[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3551":3,"related-3551":61},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":60},3551,"Diachronic Assessment of Water Springs in Ribat El Kheir Plateau (Morocco), under Climatic and Anthropogenic Pressure, Using Remote Sensing (1985-2025)","https:\u002F\u002Fdoi.org\u002F10.4028\u002Fp-9o0ojj","The Ribat El Kheir plateau, located in the northern part of the Tabular Middle Atlas (Morocco), is characterized by carbonate formations (Liasic dolomitic limestones) and a dense network of tectonic faults. This study conducts a diachronic assessment of water springs and their interaction with climatic conditions and anthropogenic factors related to the expansion of irrigated agriculture (farms) from 1985 to 2025. A multi-source methodological approach was adopted, combining the inventory and mapping of springs, the application of remote sensing, using Landsat and Sentinel satellite imagery, and the calculation of standard indices, including the Normalized Difference Water Index (NDWI), the Normalized Difference Vegetation Index (NDVI), and the Standardized Precipitation Index (SPI). The results indicate that a combination of geomorphological context primarily influences the spatial distribution of the 101 inventoried springs, the lithological nature of the formations (permeable dolomites), structural features, and climatic factors. However, a significant regression in both the number and flow of these springs has been observed. Concurrently, irrigated fruit agriculture has expanded remarkably over the study period. The SPI analysis further reveals a climatic trend towards increased aridity. These findings highlight the critical and synergistic pressure of climate change and intensive agriculture on water resources in this vulnerable semi-arid region.","位于摩洛哥中阿特拉斯板状山脉北部的里巴特·埃尔·海尔（Ribat El Kheir）高原，以碳酸盐岩地层（里阿斯统白云质灰岩）和密集的构造断裂网络为特征。本研究对1985年至2025年间泉水动态及其与气候条件和灌溉农业（农场）扩张相关人为因素的相互作用进行了历时性评估。研究采用多源方法学途径，结合泉水编录与制图、遥感技术应用（利用Landsat和Sentinel卫星影像）以及标准指数的计算，包括归一化差异水体指数（NDWI）、归一化差异植被指数（NDVI）和标准化降水指数（SPI）。结果表明，101处编录泉水的空间分布主要受地貌背景、地层岩性特征（渗透性白云岩）、构造特征及气候因素的综合影响。然而，观测到这些泉水的数量和流量均出现显著衰退。与此同时，灌溉果树农业在研究期内显著扩张。SPI分析进一步揭示了气候趋于干旱化的趋势。这些发现凸显了气候变化与集约化农业对这一脆弱半干旱地区水资源的临界协同压力。",null,"International journal of engineering research in Africa","2026-09-25T00:00:00Z","论文",10,false,67,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,20,17,13,9,1,"基于Landsat与Sentinel遥感的40年泉水退化评估，方法扎实、数据翔实，但属区域案例研究，对国内三农实践的直接参考价值有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"农业水资源","NDVI","遥感监测","灌溉农业","干旱化",[33,34],"Ribat El Kheir 泉水 遥感","摩洛哥 灌溉农业 水资源","RibatElKheir泉水遥感-3551",0,"10.4028\u002Fp-9o0ojj",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":9,"card":53,"direction":57,"ingested_from":59},"W7214294130",[41,43,44,47,49,50],{"name":42,"orcid":9},"Hamid Achiban",{"name":42,"orcid":9},{"name":45,"orcid":46},"Miloud Afenzar","https:\u002F\u002Forcid.org\u002F0009-0008-0839-0230",{"name":48,"orcid":9},"Hassan Achiban",{"name":48,"orcid":9},{"name":51,"orcid":52},"Nourddine El Gali","https:\u002F\u002Forcid.org\u002F0009-0001-7025-4765",{"tldr":54,"method":55,"finding":56,"direction":57,"opportunity":58},"基于遥感和指数分析，评估摩洛哥Ribat El