[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2535":3,"related-2535":85},{"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":18,"tags":20,"primary_topic":9,"secondary_topics":24,"classification":25,"search_phrases":55,"slug":58,"view_count":59,"doi":60,"paper":61,"created_at":84},2535,"Development of an ecological greenness index (EGI) for urban environmental monitoring: a remote sensing and multivariate analytical approach","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-70643-x","Abstract Several remote sensing-based indices have been proposed. While most measures are disjointed, several integrated ecological indices are offered. The purpose of this study is to introduce an Ecological Greenness Index (EGI) as a composite and integrated ecological index. This index was established by combining eight remote sensing-derived indices, including NDVI, NDSI, NDBI, LST, LAI, and three Tasseled Cap indices. Principal Component Analysis (PCA) was used to reduce dimensionality among RS-based derived components. The PCA eigenvalues were used as weights in the fuzzy logic method. The fuzzy logic overlay method was used to combine the retained components and produce the final EGI map. The results showed that four principal components (SIPC1–SIPC4), which explained about 99.99% of the total variance, were used for the final EGI construction. The EGI was implemented and internally assessed in Tehran, Iran, as a case study. The eigenvalue (λ) of each retained SIPC was used to derive the component weights for EGI construction. The results revealed substantial regional heterogeneity: the mean quantity of EGI in Tehran’s northern area was 0.29 (e.g., District 1), while it reduced to 0.076 in southern districts (e.g., District 10). A north–south transect analysis confirmed a steep ecological gradient across the city. EGI integrated vegetation structure, soil exposure, moisture, thermal conditions, and built-up characteristics within a unified PCA–fuzzy framework. It provides a broader diagnostic representation of urban ecological greenness. Zonal statistics depicted the spatial variation of EGI across Tehran’s 22 administrative districts. Despite the limitations of this study, such as using single-season and 30 m resolution satellite data, the EGI provides a quantitative framework for monitoring urban ecology. It represents a potentially useful tool for cities facing rapid urbanization and ecological greenness changes. Based on this case study, the EGI framework has the potential to be used as an integrated environmental quality assessment tool. The EGI integrating multiple ecological dimensions that may complement established indices such as the Remote Sensing-based Ecological Index (RSEI) in complex urban environments. Generalization of the EGI requires independent validation across additional urban contexts.","摘要 目前已提出多种基于遥感的指数。尽管大多数指标彼此独立，但也出现了一些综合生态指数。本研究的目的是引入生态绿度指数（EGI）作为一种复合综合生态指数。该指数通过整合八个遥感衍生指数建立，包括NDVI、NDSI、NDBI、LST、LAI以及三个缨帽变换指数。采用主成分分析（PCA）对遥感衍生组分进行降维。将PCA特征值作为模糊逻辑方法中的权重。利用模糊逻辑叠加方法将保留的主成分进行组合，生成最终的EGI图。结果表明，四个主成分（SIPC1–SIPC4）解释了约99.99%的总方差，被用于最终EGI的构建。EGI在伊朗德黑兰作为案例研究进行了实施和内部评估。每个保留的SIPC的特征值（λ）被用于推导EGI构建的组分权重。结果揭示了显著的区域异质性：德黑兰北部地区（如第1区）EGI的均值为0.29，而南部地区（如第10区）降至0.076。南北向样带分析证实了城市范围内存在陡峭的生态梯度。EGI在统一的PCA–模糊框架内整合了植被结构、土壤暴露、湿度、热力条件和建成区特征。它为城市生态绿度提供了更广泛的诊断性表征。分区统计描绘了德黑兰22个行政区的EGI空间变化。尽管本研究存在局限性，如使用单季节和30 m分辨率卫星数据，但EGI为监测城市生态提供了定量框架。它代表了应对快速城市化和生态绿度变化城市的一个潜在有用工具。基于本案例研究，EGI框架有潜力作为综合环境质量评估工具使用。EGI整合了多个生态维度，可在复杂城市环境中补充遥感生态指数（RSEI）等已有指数。EGI的推广需要在更多城市背景下进行独立验证。",null,"Scientific Reports","2026-09-13T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该研究聚焦城市生态绿度遥感监测，与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[19],{"name":10,"url":6},[21,22,23],"遥感监测","城市生态","生态指数",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":29},"needs_review","2026-10-22.2","rules",{"candidates":30,"agricultural_evidence":14,"reason":54},[31,40,48],{"code":32,"score":33,"supported":34,"title":35,"abstract":37,"tags":39},"I3",15,true,[36],"remote sensing",[38,36],"遥感",[21],{"code":41,"score":42,"supported":34,"title":43,"abstract":44,"tags":47},"H2",6,[],[45,46],"土壤","soil",[],{"code":49,"score":50,"supported":14,"title":51,"abstract":52,"tags":53},"H6",1,[],[],[22],"农业相关性需要复核",[56,57],"城市生态 生态指数 遥感监测","城市生态 