[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3080":3,"related-3080":52},{"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":51},3080,"Analysis of Habitat Quality Changes and Their Driving Factors in Rock Desertification Control Areas of Guizhou Province","https:\u002F\u002Fdoi.org\u002F10.22158\u002Fse.v11n4p24","Habitat quality affects the functioning of ecosystems, and analyzing its evolution characteristics and driving factors is important for regional ecological management. This study, based on multi-source remote sensing data and using methods such as the InVEST model and geographic detectors, explores the spatial and temporal evolution of habitat quality in the rocky desertification control area and quantifies the influence of various driving factors. The study found that: (1) from 2000 to 2024, the overall habitat quality in Guizhou's rocky desertification control area showed a slow upward trend, with significant spatial heterogeneity in its distribution.(2) during 2000-2024, the habitat quality level remained generally high, with areas of high-quality habitat gradually expanding and poorly rated habitat areas gradually improving through management.(3) from 2000 to 2024, habitat quality in the study area was driven by both natural and human factors, with human activity gradually becoming the dominant influence. Evaluating the habitat quality in Guizhou's rocky desertification control area allows us to quantify the impact of ecological management on regional habitat quality, providing a theoretical basis and data support for rocky desertification control.","生境质量影响生态系统功能的发挥，分析其演变特征及驱动因素对区域生态管理具有重要意义。本研究基于多源遥感数据，运用InVEST模型和地理探测器等方法，探究石漠化治理区生境质量的时空演变，并量化各驱动因素的影响程度。研究发现：(1)2000—2024年，贵州石漠化治理区生境质量整体呈缓慢上升趋势，其分布具有显著的空间异质性。(2)2000—2024年间，生境质量等级总体较高，高质量生境面积逐步扩大，低等级生境区域通过治理逐步改善。(3)2000—2024年，研究区生境质量受自然因素和人为因素共同驱动，人为活动逐渐成为主导影响因素。评估贵州石漠化治理区生境质量，可以量化生态治理对区域生境质量的影响，为石漠化治理提供理论依据和数据支撑。",null,"Sustainability in Environment","2026-09-18T00:00:00Z","论文",10,false,75,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},16,21,17,13,8,1,"基于多源遥感与InVEST模型量化贵州石漠化治理区生境质量演变及驱动因素，方法规范、数据跨度长，对区域生态治理有参考价值，但属区域案例研究，公共影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"贵州","生态修复","遥感监测","石漠化治理","生境质量",[33,34],"贵州 石漠化治理 生境质量","InVEST模型 遥感 石漠化","贵州石漠化治理生境质量-3080",0,"10.22158\u002Fse.v11n4p24",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":43,"card":44,"direction":48,"ingested_from":50},"W7213557746",[41],{"name":42,"orcid":9},"Xiaoyue Wang","https:\u002F\u002Fwww.scholink.org\u002Fojs\u002Findex.php\u002Fse\u002Farticle\u002Fdownload\u002F58083\u002F14067",{"tldr":45,"method":46,"finding":47,"direction":48,"opportunity":49},"基于多源遥感与InVEST模型，分析贵州石漠化治理区生境质量时空演变及驱动因素。","多源遥感数据、InVEST模型、地理探测器。","2000-2024年生境质量缓慢上升，空间异质性显著，人为活动渐成主导驱动力。","农业遥感与作物表型","可结合多时相遥感与机器学习，预测不同治理情景下生境质量演变，优化生态修复策略。","openalex","2026-09-21T23:30:27.396495Z",{"total":53,"page":22,"page_size":53,"items":54},6,[55,120,159,212,257,288],{"id":56,"title":57,"url":58,"summary":59,"summary_zh":60,"content":9,"source_name":61,"source_url":58,"published_at":62,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":63,"score_detail":64,"sources":69,"tags":71,"search_phrases":75,"slug":78,"view_count":36,"doi":79,"paper":80,"created_at":119},3016,"Afforestation