Kheir高原1985-2025年泉水数量与流量的退","Landsat\u002FSentinel影像、NDWI\u002FNDVI\u002FSPI指数、泉水编目与","泉水数量与流量显著减少，灌溉农业扩张与气候干旱化协同加剧水资源压力。","农业遥感与作物表型","可结合多源遥感与机器学习，量化灌溉扩张对泉水流量的贡献，并预测未来情景。","openalex","2026-09-26T23:30:29.568284Z",{"total":62,"page":22,"page_size":62,"items":63},6,[64,106,144,182,219,266],{"id":65,"title":66,"url":67,"summary":68,"summary_zh":69,"content":9,"source_name":70,"source_url":67,"published_at":71,"category":12,"cover_url":9,"hotness":72,"is_selected":14,"score":73,"score_detail":74,"sources":79,"tags":83,"search_phrases":86,"slug":89,"view_count":22,"doi":90,"paper":91,"created_at":105},2321,"ASSESSMENT OF SOIL SALINITY USING THE NDVI VEGETATION INDEX BASED ON REMOTE SENSING DATA","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702718","This article examines the assessment of soil salinity in the irrigated meadow-sierozem soils of the E. Qahhorov agricultural area in Khovos District, Syrdarya Region, based on remote sensing data. Sentinel-2 satellite data covering the period from 2016 to 2025 were used in the study, and the Normalized Difference Vegetation Index (NDVI) was calculated using geospatial technologies. The long-term and seasonal dynamics of vegetation cover in the study area were analyzed, and the relationship between NDVI values and salinity levels was assessed. Based on an NDVI classification adapted to the natural conditions of the study area, criteria for the indirect assessment of soil salinity levels were proposed. The results demonstrated that the NDVI can be effectively used as an indicator for determining the impact of soil salinity on vegetation cover, assessing salinity spatially, and conducting long-term monitoring of salinity in irrigated agricultural lands.","本文基于遥感数据，对锡尔河州霍沃斯区E. Qahhorov农业区灌溉草甸灰钙土的土壤盐渍化进行了评估。研究使用了2016年至2025年期间的Sentinel-2卫星数据，并利用地理空间技术计算了归一化植被指数（NDVI）。分析了研究区植被覆盖的长期和季节性动态，并评估了NDVI值与盐渍化程度之间的关系。基于适应研究区自然条件的NDVI分类，提出了土壤盐渍化程度间接评估的标准。结果表明，NDVI可有效用作确定土壤盐渍化对植被覆盖影响、空间评估盐渍化以及开展灌溉农田盐渍化长期监测的指标。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-11T00:00:00Z",25,65,{"impact":75,"substance":76,"depth":77,"authority":75,"freshness":17,"relevant":22,"comment":78},12,18,15,"基于Sentinel-2长时序NDVI数据提出土壤盐渍化间接评估标准，方法可复用但属区域性案例研究，公共影响有限。",[80,81],{"name":70,"url":67},{"name":70,"url":82},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22702719",[84,28,29,85,30],"智慧农业","土壤盐渍化",[87,88],"土壤盐渍化 智慧农业 灌溉农业 遥感监测","土壤盐渍化 智慧农业","土壤盐渍化智慧农业灌溉农业遥感监测-2321","10.5281\u002Fzenodo.22702718",{"doi":90,"openalex_id":92,"authors":93,"venue":70,"cited_by_count":36,"oa_url":67,"card":100,"direction":57,"ingested_from":59},"W7212227143",[94,96,98],{"name":95,"orcid":9},"U.K. Umirova",{"name":97,"orcid":9},"D.A. Kodirova",{"name":99,"orcid":9},"O.O. Davronov",{"tldr":101,"method":102,"finding":103,"direction":57,"opportunity":104},"利用Sentinel-2遥感数据计算NDVI，评估灌溉草甸灰钙土的土壤盐渍化程度。","Sentinel-2数据（2016-2025）与NDVI指数，结合地理空间技术分","NDVI可有效指示盐渍化对植被的影响，实现空间评估与长期监测。","可探索多指数融合与机器学习提升盐渍化反演精度，并推广至不同土壤类型区。","2026-09-13T23:30:22.820810Z",{"id":107,"title":108,"url":109,"summary":110,"summary_zh":111,"content":9,"source_name":112,"source_url":109,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":113,"score_detail":114,"sources":117,"tags":119,"search_phrases":123,"slug":126,"view_count":36,"doi":127,"paper":128,"created_at":143},3568,"Interpretable multi-index framework for extracting