生态指数","城市生态生态指数遥感监测-2535",2,"10.1038\u002Fs41598-026-70643-x",{"doi":60,"openalex_id":62,"authors":63,"venue":10,"cited_by_count":15,"oa_url":76,"card":77,"direction":81,"ingested_from":83},"W7212454298",[64,67,70,72,74],{"name":65,"orcid":66},"Amir Houshang Ehsani","https:\u002F\u002Forcid.org\u002F0000-0002-5483-1163",{"name":68,"orcid":69},"Hassan Darabi","https:\u002F\u002Forcid.org\u002F0000-0002-9353-4639",{"name":71,"orcid":9},"Shakila Abedi",{"name":73,"orcid":9},"Seydeh Roya khamooshian",{"name":75,"orcid":9},"Faezeh pouyanejad","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-70643-x_reference.pdf",{"tldr":78,"method":79,"finding":80,"direction":81,"opportunity":82},"构建融合八个遥感指标的生态绿度指数EGI，并在德黑兰验证其城市生态监测能力。","整合NDVI、NDSI、NDBI、LST、LAI等八指标，用PCA降维加权与模糊","四个主成分解释99.99%方差，EGI呈显著南北梯度，北部0.29、南部0.076。","农业遥感与作物表型","可将EGI框架迁移至农业区，结合多季与高分辨率数据验证其跨区域泛化性。","openalex","2026-09-15T23:30:21.213654Z",{"total":42,"page":50,"page_size":42,"items":86},[87,133,215,295,377,435],{"id":88,"title":89,"url":90,"summary":91,"summary_zh":9,"content":9,"source_name":92,"source_url":90,"published_at":93,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":94,"sources":96,"tags":98,"primary_topic":9,"secondary_topics":100,"classification":101,"search_phrases":113,"slug":116,"view_count":15,"doi":117,"paper":118,"created_at":132},5484,"Spatiotemporal Dynamics and Assess of Ecological Quality in Sylhet Metropolitan Area amid Rapid Urbanization: A Remote Sensing Approach","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11422676\u002Fv1","Spatiotemporal Dynamics and Assess of Ecological Quality in Sylhet Metropolitan Area amid Rapid Urbanization: A Remote Sensing Approach。Research Square","Research Square","2026-10-20T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":95},"研究孟加拉国锡尔赫特市生态质量，与三农及农业信息化无关，不予精选。",[97],{"name":92,"url":90},[21,99,22],"土地利用",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":102},{"candidates":103,"agricultural_evidence":14,"reason":54},[104,109],{"code":32,"score":105,"supported":34,"title":106,"abstract":107,"tags":108},12,[36],[36],[21],{"code":49,"score":59,"supported":14,"title":110,"abstract":111,"tags":112},[],[],[99,22],[114,115],"Sylhet 城市扩张 遥感","土地利用 城市生态 遥感监测","Sylhet城市扩张遥感-5484","10.21203\u002Frs.3.rs-11422676\u002Fv1",{"doi":117,"openalex_id":119,"authors":120,"venue":92,"cited_by_count":15,"oa_url":131,"card":9,"direction":81,"ingested_from":83},"W7223013355",[121,123,125,128],{"name":122,"orcid":9},"Md Saikoth Jahan",{"name":124,"orcid":9},"Mst Arjumoni Anu",{"name":126,"orcid":127},"Md. Inzamul Haque","https:\u002F\u002Forcid.org\u002F0000-0003-1756-5561",{"name":129,"orcid":130},"Most. Atia Parvin","https:\u002F\u002Forcid.org\u002F0000-0002-2718-9259","https:\u002F\u002Fwww.researchsquare.com\u002Farticle\u002Frs-11422676\u002Flatest.pdf","2026-10-21T23:30:23.223087Z",{"id":134,"title":135,"url":136,"summary":137,"summary_zh":138,"content":9,"source_name":139,"source_url":136,"published_at":140,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":141,"sources":143,"tags":145,"primary_topic":148,"secondary_topics":153,"classification":160,"search_phrases":189,"slug":192,"view_count":193,"doi":194,"paper":195,"created_at":214},3061,"Assessing the Impact of Wetland Restoration Practices on Ecosystem Services: Evidence from Nyandungu Ecotourism Park, Kigali, Rwanda","https:\u002F\u002Fdoi.org\u002F10.37284\u002Feajenr.9.3.5808","Wetlands play a critical role in sustaining ecosystem services, particularly within rapidly urbanising environments where natural systems are increasingly under pressure. In Rwanda, urban wetland degradation is intensifying due to unplanned settlement expansion, pollution, and infrastructure development. In response, the Government of Rwanda established Nyandungu Ecotourism Park as a flagship urban wetland restoration project. However, limited empirical evidence exists assessing the actual impacts of restoration practices on ecosystem service provision. This study aimed to assess the impact of wetland restoration practices on ecosystem services in Nyandungu Ecotourism Park. The study adopted a mixed-methods research design integrating spatial analysis with socio-economic assessment. Remote sensing and GIS were used to analyse land cover and vegetation changes using satellite imagery from 2008 and 2024. Primary data were collected through questionnaires