{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T18:50:13Z","timestamp":1760986213644,"version":"build-2065373602"},"reference-count":79,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T00:00:00Z","timestamp":1688688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Institute for Humanity and Nature","award":["RIHN 14200102"],"award-info":[{"award-number":["RIHN 14200102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Mining-induced or enhanced geo-hazards (MGHs) pose significant risks in rural mountainous regions with underground mining operations by harming groundwater layers, water circulation systems, and mountain stability. MGHs occurring in naturally contaminated environments can severely amplify socio-environmental risks. A high correlation was found among undermining development, precipitation, and hazards; however, details of MGHs have yet to be adequately characterized. This study investigated multiple mining-induced\/enhanced geo-hazards in a naturally contaminated mountain region in Bone Bolango Regency, Gorontalo Province, Indonesia, in 2020, where a rapidly developing coexisting mining sector was present. We utilized PlanetScope\u2019s CubeSat constellations and Sentinel-1 dataset to assess the volume, distribution, pace, and pattern of MGHs. The findings reveal that severe landslides and floods accelerated the mobilization of potentially toxic elements (PTEs) via the river water system, thus considerably exacerbating socio-environmental risks. These results indicate potential dangers of enhanced PTE contamination for marine ecosystems and humans at a regional level. The study design and data used facilitated a comprehensive assessment of the MGHs and associated risks, providing important information for decision-makers and stakeholders. However, limitations in the methodology should be considered when interpreting the findings. The societal benefits of this study include informing policies and practices that aim to mitigate the negative impacts of mining activities on the environment and society at the local and regional levels.<\/jats:p>","DOI":"10.3390\/rs15133436","type":"journal-article","created":{"date-parts":[[2023,7,7]],"date-time":"2023-07-07T02:28:46Z","timestamp":1688696926000},"page":"3436","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Monitoring Mining-Induced Geo-Hazards in a Contaminated Mountainous Region of Indonesia Using Satellite Imagery"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7137-7815","authenticated-orcid":false,"given":"Satomi","family":"Kimijima","sequence":"first","affiliation":[{"name":"Research Institute for Humanity and Nature, Kyoto 603-8047, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0625-762X","authenticated-orcid":false,"given":"Masahiko","family":"Nagai","sequence":"additional","affiliation":[{"name":"Graduate School of Science and Technology for Innovation, Yamaguchi University, Ube 755-8611, Japan"},{"name":"Center for Research and Application of Satellite Remote Sensing, Yamaguchi University, Ube 755-8611, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,7]]},"reference":[{"key":"ref_1","unstructured":"U.S. Geological Survey (2023, June 01). Landslide Types and Processes, Available online: https:\/\/pubs.usgs.gov\/fs\/2004\/3072\/fs-2004-3072.html."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s10064-014-0608-6","article-title":"Mining-induced geo-hazards with environmental protection measures in Yunnan, China: An overview","volume":"74","author":"Yang","year":"2015","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Kimijima, S., and Nagai, M. (2023). High Spatiotemporal Flood Monitoring Associated with Rapid Lake Shrinkage Using Planet Smallsat and Sentinel-1 Data. Remote Sens., 15.","DOI":"10.3390\/rs15041099"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1038\/s43017-022-00373-x","article-title":"Landslide detection, monitoring and prediction with remote-sensing techniques","volume":"4","author":"Casagli","year":"2023","journal-title":"Nat. Rev. Earth Environ."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Jiao, R., Wang, S., Yang, H., Guo, X., Han, J., Pei, X., and Yan, C. (2022). Comprehensive Remote Sensing Technology for Monitoring Landslide Hazards and Disaster Chain in the Xishan Mining Area of Beijing. Remote Sens., 14.","DOI":"10.3390\/rs14194695"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1093\/ijlct\/ctz003","article-title":"Geological disaster prevention and control and resource protection in mineral resource exploitation region","volume":"14","author":"Shao","year":"2019","journal-title":"Int. J. Low-Carbon Technol."