enhances ecosystem stability in the farming-pastoral ecotone of northern China, but its effects are constrained by water availability","https:\u002F\u002Fdoi.org\u002F10.1093\u002Fjpe\u002Frtag232","Abstract The farming-pastoral ecotone of northern China (FPENC), a typical semi-agricultural and semi-pastoral ecologically fragile zone, has long faced controversy over afforestation due to its water-limited environment, raising concerns about how afforestation affects this fragile ecosystem. In this study, based on Google Earth Engine and a Random Forest model, we derive afforestation distribution (1985-2020), and further investigated ecosystem stability under afforestation from the perspectives of short-term responses and long-term dynamic changes. The results showed: (1) By 2020, 67,700 km2 had been afforested in FPENC (6.20% of its area). Afforestation survival strongly depended on precipitation, with relatively low retention rates (40%-70%) in the zones with \u003C 400 mm. (2) At short-term timescales, afforestation mitigated ecosystem state deviations caused by extreme drought events and improved surrounding ecosystems within a 150 m buffer. (3) Over long-term timescales, NDVI across the FPENC exhibited a significant increasing trend over the past four decades, accompanied by an overall enhancement in ecosystem recovery capacity. In zones with > 400 mm annual precipitation and with forest cover exceeding 40%, ecosystem recovery capacity increased significantly, showing there might be a potential linkage among afforestation, precipitation, and ecosystem recovery processes. This study revealed despite water scarcity and low tree survival, afforestation under suitable precipitation can effectively enhance regional ecosystem stability.","中国北方农牧交错带（FPENC）是典型的半农半牧生态脆弱区，由于环境水分受限，长期以来在造林问题上存在争议，引发了人们对造林如何影响这一脆弱生态系统的担忧。本研究基于Google Earth Engine和随机森林模型，反演了1985—2020年造林分布，并进一步从短期响应和长期动态变化两个角度研究了造林条件下的生态系统稳定性。结果表明：（1）截至2020年，FPENC已造林67,700 km²，占其面积的6.20%。造林存活强烈依赖降水，在降水量小于400 mm的区域，保存率相对较低（40%—70%）。（2）在短期时间尺度上，造林缓解了极端干旱事件引起的生态系统状态偏离，并改善了150 m缓冲区内周边生态系统。（3）在长期时间尺度上，过去四十年FPENC的NDVI呈显著增加趋势，同时生态系统恢复能力总体增强。在年降水量大于400 mm且森林覆盖率超过40%的区域，生态系统恢复能力显著提高，表明造林、降水与生态系统恢复过程之间可能存在潜在联系。本研究揭示，尽管存在水分短缺和树木存活率低的问题，但在适宜降水条件下，造林能够有效增强区域生态系统稳定性。","Journal of Plant Ecology","2026-09-17T00:00:00Z",80,{"impact":65,"substance":66,"depth":65,"authority":67,"freshness":21,"relevant":22,"comment":68},18,22,14,"基于遥感与随机森林量化北方农牧交错带造林成效及水分约束，数据规模大、结论有新意，对生态修复与农业信息化有参考价值。",[70],{"name":61,"url":58},[28,29,72,73,74],"造林","农牧交错带","水资源约束",[76,77],"北方农牧交错带 造林 水资源","Google Earth Engine 造林 遥感","北方农牧交错带造林水资源-3016","10.1093\u002Fjpe\u002Frtag232",{"doi":79,"openalex_id":81,"authors":82,"venue":61,"cited_by_count":36,"oa_url":113,"card":114,"direction":48,"ingested_from":50},"W7213445880",[83,86,89,91,93,95,97,99,101,103,106,108,111],{"name":84,"orcid":85},"Yuchao Luo","https:\u002F\u002Forcid.org\u002F0000-0003-0063-3505",{"name":87,"orcid":88},"Haile Zhao","https:\u002F\u002Forcid.org\u002F0000-0002-5870-062X",{"name":90,"orcid":9},"Qianhe Wang",{"name":92,"orcid":9},"Yi Zhou",{"name":94,"orcid":9},"Xin