administered to 399 households and key informant interviews with 25 informants from park management officials, village leaders, and environmental experts. The findings revealed that restoration practices have been highly effective. Land use analysis showed a 92 percent reduction in cropland, while NDVI analysis revealed an 86 percent reduction in bareland and a 139 percent increase in high-quality vegetation cover, all statistically significant. These spatial changes were accompanied by remarkable biodiversity recovery, including 523 plant species, 158 bird species (a 90 percent increase), the Near-Threatened spotted-necked otter, and 41 aquatic macroinvertebrate families. Household survey results showed that 87.2 percent of respondents agreed that biodiversity increased, while 75.5 percent agreed that soil quality improved. However, only 19.5 percent believed the wetland contributes to food-related resources, reflecting the trade-off between conservation success and reduced community resource access.","湿地在维持生态系统服务方面发挥着关键作用，尤其是在自然系统日益承受压力的快速城市化环境中。在卢旺达，由于无序定居点扩张、污染和基础设施建设，城市湿地退化正在加剧。为此，卢旺达政府建立了尼扬敦古生态旅游公园，作为城市湿地修复的旗舰项目。然而，评估修复实践对生态系统服务供给实际影响的实证证据仍然有限。本研究旨在评估湿地修复实践对尼扬敦古生态旅游公园生态系统服务的影响。研究采用混合方法研究设计，将空间分析与社会经济评估相结合。利用2008年和2024年的卫星影像，通过遥感和地理信息系统分析土地覆盖和植被变化。原始数据通过面向399户家庭的问卷调查以及对25名关键信息提供者的访谈收集，访谈对象包括公园管理官员、村级领导和环境专家。研究结果显示，修复实践成效显著。土地利用分析表明，耕地减少了92%；NDVI分析显示，裸地减少了86%，高质量植被覆盖增加了139%，均具有统计学显著性。这些空间变化伴随着显著的生物多样性恢复，包括523种植物、158种鸟类（增加90%）、近危物种斑颈水獭以及41个水生大型无脊椎动物科。家庭调查结果显示，87.2%的受访者认为生物多样性有所增加，75.5%的受访者认为土壤质量有所改善。然而，仅有19.5%的受访者认为该湿地对食物相关资源有贡献，这反映了保护成效与社区资源获取减少之间的权衡。","East African Journal of Environment and Natural Resources","2026-09-19T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":142},"卢旺达城市湿地修复与生态系统服务评估研究，属生态学范畴，与三农、农业信息化、智慧农业主题无直接关联。",[144],{"name":139,"url":136},[21,146,22,147],"生态系统服务","湿地修复",{"code":49,"slug":149,"name":150,"path":151,"parent_code":152},"biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity","H",[154],{"code":155,"slug":156,"name":157,"path":158,"parent_code":159},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",{"status":161,"locked":14,"version":27,"method":28,"evidence":162},"classified",{"candidates":163,"agricultural_evidence":34},[164,171,180,185],{"code":49,"score":165,"supported":34,"title":166,"abstract":167,"tags":170},11,[],[168,146,149,169],"生物多样性","ecosystem service",[22,146],{"code":155,"score":172,"supported":34,"title":173,"abstract":174,"tags":179},9,[],[175,176,177,178],"地理信息","空间分析","GIS","spatial analysis",[],{"code":32,"score":181,"supported":34,"title":182,"abstract":183,"tags":184},7,[],[38,36],[21],{"code":41,"score":42,"supported":34,"title":186,"abstract":187,"tags":188},[],[45,46],[],[190,191],"Nyandungu 湿地公园","卢旺达 湿地修复","Nyandungu湿地公园-3061",4,"10.37284\u002Feajenr.9.3.5808",{"doi":194,"openalex_id":196,"authors":197,"venue":139,"cited_by_count":15,"oa_url":206,"card":207,"direction":213,"ingested_from":83},"W7213648305",[198,200,202,204],{"name":199,"orcid":9},"Oscar Niyomugabo",{"name":201,"orcid":9},"Aboubakar Gasirabo",{"name":203,"orcid":9},"Bernard Tuyishimire",{"name":205,"orcid":9},"Grace De Die Iyishaka","https:\u002F\u002Fjournals.eanso.org\u002Findex.php\u002Feajenr\u002Farticle\u002Fdownload\u002F5808\u002F6138",{"tldr":208,"method":209,"finding":210,"direction":211,"opportunity":212},"评估卢旺达Nyandungu城市湿地公园修复对生态系统服务的影响。","遥感GIS分析2008与2024土地覆盖，结合399户问卷和25位关键知情人访谈","修复使裸地减86%、优质植被增139%、鸟类增90%，但仅19.5%受访者认为湿地提供食物资源。","农业绿色发展与碳","城市湿地修复中保护成效与社区食物资源获取的权衡机制及补偿路径值得研究。","智慧农业 \u002F 农业物联网","2026-09-21T23:30:09.515975Z",{"id":216,"title":217,"url":218,"summary":219,"summary_zh":220,"content":9,"source_name":221,"source_url":218,"published_at":93,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":222,"score_detail":223,"sources":228,"tags":230,"primary_topic":9,"secondary_topics":234,"classification":235,"search_phrases":265,"slug":268,"view_count":15,"doi":269,"paper":270,"created_at":294},5577,"Assessing Land Use and Land Cover Change in the Jamanxim River Region (Brazilian Amazon) from 2015 to 2025 Using CBERS-4\u002FPAN Imagery","https:\u002F\u002Fdoi.org\u002F10.29150\u002Fjhrs.v16i4.269068","Land use and land cover (LULC) changes in the Amazon are among the main drivers of biodiversity loss, ecosystem degradation, and the intensification of climate change. This study aimed to analyze the