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Lakshmi, V. (2016). Remote Sensing of Hydrological Extremes, Springer Remote Sensing\/Photogrammetry.","DOI":"10.1007\/978-3-319-43744-6"},{"key":"ref_8","unstructured":"The UN Office for Disaster Risk Reduction (2020). Human Cost of Disasters: An Overview of the Last 20 Years (2000\u20132019), The UN Office for Disaster Risk Reduction."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0048-9697(03)00446-7","article-title":"Natural and technologic hazardous material releases during and after natural disasters: A review","volume":"322","author":"Young","year":"2004","journal-title":"Sci. Total. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Nagai, M., and Sakakibara, M. (2023). Distribution of Enhanced Potentially Toxic Element Contaminations Due to Natural and Coexisting Gold Mining Activities Using Planet Smallsat Constellations. Remote Sens., 15.","DOI":"10.3390\/rs15030861"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1130\/G33979.1","article-title":"Controls on valley width in mountainous landscapes: The role of landsliding and implications for salmonid habitat","volume":"41","author":"May","year":"2013","journal-title":"Geology"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111983","DOI":"10.1016\/j.rse.2020.111983","article-title":"InSAR-based detection method for mapping and monitoring slow-moving landslides in remote regions with steep and mountainous terrain: An application to Nepal","volume":"249","author":"Bekaert","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"60","DOI":"10.3389\/frwa.2021.656417","article-title":"Flooding Hazard and Vulnerability. An Interdisciplinary Experimental Approach for the Study of the 2016 West Virginia Floods","volume":"3","author":"Caretta","year":"2021","journal-title":"Front. Water"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.apgeog.2012.11.008","article-title":"Characterizing streamflow response of a mountaintop-mined watershed to changing land use","volume":"39","author":"Maxwell","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_15","unstructured":"Inside Climate News (2023, June 01). Appalachia\u2019s Strip-Mined Mountains Face a Growing Climate Risk: Flooding. Available online: https:\/\/insideclimatenews.org\/news\/21112019\/appalachia-mountains-flood-risk-climate-change-coal-mining-west-virginia-extreme-rainfall-runoff-analysis\/."},{"key":"ref_16","unstructured":"Deutsche Welle (2019). Deforestation Causing Flash Floods in Papua, Deutsche Welle."},{"key":"ref_17","unstructured":"World Gold Council (2023, June 01). Gold Prices. Available online: https:\/\/www.gold.org\/goldhub."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gafur, N.A., Sakakibara, M., Komatsu, S., Sano, S., and Sera, K. (2022). Environmental Survey of the Distribution and Metal Contents of Pteris vittata in Arsenic\u2013Lead\u2013Mercury-Contaminated Gold Mining Areas along the Bone River in Gorontalo Province, Indonesia. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19010530"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Sakakibara, M., Nagai, M., and Gafur, N.A. (2021). Time-Series Assessment of Camp-Type Artisanal and Small-Scale Gold Mining Sectors with Large Influxes of Miners Using LANDSAT Imagery. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18189441"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Sakakibara, M., and Nagai, M. (2021). Detection of Artisanal and Small-Scale Gold Mining Activities and Their Transformation Using Earth Observation, Nighttime Light, and Precipitation Data. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph182010954"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"566","DOI":"10.3390\/mining2030030","article-title":"Monitoring Coexisting Rapid Small-Scale and Large-Scale Gold Mining Developments Using Planet Smallsats Constellations","volume":"2","author":"Kimijima","year":"2022","journal-title":"Mining"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gafur, N.A., Sakakibara, M., Sano, S., and Sera, K. (2018). A case study of heavy metal pollution in water of Bone river by ASGM activities in Eastern part of Gorontalo, Indonesia. Water, 10.","DOI":"10.3390\/w10111507"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Sakakibara, M., Pateda, S.M., and Sera, K. (2022). Contamination Level in Geo-Accumulation Index of River Sediments at Artisanal and Small-Scale Gold Mining Area in Gorontalo Province, Indonesia. