基于Sentinel-2卫星影像的乌鲁木齐市及典型光伏电站地表环境时空演变特征研究

doi:10.12118/j.issn.1000-6060.2025.634

干旱区地理 ›› 2026, Vol. 49 ›› Issue (10): 2065-2078.doi: 10.12118/j.issn.1000-6060.2025.634 cstr: 32274.14.ALG2025634

基于Sentinel-2卫星影像的乌鲁木齐市及典型光伏电站地表环境时空演变特征研究

周腾¹(), 刘琼¹(), 陈勇航¹, 何婷¹, 吴建国², 刘瑞², 修强², 许赟红¹, 邵伟玲³, 韩雪云³

¹ 东华大学环境科学与工程学院，上海 201620
² 华能新疆能源开发有限公司，新疆乌鲁木齐 830018
³ 新疆维吾尔自治区气候中心，新疆乌鲁木齐 830002

收稿日期:2025-10-11 修回日期:2025-11-05 出版日期:2026-10-25 发布日期:2026-10-26
通讯作者: 刘琼（1987-），女，博士，副教授，主要从事大气遥感等方面的研究. E-mail: liuqiong@dhu.edu.cn
作者简介:周腾（2001-），男，硕士研究生，主要从事地理遥感等方面的研究. E-mail: zt2035046586@163.com
作者贡献
论文构思：刘琼、周腾；数据管理：周腾；规范分析：周腾；获取资助：陈勇航、刘琼、邵伟玲、韩雪云；调查研究：周腾；方法设计：刘琼、周腾；项目管理：刘琼、陈勇航；提供资源：许赟红、何婷、吴建国、刘瑞、修强；软件编程：周腾；监督指导：刘琼；验证复核：周腾、刘琼；可视化：周腾；初稿撰写：周腾；修订编辑：周腾、刘琼。
基金资助:
上海合作组织科技伙伴计划及国际科技合作计划项目(2022E01047);国家自然科学基金(41905131)

Spatiotemporal evolution characteristics of surface environment in Urumqi City and typical photovoltaic power stations based on Sentinel-2 satellite imagery

ZHOU Teng¹(), LIU Qiong¹(), CHEN Yonghang¹, HE Ting¹, WU Jianguo², LIU Rui², XIU Qiang², XU Yunhong¹, SHAO Weiling³, HAN Xueyun³

¹ College of Environmental Science and Engineering, Donghua University, Shanghai 201620, China
² Huaneng Xinjiang Energy Development Co. Ltd., Urumqi 830018, Xinjiang, China
³ Climate Center of Xinjiang Uygur Autonomous Region, Urumqi 830002, Xinjiang, China

Received:2025-10-11 Revised:2025-11-05 Published:2026-10-25 Online:2026-10-26

摘要/Abstract

摘要：

乌鲁木齐市作为我国干旱区城市地表环境演变的典型代表地区，其快速城市化进程与大规模光伏建设对区域关键地表参数产生了显著影响。基于2019—2024年Sentinel-2号卫星10 m分辨率遥感影像，反演了乌鲁木齐市地表反照率（albedo）与归一化植被指数（NDVI），系统分析了二者的时空变化特征，并进一步以典型光伏电站（米东3.5 GW光伏区）为例，探究光伏设施对地表albedo的影响。结果表明：（1） 2019—2024年乌鲁木齐市整体地表albedo呈逐年上升趋势，年均增长0.0197；其中，2022年受新疆维吾尔自治区持续性极端干旱事件影响，地表albedo急剧上升，年际增幅达0.077，较上年上升21.9%。地表albedo季节特征显著，冬季受积雪覆盖影响达到全年最高值（0.516）；夏季因植被生长旺盛处于全年最低水平（0.280）。空间上，地表albedo显著升高区域主要分布在西南山区和东部荒地，北部荒地地表albedo变化相对较小。（2）同期乌鲁木齐市NDVI整体呈下降趋势，其季节变化与地表albedo相反，冬季最低（0.024），夏季最高（0.142）。2022年受干旱影响植被退化最为显著，NDVI下降38.3%，负距平范围明显扩大，主要分布于城区周边、西南山区和东部荒地。（3）米东3.5 GW光伏区2024年建成后，光伏板覆盖的核心区地表albedo较建站前下降11.6%，形成明显的“低albedo带”；各缓冲区地表albedo也呈现不同程度下降，但总体降幅（平均3.3%）小于光伏核心区。

