滇中地区地表温度时空分布及其驱动因子分析

doi:10.16088/j.issn.1001-6600.2024053001

Abstract

Abstract: Surface temperature (LST) is an important factor affecting the energy exchange and water cycle between land and atmosphere, and plays a key role in monitoring drought, freezing damage, forest fire prevention and other disasters. Based on the LST data from 2000 to 2020, the spatial distribution characteristics and variation trend of annual, seasonal, monthly and diurnal LST in central Yunnan were analyzed by means of GIS spatial analysis, multi-ring buffer zone and geographic detector, and the key influencing factors of annual LST were discussed in combination with multi-source remote sensing data. The results show that: 1) The spatial distribution of annual average LST, annual average daytime and annual average night LST was lower in northeastern Yunnan and higher in southwestern Yunnan, all showed a warming trend, and the annual average night LST changes at the highest rate (0.043 4 ℃·a^-1); The seasonal variation rates of annual LST were summer >autumn >spring >winter; The average annual LST showed a strong symmetry pattern with June as the midpoint, with the lowest value in December and the highest value in june. 2) Air temperature, DEM, DSR, DNMI and NDVI were the main influencing factors of LST, and the explanatory power of air temperature and DEM was extremely enhanced when they interacted with other influencing factors. With every 100 m of elevation increased in central Yunnan, the annual average, annual average daytime and annual average night LST decreased by 0.48, 0.46 and 0.49 ℃, respectively. The average annual LST of different underlying surfaces was construction land > cultivated land > grassland > woodland > water. The intensity of urban heat island effect in the selected ring area was Mengzi City > Chuxiong City > Hongta District > Qilin District, while Wuhua District belongs to the urban cold island effect. The spatial pattern analysis of land surface temperature in central Yunnan can provide some theoretical support for the planning of regional agriculture and fire protection undertakings.

Key words: central Yunnan region, land surface temperature, spatial distribution, geographic detector, hot (cold) island effect, impact factor

CLC Number: P423.3

LIAO Chaolian, ZHOU Pengfei, YE Jiangxia, ZHOU Ruliang. Temporal and Spatial Distribution of Land Surface Temperature and Its Driving Factors in Central Yunnan[J].Journal of Guangxi Normal University(Natural Science Edition), 2025, 43(1): 185-200.