dry-season built-up areas: benchmarking machine learning with Sentinel-2","https:\u002F\u002Fdoi.org\u002F10.4995\u002Fraet.2027.25885","Spectral similarity between built-up surfaces and exposed dry soil significantly constrains built-up area extraction during dry seasons. Although machine-learning techniques can address this challenge by modeling complex spectral relationships, they generally require sufficiently large and representative labeled training datasets. This study therefore investigates a less data-demanding, rule-based multi-index approach for dry-season built-up mapping, aiming to reduce reliance on large labeled training datasets while maintaining effective classification performance. Sentinel-2A imagery acquired in April 2024 was analyzed, and temporal validation was conducted for 2020, 2022, and 2024. Among the tested combinations, the Built-up Area Extraction Index (BAEI), Dry BareSoil Index (DBSI), and Normalized Difference Vegetation Index (NDVI) achieved the highest performance, yielding 95 % overall accuracy and a Kappa coefficient of 0.89. This represents a substantial improvement over singleindex BAEI (80 % overall accuracy; Kappa 0.55), increasing the built-up user’s accuracy from 61 % to 92 %. Multitemporal validation confirmed that the optimized BAEI–DBSI–NDVI decision rules remained stable across the 2020–2024 dry-season images without recalibration, achieving 93–96 % overall accuracy and a built-up F1-score of 84–93 %. Spatial analysis demonstrated robust performance across peripheral and agricultural zones, with moderate variability in dense urban cores due to spectral heterogeneity. To evaluate the operational robustness of the proposed framework, it was benchmarked against machine-learning classifiers, specifically Support Vector Machine and Random Forest (RF). Under the specific conditions of this study, the proposed rule-based method (95 % accuracy) marginally outperformed both SVM (93 %) and RF (92 %), while offering greater transparency and reducing dependency on large, labeled training datasets. Furthermore, feature importance analysis confirmed the critical role of these selected indices in resolving spectral confusion. These findings suggest that the proposed framework offers a transparent and computationally efficient approach for dry-season urban monitoring in tropical coastal environments similar to Visakhapatnam.","建成表面与裸露干土之间的光谱相似性显著制约了旱季建成区提取。尽管机器学习技术可通过建模复杂光谱关系来应对这一挑战，但其通常需要足够大且具有代表性的标记训练数据集。因此，本研究探讨了一种对数据需求较低、基于规则的多指数方法用于旱季建成区制图，旨在减少对大规模标记训练数据集的依赖，同时保持有效的分类性能。研究分析了2024年4月获取的Sentinel-2A影像，并对2020年、2022年和2024年进行了时间验证。在测试的组合中，建成区提取指数（BAEI）、干裸土指数（DBSI）和归一化差异植被指数（NDVI）表现最佳，总体精度达95%，Kappa系数为0.89。相较于单一指数BAEI（总体精度80%；Kappa 0.55），这一结果有显著提升，建成区用户精度从61%提高至92%。多时相验证证实，优化后的BAEI–DBSI–NDVI决策规则在2020—2024年旱季影像上无需重新校准即可保持稳定，总体精度达93%—96%，建成区F1分数为84%—93%。空间分析表明，该方法在外围和农业区域表现稳健，而在密集城市核心区由于光谱异质性存在中等程度变异。为评估所提框架的业务化稳健性，将其与机器学习分类器进行了基准比较，具体为支持向量机（SVM）和随机森林（RF）。在本研究的特定条件下，所提出的基于规则的方法（95%精度）略优于SVM（93%）和RF（92%），同时具有更高的透明性并减少了对大规模标记训练数据集的依赖。此外，特征重要性分析证实了所选指数在解决光谱混淆方面的关键作用。