关键词: 地表反照率, 归一化植被指数, 空间格局, 光伏电站, 缓冲区

Abstract:

As a representative of urban surface environment evolution in arid regions of China, Urumqi City has experienced rapid urbanization and extensive photovoltaic construction, significantly affecting key surface parameters. Utilizing 10-m resolution remote sensing images from the Sentinel-2 satellite spanning 2019 to 2024, this study retrieved the surface albedo and normalized difference vegetation index (NDVI) of Urumqi City, analyzed their spatiotemporal variation characteristics, and examined the effects of photovoltaic facilities on surface albedo using the Midong 3.5 GW photovoltaic area as a case study. The results revealed the following: (1) From 2019 to 2024, Urumqi City’s overall albedo exhibited a year-by-year upward trend, with an average annual increase of 0.0197. In 2022, influenced by a prolonged extreme drought in Xinjiang, albedo rose sharply by 0.077, marking a 21.9% increase from the previous year. Seasonal analysis showed that winter had the highest albedo value of the year (0.516) due to snow cover, whereas summer recorded the lowest (0.280) due to vigorous vegetation growth. Spatially, significant increases in albedo were mainly observed in the foothills of the Tianshan Mountains in the southwest and the eastern wasteland, with smaller changes in the northern wasteland. (2) During the same period, the NDVI of Urumqi City showed an overall downward trend. Its seasonal variation was opposite that of albedo, with the lowest value in winter (0.024) and the highest in summer (0.142). In 2022, vegetation degradation peaked due to drought, with NDVI decreasing by 38.3% and the negative anomaly range significantly expanding, primarily affecting the areas around the city, the southwestern mountainous region, and the eastern wasteland. (3) Following the completion of the 3.5 GW photovoltaic area in Midong in 2024, the albedo in the core area covered by photovoltaic panels decreased by 11.6% compared to pre-construction levels, forming a distinct “low albedo zone”. Albedo in surrounding buffer zones also declined, though the overall average decline (3.3%) was less than that observed in the photovoltaic core area.

Key words: surface albedo, normalized difference vegetation index, spatial pattern, photovoltaic power station, buffer zone

周腾, 刘琼, 陈勇航, 何婷, 吴建国, 刘瑞, 修强, 许赟红, 邵伟玲, 韩雪云. 基于Sentinel-2卫星影像的乌鲁木齐市及典型光伏电站地表环境时空演变特征研究[J]. 干旱区地理, 2026, 49(10): 2065-2078.

ZHOU Teng, LIU Qiong, CHEN Yonghang, HE Ting, WU Jianguo, LIU Rui, XIU Qiang, XU Yunhong, SHAO Weiling, HAN Xueyun. Spatiotemporal evolution characteristics of surface environment in Urumqi City and typical photovoltaic power stations based on Sentinel-2 satellite imagery[J]. Arid Land Geography, 2026, 49(10): 2065-2078.

