计量	2000年	2005年	2010年	2015年	2020年
Moran's I指数	0.719	0.815	0.844	0.810	0.797
Z得分	13.045	14.764	15.262	14.640	14.405
P值	0.000	0.000	0.000	0.000	0.000
预期指数	-0.008	-0.008	-0.008	-0.008	-0.008
方差	0.003	0.003	0.003	-0.008	0.003