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19106094"},{"key":"ref_24","unstructured":"World Health Organization (2023, June 01). Guidelines for Drinking-Water Quality. Available online: https:\/\/apps.who.int\/iris\/bitstream\/handle\/10665\/352532\/9789240045064-eng.pdf?sequence=1&isAllowed=y#page=29."},{"key":"ref_25","unstructured":"U.S. Environmental Protection Agency (1993). Clean Water Act: Section 503."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1016\/j.proche.2015.03.058","article-title":"Heavy Metals in Water of Stream Near an Amalgamation Tailing Ponds in Talawaan\u2014Tatelu Gold Mining, North Sulawesi, Indonesia","volume":"14","author":"Palapa","year":"2015","journal-title":"Procedia Chem."},{"key":"ref_27","unstructured":"Persaud, D., Jaagumagi, R., and Hayton, A. (1993). Guidelines for the Protection and Management of Aquatic Sediment Quality in Ontario, Ministry of Environment and Energy."},{"key":"ref_28","unstructured":"U.S. Environmental Protection Agency (1997). The Incidence and Severity of Sediment Contamination in Surface Waters of the United States, Volume 1\u2014National Sediment Quality Survey."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1007\/s002440010075","article-title":"Development and Evaluation of Consensus-Based Sediment Quality Guidelines for Freshwater Ecosystems","volume":"39","author":"MacDonald","year":"2000","journal-title":"Arch. Environ. Contam. Toxicol."},{"key":"ref_30","unstructured":"Ontario Ministry of Environment Conservation and Parks (2020). Rules for Soil Management and Excess Soil Quality Standards, Ontario Ministry of Environment Conservation and Parks."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Sakakibara, M., and Nagai, M. (2022). Characterizing Time-Series Roving Artisanal and Small-Scale Gold Mining Activities in Indonesia Using Sentinel-1 Data. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19106266"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Sakakibara, M., and Nagai, M. (2022). Investigation of Long-Term Roving Artisanal and Small-Scale Gold Mining Activities Using Time-Series Sentinel-1 and Global Surface Water Datasets. Int. J. Environ. Res. Public Health, 19.","DOI":"10.3390\/ijerph19095530"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1080\/17538947.2011.629009","article-title":"Application of remote sensing for investigating mining geological hazards","volume":"6","author":"Wang","year":"2013","journal-title":"Int. J. Digit. Earth"},{"key":"ref_34","first-page":"102447","article-title":"Long-term Landsat monitoring of mining subsidence based on spatiotemporal variations in soil moisture: A case study of Shanxi Province, China","volume":"102","author":"Yi","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_35","unstructured":"Satellite Imaging Corporation (2023, June 01). Satellite Sensors. Available online: https:\/\/www.satimagingcorp.com\/satellite-sensors\/."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4136837","DOI":"10.1155\/2020\/4136837","article-title":"Inversion and Analysis of Mining Subsidence by Integrating DInSAR, Offset Tracking, and PIM Technology","volume":"2020","author":"Xu","year":"2020","journal-title":"J. Sens."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Ma, C., Cheng, X., Yang, Y., Zhang, X., Guo, Z., and Zou, Y. (2016). Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset\u2014Case Study of Working Faces 22201-1\/2 in Bu\u2019ertai Mine, Shendong Coalfield, China. Remote Sens., 8.","DOI":"10.3390\/rs8110951"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1476","DOI":"10.3390\/rs6021476","article-title":"Evaluation of InSAR and TomoSAR for Monitoring Deformations Caused by Mining in a Mountainous Area with High Resolution Satellite-Based SAR","volume":"6","author":"Liu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_39","unstructured":"Remote Sensing Technology Center of Japan (2023, June 01). Satellite Information Database. Available online: https:\/\/www.restec.or.jp\/en\/index.html."