References

[1] 吴骅,李秀娟,李召良,等.高光谱热红外遥感:现状与展望[J].遥感学报,2021,25(8):1567-1590. DOI: 10.11834/jrs.20211306.
[2] ANDERSON M C, NORMAN J M, KUSTAS W P, et al. A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales[J]. Remote Sensing of Environment, 2008, 112(12): 4227-4241. DOI: 10.1016/j.rse.2008.07.009.
[3] 李召良,段四波,唐伯惠,等.热红外地表温度遥感反演方法研究进展[J].遥感学报,2016,20(5):899-920. DOI: 10.11834/jrs.20166192.
[4] 张伟伟,贾若愚,田明,等.利用ECOSTRESS探究LCZ类间和类内城市热环境日动态变化[J].地球信息科学学报,2024,26(3):679-692. DOI: 10.12082/dqxxkx.2024.230511.
[5] IPCC. AR6 synthesis report: climate change 2023[R]. Geneva: IPCC, 2023. DOI: 10.59327/IPCC/AR6-9789291691647.
[6] 王冰,李启权,罗琳,等.1981—2011年川南山区地温和气温的变化特征[J].干旱区地理,2019,42(6):1322-1329. DOI: 10.12118/j.issn.1000-6060.2019.06.10.
[7] 肖尧,马明国,闻建光,等.复杂地表地表温度反演研究进展[J].遥感技术与应用,2021,36(1):33-43. DOI: 10.11873/j.issn.1004-0323.2021.1.0033.
[8] 李元征,尹科,周宏轩,等.基于遥感监测的城市热岛研究进展[J].地理科学进展,2016,35(9):1062-1074. DOI: 10.18306/dlkxjz.2016.09.002.
[9] 唐荣林,王晟力,姜亚珍,等.基于地表温度-植被指数三角/梯形特征空间的地表蒸散发遥感反演综述[J].遥感学报,2021,25(1):65-82. DOI: 10.11834/jrs.20210388.
[10] 毛克彪,严毅博,赵冰,等.中国地表温度时空变化及驱动因素分析[J].灾害学,2023,38(2):60-73. DOI: 10.3969/j.issn.1000-811X.2023.02.010.
[11] 纪王迪,黄晓军,包微,等.关中地区人类活动强度与地表温度的时空关联特征及其驱动作用[J].干旱区地理,2024,47(6):967-979. DOI: 10.12118/j.issn.1000-6060.2023.266.
[12] 康利刚,曹生奎,曹广超,等.青海湖流域地表温度时空变化特征研究[J].干旱区地理,2023,46(7):1084-1097. DOI: 10.12118/j.issn.1000-6060.2022.525.
[13] MUSHORE T D, MUTANGA O, ODINDI J. Estimating urban LST using multiple remotely sensed spectral indices and elevation retrievals[J]. Sustainable Cities and Society, 2022, 78: 103623. DOI: 10.1016/j.scs.2021.103623.
[14] 李斌,王慧敏,秦明周,等.NDVI、NDMI与地表温度关系的对比研究[J].地理科学进展,2017,36(5):585-596. DOI: 10.18306/dlkxjz.2017.05.006.
[15] 张秀,王旭红,郑玉蓉,等.气溶胶光学厚度和不透水地表覆盖度对城市热岛强度的影响:以关中地区为例[J].生态学报,2021,41(22):8965-8976. DOI: 10.5846/stxb202102210480.
[16] 王斐,覃志豪,樊伟,等.云下地表温度与辐射变化关系的定量分析[J].遥感学报,2019,23(6):1113-1122. DOI: 10.11834/jrs.20198151.
[17] 周桃勇,王正海,秦昊洋,等.地形效应校正的遥感地热异常提取[J].遥感学报,2020,24(3):265-276. DOI: 10.11834/jrs.20208299.
[18] 王万同,王卷乐,杜佳.基于ETM+与MODIS数据融合的伊洛河流域地表蒸散估算[J].地理研究,2013,32(5):817-827.
[19] 叶钰,秦建新,胡顺石.长沙市热岛效应时空特征变化研究[J].地球信息科学学报,2017,19(4):518-527. DOI: 10.3969/j.issn.1560-8999.2017.04.010.
[20] 张祎.长江流域土地利用/覆被变化对地表温度的影响[D].武汉:中国地质大学,2018.
[21] 康紫薇,张正勇,刘琳,等.基于MODIS的新疆地表温度时空变化特征分析[J].地理研究,2022,41(4):997-1017. DOI: 10.11821/dlyj020210232.
[22] 孟翔飞,魏虹,谢小红,等.基于MODIS数据的云南地表温度空间分布特征[J].西南大学学报(自然科学版),2010,32(12):154-157. DOI: 10.13718/j.cnki.xdzk.2010.12.015.
[23] 陈晶,张天力.滇中高原地区干旱特性及风险分析[J].人民长江,2024,55(6):114-121. DOI: 10.16232/j.cnki.1001-4179.2024.06.016.
[24] 魏莉莉,蒋求名,马捷,等.昆明主城区土地覆盖时空分布及地表温度响应[J].农机化研究,2023,45(2):56-61. DOI: 10.13427/j.cnki.njyi.2023.02.042.
[25] 周纪,张晓东,唐文彬,等.中国陆域及周边逐日1 km全天候地表温度数据集(TRIMS LST;2000-2022)[DB/OL].(2024-01-19)[2024-05-28].https://www.doi.org/10.11888/Meteoro.tpdc.271252. DOI: 10.11888/Meteoro.tpdc.271252.
[26] 文刚,高孟平,高振宇,等.多因子协同作用下的云南省山火风险评估[J].广东电力,2022,35(4):96-102. DOI: 10.3969/j.issn.1007-290X.2022.004.012.
[27] 胡李发,谢元礼,崔思颖,等.关中平原城市群夏季城市热岛特征及驱动力[J].中国环境科学,2021,41(8):3842-3852. DOI: 10.19674/j.cnki.issn1000-6923.20210331.016.
[28] 高吉喜,史园莉,张宏伟,等.中国区域250米归一化植被指数数据集(2000-2023)[DB/OL].(2024-05-20)[2024-05-28].https://doi.org/10.11888/Terre.tpdc.300328. DOI: 10.11888/Terre.tpdc.300328.
[29] 郑超磊,贾立,赵天杰.全球1公里分辨率地表土壤水分数据集(2000-2020)[DB/OL].(2023-07-01)[2024-07-09].https://doi.org/10.11888/Terre.tpdc.300328. DOI: 10.11888/RemoteSen.tpdc.272760.
[30] PENG S Z. High-spatial-resolution monthly temperatures dataset over China during 1901-2017[DB/OL]. (2019-05-17)[2024-05-28]. https://www.doi.org/10.5281/zenodo.3185722. DOI: 10.5281/zenodo.3185722.
[31] 彭守璋.中国1km分辨率逐月平均气温数据集(1901-2023)[DB/OL].(2024-07-17)[2024-05-28].https://www.doi.org/10.11888/Meteoro.tpdc.270961. DOI: 10.11888/Meteoro.tpdc.270961.
[32] ZHANG X T, WANG D D, LIU Q, et al. An operational approach for generating the global land surface downward shortwave radiation product from MODIS data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(7): 4636-4650. DOI: 10.1109/TGRS.2019.2891945.
[33] WU Y Z, SHI K F, CHEN Z Q, et al. Developing improved time-series DMSP-OLS-like data (1992-2019) in China by integrating DMSP-OLS and SNPP-VIIRS[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 1-14. DOI: 10.1109/TGRS.2021.3135333.
[34] WEI J, LI Z Q. ChinaHighPM2.5: big data seamless 1 km ground-level PM2.5 dataset for China (2000-present)[DB/OL]. (2019-11-12)[2024-05-28]. https://doi.org/10.5281/zenodo.3539349. DOI: 10.5281/zenodo.3539349.
[35] 管延龙,王让会,李成,等.基于MODIS数据的天山区域地表温度时空特征[J].应用生态学报,2015,26(3):681-688. DOI: 10.13287/j.1001-9332.20141223.027.
[36] 王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134. DOI: 10.11821/dlxb201701010.
[37] 朱柏露,杨奇勇,谢运球,等.漓江流域土地石漠化空间分布及驱动因子分析[J].广西师范大学学报(自然科学版),2021,39(3):139-150. DOI: 10.16088/j.issn.1001-6600.2020052702.
[38] 谢玲,陈展图,蒋瑜,等.基于InVEST&GEO-detectors模型的会仙湿地生境质量变化及影响因素研究[J].广西师范大学学报(自然科学版),2023,41(5):180-190. DOI: 10.16088/j.issn.1001-6600.2022071204.
[39] LI Q X, SUN W B, HUANG B Y, et al. Consistency of global warming trends strengthened since 1880s[J]. Science Bulletin, 2020, 65(20): 1709-1712. DOI: 10.1016/j.scib.2020.06.009.
[40] 王佳津,孟耀斌,张朝,等.云南省Palmer旱度模式的建立:2010年干旱灾害特征分析[J].自然灾害学报,2012,21(1):190-197. DOI: 10.13577/j.jnd.2012.0129.
[41] ZHANG B P, YAO Y H. Implications of mass elevation effect for the altitudinal patterns of global ecology[J]. Journal of Geographical Sciences, 2016, 26(7): 871-877. DOI: 10.1007/s11442-016-1303-2.
[42] WEI B C, BAO Y H, YU S, et al. Analysis of land surface temperature variation based on MODIS data a case study of the agricultural pastural ecotone of northern China[J]. International Journal of Applied Earth Observation and Geoinformation, 2021, 100: 102342. DOI: 10.1016/J.JAG.2021.102342.
[43] 张沁,张守平,杨清伟.重庆市悦来新城土地利用/覆被变化对地表温度的影响[J].生态学杂志,2024,43(1):206-215. DOI: 10.13292/j.1000-4890.202401.010.
[44] 刘勇洪,房小怡,张硕,等.京津冀城市群热岛定量评估[J].生态学报,2017,37(17):5818-5835. DOI: 10.5846/stxb201606031074.
[45] DEO R C, ŞAHIN M. Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland[J]. Renewable and Sustainable Energy Reviews, 2017, 72: 828-848. DOI: 10.1016/j.rser.2017.01.114.
[46] 程清平,王平,徐强.1960—2013年云南地面温度时空变化特征[J].水土保持研究,2017,24(6):111-121,397. DOI: 10.13869/j.cnki.rswc.2017.06.018.
[47] 田浩,刘琳,张正勇,等.2001—2020年中国地表温度时空分异及归因分析[J].地理学报,2022,77(7):1713-1729. DOI: 10.11821/dlxb202207010.
[48] 赵冰,毛克彪,蔡玉林,等.中国地表温度时空演变规律研究[J].国土资源遥感,2020,32(2):233-240. DOI: 10.6046/gtzyyg.2020.02.30.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 10