图/表 18

图1

表1

表2

图2

表3

图3

图4

图5

图6

图7

图8

图9

图10

图11

图12

图13

图14

图15

参考文献 32

[1]	邓文彬, 翟春春. 乌鲁木齐市时空扩张变化及驱动力分析[J]. 绿色科技, 2023, 25(7): 241-246, 252.
	[Deng Wenbin, Zhai Chunchun. Analysis of spatio-temporal expansion changes and driving forces of Urumqi[J]. Journal of Green Science and Technology, 2023, 25(7): 241-246, 252. ]
[2]	马丽莎, 郑江华, 彭建, 等. 新疆生态脆弱性特征及其驱动力[J]. 生态学报, 2024, 44(20): 9053-9066.
	[Ma Lisha, Zheng Jianghua, Peng Jian, et al. Research on the characteristics and driving forces of ecological vulnerability in Xinjiang[J]. Acta Ecologica Sinica, 2024, 44(20): 9053-9066. ]
[3]	王福红, 夏咏. 干旱区主要农作物生产时空格局演化及影响因素分析--以新疆地区为例[J]. 干旱区地理, 2025, 48(3): 444-454. doi: 10.12118/j.issn.1000-6060.2024.201
	[Wang Fuhong, Xia Yong. Spatio-temporal pattern evolution and influencing factors of main crops production in arid region: A case of Xinjiang[J]. Arid Land Geography, 2025, 48(3): 444-454. ] doi: 10.12118/j.issn.1000-6060.2024.201
[4]	陈杨杨. 典型地表覆被变化对地表反照率的影响[D]. 阜新: 辽宁工程技术大学, 2023.
	[Chen Yangyang. Effect of typical ground cover changes on surface albedo[D]. Fuxin: Liaoning Technical University, 2023. ]
[5]	许赟红, 刘琼, 陈勇航, 等. 新疆及周边中亚地区土地覆盖变化对地表反照率的影响[J]. 干旱区研究, 2024, 41(10): 1649-1661. doi: 10.13866/j.azr.2024.10.04
	[Xu Yunhong, Liu Qiong, Chen Yonghang, et al. Impact of land cover variations on surface albedo in Xinjiang and its surrounding Central Asian region[J]. Arid Zone Research, 2024, 41(10): 1649-1661. ] doi: 10.13866/j.azr.2024.10.04
[6]	刘福寿, 赵锐锋, 陈喜东, 等. 城市扩张与植被变化的时空耦合特征及影响因素--以赣州市为例[J]. 长江流域资源与环境, 2025, 34(8): 1754-1766.
	[Liu Fushou, Zhao Ruifeng, Chen Xidong, et al. Spatiotemporal coupling characteristics and influencing factors of urban expansion and vegetation change: A case study of Ganzhou City[J]. Resources and Environment in the Yangtze Basin, 2025, 34(8): 1754-1766. ]
[7]	尹霞. 贵州地区的植被变化对地表反照率的影响研究[D]. 贵阳: 贵州师范大学, 2024.
	[Yin Xia. A study on the impact of vegetation changes on albedo in Guizhou region[D]. Guiyang: Guizhou Normal University, 2024. ]
[8]	石磊, 苟志文, 张东东. 2001-2020年青藏高原植被界限变化分析[J]. 草业科学, 2025, 42(6): 1437-1448.
	[Shi Lei, Gou Zhiwen, Zhang Dongdong. Vegetation boundary changes on the Tibetan Plateau from 2001 to 2020[J]. Pratacultural Science, 2025, 42(6): 1437-1448. ]
[9]	侯春华, 李富平, 何宝杰, 等. 地表反照率和植被覆盖度对矿区热环境的影响[J]. 哈尔滨工业大学学报, 2022, 54(12): 117-126.
	[Hou Chunhua, Li Fuping, He Baojie, et al. Influence of surface albedo and vegetation fractional coverage on thermal environment of mining area[J]. Journal of Harbin Institute of Technology, 2022, 54(12): 117-126. ]
[10]	吕雪, 王旭升, 吕学文. 基于Landsat遥感数据新疆某煤炭矿区沙漠化监测分析[J]. 绿色科技, 2024, 26(10): 45-52.
	[Lü Xue, Wang Xusheng, Lü Xuewen. Monitoring and analysis of desertification in a coal mining area in Xinjiang based on Landsat remote sensing data[J]. Journal of Green Science and Technology, 2024, 26(10): 45-52. ]
[11]	陈淋淋, 刘绥华, 邓玲玲, 等. 基于MODIS数据探讨自然因子和人为因子对贵州省地表反照率演变的贡献[J]. 北京大学学报(自然科学版), 2025, 61(4): 719-732.