multitemporal dynamics of LULC around the Jamanxim River, Pará, Brazilian Amazon, between 2015 and 2025, using high-resolution imagery from the CBERS-4\u002FPAN satellite. The study area covers 492.74 km², including part of the Jamanxim National Forest, a conservation unit under strong pressure from agricultural expansion and logging activities. The methodology included geometric correction of the images, Gram–Schmidt pansharpening, and supervised classification with the Random Forest algorithm, validated with historical imagery from Google Earth Pro. Thematic maps of land use and cover were generated, and performance metrics such as overall accuracy, omission and commission errors, and F1-scores were assessed. The results indicated a significant reduction in forest cover, from 412.28 km² in 2015 to 355.47 km² in 2025 (–13.78%). Non-vegetated areas increased by 132.47%, while agricultural areas expanded by 54.97%. The forest and water body classes showed high accuracy (F1-score > 0.95), while confusion persisted between agricultural and bare soil classes. Overall accuracy remained above 90% across all years, with the highest performance recorded in 2020 (96.31%). These results highlight the potential of CBERS-4\u002FPAN imagery for monitoring multitemporal changes in tropical forest landscapes. At the same time, they reveal the intensification of deforestation and the growing threats to conservation in the Amazon, reinforcing the importance of remote sensing for environmental management and policy support.","亚马逊地区的土地利用与土地覆盖（LULC）变化是生物多样性丧失、生态系统退化以及气候变化加剧的主要驱动因素之一。本研究旨在利用CBERS-4\u002FPAN卫星的高分辨率影像，分析2015年至2025年间巴西亚马孙州雅曼辛河（Jamanxim River）周边土地利用与土地覆盖的多时相动态。研究区面积为492.74 km²，包括雅曼辛国家森林（Jamanxim National Forest）的一部分，该保护区正面临农业扩张和采伐活动的强烈压力。研究方法包括影像几何校正、Gram–Schmidt全色锐化以及基于随机森林（Random Forest）算法的监督分类，并利用Google Earth Pro的历史影像进行验证。研究生成了土地利用与覆盖专题图，并评估了总体精度、漏分误差与错分误差以及F1分数等性能指标。结果表明，森林覆盖显著减少，从2015年的412.28 km²降至2025年的355.47 km²（–13.78%）。无植被区域增加了132.47%，农业区域扩张了54.97%。森林和水体类别表现出较高精度（F1分数 > 0.95），而农业类别与裸土类别之间仍存在混淆。各年份总体精度均保持在90%以上，其中2020年性能最高（96.31%）。这些结果凸显了CBERS-4\u002FPAN影像在监测热带森林景观多时相变化方面的潜力，同时揭示了亚马逊地区森林砍伐的加剧以及保护面临的日益增长的威胁，进一步强调了遥感在环境管理和政策支持中的重要性。","Journal of Hyperspectral Remote Sensing",78,{"impact":224,"substance":225,"depth":226,"authority":105,"freshness":172,"relevant":50,"comment":227},18,22,17,"该研究利用CBERS-4\u002FPAN影像量化亚马逊保护区十年间森林减少13.78%，方法规范、结论可靠，对遥感监测与生态保护有参考价值，但地域性强、与国内三农直接关联有限。",[229],{"name":221,"url":218},[21,99,231,232,233],"森林保护","亚马逊","CBERS-4",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":236},{"candidates":237,"agricultural_evidence":34,"reason":264},[238,242,246,253,258],{"code":49,"score":181,"supported":34,"title":239,"abstract":240,"tags":241},[],[168,149],[99],{"code":32,"score":181,"supported":34,"title":243,"abstract":244,"tags":245},[],[38,36],[21],{"code":247,"score":42,"supported":34,"title":248,"abstract":249,"tags":252},"H7",[],[250,251],"气候变化","climate change",[],{"code":41,"score":254,"supported":34,"title":255,"abstract":256,"tags":257},3,[],[46],[],{"code":259,"score":254,"supported":34,"title":260,"abstract":261,"tags":263},"I7",[],[262],"研究方法",[],"多个产业证据相当，需要确认主归属",[266,267],"CBERS-4 亚马逊 土地利用","Jamanxim 森林覆盖 遥感","CBERS-4亚马逊土地利用-5577","10.29150\u002Fjhrs.v16i4.269068",{"doi":269,"openalex_id":271,"authors":272,"venue":221,"cited_by_count":15,"oa_url":218,"card":289,"direction":81,"ingested_from":83},"W7223141286",[273,276,278,281,284,287],{"name":274,"orcid":275},"Ubiratan Joaquim da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-7995-6416",{"name":277,"orcid":9},"Gabriel Henrique Santos Silva",{"name":279,"orcid":280},"Juarez Antonio da Silva","https:\u002F\u002Forcid.org\u002F0000-0002-2898-0309",{"name":282,"orcid":283},"Anderson Luiz Ribeiro de Paiva","https:\u002F\u002Forcid.org\u002F0000-0003-3475-1454",{"name":285,"orcid":286},"Leidjane Maria Maciel de Oliveira","https:\u002F\u002Forcid.org\u002F0000-0003-1251-6998",{"name":288,"orcid":9},"Sylvana Melo dos Santos",{"tldr":290,"method":291,"finding":292,"direction":81,"opportunity":293},"用CBERS-4\u002FPAN影像分析亚马逊Jamanxim河流域2015-2025年土地利用变化。","几何校正、Gram-Schmidt融合、随机森林监督分类，Google