[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2533":3},{"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,"view_count":32,"doi":33,"paper":34,"created_at":62},2533,"Quantifying the Environmental Impact of Artisanal and Small‐Scale Mining: An Integrated Approach for Sustainable Development Insights","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fsd.71693","ABSTRACT Artisanal and small‐scale mining (ASM) provides livelihoods for over 44.5 million people globally, yet its largely unregulated nature causes severe environmental degradation in host communities. In Nigeria, where ASM accounts for over 90% of solid mineral production, the sector increasingly encroaches on agricultural land. Despite growing recognition of ASM's environmental impacts across West Africa, no study has yet applied the novel SDGSAT‐1 satellite purpose‐built for SDG monitoring at 10 m resolution to quantify ASM land degradation in Nigeria, and few studies simultaneously integrate multi‐sensor remote sensing, in‐situ soil contamination assessment, and hydrological transport modelling within a single integrated framework. This study addresses that gap. This study integrates SDGSAT‐1 Multispectral Imager and Landsat 9 imagery (both acquired 12 January 2024) with field‐based soil sampling (November 2023, dry season) and GIS hydrological modelling for Igbojaiye community, Oyo State, Nigeria. Eight vegetation, water and soil indices (NDVI, EVI, SAVI, TSAVI, TVI, NDWI, BSI) and Land Surface Temperature were derived from satellite imagery. Soil samples from eight mining‐affected points and four undisturbed control points were analyzed for physicochemical properties and heavy metals (Fe, Pb, Zn) using Atomic Absorption Spectrometry. Contamination Factor, Geoaccumulation Index, Pollution Load Index, and a Potential Ecological Risk Index were computed. A Digital Elevation Model was used to delineate contaminant transport pathways. ASM‐affected areas exhibited severe vegetation loss (68% of land within 500 m of mining pits classified as Degraded; mean NDVI −0.08 vs. +0.18 in control areas) and elevated Land Surface Temperature (mean 35.2°C ± 1.3°C vs. 28.9°C ± 0.8°C in controls). Mining soils showed markedly degraded physicochemical properties (organic carbon 4× lower, moisture 5× lower, pH more acidic). Lead exhibited very high contamination (mean Contamination Factor 10.0; Geoaccumulation Index Class 3: moderately to heavily contaminated) with a statistically significant distance‐decay gradient ( r = −0.60, p = 0.04). No metal exceeded WHO\u002FFAO soil limits in absolute terms. Hydrological modelling identified direct flow pathways from mining pits to downstream farmland and waterbodies. ASM in Igbojaiye initiates a cascade of compounding degradation, soil toxicity, microclimatic disruption, and hydrological pollutant dispersal that collectively undermine agricultural productivity and water security, directly impeding SDGs 2, 6, 13, and 15. This study represents one of the first applications of SDGSAT‐1 for ASM monitoring in Nigeria, establishing a replicable multi‐sensor framework for evidence‐based environmental governance of ASM in data‐scarce sub‐Saharan African contexts. Remediation priorities include sediment traps at mining pit outflows, phytoremediation with native metal‐tolerant species, and satellite‐based biannual monitoring protocols.","手工和小规模采矿（ASM）为全球超过4450万人提供了生计，但其基本上不受监管的性质对所在社区造成了严重的环境退化。在尼日利亚，手工和小规模采矿占固体矿产产量的90%以上，该行业日益侵占农业用地。尽管西非地区对ASM环境影响的认知不断增加，但尚无研究应用专为可持续发展目标监测而设计的10米分辨率SDGSAT-1卫星来量化尼日利亚的ASM土地退化，且很少有研究将多传感器遥感、原位土壤污染评估和水文输移建模同时整合于单一综合框架中。本研究填补了这一空白。本研究将SDGSAT-1多光谱成像仪和Landsat 9影像（均于2024年1月12日获取）与实地土壤采样（2023年11月，旱季）及GIS水文建模相结合，以尼日利亚奥约州Igbojaiye社区为研究区。从卫星影像中提取了八个植被、水体和土壤指数（NDVI、EVI、SAVI、TSAVI、TVI、NDWI、BSI）及地表温度。采用原子吸收光谱法对来自八个受采矿影响点和四个未受干扰对照点的土壤样品进行了理化性质和重金属（Fe、Pb、Zn）分析。计算了污染因子、地累积指数、污染负荷指数和潜在生态风险指数。利用数字高程模型划定了污染物输移路径。受ASM影响的区域表现出严重的植被丧失（采矿坑500米范围内68%的土地被归类为退化；NDVI均值为−0.08，对照区为+0.18）和升高的地表温度（均值35.2°C ± 1.3°C，对照区为28.9°C ± 0.8°C）。矿区土壤理化性质显著退化（有机碳低4倍，含水量低5倍，pH更偏酸性）。铅表现出极高的污染水平（污染因子均值10.0；地累积指数3级：中度至重度污染），并具有统计学显著的距离衰减梯度（r = −0.60，p = 0.04）。就绝对值而言，无金属超过WHO\u002FFAO土壤限值。水文建模识别出从采矿坑到下游农田和水体的直接径流路径。Igbojaiye的ASM引发了一系列叠加退化、土壤毒性、微气候扰动和水文污染物扩散的级联效应，共同导致",null,"Sustainable Development","2026-09-14T00:00:00Z","论文",10,false,82,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,23,19,14,8,1,"首次将SDGSAT-1遥感与土壤、水文模型整合量化尼日利亚小规模采矿对农地的复合退化，方法可复用于数据稀缺地区农业环境治理，对农业遥感与耕地保护主题有聚合价值。",[25],{"name":10,"url":6},[27,28,29,30,31],"数字乡村","可持续发展","耕地保护","遥感监测","农业环境",0,"10.1002\u002Fsd.71693",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":9,"card":55,"direction":59,"ingested_from":61},"W7213179964",[37,40,42,45,47,49,52],{"name":38,"orcid":39},"Sehinde Akinbiola","https:\u002F\u002Forcid.org\u002F0000-0001-9602-2420",{"name":41,"orcid":9},"Julia Blumensaat",{"name":43,"orcid":44},"Ayobami Salami","https:\u002F\u002Forcid.org\u002F0000-0002-7567-9762",{"name":46,"orcid":9},"Jürgen Runge",{"name":48,"orcid":9},"Tella Iyiola",{"name":50,"orcid":51},"Olamide Omolafe Ogunremi","https:\u002F\u002Forcid.org\u002F0000-0002-6776-4983",{"name":53,"orcid":54},"Ayomide Emmanuel Olubaju","https:\u002F\u002Forcid.org\u002F0000-0003-2118-6759",{"tldr":56,"method":57,"finding":58,"direction":59,"opportunity":60},"用SDGSAT-1等多源遥感与实地采样量化尼日利亚手工采矿对土地与农田的环境退化。","SDGSAT-1与Landsat 9影像、8种植被水体土壤指数、土壤重金属AAS","矿区植被严重退化、地表温度升高、铅污染极重，并存在向农田与水体扩散的水文通道。","农业遥感与作物表型","可将SDGSAT-1 10米影像与土壤、水文模型耦合，构建矿区农田退化与重金属风险的早期预警框架。","openalex","2026-09-15T23:30:20.829150Z"]