这些发现表明，所提框架为类似维沙卡帕特南的热带沿海环境旱季城市监测提供了一种透明且计算高效的方法。","Revista de teledetección: Revista de la Asociación Española de Teledetección",72,{"impact":75,"substance":115,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":116},21,"该研究提出可解释的多指数规则框架，在旱季建成区提取上以更少标注数据达到95%精度并优于SVM\u002FRF，方法新颖、验证充分，对农业遥感与乡村土地利用监测有参考价值。",[118],{"name":112,"url":109},[120,121,28,29,122],"Sentinel-2","机器学习","建成区提取",[124,125],"Sentinel-2 建成区提取","BAEI DBSI NDVI 旱季","Sentinel-2建成区提取-3568","10.4995\u002Fraet.2027.25885",{"doi":127,"openalex_id":129,"authors":130,"venue":112,"cited_by_count":36,"oa_url":109,"card":137,"direction":142,"ingested_from":59},"W7214385607",[131,134],{"name":132,"orcid":133},"Sarah Sejari","https:\u002F\u002Forcid.org\u002F0009-0002-7300-9084",{"name":135,"orcid":136},"Vazeer Mahammood","https:\u002F\u002Forcid.org\u002F0000-0003-1667-5232",{"tldr":138,"method":139,"finding":140,"direction":57,"opportunity":141},"提出可解释多指数规则框架，用Sentinel-2提取旱季建成区，性能优于机器学习。","Sentinel-2A影像，BAEI、DBSI、NDVI组合规则，对比SVM与随","BAEI-DBSI-NDVI规则达95%精度、Kappa 0.89，优于单指数及SVM\u002FRF且无需重","可探索该规则框架向其他气候带与传感器迁移，并结合少量样本的半监督学习提升城市核心区精度。","农业人工智能与决策模型","2026-09-26T23:30:53.200163Z",{"id":145,"title":146,"url":147,"summary":148,"summary_zh":149,"content":9,"source_name":150,"source_url":147,"published_at":151,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":152,"score_detail":153,"sources":155,"tags":157,"search_phrases":161,"slug":164,"view_count":36,"doi":165,"paper":166,"created_at":181},3558,"Meteorolojik Kuraklığın Vejetasyon Sağlığı Üzerindeki Mekânsal ve Zamansal Etkilerinin SPI ve NDVI ile Analizi: Gediz Havzası Örneği","https:\u002F\u002Fdoi.org\u002F10.48123\u002Frsgis.1858019","Kuraklık, özellikle yarı kurak iklim koşullarına sahip havzalarda su kaynakları, tarımsal üretim ve ekosistem sürdürülebilirliği üzerinde belirleyici etkiler oluşturan başlıca doğal afetlerden biridir. Bu bağlamda, kuraklığın bitki örtüsü üzerindeki mekânsal ve zamansal etkilerinin bütüncül yaklaşımlarla değerlendirilmesi büyük önem taşımaktadır. Bu çalışmada, meteorolojik kuraklığın vejetasyon sağlığı üzerindeki mekânsal ve zamansal etkileri, Standartlaştırılmış Yağış İndeksi (SPI) ve Normalize Fark Bitki Örtüsü İndeksi (NDVI) kullanılarak Gediz Havzası örneğinde analiz edilmiştir. SPI analizleri 1970–2023 yılları arasındaki uzun dönem yağış verilerine dayanırken, NDVI verileri 2000–2023 dönemine ait MODIS uydu görüntülerinden elde edilmiştir. İki veri seti arasındaki ilişkiler, ortak dönem olan 2000–2023 yılları için incelenmiştir. Elde edilen bulgular, meteorolojik kuraklık ile vejetasyon sağlığı arasındaki ilişkinin mevsimsel olarak değişkenlik gösterdiğini ortaya koymaktadır. En güçlü ilişki yaz mevsiminde gözlenmiş (r ≈ 0.70) ve bu durum vejetasyonun yağış eksikliklerine en duyarlı olduğu dönemin yaz ayları olduğunu göstermiştir. Buna karşılık, kış (r ≈ 0.05) ve ilkbahar (r ≈ 0.02) mevsimlerinde ilişki oldukça zayıf bulunmuştur. Belirlenen kurak yıllarda (2004, 2008 ve 2022) NDVI değerlerinde belirgin düşüşler gözlenmiştir. Sonuç olarak, vejetasyonun kuraklığa verdiği tepkinin yıl boyunca homojen olmadığı, mevsimsel iklim koşulları ve diğer çevresel faktörlere bağlı olarak değiştiği belirlenmiştir.","干旱是主要自然灾害之一，尤其在具有半干旱气候条件的流域中，对水资源、农业生产和生态系统可持续性产生决定性影响。在此背景下，以整体性方法评估干旱对植被的时空影响具有重要意义。本研究以盖迪兹流域为例，利用标准化降水指数（SPI）和归一化植被指数（NDVI）分析了气象干旱对植被健康的时空影响。SPI分析基于1970—2023年的长期降水数据，而NDVI数据则来自2000—2023年期间的MODIS卫星影像。两个数据集之间的关系在共同时段2000—2023年进行了分析。研究结果表明，气象干旱与植被健康之间的关系呈现季节性变化。最显著的关系出现在夏季（r ≈ 0.70），这表明夏季是植被对降水亏缺最为敏感的时期。