Study on animal diversity in the Yellow River basin based on remote sensing and GIS technology

doi:10.13474/j.cnki.11-2246.2025.1204

Abstract

Abstract: Changes in biodiversity and their driving mechanisms are of great significance to the development of biodiversity conservation measures.Remote sensing technology has outstanding advantages in large-scale and long time-series research.In order to grasp the spatial pattern and time-series changes of animal diversity in the Yellow River basin,this study utilizes the time-series Landsat and MODIS satellite image data from 2000 to 2022,and combines the GEE,InVEST model,and GIS-related technologies to construct an index for assessing the animal diversity in the Yellow River basin based on 7 indicators in 2 aspects:species diversity and ecosystem diversity.The animal diversity assessment index of the Yellow River basin is constructed based on seven indicators of species diversity and ecosystem diversity,and the accuracy assessment is carried out based on the measured data,and the analysis of the driving factors is also carried out.The results show that:the BI constructed in this study had high precision,and the correlation with the measured species data is 0.80; the BI in the Yellow River basin shows an overall increasing trend during the 22 year perios; the area of the BI increases accounted for 70.63%of the total area,and the area of the BI decreases accounted for 29.37%; based on the analysis of the contribution of the driving factors,evapotranspiration is the primary environmental control factor.

Key words: faunal diversity, Yellow River basin, Google Earth Engine, index system, GIS

CLC Number:

P237
P208

MA Chijie, LI Xiaotong, BU Yuankun, FU Pingjie, WANG Yuqiang, MA Mingliang. Study on animal diversity in the Yellow River basin based on remote sensing and GIS technology[J]. Bulletin of Surveying and Mapping, 2025, 0(12): 20-26.

References

[1] 李俊生, 高吉喜, 张晓岚, 等.贵清山自然保护区生物多样性现状和可持续发展对策[J].环境科学研究, 2006, 19(3):41-45.
[2] 万本太, 徐海根, 丁晖, 等.生物多样性综合评价方法研究[J].生物多样性, 2007, 15(1):97-106.
[3] 魏之首, 关燕宁, 蔡丹路, 等.基于改进型遥感生态指数的生态系统服务价值评估方法[J].地球信息科学学报, 2024, 26(7):1763-1778.
[4] 唐希颖, 李化哲, 崔丽娟, 等.湿地植物物种多样性无人机高光谱遥感反演研究[J].地球信息科学学报, 2024, 26(8):1954-1974.
[5] 林森, 胡喜生, 吴承祯, 等.武夷山国家公园植被覆盖演变的时空特征[J].森林与环境学报, 2020, 40(4):347-355.
[6] BEHERA M D, KUSHWAHA S P S, ROY P S.Rapid assessment of biological richness in a part of Eastern Himalaya:an integrated three-tier approach[J].Forest Ecology and Management, 2005, 207(3):363-384.
[7] MAHANAND S, BEHERA M D, ROY P S, et al.Satellite based fraction of absorbed photosynthetically active radiation is congruent with plant diversity in India[J].Remote Sensing, 2021, 13(2):159.
[8] HABYARIMANA E, PICCARD I, CATELLANI M, et al.Towards predictive modeling of sorghum biomass yields using fraction of absorbed photosynthetically active radiation derived from Sentinel-2 satellite imagery and supervised machine learning techniques[J].Agronomy, 2019, 9(4):203.
[9] 彭隆, 陈圣宾, 彭培好.县域生物多样性保护优先性评价指标体系构建与应用:以甘孜藏族自治州为例[J].水土保持研究, 2014, 21(4):127-132.
[10] 李晓宇, 李飞, 包玉海, 等.基于HJ-1CCD影像的呼伦贝尔草原区MODIS/FPAR产品验证与分析[J].遥感技术与应用, 2015, 30(6):1129-1137.
[11] 杨飞, 张柏, 王宗明, 等.基于MODIS数据的玉米植被参数估算方法的对比分析[J].遥感技术与应用, 2008, 23(2):147-153.
[12] 任涵, 张静静, 朱文博, 等.太行山淇河流域土地利用变化对生境的影响[J].地理科学进展, 2018, 37(12):1693-1704.
[13] 杨洁, 谢保鹏, 张德罡.基于InVEST模型的黄河流域产水量时空变化及其对降水和土地利用变化的响应[J].应用生态学报, 2020, 31(8):2731-2739.
[14] 吕明轩, 张红, 贺桂珍, 等.黄河流域水源涵养服务功能动态演变及驱动因素[J].生态学报, 2024, 44(7):2761-2771.
[15] 李冠稳, 高晓奇, 肖能文, 等.基于遥感技术的青海省玛多县生物多样性监测与评估[J].环境科学研究, 2021, 34(10):2419-2427.
[16] 刘猛, 夏自强, 韩帅, 等.黄河源区蒸散量变化与生态恶化的关系[J].河海大学学报(自然科学版), 2009, 37(6):631-634.
[17] 查苏娜, 吴桂林, 周璋, 等.海南岛热带次生草地生物多样性变化的气候驱动效应[J].生态学报, 2024, 44(23):10864-10874.
[18] 刘晓娟.城市发展对生物多样性的影响研究:以中国鸟类多样性为例[D].上海:华东师范大学, 2024.
[19] WANG Xu, LI Boyu, LIU Yingying, et al.Trends and attributions of the long-term thermal comfort across the urban-rural gradient in major Chinese cities[J].Applied Geography, 2024, 164:103221.