	[Chen Linlin, Liu Suihua, Deng Lingling, et al. Assessing the contribution of natural factors and human factors to land surface albedo changes in Guizhou Province using MODIS data[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2025, 61(4): 719-732. ]
[12]	彭燕, 何国金, 张兆明, 等. 青藏高原30 m空间分辨率年度NDVI和FVC合成产品[J]. 中国科学数据(中英文网络版), 2025, 10(2): 148-163.
	[Peng Yan, He Guojin, Zhang Zhaoming, et al. Annual NDVI and FVC product with 30 m spatial resolution over Qinghai-Tibetan Plateau[J]. China Scientific Data, 2025, 10(2): 148-163. ]
[13]	刘雅婧, 王丹阳, 常旭, 等. 光伏电站建设对西北荒漠区生态环境的影响研究进展[J]. 中国水土保持科学(中英文), 2025, 23(2): 9-17.
	[Liu Yajing, Wang Danyang, Chang Xu, et al. Research progress in the impact of photovoltaic power station construction on the ecological environment of the desert region of northwest China[J]. Science of Soil and Water Conservation, 2025, 23(2): 9-17. ]
[14]	王怡雯, 马瑶瑶, 史培军, 等. 干旱区光伏电站运营对局地生态环境的影响[J]. 干旱区研究, 2024, 41(8): 1423-1433. doi: 10.13866/j.azr.2024.08.16
	[Wang Yiwen, Ma Yaoyao, Shi Peijun, et al. The impact of photovoltaic power plant operation on local ecological environments in arid areas[J]. Arid Zone Research, 2024, 41(8): 1423-1433. ] doi: 10.13866/j.azr.2024.08.16
[15]	崔杨, 陈正洪. 光伏电站对局地气候的影响研究进展[J]. 气候变化研究进展, 2018, 14(6): 593-601.
	[Cui Yang, Chen Zhenghong. Research progresses of the impacts of photovoltaic power plants on local climate[J]. Climate Change Research, 2018, 14(6): 593-601. ]
[16]	尚小伟, 王云正, 霍毅, 等. 荒漠集中式光伏电站的气候生态影响机制与植被恢复模式[J]. 中国水土保持科学(中英文), 2025, 23(1): 10-20.
	[Shang Xiaowei, Wang Yunzheng, Huo Yi, et al. Climate ecological impact mechanism and vegetation restoration modes of desert centralized photovoltaic power stations[J]. Science of Soil and Water Conservation, 2025, 23(1): 10-20. ]
[17]	Xia Z L, Li Y J, Zhang W, et al. Solar photovoltaic program helps turn deserts green in China: Evidence from satellite monitoring[J]. Journal of Environmental Management, 2022, 324: 116338, doi: 10.1016/j.jenvman.2022.116338.
[18]	Xu Z J, Li Y, Qin Y Z, et al. A global assessment of the effects of solar farms on albedo, vegetation, and land surface temperature using remote sensing[J]. Solar Energy, 2024, 268: 112198, doi: 10.1016/j.solener.2023.112198.
[19]	龚春丽. 阿克苏地区土地利用变化的自然资本及生态系统服务价值核算[D]. 阿拉尔: 塔里木大学, 2021.
	[Gong Chunli. Calculation of natural and ecosystem service value of land use change in Aksu area[D]. Alaer: Tarim University, 2021. ]
[20]	阴瑜鑫. 西北五省省会城市热岛效应特征及预测研究[D]. 兰州: 西北师范大学, 2023.
	[Yin Yuxin. Study on the characteristics and prediction of urban heat island effect in the capital cities of five northwestern provinces[D]. Lanzhou: Northwest Normal University, 2023. ]
[21]	Feng Q L, Niu B W, Ren Y, et al. A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020[J]. Scientific Data, 2024, 11(1): 198, doi: 10.1038/s41597-024-02-994-x. pmid: 38351164
[22]	Brown C F, Brumby S P, Guzder-Williams B, et al. Dynamic world, near real-time global 10 m land use land cover mapping[J]. Scientific Data, 2022, 9(1): 251, doi: 10.1038/s41597-022-01307-4.