相比之下，冬季（r ≈ 0.05）和春季（r ≈ 0.02）的关系则非常微弱。在确定的干旱年份（2004年、2008年和2022年），NDVI值出现了明显下降。综上，植被对干旱的响应在全年并非均匀一致，而是随季节性气候条件及其他环境因素而变化。","Turkish Journal of Remote Sensing and GIS","2026-09-24T00:00:00Z",71,{"impact":75,"substance":115,"depth":19,"authority":20,"freshness":17,"relevant":22,"comment":154},"基于SPI与NDVI长时序数据揭示气象干旱对植被健康影响的季节性差异，方法规范、结论可靠，对农业干旱遥感监测有参考价值，但属区域案例研究，公共影响有限。",[156],{"name":150,"url":147},[28,29,158,159,160],"干旱监测","植被指数","SPI",[162,163],"Gediz Havzası SPI NDVI","气象干旱 植被健康 遥感","GedizHavzasıSPINDVI-3558","10.48123\u002Frsgis.1858019",{"doi":165,"openalex_id":167,"authors":168,"venue":150,"cited_by_count":36,"oa_url":175,"card":176,"direction":57,"ingested_from":59},"W7214166880",[169,172],{"name":170,"orcid":171},"Kemal Yurddaş","https:\u002F\u002Forcid.org\u002F0000-0003-4691-4038",{"name":173,"orcid":174},"Murat Karabulut","https:\u002F\u002Forcid.org\u002F0000-0002-1456-6908","https:\u002F\u002Fdergipark.org.tr\u002Ftr\u002Fdownload\u002Farticle-file\u002F5578303",{"tldr":177,"method":178,"finding":179,"direction":57,"opportunity":180},"用SPI和NDVI分析土耳其盖迪兹流域气象干旱对植被健康的时空影响。","基于1970-2023年降水SPI与2000-2023年MODIS NDVI，做","干旱与植被关系随季节变化，夏季最强(r≈0.70)，冬春极弱；干旱年NDVI明显下降。","可引入滞后效应与多尺度SPI，结合土壤水分和灌溉数据，提升干旱对植被影响的预测能力。","2026-09-26T23:30:31.357310Z",{"id":183,"title":184,"url":185,"summary":186,"summary_zh":187,"content":9,"source_name":70,"source_url":185,"published_at":188,"category":12,"cover_url":9,"hotness":72,"is_selected":14,"score":189,"score_detail":190,"sources":192,"tags":196,"search_phrases":199,"slug":202,"view_count":36,"doi":203,"paper":204,"created_at":218},3279,"ASSESSMENT OF SOIL SALINIZATION IN IRRIGATED LANDS BASED ON REMOTE SENSING AND GIS TECHNOLOGIES","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900049","This thesis analyzes modern approaches to monitoring and assessing soil salinity in irrigated areas of Uzbekistan and Central Asia. Soil salinization is one of the major land degradation processes affecting the reclamation condition of irrigated lands, crop growth and agricultural productivity. Although conventional field and laboratory surveys provide detailed information, they have limitations in terms of regular monitoring of large areas. Therefore, remote sensing and geographic information systems provide promising tools for rapid and spatial assessment of soil salinity. The study considers the application of satellite imagery, particularly Sentinel-2 and Landsat data, for soil salinity assessment, including the use of spectral bands and salinity indices, GIS-based thematic mapping, and validation using field and laboratory observations. Recent studies demonstrate the potential of remote sensing data for spatial assessment and mapping of soil salinity under the conditions of Uzbekistan. Such an integrated approach can support rapid monitoring of the reclamation status of irrigated lands, identification of salt-affected areas and spatial planning of appropriate reclamation measures.","本论文分析了乌兹别克斯坦和中亚灌溉区土壤盐分监测与评估的现代方法。土壤盐渍化是影响灌溉土地改良状况、作物生长和农业生产力的主要土地退化过程之一。尽管传统的野外调查和实验室分析能够提供详细信息，但在大范围定期监测方面存在局限性。因此，遥感与地理信息系统为土壤盐分的快速空间评估提供了有前景的工具。本研究探讨了卫星影像，特别是Sentinel-2和Landsat数据在土壤盐分评估中的应用，包括光谱波段和盐分指数的使用、基于GIS的主题制图，以及利用野外和实验室观测数据进行验证。近期研究表明，遥感数据在乌兹别克斯坦条件下用于土壤盐分空间评估与制图具有潜力。