Chen",{"name":96,"orcid":9},"Yuling Jin",{"name":98,"orcid":9},"Xingjie Yin",{"name":100,"orcid":9},"Guoliang Zhang",{"name":102,"orcid":9},"Haorui Sun",{"name":104,"orcid":105},"Jun Bai","https:\u002F\u002Forcid.org\u002F0000-0002-1408-4271",{"name":107,"orcid":9},"Huiyao Shi",{"name":109,"orcid":110},"Zhihua Pan","https:\u002F\u002Forcid.org\u002F0000-0002-8187-1574",{"name":112,"orcid":9},"Pingli An","https:\u002F\u002Facademic.oup.com\u002Fjpe\u002Fadvance-article-pdf\u002Fdoi\u002F10.1093\u002Fjpe\u002Frtag232\u002F71179175\u002Frtag232.pdf",{"tldr":115,"method":116,"finding":117,"direction":48,"opportunity":118},"基于GEE和随机森林反演1985-2020年北方农牧交错带造林分布，评估其对生态系统稳定性的影响。","Google Earth Engine遥感数据与随机森林模型，分析造林分布及ND","造林可缓解干旱影响并提升恢复力，但存活率与效果受降水制约，400mm为关键阈值。","可探究不同降水梯度下造林-水分-恢复力耦合机制，优化生态修复的水资源约束阈值。","2026-09-20T23:30:22.592517Z",{"id":121,"title":122,"url":123,"summary":124,"summary_zh":125,"content":9,"source_name":126,"source_url":123,"published_at":127,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":36,"score_detail":128,"sources":130,"tags":132,"search_phrases":135,"slug":138,"view_count":36,"doi":139,"paper":140,"created_at":158},2671,"Burn severity, vegetation degradation, and carbon storage loss in the Belemedik forest fire: implications for protected area management and post-fire restoration","https:\u002F\u002Fdoi.org\u002F10.46309\u002Fbiodicon.2026.2000016","Purpose: This study evaluates the ecological impacts of the 9 September 2020 forest fire in the Kaleboynu area of Eskikonacık Neighborhood, Pozantı District, Adana Province, on the Çakıt Stream micro-watershed, which partially overlaps with Belemedik Nature Park. Using an integrated remote sensing approach, it assesses fire-induced changes in burn severity, vegetation structure, and carbon storage capacity to support post-fire restoration planning in a protected Mediterranean ecosystem.Methods: The study was conducted within the 9,783.06-ha Çakıt Stream micro-watershed. Cloud-free Sentinel-2A MSI Level-2A imagery acquired before (05.09.2020) and after the fire (15.09.2020) was used to calculate the Normalized Burn Ratio (NBR), Differenced NBR (dNBR), and Normalized Difference Vegetation Index (NDVI). Carbon storage was estimated using a nonlinear regression model relating NDVI to pixel-level carbon content. Spatial analyses were performed in ArcGIS 10.8.Findings: dNBR analysis showed that 92.49% (9,049.16 ha) of the watershed remained unburned or unchanged, while 725.92 ha was affected to varying degrees. NDVI results revealed losses of 330.65 ha of tree cover and 96.09 ha of shrub\u002Fgrassland vegetation, accompanied by a 426.74 ha increase in bare surfaces. Total carbon storage declined from 105,465.71 tC to 105,450.25 tC, representing a loss of 15.46 tC (56.69 t CO₂e), primarily concentrated on forested slopes surrounding the Çakıt Stream valley.Conclusions: Although the wildfire affected only a limited portion of the watershed, it caused substantial biomass losses, disrupted vegetation continuity, and reduced carbon sequestration capacity. The concentration of damage on steep slopes indicates increased risks of erosion and surface runoff. Erosion control, restoration with pioneer and fire-adapted native species, and long-term remote sensing monitoring are recommended to support ecosystem recovery, restore habitat connectivity, and sustain ecosystem services.","目的：本研究评估2020年9月9日发生在阿达纳省波赞特ı区埃斯基科纳吉克街区卡莱博伊努地区的森林火灾对恰克特溪微流域（该流域与贝莱梅迪克自然公园部分重叠）的生态影响。