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Sousa, J.J., Liu, G., Fan, J., Perski, Z., Steger, S., Bai, S., Wei, L., Salvi, S., Wang, Q., and Tu, J. (2021). Geohazards Monitoring and Assessment Using Multi-Source Earth Observation Techniques. Remote Sens., 13.","DOI":"10.3390\/rs13214269"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ma, D., and Zhao, S. (2022). Quantitative Analysis of Land Subsidence and Its Effect on Vegetation in Xishan Coalfield of Shanxi Province. ISPRS Int. J. Geo-Inf., 11.","DOI":"10.3390\/ijgi11030154"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Psomiadis, E., Diakakis, M., and Soulis, K.X. (2020). Combining SAR and Optical Earth Observation with Hydraulic Simulation for Flood Mapping and Impact Assessment. Remote Sens., 12.","DOI":"10.3390\/rs12233980"},{"key":"ref_43","first-page":"103010","article-title":"Automatic monitoring of surface water dynamics using Sentinel-1 and Sentinel-2 data with Google Earth Engine","volume":"113","author":"Chen","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kimijima, S., Nagai, M., Sakakibara, M., and Jahja, M. (2022). Investigation of Cultural\u2013Environmental Relationships for an Alternative Environmental Management Approach Using Planet Smallsat Constellations and Questionnaire Datasets. Remote Sens., 14.","DOI":"10.3390\/rs14174249"},{"key":"ref_45","unstructured":"The National Aeronautics and Space Administration (2022). What Is Synthetic Aperture Radar?, The National Aeronautics and Space Administration."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3372","DOI":"10.3390\/rs70303372","article-title":"Examining the Capability of Supervised Machine Learning Classifiers in Extracting Flooded Areas from Landsat TM Imagery: A Case Study from a Mediterranean Flood","volume":"7","author":"Ireland","year":"2015","journal-title":"Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"035002","DOI":"10.1088\/1748-9326\/9\/3\/035002","article-title":"Flood extent mapping for Namibia using change detection and thresholding with SAR","volume":"9","author":"Long","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Lei, T., Wang, J., Li, X., Wang, W., Shao, C., and Liu, B. (2022). Flood Disaster Monitoring and Emergency Assessment Based on Multi-Source Remote Sensing Observations. Water, 14.","DOI":"10.3390\/w14142207"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Ahamed, A., Bolten, J., Doyle, C., and Fayne, J. (2017). Near Real-Time Flood Monitoring and Impact Assessment Systems, Springer International Publishing.","DOI":"10.1007\/978-3-319-43744-6_6"},{"key":"ref_50","unstructured":"Planet Labs (2023, June 01). PlanetScope. Available online: https:\/\/developers.planet.com\/docs\/data\/planetscope\/#:~:text=lastupdated%3AJune01%2C2022,200millionkm2%2Fday."},{"key":"ref_51","unstructured":"Japan International Cooperation Agency (2002). Summary: The Study on Flood Control and Water Management in Limboto-Bolango-Bone Basin, Japan International Cooperation Agency."},{"key":"ref_52","unstructured":"ASEAN Disaster Information Network (2023, June 01). SEARCH. Available online: https:\/\/adinet.ahacentre.org\/."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"9598","DOI":"10.3390\/su12229598","article-title":"Mechanism of the rapid shrinkage of limboto lake in Gorontalo, Indonesia","volume":"12","author":"Kimijima","year":"2020","journal-title":"Sustainability"},{"key":"ref_54","unstructured":"(2023, June 01). ASEAN Disaster Information Network. Indonesia, Flooding and Landslide in Bone Bolango Regency, Gorontalo Province. Available online: https:\/\/adinet.ahacentre.org\/report\/indonesia-flooding-and-landslide-in-bone-bolango-regency-gorontalo-province-20200804."},{"key":"ref_55","unstructured":"(2023, June 01). ZONAUTARA.com. Floods and Landslides Ravaged Bone Bolango Regency. Available online: https:\/\/zonautara.com\/2020\/09\/10\/banjir-dan-tanah-longsor-porak-porandakan-kabupaten-bone-bolango\/."},{"key":"ref_56","unstructured":"Research Institute for Humanity and Nature (2023, June 01). Let\u2019s Explore RIHN: Gorontalo, Indonesia. Available online: https:\/\/www.chikyu.ac.jp\/minna\/nozoite\/2020\/bouken_no6.html."},{"key":"ref_57","unstructured":"Planet Labs (2023, June 01). Planet Explore. Available online: https:\/\/www.planet.com\/expl."},{"key":"ref_58","unstructured":"Planet Labs (2023, June 01). Daily Earth Data to See Change and Make Better Decisions. Available online: https:\/\/www.planet.com\/."},{"key":"ref_59","unstructured":"European Space Agency (2023, June 01). Worldwide Land Cover Mapping. Available online: https:\/\/esa-worldcover.org\/en."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"124377","DOI":"10.1016\/j.jhydrol.2019.124377","article-title":"Towards high resolution flood monitoring: An integrated methodology using passive microwave brightness temperatures and Sentinel synthetic aperture radar imagery","volume":"582","author":"Zeng","year":"2020","journal-title":"J. Hydrol."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/0031-3203(94)E0043-K","article-title":"Image thresholding by minimizing the measures of fuzziness","volume":"28","author":"Huang","year":"1995","journal-title":"Pattern Recognit."