[23]	赵聪聪, 闻建光, 游冬琴, 等. 高分辨率地表反照率遥感估算研究进展[J]. 遥感学报, 2023, 27(3): 724-737.
	[Zhao Congcong, Wen Jianguang, You Dongqin, et al. Remote sensing retrieval of high-spatial-resolution land surface albedo[J]. National Remote Sensing Bulletin, 2023, 27(3): 724-737. ] doi: 10.11834/jrs.20231732
[24]	Lin X W, Wu S B, Chen B, et al. Estimating 10 m land surface albedo from Sentinel-2 satellite observations using a direct estimation approach with Google Earth Engine[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2022, 194: 1-20. doi: 10.1016/j.isprsjprs.2022.09.016
[25]	韦鑫海, 张贇贇, 孙少波, 等. 青藏高原生长季植被对气候变化的响应特征[J]. 地球与环境, 2025, 53(5): 631-642.
	[Wei Xinhai, Zhang Yunyun, Sun Shaobo, et al. The response characteristics of vegetation to climate change of the growing season on the Tibetan Plateau[J]. Earth and Environment, 2025, 53(5): 631-642. ] doi: 10.3724/EE.1672-9250.2025.53.033
[26]	吴汤婷, 罗馨语, 超能芳, 等. 基于GNSS垂直位移量化分析新疆干旱特征[J]. 地球物理学报, 2025, 68(8): 3050-3068.
	[Wu Tangting, Luo Xinyu, Chao Nengfang, et al. Quantitative analysis of drought characteristics in Xinjiang based on GNSS vertical displacements[J]. Chinese Journal of Geophysics, 2025, 68(8): 3050-3068. ]
[27]	吴秀兰, 程贺前, 佟欣怡, 等. 新疆天山山区植被变化对气象干旱的响应[J]. 干旱区地理, 2025, 48(6): 985-994. doi: 10.12118/j.issn.1000-6060.2024.536
	[Wu Xiulan, Cheng Heqian, Tong Xinyi, et al. Response of vegetation changes to meteorological drought in Tianshan Mountains, Xinjiang[J]. Arid Land Geography, 2025, 48(6): 985-994. ] doi: 10.12118/j.issn.1000-6060.2024.536
[28]	陈珍, 蔡朝朝, 马楠, 等. 2001-2023年新疆NDVI时空格局与驱动力分析[J]. 干旱区研究, 2025, 42(5): 922-932. doi: 10.13866/j.azr.2025.05.14
	[Chen Zhen, Cai Zhaozhao, Ma Nan, et al. Spatial-temporal pattern and driving force analysis of NDVI in Xinjiang from 2001 to 2023[J]. Arid Zone Research, 2025, 42(5): 922-932. ] doi: 10.13866/j.azr.2025.05.14
[29]	刘雅洁, 郭金停, 王铁娟. 西鄂尔多斯地区植被NDVI时空变化及其对气温和降水的响应[J]. 内蒙古师范大学学报(自然科学版), 2023, 52(6): 559-567.
	[Liu Yajie, Guo Jinting, Wang Tiejuan. Spatiotemporal variation of the NDVI and its responses to temperature and precipitation in west ordos[J]. Journal of Inner Mongolia Normal University (Natural Science Edition), 2023, 52(6): 559-567. ]
[30]	马森, 张代青, 张惠, 等. 塔里木河流域NDVI时空变化特征及其影响因素分析[J]. 高原山地气象研究, 2023, 43(4): 76-83.
	[Ma Sen, Zhang Daiqing, Zhang Hui, et al. Spatiotemporal variation characteristics and influencing factors analysis of NDVI in Tarim River Basin[J]. Plateau and Mountain Meteorology Research, 2023, 43(4): 76-83. ]
[31]	Li Z C, Zhao Y Y, Luo Y, et al. A comparative study on the surface radiation characteristics of photovoltaic power plant in the Gobi desert[J]. Renewable Energy, 2022, 182: 764-771. doi: 10.1016/j.renene.2021.10.054
[32]	杨丽薇, 高晓清, 吕芳, 等. 光伏电站对格尔木荒漠地区太阳辐射场的影响研究[J]. 太阳能学报, 2015, 36(9): 2160-2166.
	[Yang Liwei, Gao Xiaoqing, Lü Fang, et al. Study on the impact of large solar farm on radiation field in desert areas of Golmud[J]. Acta Energiae Solaris Sinica, 2015, 36(9): 2160-2166. ]