[1]	HE Jing, FENG Yuanliu, SHAO Jingwen. Research Progress on Multi-source Data Fusion Based on CiteSpace[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(5): 13 -27 .
[2]	LIU Changping, SONG Shuxiang, JIANG Pinqun, CEN Mingcan. Differential Passive N-path Filter Based on Switched Capacitors[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(5): 52 -60 .
[3]	WANG Shuying, LU Yuxiang, DONG Shutong, CHEN Mo, KANG Bingya, JIANG Zhanglan, SU Chengyuan. Research Progress on the Propagation Process and Control Technology of ARGs in Wastewater[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 1 -15 .
[4]	ZHONG Qiao, CHEN Shenglong, TANG Congcong. Hydrogel Technology for Microalgae Collection: Status Overview, Challenges and Development Analysis[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 16 -29 .
[5]	ZHAI Siqi, CAI Wenjun, ZHU Su, LI Hanlong, SONG Hailiang, YANG Xiaoli, YANG Yuli. Dynamic Relationship Between Reverse Solute Flux and Membrane Fouling in Forward Osmosis[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 30 -39 .
[6]	ZHENG Guoquan, QIN Yongli, WANG Chenxiang, GE Shijia, WEN Qianmin, JIANG Yongrong. Stepwise Precipitation of Heavy Metals from Acid Mine Drainage and Mineral Formation in Sulfate-Reducing Anaerobic Baffled Reactor System[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 40 -52 .
[7]	LIU Yang, ZHANG Yijie, ZHANG Yan, LI Ling, KONG Xiangming, LI Hong. Current Status and Trends of Algal Coagulation Elimination Technology in Drinking Water Treatment: a Visual Analysis Based on CiteSpace[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 53 -66 .
[8]	TIAN Sheng, CHEN Dong. A Joint Eco-driving Optimization Research for Connected Fuel Cell Hybrid Vehicle via Deep Reinforcement Learning[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 67 -80 .
[9]	CHEN Xiufeng, WANG Chengxin, ZHAO Fengyang, YANG Kai, GU Kexin. A Single Intersection Signal Control Method Based on Improved DQN Algorithm[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 81 -88 .
[10]	LI Xin, NING Jing. Online Assessment of Transient Stability in Power Systems Based on Spatiotemporal Feature Fusion[J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(6): 89 -100 .