研究采用综合遥感方法，评估火灾引起的火烧严重程度、植被结构和碳储量变化，以支持这一受保护地中海生态系统的火后恢复规划。方法：研究在面积9，783.06公顷的恰克特溪微流域内开展。利用火灾前（2020年9月5日）和火灾后（2020年9月15日）获取的无云Sentinel-2A MSI Level-2A影像，计算归一化燃烧比率（NBR）、差值归一化燃烧比率（dNBR）和归一化植被指数（NDVI）。碳储量采用将NDVI与像元级碳含量关联的非线性回归模型进行估算。空间分析在ArcGIS 10.8中完成。结果：dNBR分析表明，流域92.49%（9，049.16公顷）的区域未过火或未发生变化，725.92公顷受到不同程度影响。NDVI结果显示，乔木覆盖损失330.65公顷，灌木\u002F草地植被损失96.09公顷，同时裸露地表增加426.74公顷。总碳储量从105，465.71吨碳下降至105，450.25吨碳，损失15.46吨碳（56.69吨二氧化碳当量），主要集中在恰克特溪谷周围的森林坡面上。结论：尽管此次野火仅影响流域的有限部分，但造成了大量生物量损失，破坏了植被连续性，并降低了碳固存能力。损害集中在陡坡上，表明侵蚀和地表径流风险增加。建议采取侵蚀控制、利用先锋树种和适应火灾的本地物种进行恢复，以及长期遥感监测，以支持生态系统恢复、恢复栖息地连通性并维持生态系统服务。","Biological Diversity and Conservation","2026-09-15T00:00:00Z",{"impact":36,"substance":36,"depth":36,"authority":36,"freshness":36,"relevant":36,"comment":129},"该研究聚焦土耳其地中海保护区火烧严重度与碳储量损失评估，属生态遥感领域，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。",[131],{"name":126,"url":123},[28,29,133,134],"森林碳汇","自然保护地",[136,137],"自然保护地 森林碳汇 生态修复 遥感监测","自然保护地 森林碳汇","自然保护地森林碳汇生态修复遥感监测-2671","10.46309\u002Fbiodicon.2026.2000016",{"doi":139,"openalex_id":141,"authors":142,"venue":126,"cited_by_count":36,"oa_url":152,"card":153,"direction":48,"ingested_from":50},"W7213299850",[143,146,149],{"name":144,"orcid":145},"Nuriye Ebru Yıldız","https:\u002F\u002Forcid.org\u002F0000-0002-3508-4895",{"name":147,"orcid":148},"Barış Kahveci","https:\u002F\u002Forcid.org\u002F0000-0002-8508-1748",{"name":150,"orcid":151},"Tülay Ezer","https:\u002F\u002Forcid.org\u002F0000-0002-6485-5505","https:\u002F\u002Fdergipark.org.tr\u002Fen\u002Fdownload\u002Farticle-file\u002F6248142",{"tldr":154,"method":155,"finding":156,"direction":48,"opportunity":157},"用哨兵2号影像评估2020年土耳其Belemedik林火后的火烧严重度、植被退化与碳储量损失。","Sentinel-2A影像计算NBR\u002FdNBR\u002FNDVI，非线性回归估算碳储量，","仅7.5%流域过火，但损失330.65公顷林地，碳储量减少15.46吨碳，集中于陡坡。","可结合多时相遥感与生态模型，量化火后恢复轨迹及保护区分区管理对碳汇的长期影响。","2026-09-16T23:30:30.571646Z",{"id":160,"title":161,"url":162,"summary":163,"summary_zh":164,"content":9,"source_name":165,"source_url":162,"published_at":127,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":166,"score_detail":167,"sources":170,"tags":172,"search_phrases":176,"slug":179,"view_count":36,"doi":180,"paper":181,"created_at":211},2639,"Post-disturbance soil monitoring in forests using remote sensing: an evidence map","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fsoil-12-885-2026","Forest soils underpin ecosystem resilience and productivity but are increasingly threatened by natural and anthropogenic disturbances. Monitoring post-disturbance soil degradation at operational scales remains challenging in forests, where ground-signal obstruction and reliance on proxy indicators constrain remote sensing (RS) applications. To identify where RS can benefit soil monitoring and inform emerging reporting needs, we developed a structured evidence map of studies assessing post-disturbance forest soil degradation using RS methods. From 4338 records, 72 primary studies were synthesized