波段	分辨率/m	波长/nm	波段信息
B1	60	443	海岸气溶胶波段
B2	10	490	蓝光波段
B3	10	560	绿光波段
B4	10	665	红光波段
B5	20	705	红光波段1
B6	20	740	红光波段2
B7	20	783	红光波段3
B8	10	842	近红外波段
B9	60	945	水汽波段
B11	20	1610	短红外波段1
B12	20	2190	短红外波段2

编号	土地类型	描述
0	水体	永久性和季节性水体
1	树木	原生林和次生林以及大型人工林
2	草地	天然草原、畜牧场和公园
3	被淹没的植被	红树林和其他被淹没的生态系统
4	农田	行作物和水稻作物
5	落叶灌木/灌丛	灌木组成的稀疏到密集的开阔植被
6	建成区/城市	建筑物、道路和城市开放空间
7	裸地	沙漠和裸露的岩石
8	雪/冰	永久和季节性积雪

波段	权重系数
B2	0.1550
B3	0.2375
B4	0.2244
B8	0.3579

基于Sentinel-2卫星影像的乌鲁木齐市及典型光伏电站地表环境时空演变特征研究

Spatiotemporal evolution characteristics of surface environment in Urumqi City and typical photovoltaic power stations based on Sentinel-2 satellite imagery

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 18

参考文献 32

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	罗庆, 臧永婷, 王云龙, 王山冰, 刘乐. 黄河流域乡镇人口分布格局的演变特征及其驱动机制[J]. 干旱区地理, 2026, 49(8): 1711-1723.
[2]	雷霆, 张丽娜, 逯浩. 中国数字乡村建设水平的时空差异及驱动因素异质性[J]. 干旱区地理, 2026, 49(10): 1993-2005.
[3]	田小波. 黄河流域城市旅游业高质量发展水平测度与空间格局特征[J]. 干旱区地理, 2025, 48(9): 1660-1671.
[4]	孙玉博, 赵善超, 王雅佩, 马晓丽, 陈玉雯, 黄选胜, 王卫霞. 天山中部天山云杉林生态服务价值量化与空间分异研究[J]. 干旱区地理, 2025, 48(8): 1396-1405.
[5]	程鹏, 彭海洋, 侯丁榕, 孙明东, 宋晓伟. 黄河流域农业灰水足迹强度空间格局及演进趋势[J]. 干旱区地理, 2025, 48(7): 1185-1197.
[6]	王佩佩, 王娇, 蔡咏梅. 多尺度视域下中国滑雪场空间分异格局及其驱动因素研究[J]. 干旱区地理, 2025, 48(6): 1080-1088.
[7]	李鸿飞, 常凯. 中国国家级自然保护区时空分布特征与空间网络构建[J]. 干旱区地理, 2025, 48(11): 1971-1982.
[8]	吴彩云, 何清, 谢翔. 阿克达拉大气本底站地表辐射收支特征[J]. 干旱区地理, 2024, 47(6): 942-952.
[9]	邢立文, 赵景峰, 何清, 李娟, 苏华丽, 何亚玲. 塔克拉玛干沙漠南缘戈壁下垫面辐射平衡与地表反照率特征[J]. 干旱区地理, 2024, 47(5): 762-772.
[10]	朱磊, 王科, 丁一民, 孙振源, 孙伯颜. 基于Sentinel-2的青铜峡灌区水稻和玉米种植分布早期识别[J]. 干旱区地理, 2024, 47(5): 850-860.
[11]	唐宇, 薛东前, 宋永永, 叶昊, 王莎. 中国夜间文旅消费集聚区空间格局及影响机理[J]. 干旱区地理, 2024, 47(3): 485-495.
[12]	张红伟, 何清, 杨明凤, 安冬亮, 吴春霞, 王进, 陈非凡. 石河子垦区绿洲农田下垫面辐射收支特征研究[J]. 干旱区地理, 2024, 47(12): 1991-2004.
[13]	火红, 刘艳, 买吾拉夏·木巴热克. 1990—2020年新疆伊犁地区雪灾时空分布特征及其影响评估[J]. 干旱区地理, 2024, 47(11): 1828-1840.
[14]	宋小龙, 马明德, 李陇堂, 米文宝, 王鹏, 吴月, 任婕. 宁夏乡村旅游重点村空间格局与影响因素分析[J]. 干旱区地理, 2024, 47(11): 1957-1969.
[15]	王瑞, 郭荔, 戴俊骋, 程哲. 中国包容性旅游发展评估及空间格局研究——基于287个城市面板数据[J]. 干旱区地理, 2024, 47(1): 127-136.