Eart","森林覆盖减少13.78%，农业扩张54.97%，裸地增132.47%，总体精度超90%。","可探索中巴地球资源卫星在热带森林退化监测中的业务化应用与多源数据融合。","2026-10-22T11:20:42.901761Z",{"id":296,"title":297,"url":298,"summary":299,"summary_zh":300,"content":9,"source_name":301,"source_url":298,"published_at":93,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":302,"score_detail":303,"sources":307,"tags":309,"primary_topic":314,"secondary_topics":317,"classification":318,"search_phrases":339,"slug":342,"view_count":15,"doi":343,"paper":344,"created_at":376},5576,"Land cover change and soil salinization in Mozambique: A counterfactual analysis over two decades (2001−2022)","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.catena.2026.110691","Soil salinization is a major issue that constrains the sustainable development of agriculture in arid, semi-arid, and coastal lowland areas. It is of great importance for regional land management and climate adaptation to clarify the influence of land cover change on soil salinization. This study aims to quantitatively assess the contribution of land cover change to soil salinization in Mozambique, where both rapid land cover transformation and salinization issues are evident. Firstly, we integrated soil profile electrical conductivity (EC) data, Landsat time-series remote sensing imagery, TerraClimate meteorological data, and the 30 m resolution land cover data, to construct a remote sensing-based EC inversion model for Mozambique. Secondly, we applied a spatially and environmentally constrained counterfactual matching method to quantitatively identify the contributions of different land cover changes on soil salinization trends. Our results reveal that: (1) the spatial distribution of soil salinization in Mozambique exhibits distinct a clear association with proximity to water bodies, with high EC areas primarily concentrated around Lake Malawi in the north and in the coastal regions of Greater Maputo in the south. (2) 26.98% of Mozambique's territory showed a trend of intensifying soil salinization, while 10.88% exhibited a decreasing trend. Areas with intensifying trends are primarily concentrated in the central alluvial plains, localized agricultural development zones, and coastal lowlands. (3) Urbanization was significantly associated with an increasing salinization trend after false discovery rate correction, suggesting that the expansion of impervious surfaces, changes in drainage patterns, and soil compaction may exacerbate localized salt accumulation. Agricultural expansion showed a negative trend difference, consistent with the potential influence of crop cover, tillage, and wet-season leaching, although this association was not significant after false discovery rate correction. The effects of ecological restoration and other factors were not statistically significant. In addition to elucidating the heterogeneous impacts of land cover changes in Mozambique on soil salinization trends, this study also provides methodological guidance and a scientific basis for monitoring\u002Fmanaging soil salinity risks in other coastal lowlands.","土壤盐渍化是制约干旱、半干旱及沿海低地地区农业可持续发展的主要问题。阐明土地覆盖变化对土壤盐渍化的影响，对区域土地管理和气候适应具有重要意义。本研究旨在定量评估土地覆盖变化对莫桑比克土壤盐渍化的贡献，该国土地覆盖转型迅速且盐渍化问题突出。首先，我们整合了土壤剖面电导率（EC）数据、Landsat时间序列遥感影像、TerraClimate气象数据以及30 m分辨率土地覆盖数据，构建了基于遥感的莫桑比克EC反演模型。其次，我们采用空间与环境约束的反事实匹配方法，定量识别不同土地覆盖变化对土壤盐渍化趋势的贡献。研究结果表明：（1）莫桑比克土壤盐渍化的空间分布与水体邻近性呈现明显的关联，高EC区域主要集中于北部的马拉维湖周边以及南部大马普托沿海地区。（2）莫桑比克26.98%的国土面积呈现土壤盐渍化加剧趋势，而10.88%呈现减轻趋势。加剧趋势区域主要集中于中部冲积平原、局部农业开发区及沿海低地。（3）经错误发现率校正后，城市化与盐渍化加剧趋势显著相关，表明不透水面扩张、排水格局改变及土壤压实可能加剧局部盐分累积。农业扩张呈现负向趋势差异，与作物覆盖、耕作及湿季淋洗的潜在影响一致，但该关联经错误发现率校正后不显著。生态恢复及其他因素的影响在统计上不显著。本研究不仅阐明了莫桑比克土地覆盖变化对土壤盐渍化趋势的异质性影响，还为其他沿海低地土壤盐渍化风险的监测与管理提供了方法学指导和科学依据。","CATENA",79,{"impact":304,"substance":225,"depth":224,"authority":305,"freshness":172,"relevant":50,"comment":306},16,14,"该研究基于遥感与反事实匹配方法，定量评估土地覆盖变化对盐渍化的贡献，方法新颖、结论可靠，对沿海低地盐渍化监测具有参考价值，但属境外区域研究，国内政策与产业影响有限。",[308],{"name":301,"url":298},[21,310,311,312,313],"莫桑比克","土壤盐渍化","土地覆盖变化","盐分反演",{"code":41,"slug":46,"name":315,"path":316,"parent_code":152},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",[],{"status":161,"locked":14,"version":27,"method":28,"evidence":319},{"candidates":320,"agricultural_evidence":34},[321,325,329,335],{"code":41,"score":305,"supported":34,"title":322,"abstract":323,"tags":324},[46],[45,46],[],{"code":32,"score":181,"supported":34,"title":326,"abstract":327,"tags":328},[],[38,36],[21],{"code":247,"score":42,"supported":34,"title":330,"abstract":331,"tags":334},[],[332,333],"气候适应","干旱",[],{"code":49,"score":50,"supported":14,"title":336,"abstract":337,"tags":338},[],[],[312],[340,341],"莫桑比克 