across disturbance types, biomes, platforms, scales, and indicators. The evidence base is dominated by wildfire and harvesting, reflecting disturbance pathways that produce observable surface impacts. Multispectral satellite data remain the primary tool for mapping post-fire severity and erosion-related indicators, while LiDAR and stereo-photogrammetry are most often used to quantify surface deformation after harvest operations. Indicators tied to subsurface physical, chemical, or biological change remain sparsely represented due to observability limits. Overall, RS is most effective for mapping disturbance footprints, detecting surface-expressed indicators, and stratifying landscapes for targeted field assessment, rather than directly measuring soil properties. This evidence map clarifies the benefits and limits of RS, identifies persistent gaps, and highlights priorities for developing disturbance-aware soil-monitoring frameworks. It also clarifies which soil indicators are most consistently observable with RS and which require complementary approaches. By linking disturbance processes to observable indicators, this synthesis helps identify realistic RS-supported objectives that may inform future reporting frameworks within national forest monitoring and assessment programs.","森林土壤支撑着生态系统的韧性与生产力，却日益受到自然和人为干扰的威胁。在森林中，由于地面信号遮挡以及对代理指标的依赖限制了遥感（RS）应用，在可操作尺度上监测干扰后的土壤退化仍具挑战性。为明确遥感可在何处助力土壤监测并满足新兴的报告需求，我们编制了一份结构化证据图，涵盖利用遥感方法评估干扰后森林土壤退化的研究。从4338条记录中，综合了72项原始研究，涉及干扰类型、生物群系、平台、尺度和指标。证据基础以野火和采伐为主，反映了可产生可观测地表影响的干扰路径。多光谱卫星数据仍是绘制火灾后严重程度和侵蚀相关指标的主要工具，而激光雷达（LiDAR）和立体摄影测量最常用于量化采伐作业后的地表形变。由于可观测性限制，与地下物理、化学或生物变化相关的指标仍鲜有涉及。总体而言，遥感最适用于绘制干扰足迹、探测地表表现的指标，以及为针对性实地评估进行景观分层，而非直接测量土壤属性。该证据图阐明了遥感的优势与局限，识别了持续存在的空白，并指出了开发干扰感知土壤监测框架的优先事项。它还明确了哪些土壤指标最易通过遥感持续观测，哪些需要互补方法。通过将干扰过程与可观测指标相联系，本综合有助于确定现实的遥感支持目标，可为国家级森林监测与评估项目未来的报告框架提供参考。","SOIL",79,{"impact":17,"substance":66,"depth":65,"authority":67,"freshness":168,"relevant":22,"comment":169},9,"系统梳理遥感监测灾后森林土壤退化的证据图谱，方法规范、数据规模可观，对林业遥感与土壤监测应用有实质参考价值。",[171],{"name":165,"url":162},[28,29,173,174,175],"森林土壤","林业信息化","证据图谱",[177,178],"林业信息化 森林土壤 生态修复 证据图谱","林业信息化 森林土壤","林业信息化森林土壤生态修复证据图谱-2639","10.5194\u002Fsoil-12-885-2026",{"doi":180,"openalex_id":182,"authors":183,"venue":165,"cited_by_count":22,"oa_url":204,"card":205,"direction":210,"ingested_from":50},"W7140718837",[184,186,188,190,192,195,198,200,202],{"name":185,"orcid":9},"Maisy Roach-Krajewski",{"name":187,"orcid":9},"Xavier Giroux-Bougard",{"name":189,"orcid":9},"David Paré",{"name":191,"orcid":9},"Catlan Dallaire",{"name":193,"orcid":194},"Luc Guindon","https:\u002F\u002Forcid.org\u002F0000-0002-4346-7351",{"name":196,"orcid":197},"Florian Jordan","https:\u002F\u002Forcid.org\u002F0000-0003-2242-7411",{"name":199,"orcid":9},"Charlotte Norris",{"name":201,"orcid":9},"Kara Webster",{"name":203,"orcid":9},"Jérôme Laganière","https:\u002F\u002Fsoil.copernicus.org\u002Farticles\u002F12\u002F885\u002F2026\u002Fsoil-12-885-2026.pdf",{"tldr":206,"method":207,"finding":208,"direction":48,"opportunity":209},"用证据图方法系统梳理遥感监测干扰后森林土壤退化的72项研究，明确其能力与局限。","证据图法，从4338条记录筛选72项研究，按干扰、平台、指标等分类。","遥感擅长制图干扰范围与地表指标，难以直接测量土壤理化生物属性。","可构建干扰感知的土壤监测框架，并研发地表-地下指标耦合的遥感反演方法。","智慧农业 \u002F 