Temporal and Spatial Distribution of Land Surface Temperature and Its Driving Factors in Central Yunnan

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 6

Metrics

Comments

Recommended 10

[1]	GUO Yongli, QUAN Xiqiang, WU Qing. Pollution Characteristics and Health Risk Assessment of Volatile Organic Compounds of Typical Karst Groundwater Source in North China [J]. Journal of Guangxi Normal University(Natural Science Edition), 2020, 38(6): 102-113.
[2]	LI Xuanjing, LI Shengqiang, WANG Guohai, SHI Zepan, ZHOU Qihai. Diversity and Spatial Distribution of Birds in Guangxi Maoershan National Nature Reserve:Based on Line Transect Surveys and Camera Traps [J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(2): 143-151.
[3]	LI Jianhong, MENG Xinyuan, ZHAI Luxin, WANG Yue. Analysis of the Trend of Extreme Continuous Precipitation underClimate Change Condition in Guangxi,China, from 1951 to 2006 [J]. Journal of Guangxi Normal University(Natural Science Edition), 2016, 34(1): 187-196.
[4]	ZHANG Yong-xiang, CAI De-suo, YI Ran. Ecological Fragility and Impact Factor of Water-level-fluctuation of the Qingshitan Reservoir,Guilin,China [J]. Journal of Guangxi Normal University(Natural Science Edition), 2012, 30(4): 156-160.
[5]	XU Jiu-cheng, LI Xiao-yan, LI Shuang-qun, ZHANG Ling-jun. Feature Images Retrieval Method of Tolerance Granular-basedMulti-level Texture [J]. Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(1): 186-187.
[6]	WANG Xiu-xin, QIN Li-mei, NONG Jing-hui, LIANG Zong-jin, ZHU Qi-jiang. Land Surface Temperature Retrieval with Mono-window Algorithm in Karst City [J]. Journal of Guangxi Normal University(Natural Science Edition), 2010, 28(3): 10-14.