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2000~2020年巴基斯坦土地生产力演变趋势及对气候的响应
Evolution Trend of Land Productivity and Its Response to Climate in Pakistan from 2000 to 2020

DOI: 10.12677/AG.2022.129119, PP. 1235-1246

Keywords: 巴基斯坦,土地生产力,时空变化,趋势分析,Hurst指数,相关分析,气候因素
Pakistan
, Land Productivity, Temporal and Spatial Changes, Trend Analysis, Hurst Index, Correlation Analysis, Climatic Factors

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Abstract:

土地生产力是土地重要功能之一,能够有效反映土地资源质量状况。本文选取归一化植被指数(NDVI)以及气温、降水、水汽压等气象数据,利用趋势分析、显著性检验、Hurst指数以及相关分析等方法,逐像元分析,探讨了巴基斯坦地区2000~2020年土地生产力时空变化特征、变化趋势特征以及对自然因素的响应特征,结果表明:1) 从时间上看,2000~2020年巴基斯坦年均NDVI值呈波动上升趋势,波动范围为0.157~0.217,增速为0.022/10a。从空间上看,巴基斯坦NDVI主要呈现印度河流域及中东部平原地区高,西部高原、北部山地以及西南沙漠地区低的分布特征。2) 巴基斯坦2000~2020年土地生产力改善地区远大于退化地区,其中明显改善与轻微改善的区域分别占51.62%和15.19%,严重退化与轻微退化的区域分别占1.12%和2.70%,基本稳定区域为24.37%。巴基斯坦近一半区域土地生产力变化趋势具有反持续性。土地生产力持续退化区域占1.97%、由退化到改善区域占1.84%、基本稳定区占18.35%、由改善到退化区占34.34%、持续改善区面积占比最大为37.47%、变化趋势不确定区占10.53%。3) 降水是巴基斯坦地区最显著的影响因子,对土地生产力有明显的促进作用。西北部高原地区干旱严重,降水对土地生产力促进作用十分显著,而位于印度河流域的耕地,由于绝大多数处于灌溉区,土地生产力受降水影响相对较弱。其次为潜在蒸散水汽压、最高气温、最低气温,平均气温影响最弱。
Land productivity is one of the important functions of land, which can effectively reflect the quality of land resources. In this paper, the Normalized Vegetation Index (NDVI) and meteorological data such as air temperature, precipitation and water vapor pressure are selected and analyzed by means of trend analysis, significance test, Hurst index and correlation analysis to discuss the spatial-temporal change characteristics, change trend characteristics and response characteristics to natural factors of land productivity in Pakistan from 2000 to 2020. The results showed that: 1) In terms of time, from 2000 to 2020, the average annual NDVI value of Pakistan showed a fluctuating upward trend, with a fluctuation range of 0.157~0.217 and a growth rate of 0.022/10a. Spatially, NDVI in Pakistan is high in the Indus River Basin and the central and eastern plains, and low in the western plateau, the northern mountains and the southwest desert. 2) From 2000 to 2020, the land productivity improvement areas in Pakistan were far greater than the degraded areas, of which the areas with obvious improvement and slight improvement accounted for 51.62% and 15.19% respectively, the areas with severe degradation and slight degradation accounted for 1.12% and 2.70% respectively, and the basically stable areas accounted for 24.37%. The change trend of land productivity in nearly half of Pakistan is anti sustainable. The area of continuous degradation of land productivity accounts for 1.97%, the area from degradation to improvement accounts for 1.84%, the basic stable area accounts for 18.35%, the area from improvement to degradation accounts for 34.34%, the area of continuous improvement accounts for 37.47%, and the area of uncertain change trend accounts for 10.53%. 3) Precipitation is the most significant influencing factor in Pakistan, and it has an obvious promoting effect on land productivity. The northwest plateau area is seriously