农业物联网","2026-09-16T23:30:09.927061Z",{"id":213,"title":214,"url":215,"summary":216,"summary_zh":217,"content":9,"source_name":218,"source_url":215,"published_at":219,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":220,"score_detail":221,"sources":225,"tags":227,"search_phrases":231,"slug":234,"view_count":36,"doi":235,"paper":236,"created_at":256},2063,"Higher vegetation diversity and stronger forest structure occur in managed zones despite widespread land cover degradation in Ise Forest Reserve Nigeria","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44415-026-00129-1","The forest ecosystem of Ise Forest Reserve in Nigeria is threatened by land-use conversion and timber exploitation. However, part of the enclave was managed under the Southwest\u002FNiger Delta Forest Project, described as the “managed zone”. This study investigated spatial differences in vegetation condition and temporal patterns of land-cover degradation by integrating systematic field sampling, remote sensing and geographic information technologies. Eleven 25 × 25 m plots were laid along 200 m transects during a field sampling exercise carried out in disturbed and managed zones and were used to test differences in species diversity and structural attributes. In total, 27 species (17 families) were recorded, with Ricinodendron heudelotii achieving the highest frequency ( n = 55) and Diospyros lotus exhibiting the most significant mean height (12.20 ± 0.00 m), canopy cover (18.60 ± 0.00 m), and diameter at breast height, DBH (138.13 ± 0.00 cm). Significant differences ( p \u003C 0.001) in height, DBH, and canopy cover were observed between the disturbed and managed zones. Vegetation diversity was higher in the managed zone than in the disturbed zone. The values of the Shannon–Wiener, Simpson concentration, and Margalef richness indices were higher in the managed zone than in the disturbed zone. The lower rates of farmland expansion and secondary forest loss in the managed zone indicated spatial differences in the severity of land degradation. Since data on the area’s pre-intervention stage for direct comparison were not available, the differences between the managed and disturbed zones could not be attributed solely to the 2021 conservation project and remain subject to review in a long-term evaluation.","尼日利亚伊势森林保护区的森林生态系统正受到土地利用转换和木材采伐的威胁。然而，该飞地的一部分在“西南\u002F尼日尔三角洲森林项目”下得到管理，被称为“管理区”。本研究通过整合系统野外采样、遥感与地理信息技术，探讨了植被状况的空间差异以及土地覆盖退化的时间格局。在受干扰区和管理区开展的野外采样中，沿200 m样带设置了11个25 × 25 m样方，用于检验物种多样性和结构属性的差异。共记录27个物种（17科），其中非洲樱桃（Ricinodendron heudelotii）出现频率最高（n = 55），而君迁子（Diospyros lotus）的平均高度（12.20 ± 0.00 m）、冠层盖度（18.60 ± 0.00 m）和胸径（DBH，138.13 ± 0.00 cm）最大。受干扰区与管理区在高度、胸径和冠层盖度方面存在显著差异（p \u003C 0.001）。管理区的植被多样性高于受干扰区。Shannon–Wiener指数、Simpson集中度指数和Margalef丰富度指数在管理区均高于受干扰区。管理区农田扩张和次生林丧失速率较低，表明土地退化严重程度存在空间差异。