这种综合方法可支持灌溉土地改良状况的快速监测、盐渍化区域的识别以及适当改良措施的空间规划。","2026-09-22T00:00:00Z",66,{"impact":75,"substance":76,"depth":77,"authority":75,"freshness":21,"relevant":22,"comment":191},"基于遥感与GIS的灌溉区土壤盐渍化监测论文，方法成熟、结论可靠，对盐碱地治理与农业信息化有参考价值，但属区域性研究，影响层级有限。",[193,194],{"name":70,"url":185},{"name":70,"url":195},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900048",[197,29,198,85,30],"土地退化","GIS",[200,201],"乌兹别克斯坦 土壤盐渍化 遥感","Sentinel-2 盐渍化 灌溉","乌兹别克斯坦土壤盐渍化遥感-3279","10.5281\u002Fzenodo.22900049",{"doi":203,"openalex_id":205,"authors":206,"venue":70,"cited_by_count":36,"oa_url":185,"card":213,"direction":57,"ingested_from":59},"W7214052773",[207,209,211],{"name":208,"orcid":9},"Mardiyev",{"name":210,"orcid":9},"Ergashaliyev",{"name":212,"orcid":9},"G'aniyev",{"tldr":214,"method":215,"finding":216,"direction":57,"opportunity":217},"综述遥感与GIS评估乌兹别克斯坦及中亚灌溉土壤盐渍化的方法。","Sentinel-2与Landsat影像、光谱盐分指数、GIS制图及野外验证。","遥感与GIS可快速空间评估盐渍化，支持灌溉地改良状态监测与规划。","可探索多源遥感与机器学习融合的盐分指数模型，提升干旱区盐渍化反演精度与时效。","2026-09-23T23:30:19.341486Z",{"id":220,"title":221,"url":222,"summary":223,"summary_zh":224,"content":9,"source_name":225,"source_url":222,"published_at":226,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":227,"score_detail":228,"sources":232,"tags":234,"search_phrases":238,"slug":241,"view_count":36,"doi":242,"paper":243,"created_at":265},3181,"Estimating groundwater abstraction for irrigation in a data-scarce semi-arid region using optical and InSAR time-series analysis: the Tensift catchment, Morocco","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffrwa.2026.1917387","In Morocco, the expansion of irrigated agriculture has intensified groundwater abstraction and increased pressure on overexploited aquifer systems. Moreover, the substantial lack of pumping measurement data represents a critical limitation for water resources management. To address this gap, the present study quantifies groundwater abstraction at the perimeter scale during agricultural season (2015–2016) in the Tensift catchment, using an integrated methodology combining optical and radar remote sensing (Sentinel-1,-2) with field-based observations. The results show that the total groundwater abstraction reached 4.13 × 10 6 m 3 with a monthly average of 344,515 m 3 . During the April–August period, groundwater supplied 36.1% of crop water requirements, while dam releases contributed 63.9%. These estimates were validated against pumping records from monitoring wells, where field measurements quantified groundwater and dam release contributions of 45% and 55%, respectively. The water balance assessment indicated a total agricultural water supply of 18.8 × 10 6 m 3 .yr −1 , consistent with crop water requirements estimated at 17.8 × 10 6 m 3 .yr −1 . InSAR-derived land subsidence analysis revealed marked spatial heterogeneity, with maximum subsidence rates reaching 6.5 mm.yr −1 , concentrated in the northern sector and isolated central clusters. Overlap analysis showed a co-occurrence rate of 70.6% between high-abstraction and subsidence zones. The spatial Pearson correlation between land subsidence and groundwater abstraction ranges from 0.39 to 0.71. This study demonstrates that the proposed approach provides a robust and scalable framework for groundwater abstraction monitoring in data-scarce environments.","在摩洛哥，灌溉农业的扩张加剧了地下水开采，并增加了对过度开采含水层系统的压力。