References

[1]  郭晓娜, 陈睿山, 李强, 等. 土地退化过程、机制与影响——以土地退化与恢复专题评估报告为基础[J]. 生态学报, 2019, 39(17): 6567-6575.
https://doi.org/10.5846/stxb201805231137
[2]  郭晓娜, 陈睿山, 李强, 等. IPBES土地退化与恢复驱动因素审视[J]. 华东师范大学学报(自然科学版), 2020(3): 109-118.
[3]  United Nations Convention to Combat Desertification. 2015. Dec.3/C-OP.12. https://www.unccd.int/sites/default/files/relevant-links/2017-03/Decision_3_COP_12_GM.pdf
[4]  United Nations (2017) Revised list of global Sustainable Development Goal Indicators. Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators (E/CN.3/2017/2), Annex III. https://unstats.un.org/sdgs/indicators/official%20revised%20list%20of%20global%20sdg%20indicators.pdf
[5]  United Nations (2017) SDG15.3.1. https://unstats.un.org/sdgs/metadata/
[6]  United Nations Convention to Combat Desertification (2017) Good Practice Guidance_SDG Indicator 15.3.1. https://catalogue.unccd.int/1531_Good_Practice_Guidance_SDG_Indicator_15.3.1_Version_1.0.pdf
[7]  Assennato, F., Di Leginio, M., D’Antona, M., et al. (2020) Land Degradation Assessment for Sustainable Soil Management. Italian Journal of Agronomy, 15, 299-305.
https://doi.org/10.4081/ija.2020.1770
[8]  黄豪奔, 徐海量, 林涛, 等. 2001-2020年新疆阿勒泰地区归一化植被指数时空变化特征及其对气候变化的响应[J]. 生态学报, 2022, 42(7): 2798-2809.
[9]  Tucker, C.J. (1979) Red and Photographic Infrared Linear Combination for Monitoring Vegetation. Remote Sensing of Environment, 8, 127-150.
https://doi.org/10.1016/0034-4257(79)90013-0
[10]  Hoell, A., Evans, J., Black, E., et al. (2016) A Review of Drought in the Middle East and Southwest Asia. Journal of Climate, 29, 8547-8574.
https://doi.org/10.1175/JCLI-D-13-00692.1
[11]  Adnan, S., Ullah, K., Shuanglin, L., et al. (2018) Comparison of Various Drought Indices to Monitor Drought Status in Pakistan. Climate Dynamics, 51, 1885-1899.
https://doi.org/10.1007/s00382-017-3987-0
[12]  Majeed, M., Tariq, A., Anwar, M.M., et al. (2021) Monitoring of Land Use-Land Cover Change and Potential Causal Factors of Climate Change in Jhelum District, Punjab, Pakistan, through GIS and Multi-Temporal Satellite Data. Land, 10, Article No. 1043.
https://doi.org/10.3390/land10101026
[13]  Gilani, H., Ahmad, A., Younes, I., et al. (2021) Impact Assessment of Land Cover and Land Use Changes on Soil Erosion Changes (2005-2015) in Pakistan. Land Degradation & Development, 33, 204-217.
https://doi.org/10.1002/ldr.4138
[14]  Ullah, S., Israr, M., Ahmad, S., et al. (2019) Farming Household Socio-Economic Influences on Land Degradation in District Mardan of Pakistan. Sarhad Journal of Agriculture, 35, 449-458.
https://doi.org/10.17582/journal.sja/2019/35.2.449.458
[15]  Muhammad, I., Saeed, U. and Nafees, A. (2020) Livelihood Sustainability and Land Degradation in Central Pakhtunkhwa of Pakistan. American Journal of Environmental Protection, 8, 43-48.
[16]  Niazi, T. (2003) Land Tenure, Land Use, and Land Degradation: A Case for Sustainable Development in Pakistan. The Journal of Environment & Development, 12, 275-294.
https://doi.org/10.1177/1070496503255485
[17]  Ullah, S., Ali, A., Iqbal, M., et al. (2018) Geospatial Assessment of Soil Erosion Intensity and Sediment Yield: A Case Study of Potohar Region, Pakistan. Environmental Earth Sciences, 77, Article No. 705.
https://doi.org/10.1007/s12665-018-7867-7
[18]  Holben, B.N. (2007) Characteristics of Maximum-Value Composite Images from Temporal AVHRR Data. International Journal of Remote Sensing, 7, 1417-1434.
https://doi.org/10.1080/01431168608948945
[19]  Harris, I., Osborn, T.J., Jones, P., et al. (2020) Version 4 of the CRU TS Monthly High-Resolution Gridded Multivariate Climate Dataset. Scientific Data, 7, Article No. 109.
https://doi.org/10.1038/s41597-020-0453-3
[20]  李辉霞, 周红艺, 魏兴琥. 基于RUE和NDVI的人类活动对植被干扰强度分析——以桂西北为例[J]. 中国沙漠, 2014, 34(3): 927-937.
[21]  殷贺, 李正国, 王仰麟, 等. 基于时间序列植被特征的内蒙古荒漠化评价[J]. 地理学报, 2011, 66(5): 653-661.
[22]  蔡博峰. 基于遥感的植被长时序趋势特征研究进展及评价[J]. 遥感学报, 2009, 13(6): 1170-1186.
[23]  Ali, Kuriqi, Abubaker, et al. (2019) Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method. Water, 11, Article No. 1855.
https://doi.org/10.3390/w11091855
[24]  Cai, B. and Yu, R. (2009) Advance and Evaluation in the Long Time Series Vegetation Trends Research Based on Remote Sensing. Journal of Remote Sensing, 13, 1170-1186.
[25]  Kumar Sen, P. (1968) Estimates of the Regression Coefficient Based on Kendall’s Tau. Journal of the American Statistical Association, 63, 1379-1389.
https://doi.org/10.1080/01621459.1968.10480934
[26]  Kendall, M.G. (1948) Rank Correlation Methods. 4th Edition, Griffin, London.
[27]  To?i?, I. (2004) Spatial and Temporal Variability of Winter and Summer Precipitation over Serbia and Montenegro. Theoretical and Applied Climatology, 77, 47-56.
https://doi.org/10.1007/s00704-003-0022-7
[28]  袁丽华, 蒋卫国, 申文明, 等. 2000-2010年黄河流域植被覆盖的时空变化[J]. 生态学报, 2013, 33(24): 7798-7806.
https://doi.org/10.5846/stxb201305281212
[29]  谢平, 陈广才, 雷红富. 基于Hurst系数的水文变异分析方法[J]. 应用基础与工程科学学报, 2009, 17(1): 32-39.
[30]  鲁晖, 董敬儒, 贺思嘉, 等. 2000-2017年河西地区山地-绿洲-荒漠系统植被变化趋势与可持续性分析[J]. 兰州大学学报(自然科学版), 2021, 57(1): 99-108.
[31]  严恩萍, 林辉, 党永峰, 等. 2000-2012年京津风沙源治理区植被覆盖时空演变特征[J]. 生态学报, 2014, 34(17): 5007-5020.
https://doi.org/10.5846/stxb201305251179
[32]  潘竟虎, 黄克军, 李真. 2001-2010年疏勒河流域植被净初级生产力时空变化及其与气候因子的关系[J]. 生态学报, 2017, 37(6): 1888-1899.
https://doi.org/10.5846/stxb201511012207
[33]  Rehman, A., Jingdong, L., Chandio, A.A., et al. (2017) Livestock Production and Population Census in Pakistan: Determining Their Relationship with Agricultural GDP Using Econometric Analysis. Information Processing in Agriculture, 4, 168-177.
https://doi.org/10.1016/j.inpa.2017.03.002

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