由于缺乏该地区干预前阶段的数据以进行直接比较，管理区与受干扰区之间的差异不能完全归因于2021年的保护项目，仍有待长期评估加以审视。","Discover Forests","2026-09-08T00:00:00Z",61,{"impact":21,"substance":65,"depth":222,"authority":223,"freshness":21,"relevant":22,"comment":224},15,12,"尼日利亚保护区管理成效的实证研究，方法扎实但地域性强、与国内三农信息化关联有限，可作为遥感生态监测案例参考。",[226],{"name":218,"url":215},[28,228,229,29,230],"生物多样性","土地退化","森林保护",[232,233],"生物多样性 土地退化 森林保护 生态修复","生物多样性 土地退化","生物多样性土地退化森林保护生态修复-2063","10.1007\u002Fs44415-026-00129-1",{"doi":235,"openalex_id":237,"authors":238,"venue":218,"cited_by_count":36,"oa_url":250,"card":251,"direction":48,"ingested_from":50},"W7211968416",[239,242,244,246,248],{"name":240,"orcid":241},"Oluwatobi Emmanuel Olaniyi","https:\u002F\u002Forcid.org\u002F0000-0002-1421-9068",{"name":243,"orcid":9},"Elijah Ogunsakin",{"name":245,"orcid":9},"Babafemi Ogunjemite",{"name":247,"orcid":9},"Kawiyu Rafiu",{"name":249,"orcid":9},"Ebere Anozie","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44415-026-00129-1.pdf",{"tldr":252,"method":253,"finding":254,"direction":48,"opportunity":255},"研究尼日利亚Ise森林保护区管理区与干扰区的植被多样性和结构差异及土地覆盖退化。","野外样方调查、遥感与GIS结合，比较管理区和干扰区植被指标。","管理区植被多样性和森林结构显著优于干扰区，农田扩张和次生林损失更低。","可开展长期监测评估保护项目效果，结合多时相遥感量化管理措施对植被恢复的因果影响。","2026-09-10T23:30:30.245193Z",{"id":258,"title":259,"url":260,"summary":261,"summary_zh":9,"content":9,"source_name":262,"source_url":9,"published_at":263,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":264,"score_detail":265,"sources":268,"tags":270,"search_phrases":275,"slug":278,"view_count":36,"doi":9,"paper":279,"created_at":287},3122,"Advances in Information Sensing and Intelligent Monitoring of Field Crops Throughout the Full Growth Cycle（大田作物全生育期信息感知与智能监测研究进展）","https:\u002F\u002Fwww.mdpi.com\u002F2073-4395\u002F16\u002F18\u002F1852","江苏大学农业工程学院 Tang Ruifan 等在《Agronomy》16(18): 1852 发表综述（2026-09-20 发表）：大田作物在不同生育阶段持续变化、呈现显著空间异质性、需在短作业窗口内进行管理。研究以生育阶段为主线组织文献，通过\"农业需求—可观测变量—感知平台—数据处理方法—验证设计—状态解释—管理或装备输出\"通用链条分析。从卫星遥感、无人机感知、地面与近端感知、田间物联网、机载传感器、多源融合、作物模型与机器学习方法按空间支撑、时间连续性、尺度匹配、田间稳健性、迁移条件、不确定性与操作适用性比较。综述报告作物表型反演、田间环境表征、生物胁迫识别在特定条件下已建立；跨阶段状态继承、一致参考测量、独立验证、监测结果向可执行任务转化仍不充分。提出生命周期导向的信息处理视角，未来应加强跨作物跨区域验证、机理性与数据驱动模型协同、不确定性报告、互操作性和田间反馈。","MDPI Agronomy","2026-09-20T00:00:00Z",76,{"impact":17,"substance":266,"depth":65,"authority":20,"freshness":168,"relevant":22,"comment":267},20,"江苏大学团队在核心期刊发表的综述，系统梳理大田作物全生育期感知与监测技术链条，专业深度与信息增量较高，但属学术综述、产业影响有限，适合进入主题聚合而非头条精选。",[269],{"name":262,"url":260},[271,272,273,29,274],"智慧农业","农业物联网","作物表型","大田作物",[276,277],"江苏大学 大田作物 智能监测","Agronomy 作物全生育期 信息感知","江苏大学大田作物智能监测-3122",{"doi":9,"openalex_id":9,"authors":280,"venue":9,"cited_by_count":36,"oa_url":9,"card":281,"direction":48,"ingested_from":286},[],{"tldr":282,"method":283,"finding":284,"direction":48,"opportunity":285},"综述大田作物全生育期信息感知与智能监测，按生育阶段梳理技术并指出转化不足。","以生育阶段为主线，比较卫星、无人机、地面物联网、模型与机器学习等方法。","表型反演与胁迫识别已有条件建立，但跨阶段继承、独立验证与可执行转化不足。","可研究跨生育阶段状态继承建模、一致参考测量与监测结果向田间作业指令的转化。","agent","2026-09-22T00:05:38.276747Z",{"id":289,"title":290,"url":291,"summary":292,"summary_zh":293,"content":9,"source_name":294,"source_url":291,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":63,"score_detail":295,"sources":297,"tags":299,"search_phrases":304,"slug":307,"view_count":36,"doi":308,"paper":309,"created_at":337},3084,"Spatiotemporal evolution and drivers of eco-environmental quality for sustainable rural tourism in China’s Yangtze River Basin: an explainable AI approach","https:\u002F\u002Fdoi.org\u002F10.1080\u002F17538947.2026.2735566","Balancing tourism-driven growth (SDG 8.9) with terrestrial ecosystem conservation (SDG 15) is vital for sustainable watershed