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1111\/j.1749-6632.1965.tb11715.x","article-title":"The Analysis of Cell Images","volume":"128","author":"Prewitt","year":"2006","journal-title":"Ann. New York Acad. Sci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1145\/321119.321123","article-title":"Operations Useful for Similarity-Invariant Pattern Recognition","volume":"9","author":"Doyle","year":"1962","journal-title":"J. ACM"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1006\/cgip.1994.1037","article-title":"Utilization of Information Measure as a Means of Image Thresholding","volume":"56","author":"Shanbhag","year":"1994","journal-title":"CVGIP Graph. Model. Image Process."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1177\/25.7.70454","article-title":"Automatic measurement of sister chromatid exchange frequency","volume":"25","author":"Zack","year":"1977","journal-title":"J. Histochem. Cytochem."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/83.366472","article-title":"A new criterion for automatic multilevel thresholding","volume":"4","author":"Yen","year":"1995","journal-title":"IEEE Trans. Image Process."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1109\/TSMC.1978.4310039","article-title":"Picture Thresholding Using an Iterative Selection Method","volume":"8","author":"Ridler","year":"1978","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/0031-3203(93)90115-D","article-title":"Minimum cross entropy thresholding","volume":"26","author":"Li","year":"1993","journal-title":"Pattern Recognit."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"771","DOI":"10.1016\/S0167-8655(98)00057-9","article-title":"An iterative algorithm for minimum cross entropy thresholding","volume":"19","author":"Li","year":"1998","journal-title":"Pattern Recognit. Lett."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1117\/1.1631315","article-title":"Survey over image thresholding techniques and quantitative performance evaluation","volume":"13","author":"Sankur","year":"2004","journal-title":"J. Electron. Imaging"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","article-title":"A new method for gray-level picture thresholding using the entropy of the histogram","volume":"29","author":"Kapur","year":"1985","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1006\/cgip.1993.1040","article-title":"An Analysis of Histogram-Based Thresholding Algorithms","volume":"55","author":"Glasbey","year":"1993","journal-title":"Graph. Model. Image Process."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/0031-3203(86)90030-0","article-title":"Minimum error thresholding","volume":"19","author":"Kittler","year":"1986","journal-title":"Pattern Recognit."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/0734-189X(85)90133-1","article-title":"Moment-preserving thresolding: A new approach","volume":"29","author":"Tsai","year":"1985","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_76","unstructured":"KONTAN (2022, July 07). Gorontalo Minerals Immediately Implements Gold Mine Development. Available online: https:\/\/industri.kontan.co.id\/news\/gorontalo-minerals-segera-melaksanakan-pengembangan-tambang-emas."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/j.scienta.2017.12.039","article-title":"Heavy metals and metalloids: Sources, risks and strategies to reduce their accumulation in horticultural crops","volume":"234","author":"Edelstein","year":"2018","journal-title":"Sci. Hortic."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"111197","DOI":"10.1016\/j.molliq.2019.111197","article-title":"A review on heavy metal pollution, toxicity and remedial measures: Current trends and future perspectives","volume":"290","author":"Vardhan","year":"2019","journal-title":"J. Mol. Liq."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1016\/j.chemosphere.2005.04.001","article-title":"Distribution and partition of heavy metals in surface and sub-surface sediments of Naples city port","volume":"61","author":"Adamo","year":"2005","journal-title":"Chemosphere"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/13\/3436\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:07:45Z","timestamp":1760126865000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/13\/3436"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,7]]},"references-count":79,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["rs15133436"],"URL":"https:\/\/doi.org\/10.3390\/rs15133436","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,7,7]]}}}