土壤盐渍化 遥感","土地覆盖变化 盐渍化 反事实分析","莫桑比克土壤盐渍化遥感-5576","10.1016\u002Fj.catena.2026.110691",{"doi":343,"openalex_id":345,"authors":346,"venue":301,"cited_by_count":15,"oa_url":298,"card":371,"direction":81,"ingested_from":83},"W7223069171",[347,349,351,353,356,358,361,364,366,368],{"name":348,"orcid":9},"Yue Li",{"name":350,"orcid":9},"Mengfei Shi",{"name":352,"orcid":9},"Fei Zhang",{"name":354,"orcid":355},"Brian Alan Johnson","https:\u002F\u002Forcid.org\u002F0000-0003-1911-3585",{"name":357,"orcid":9},"Gowhar Meraj",{"name":359,"orcid":360},"Jaime Carlos Macuácua","https:\u002F\u002Forcid.org\u002F0000-0002-4822-6098",{"name":362,"orcid":363},"Pankaj Kumar","https:\u002F\u002Forcid.org\u002F0000-0002-5264-3951",{"name":365,"orcid":9},"Yuanfang Chai",{"name":367,"orcid":9},"Hongtao Xu",{"name":369,"orcid":370},"Xu Ma","https:\u002F\u002Forcid.org\u002F0000-0003-0644-7498",{"tldr":372,"method":373,"finding":374,"direction":81,"opportunity":375},"量化莫桑比克2001-2022年土地覆盖变化对土壤盐渍化的贡献。","融合EC剖面、Landsat时序与气候数据反演EC，并用空间环境约束的反事实匹配","26.98%区域盐渍化加剧；城市化显著关联盐渍化上升，农业扩张关联不显著。","可将反事实匹配框架迁移至其他滨海低地，并引入作物类型与灌溉制度细化农业扩张的盐渍化效应。","2026-10-22T11:20:42.713789Z",{"id":378,"title":379,"url":380,"summary":381,"summary_zh":382,"content":9,"source_name":383,"source_url":380,"published_at":384,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":302,"score_detail":385,"sources":387,"tags":389,"primary_topic":394,"secondary_topics":400,"classification":401,"search_phrases":418,"slug":421,"view_count":15,"doi":422,"paper":423,"created_at":434},5565,"A Unified Survival-Based Energy Framework Linking Plant Color, Stress, and Productivity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23540961","Plant coloration, expressed through leaf greenness, floral pigmentation, and fruit color intensity, reflects the integrated outcome of pigment biosynthesis, optical absorption, metabolic regulation, and energy–mass exchange with the environment. While the biochemical pathways governing the synthesis and degradation of major pigment classes—including chlorophylls, carotenoids, and anthocyanins—are well established, existing models largely interpret color expression as a localized biochemical phenomenon. Such approaches do not explicitly account for whole-plant energy balance, transpiration-driven losses, or thermodynamic constraints, limiting their ability to explain widely observed patterns of color saturation, stress-induced fading, and species-specific stability across environmental gradients. Here we develop a unified framework for plant color generation and stability that treats pigmentation as a survival-limited energetic process embedded within the broader dynamics of absorption, transport, metabolism, and entropy production. Central to the framework is a dimensionless energy survival factor, Ψ=AE\u002FTE+ε where AE represents absorbed and retained energetic and elemental resources relevant to pigment formation, TE denotes transpiration-linked, metabolic, and environmental dissipation losses, and ε captures irreducible entropy-producing degradation inherent to non-equilibrium biological systems. By construction, 0\u003CΨ\u003C1, ensuring full compliance with the second law of thermodynamics. When combined with pigment-specific optical absorption coefficients and physiological limitation functions, the framework yields a physically interpretable description of both pigment concentration and color stability. Empirical ranges for absorbed photosynthetically active radiation (≈45–70%), excitation survival (≈85–95%), and respiratory and transpiration losses (≈30–60% of assimilated resources) naturally constrain Ψ, predicting observed limits on sustained pigment accumulation without invoking biochemical inefficiency or ad hoc correction factors. The analysis demonstrates that increased light availability or enhanced biosynthetic capacity alone does not intensify coloration unless absorbed resources survive transport and loss processes. Stress-induced chlorosis, transient anthocyanin accumulation, and saturation of greenness under high irradiance emerge as direct consequences of reduced energy survival rather than impaired pigment synthesis. By explicitly separating survival from synthesis, the framework reconciles molecular-scale pigment biochemistry with whole-plant and ecosystem-scale color dynamics. This survival-based formulation provides a unified physical basis for interpreting plant color variation across species and environments and offers a scalable foundation for crop stress diagnostics, remote-sensing interpretation, and comparative plant phenotyping. More broadly, it extends survival-limited energy principles to visible plant traits, advancing plant science beyond isolated biochemical descriptions toward a systems-level understanding of how energy governs phenotypic expression.","植物色泽通过叶片绿色度、花色苷着色和果实颜色强度体现，反映了色素生物合成、光学吸收、代谢调控以及与环境的能量-物质交换的综合结果。