management. Focusing on 409 Key Rural Tourism Villages in China’s Yangtze River Basin, this study integrates Google Earth Engine and MODIS data to assess eco-environmental quality (EEQ) from 2000 to 2024 using the Remote Sensing Ecological Index (RSEI), employing an XGBoost-SHAP framework to decode driving mechanisms. Results indicate that these villages exhibit a clustered spatial distribution pattern, with three core agglomerations. The mean RSEI across all villages exceeds 0.73, indicating overall improvement and resilient recovery after 2020. However, a distinct north-south spatial disparity emerged: improved villages were predominantly concentrated north of the Yangtze River mainstem, whereas degraded villages clustered in the Taihu, Poyang, and Dongting Lake basins to the south. Elevation, land-use change, and temperature are the primary drivers, with a critical altitudinal threshold near 2,500 metres, where synergistic effects turn antagonistic. Although the XGBoost model achieved strong predictive performance (R2 = 0.853, RMSE = 0.071), 14.7% of the variance remains unexplained, suggesting the influence of additional unmeasured factors. These findings advance SDG 15 localisation by establishing spatial baselines and threshold-guided carrying-capacity regulations for watershed tourism governance.","在可持续流域管理中，平衡旅游驱动型增长（SDG 8.9）与陆地生态系统保护（SDG 15）至关重要。本研究以中国长江流域409个全国乡村旅游重点村为对象，集成Google Earth Engine与MODIS数据，基于遥感生态指数（RSEI）评估2000—2024年生态环境质量（EEQ），并采用XGBoost-SHAP框架解析其驱动机制。结果表明，这些村庄呈集聚型空间分布格局，形成三个核心集聚区。所有村庄的RSEI均值超过0.73，表明生态环境质量总体改善，并在2020年后呈现韧性恢复。然而，南北空间分异显著：改善型村庄主要集中于长江干流以北，而退化型村庄则聚集于以南的太湖、鄱阳湖和洞庭湖流域。海拔、土地利用变化和气温是主要驱动因子，在约2500 m处存在关键海拔阈值，超过该阈值后协同效应转为拮抗效应。尽管XGBoost模型具有较强预测性能（R² = 0.853，RMSE = 0.071），仍有14.7%的方差未能解释，提示其他未测因素的影响。本研究通过建立空间基线和阈值引导的承载力调控措施，推动了SDG 15的本土化，为流域旅游治理提供了依据。","International Journal of Digital Earth",{"impact":65,"substance":66,"depth":65,"authority":67,"freshness":21,"relevant":22,"comment":296},"基于GEE与MODIS的乡村文旅生态质量长时序评估，方法新颖、数据规模大，对流域旅游承载力治理有参考价值。",[298],{"name":294,"url":291},[300,29,301,302,303],"长江流域","乡村文旅","生态遥感","可持续旅游",[305,306],"长江流域 乡村旅游 生态质量","RSEI 遥感生态指数 乡村","长江流域乡村旅游生态质量-3084","10.1080\u002F17538947.2026.2735566",{"doi":308,"openalex_id":310,"authors":311,"venue":294,"cited_by_count":36,"oa_url":329,"card":330,"direction":336,"ingested_from":50},"W7213546376",[312,314,317,319,321,323,326],{"name":313,"orcid":9},"Xiaojuan Zhang",{"name":315,"orcid":316},"Zhe Chen","https:\u002F\u002Forcid.org\u002F0000-0001-7579-1968",{"name":318,"orcid":9},"Libin Guo",{"name":320,"orcid":9},"Guoyan Wang",{"name":322,"orcid":9},"Yongxiu Zhou",{"name":324,"orcid":325},"Hui Li","https:\u002F\u002Forcid.org\u002F0000-0002-3565-1773",{"name":327,"orcid":328},"Zhongchang Sun","https:\u002F\u002Forcid.org\u002F0000-0003-3219-0542","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F17538947.2026.2735566?needAccess=true",{"tldr":331,"method":332,"finding":333,"direction":334,"opportunity":335},"评估长江流域409个乡村旅游村2000-2024年生态环境质量演变并解析驱动机制。","GEE与MODIS数据、RSEI指数、XGBoost-SHAP可解释AI框架。","整体EEQ改善但南北分异明显，海拔、土地利用与温度为主导驱动，2500米为协同转拮抗阈值。","农业绿色发展与碳","可探究未解释的14.7%方差来源，并针对太湖、鄱阳湖、洞庭湖退化区开展旅游承载力调控研究。","数字乡村与农业信息化","2026-09-21T23:30:36.842989Z"]