此外，抽水计量数据的大量缺失是水资源管理的一个关键限制。为弥补这一空白，本研究采用结合光学与雷达遥感（Sentinel-1、-2）及实地观测的综合方法，量化了Tensift流域农业季（2015—2016年）周边尺度的地下水开采量。结果表明，地下水总开采量达4.13 × 10⁶ m³，月均344,515 m³。在4月至8月期间，地下水满足了作物需水量的36.1%，而水库放水贡献了63.9%。这些估算结果经监测井抽水记录验证，实地测量量化地下水与水库放水的贡献分别为45%和55%。水量平衡评估表明，农业总供水量为18.8 × 10⁶ m³·yr⁻¹，与估算的作物需水量17.8 × 10⁶ m³·yr⁻¹一致。基于InSAR的地面沉降分析揭示了显著的空间异质性，最大沉降速率达6.5 mm·yr⁻¹，集中于北部区域和孤立的中部簇群。重叠分析显示，高开采区与沉降区的共现率为70.6%。地面沉降与地下水开采之间的空间Pearson相关系数范围为0.39至0.71。本研究表明，所提出的方法为数据稀缺环境下的地下水开采监测提供了一个稳健且可扩展的框架。","Frontiers in Water","2026-09-21T00:00:00Z",78,{"impact":229,"substance":230,"depth":76,"authority":20,"freshness":21,"relevant":22,"comment":231},16,22,"结合光学与InSAR遥感估算数据稀缺区灌溉地下水开采量，方法新颖、结论可靠，对农业水资源信息化管理有参考价值。",[233],{"name":225,"url":222},[27,29,235,236,237],"半干旱农业","地下水灌溉","InSAR",[239,240],"Tensift 流域 地下水 灌溉","Sentinel-1 Sentinel-2 灌溉 遥感","Tensift流域地下水灌溉-3181","10.3389\u002Ffrwa.2026.1917387",{"doi":242,"openalex_id":244,"authors":245,"venue":225,"cited_by_count":36,"oa_url":222,"card":260,"direction":57,"ingested_from":59},"W7213955905",[246,248,251,253,256,258],{"name":247,"orcid":9},"Youssef Hajhouji",{"name":249,"orcid":250},"Abdelhakim Amazirh","https:\u002F\u002Forcid.org\u002F0000-0002-6665-3843",{"name":252,"orcid":9},"Wassim Mohamed Baba",{"name":254,"orcid":255},"Marieme Seif-Ennasr","https:\u002F\u002Forcid.org\u002F0009-0005-8205-265X",{"name":257,"orcid":9},"M Serraj",{"name":259,"orcid":9},"Salah Er-Raki",{"tldr":261,"method":262,"finding":263,"direction":57,"opportunity":264},"结合光学与InSAR遥感估算摩洛哥半干旱区灌溉地下水开采量。","Sentinel-1\u002F2时序遥感、实地观测与InSAR沉降分析。","地下水满足36.1%作物需水，高开采区与沉降区重叠达70.6%。","可迁移至其他数据稀缺区，融合多源遥感与机器学习提升开采量估算精度。","2026-09-22T23:30:24.043679Z",{"id":267,"title":268,"url":269,"summary":270,"summary_zh":9,"content":9,"source_name":271,"source_url":269,"published_at":226,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":272,"score_detail":273,"sources":275,"tags":277,"search_phrases":281,"slug":284,"view_count":36,"doi":285,"paper":286,"created_at":299},3180,"Satellite-Based Assessment of Vegetation and Hydrological Dynamics at the Garâa of Sejnane Ramsar Wetland (Tunisia): A Multi-Temporal NDVI and NDWI Analysis","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-10690691\u002Fv1","Satellite-Based Assessment of Vegetation and Hydrological Dynamics at the Garâa of Sejnane Ramsar Wetland (Tunisia): A Multi-Temporal NDVI and NDWI Analysis。Research Square","Research Square",56,{"impact":17,"substance":76,"depth":77,"authority":62,"freshness":21,"relevant":22,"comment":274},"基于多时相NDVI\u002FNDWI的湿地植被与水文动态遥感评估，方法规范但属区域性案例研究，公共影响有限。",[276],{"name":271,"url":269},[28,278,29,279,280],"农业生态","湿地保护","NDWI",[282,283],"Sejnane 湿地 NDVI NDWI","突尼斯 拉姆萨尔湿地 遥感","Sejnane湿地NDVINDWI-3180","10.21203\u002Frs.3.rs-10690691\u002Fv1",{"doi":285,"openalex_id":287,"authors":288,"venue":271,"cited_by_count":36,"oa_url":269,"card":9,"direction":57,"ingested_from":59},"W7213955587",[289,291,293,296],{"name":290,"orcid":9},"Imen Khemiri",{"name":292,"orcid":9},"Chahida Chemingui",{"name":294,"orcid":295},"Alaeddine Rouissi","https:\u002F\u002Forcid.org\u002F0009-0000-9319-5182",{"name":297,"orcid":298},"Sahar Abidi","https:\u002F\u002Forcid.org\u002F0000-0003-3355-6876","2026-09-22T23:30:23.965045Z"]