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基于XGBoost融合多维度时空数据的干旱遥感建模及应用研究

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西南地区是我国重要的生态环境保护区,复杂的气候与地理条件导致干旱事件频繁发生,准确掌握干旱的空间分布情况及变化趋势对保护西南地区生态环境具有重要意义.本研究基于极端梯度提升算法,利用表征多维度特征变量的遥感干旱指标,构建了一种考虑植被状态、地表状态、气候状态及环境因素的干旱遥感监测模型(eXtreme Gradient Boosting Drought Monitor,XGBDM).利用该模型对西南地区2001-2020年干旱情况进行监测,选取典型干旱事件与土壤墒情数据对模型精度进行评价,并结合Theil-Sen Median趋势分析、Mann-Kendall显著性检验、Hurst指数、重心迁移模型,揭示了西南地区干旱时空演变特征、未来变化趋势及干旱重心迁移情况.结果表明:①在不同季节中,XGBDM模型均能准确监测西南地区干旱事件,模型精度指标R2为0.816~0.897,MAE为0.200~0.283,RMSE为0.296~0.424,模型与土壤墒情相关性为-0.60~0.86.相比于站点SPEI-3监测方法,XGBDM模型监测结果与土壤墒情相关性更高,且更能准确反映旱情的空间分布细节特征;②时间上,2001-2020年西南地区XGBDM年均值整体呈波动下降趋势,表明干旱情况呈加重趋势,其中春季和夏季干旱呈加重趋势,秋季和冬季干旱呈减轻趋势.空间上,西南地区XGBDM值变化斜率在春季和夏季呈"北高南低"的空间分布格局,在秋季和冬季呈"南高北低"的空间分布格局,其中不同季节干旱呈加重趋势的面积占比分别为春季69.17%、夏季76.02%、秋季34.43%、冬季47.5%;③西南地区XGBDM值整体呈弱反持续性变化,春季、夏季以及冬季未来旱情以减轻为主,旱情由加重转为减轻的区域面积在不同季节占比为28.44%~63.82%.旱情持续加重面积在春季最高,占比为17.97%,持续减轻情况在冬季占比最高,为15.92%;④2001-2020年干旱重心主要分布于研究区中部,呈西北至东南的分布格局,未来干旱重心在西北至东南方向进行迁移的概率更高.研究结果可为西南地区干旱监测及治理提供理论依据.
Remote Sensing Modeling and Applications in Drought Monitoring Based on XGBoost and Fusion of Multi-dimensional Spatiotemporal Data
Southwest China is an important ecological conservation area in the country.Its complex climatic and geographical conditions frequently lead to drought events.Accurately understanding the spatial distribution and trends of drought is essential for protecting the ecological environment in this region.This study utilizes the eXtreme Gradient Boosting algorithm to construct a remote sensing drought monitoring model(eXtreme Gradient Boosting Drought Monitor,XGBDM).The model considers vegetation status,land surface conditions,climate variables,and environmental factors using remote sensing drought indicators,which characterize multidimensional feature variables.The model was used to monitor drought conditions in Southwest China from 2001 to 2020.Typical drought events and soil moisture data were selected to evaluate the accuracy of the model.Combining Theil-Sen Median trend analysis,Mann-Kendall significance test,Hurst index,and the center of gravity shift model,this study reveals the spatio-temporal variation characteristics of drought,future trends,and the shift in drought center of gravity in Southwest China.Results indicate that:(1)The XGBDM model accurately monitors drought events in Southwest China across different seasons,with model accuracy indicators R2 ranging from 0.816 to 0.897,MAE from 0.200 to 0.283,RMSE from 0.296 to 0.424,and correlation between the model and soil moisture ranging from-0.60 to 0.86.Compared to the station-based SPEI-3 monitoring method,the XGBDM model shows a higher correlation with soil moisture and can more accurately reflect the spatial distribution details of drought conditions.(2)Temporally,from 2001 to 2020,the annual average XGBDM values in Southwest China exhibit an overall fluctuating declining trend,indicating an exacerbation of drought conditions,particularly in spring and summer,while alleviating in autumn and winter.Spatially,the changing rate of XGBDM values in Southwest China presents a pattern of"high in the north and low in the south"in spring and summer,and"high in the south and low in the north"in autumn and winter.The proportion of areas with increasing drought varies by season,with 69.17%in spring,76.02%in summer,34.43%in autumn,and 47.5%in winter,respectively.(3)The XGBDM values in Southwest China generally exhibit weak anti-persistence changes.In spring,summer,and winter,future drought conditions are mainly alleviated,with the proportion of areas transitioning from exacerbation to alleviation ranging from 28.44%to 63.82%across different seasons.The area with persistently exacerbating drought conditions is highest in spring(17.97%),while the highest proportion of persistently alleviating conditions is in winter(15.92%).(4)The center of drought conditions from 2001 to 2020 is mainly located in the central part of the study area,following a northwest-to-southeast distribution pattern.In the future,there is a higher probability of the drought center migrating in the northwest-to-southeast direction.These findings can serve as a theoretical basis for drought monitoring and management in Southwest China.

Southwest ChinaSPEI-3droughtremote sensing monitoringXGBoostspatio-temporal varia-tioncenter of gravity migration modelsoil moisture

晏红波、梁雨豪、卢献健、王佳华、吴思怡

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桂林理工大学测绘地理信息学院,桂林 541004

广西空间信息与测绘重点实验室,桂林 541004

西南地区 SPEI-3 干旱 遥感监测 XGBoost 时空变化 重心迁移模型 土壤墒情

国家自然科学基金广西自然科学基金

423610522022GXNSFBA035639

2024

地球信息科学学报
中国科学院地理科学与资源研究所

地球信息科学学报

CSTPCD北大核心
影响因子:1.004
ISSN:1560-8999
年,卷(期):2024.26(6)
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