尽管主要色素类别——包括叶绿素、类胡萝卜素和花青素——的合成与降解生化途径已较为明确，但现有模型大多将颜色表达解释为局部生化现象。此类方法未明确考虑整株植物能量平衡、蒸腾驱动的损耗或热力学约束，限制了其解释广泛观察到的颜色饱和度、胁迫诱导褪色以及跨环境梯度的物种特异性稳定性等模式的能力。本文构建了一个统一的植物颜色生成与稳定性框架，将色素沉着视为一种受生存限制的能量过程，并将其嵌入吸收、运输、代谢和熵产生的更广泛动力学之中。该框架的核心是一个无量纲能量生存因子Ψ=AE\u002FTE+ε，其中AE代表与色素形成相关的被吸收并保留的能量和元素资源，TE表示与蒸腾相关的、代谢的和环境的耗散损失，ε则捕捉非平衡生物系统固有的不可约熵产生降解。根据构建方式，0\u003CΨ\u003C1，确保完全符合热力学第二定律。当与色素特异性光学吸收系数和生理限制函数相结合时，该框架可对色素浓度和颜色稳定性给出具有物理可解释性的描述。吸收性光合有效辐射（约45–70%）、激发能存活率（约85–95%）以及呼吸和蒸腾损失（约占同化资源的30–60%）的经验范围自然约束了Ψ，从而预测出所观察到的持续色素积累限度，而无需引入生化低效性或特设校正因子。分析表明，仅增加光照可用性或增强生物合成能力并不会加深颜色，除非被吸收的资源能够在运输和损失过程中存活下来。胁迫诱导的黄化、瞬时花青素积累以及高辐照下绿色度饱和，均表现为能量生存率降低而非色素合成受损的直接后果。通过明确分离生存","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",{"impact":224,"substance":225,"depth":224,"authority":105,"freshness":172,"relevant":50,"comment":386},"提出以能量生存因子统一解释植物颜色与胁迫的物理框架，方法新颖且对遥感解译和作物诊断有潜在价值，但属预印本理论模型，尚缺田间验证。",[388],{"name":383,"url":380},[390,21,391,392,393],"智慧农业","植物表型","作物胁迫诊断","能量平衡",{"code":395,"slug":396,"name":397,"path":398,"parent_code":399},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[],{"status":161,"locked":14,"version":27,"method":28,"evidence":402},{"candidates":403,"agricultural_evidence":34},[404,409,414],{"code":395,"score":254,"supported":34,"title":405,"abstract":406,"tags":408},[],[407],"萝卜",[],{"code":410,"score":50,"supported":14,"title":411,"abstract":412,"tags":413},"I1",[],[],[390],{"code":32,"score":50,"supported":14,"title":415,"abstract":416,"tags":417},[],[],[21],[419,420],"植物颜色 能量生存因子","作物胁迫 遥感诊断","植物颜色能量生存因子-5565","10.5281\u002Fzenodo.23540961",{"doi":422,"openalex_id":424,"authors":425,"venue":383,"cited_by_count":15,"oa_url":380,"card":429,"direction":81,"ingested_from":83},"W7223098474",[426],{"name":427,"orcid":428},"Mokhdum Azam Mashrafi","https:\u002F\u002Forcid.org\u002F0009-0002-1801-1130",{"tldr":430,"method":431,"finding":432,"direction":81,"opportunity":433},"提出基于生存的能量框架，用能量存活因子解释植物颜色生成与稳定性。","构建无量纲能量存活因子Ψ=AE\u002F(TE+ε)，结合色素吸收系数与生理限制函数。","颜色深浅取决于吸收资源经运输损耗后的存活率，而非单纯合成能力。","可将Ψ因子与冠层光谱\u002F表型遥感结合，发展胁迫早期诊断与生产力预测模型。","2026-10-22T11:20:31.195819Z",{"id":436,"title":437,"url":438,"summary":439,"summary_zh":440,"content":9,"source_name":383,"source_url":438,"published_at":384,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":441,"score_detail":442,"sources":445,"tags":447,"primary_topic":451,"secondary_topics":455,"classification":456,"search_phrases":494,"slug":497,"view_count":15,"doi":498,"paper":499,"created_at":510},5563,"AI-Powered Early Detection of Crop Diseases and Pest Infestations: A New Paradigm for Plantation Risk Management","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23531525","Abstract: Crop diseases and pest infestations remain persistent threats to plantation productivity, with pests estimated to destroy up to 40% of global crop production and plant diseases and invasive insects imposing substantial economic losses worldwide (Food and Agriculture Organization of the United Nations [FAO], 2019). Climate change is intensifying these risks by altering the geographic range, seasonality, and population dynamics of pathogens and pests (Gullino et al., 2021; Skendžić et al., 2021). This paper examines how artificial intelligence (AI) — including convolutional neural networks (CNNs), vision transformers (ViTs), unmanned aerial vehicle (UAV)-based multispectral and hyperspectral sensing, and Internet of Things (IoT)-enabled monitoring — can strengthen the early detection of biotic stress in plantation crops and thereby support plantation risk management. Drawing on recent peer-reviewed and industry literature, the paper synthesises evidence on detection performance, deployment modalities, and pathways for integration into enterprise risk-management systems. It proposes a conceptual framework in which AI-enabled early-warning systems operate as a continuous, spatially explicit risk-sensing layer linking agronomic observations with operational, financial, and insurance decision-making. AI can improve the timeliness, spatial precision, and consistency of surveillance; however, its risk-management value depends on field validation, representative training data, reliable infrastructure, affordable deployment, and appropriate governance. AI should therefore currently be positioned as decision support that augments, rather than replaces, agronomic expertise and ground-truthing. Keywords: artificial intelligence; plant disease detection; pest infestation; precision agriculture; plantation risk management; machine learning; remote sensing. Title: AI-Powered Early Detection of Crop Diseases and Pest Infestations: A New Paradigm for Plantation Risk Management Author: Dr. Geetha Govindan K Gopalakrishnan International Journal of Management and Commerce Innovations ISSN 2348-7585 (Online) Vol. 14, Issue 2, October 2026 - March 2027 Page No: 54-59 Research Publish Journals Website: www.researchpublish.com Published Date: 21-October-2026 DOI: https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23531526 Paper Download Link (Source) https:\u002F\u002Fwww.researchpublish.com\u002Fpapers\u002Fai-powered-early-detection-of-crop-diseases-and-pest-infestations-a-new-paradigm-for-plantation-risk-management","摘要：作物病害与虫害侵染始终是种植园生产力的持续威胁，据估计，害虫每年可摧毁全球高达40%的作物产量，植物病害与入侵昆虫在全球范围内造成重大经济损失（联合国粮食及农业组织[FAO]，2019）。气候变化通过改变病原体与害虫的地理分布范围、季节性规律及种群动态，正在加剧这些风险（Gullino等，2021；Skendžić等，2021）。本文探讨人工智能（AI）——包括卷积神经网络（CNN）、视觉变换器（ViT）、基于无人机（UAV）的多光谱与高光谱遥感，以及物联网（IoT）赋能的监测技术——如何强化种植园作物生物胁迫的早期检测，从而支撑种植园风险管理。本文基于近期同行评审文献与行业文献，综合梳理了检测性能、部署模式及其融入企业风险管理系统的路径等方面的证据。文章提出一个概念框架，其中AI赋能的预警系统作为持续运行、空间显性的风险感知层，将农艺观测与运营、财务及保险决策相衔接。AI能够提升监测的及时性、空间精度与一致性；然而，其风险管理价值取决于田间验证、具有代表性的训练数据、可靠的基础设施、可负担的部署成本以及适当的治理。因此，当前应将AI定位为决策支持工具，用以增强而非替代农艺专业知识与实地核验。关键词：人工智能；植物病害检测；虫害侵染；精准农业；种植园风险管理；机器学习；遥感。题目：AI驱动的作物病害与虫害侵染早期检测：种植园风险管理的新范式。作者：Geetha Govindan K Gopalakrishnan博士。《国际管理与商业创新期刊》ISSN 2348-7585（在线）第14卷第2期，2026年10月—2027年3月，第54-59页。研究出版期刊网站：www.researchpublish.com。发布日期：2026年10月21日。DOI：https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23531526。论文下载链接（来源）：https:\u002F\u002Fwww.researchpublish.com\u002Fpapers\u002Fai-powered-early-detection-of-crop-diseases-and-pest-infestations-a-new-paradigm-for-plantation-risk-ma",56,{"impact":105,"substance":304,"depth":443,"authority":42,"freshness":172,"relevant":50,"comment":444},13,"综述性论文，系统梳理AI与遥感在作物病虫害早期预警中的应用并提出风险管理框架，有参考价值但方法创新与数据规模有限，信源为普通出版平台。",[446],{"name":383,"url":438},[390,448,21,449,450],"农业人工智能","风险管理","病虫害监测",{"code":159,"slug":452,"name":453,"path":454,"parent_code":9},"digital-agriculture","数字农业与前沿技术","\u002Ftopic\u002Fdigital-agriculture",[],{"status":457,"locked":14,"version":27,"method":28,"evidence":458},"partial",{"candidates":459,"agricultural_evidence":34,"reason":493},[460,469,475,483,489],{"code":461,"score":13,"supported":34,"title":462,"abstract":463,"tags":468},"I2",[],[464,465,466,467],"机器学习","machine learning","artificial intelligence","decision support",[448],{"code":32,"score":13,"supported":34,"title":470,"abstract":471,"tags":474},[],[38,36,472,473],"multispectral","hyperspectral",[21],{"code":476,"score":172,"supported":34,"title":477,"abstract":478,"tags":482},"I5",[],[479,480,481],"物联网","internet of things","IoT",[],{"code":410,"score":181,"supported":34,"title":484,"abstract":485,"tags":488},[],[486,487],"精准农业","precision agriculture",[390],{"code":247,"score":42,"supported":34,"title":490,"abstract":491,"tags":492},[],[250,251],[],"一级领域明确，二级方向需要细分",[495,496],"AI 作物病害 早期检测","无人机 多光谱 病虫害监测","AI作物病害早期检测-5563","10.5281\u002Fzenodo.23531525",{"doi":498,"openalex_id":500,"authors":501,"venue":383,"cited_by_count":15,"oa_url":438,"card":504,"direction":213,"ingested_from":83},"W7223085400",[502],{"name":503,"orcid":9},"Dr. Geetha Govindan K Gopalakrishnan",{"tldr":505,"method":506,"finding":507,"direction":508,"opportunity":509},"综述AI（CNN、ViT、无人机遥感、物联网）用于作物病虫害早期检测并融入种植园风险管理。","文献综述，整合CNN、ViT、无人机多\u002F高光谱与IoT监测的检测性能与部署方式。","AI可提升监测及时性与空间精度，但价值取决于田间验证、代表性数据与治理，应作决策支持而非替代专家。","农业人工智能与决策模型","可将AI预警层与保险、金融风控系统对接，研究跨域数据融合与可解释风险定价的空白。","2026-10-22T11:20:24.428080Z"]