{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T22:42:12Z","timestamp":1763764932153,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,24]],"date-time":"2022-03-24T00:00:00Z","timestamp":1648080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003524","name":"Ministry of Business, Innovation and Employment","doi-asserted-by":"publisher","award":["C09X1709"],"award-info":[{"award-number":["C09X1709"]}],"id":[{"id":"10.13039\/501100003524","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The southern beech (genus Fuscospora and Lophozonia) forest in New Zealand periodically has \u201cmast\u201d years, during which very large volumes of seeds are produced. This excessive seed production results in a population explosion of rodents and mustelids, which then puts pressure on native birds. To protect the birds, extra pest controls, costing in the order of NZD 20 million, are required in masting areas. To plan pest control and keep it cost-effective, it would be helpful to have a map of the masting areas. In this study, we developed a remote sensing method for the creation of a national beech flowering map. It used a temporal sequence of Sentinel-2 satellite imagery to determine areas in which a yellow index, which was based on red and green reflectance (red-green)\/(red + green), was higher than normal in spring. The method was used to produce national maps of heavy beech flowering for the years 2017 to 2021. In 2018, which was a major beech masting year, of the 4.1 million ha of beech forest in New Zealand, 27.6% was observed to flower heavily. The overall classification accuracy of the map was 90.8%. The method is fully automated and could be used to help to identify areas of potentially excessive seed fall across the whole of New Zealand, several months in advance of when pest control would be required.<\/jats:p>","DOI":"10.3390\/rs14071573","type":"journal-article","created":{"date-parts":[[2022,3,24]],"date-time":"2022-03-24T23:31:43Z","timestamp":1648164703000},"page":"1573","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Detection of Southern Beech Heavy Flowering Using Sentinel-2 Imagery"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8984-3201","authenticated-orcid":false,"given":"Ben","family":"Jolly","sequence":"first","affiliation":[{"name":"Manaaki Whenua\u2014Landcare Research, Palmerston North 4472, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6462-6203","authenticated-orcid":false,"given":"John R.","family":"Dymond","sequence":"additional","affiliation":[{"name":"Manaaki Whenua\u2014Landcare Research, Palmerston North 4472, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4809-0055","authenticated-orcid":false,"given":"James D.","family":"Shepherd","sequence":"additional","affiliation":[{"name":"Manaaki Whenua\u2014Landcare Research, Palmerston North 4472, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4183-0719","authenticated-orcid":false,"given":"Terry","family":"Greene","sequence":"additional","affiliation":[{"name":"Department of Conservation, Christchurch 8140, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0457-4357","authenticated-orcid":false,"given":"Jan","family":"Schindler","sequence":"additional","affiliation":[{"name":"Manaaki Whenua\u2014Landcare Research, Palmerston North 4472, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.11646\/phytotaxa.146.1.1","article-title":"Revised circumscription of Nothofagus and recognition of the segregate genera Fuscospora, Lophozonia, and Trisyngyne (Nothofagaceae)","volume":"146","author":"Heenan","year":"2013","journal-title":"Phytotaxa"},{"key":"ref_2","unstructured":"Shepherd, J.R.D., Ausseil, A.G., and Dymond, J.R. (2005). EcoSat Forests: A 1: 750,000 Scale Map of Indigenous Forest Classes in New Zealand, Manaaki Whenua Press."},{"key":"ref_3","unstructured":"Wardle, J.A. (1984). The New Zealand Beeches. Ecology, Utilisation and Management."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1111\/emr.12227","article-title":"Large-scale pest control in New Zealand beech forests","volume":"17","author":"Elliott","year":"2016","journal-title":"Ecol. Manag. Restor."},{"key":"ref_5","unstructured":"Singleton, G., Belmain, S., Brown, P., and Hardy, B. (2010). Rodent Outbreaks: Ecology and Impacts. Rodent Outbreaks: Ecology and Impacts, Internationl Rice Research Institute."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3039","DOI":"10.1007\/s10530-011-9993-y","article-title":"Managing an invasive predator pre-adapted to a pulsed resource: A model of stoat (Mustela erminea) irruptions in New Zealand beech forests","volume":"13","author":"King","year":"2011","journal-title":"Biol. Invasions"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1111\/ele.12020","article-title":"Of mast and mean: Differential-temperature cue makes mast seeding insensitive to climate change","volume":"16","author":"Kelly","year":"2013","journal-title":"Ecol. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3525","DOI":"10.1002\/ece3.1210","article-title":"Elevation-dependent responses of tree mast seeding to climate change over 45 years","volume":"4","author":"Allen","year":"2014","journal-title":"Ecol. Evol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1038\/s41477-020-0592-8","article-title":"Climate warming disrupts mast seeding and its fitness benefits in European beech","volume":"6","author":"Bogdziewicz","year":"2020","journal-title":"Nat. Plants"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1111\/gcb.15560","article-title":"Climate warming causes mast seeding to break down by reducing sensitivity to weather cues","volume":"27","author":"Bogdziewicz","year":"2021","journal-title":"Glob. Chang. Biol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"111685","DOI":"10.1016\/j.rse.2020.111685","article-title":"Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery","volume":"240","author":"Bolton","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Misra, G., Cawkwell, F., and Wingler, A. (2020). Status of phenological research using sentinel-2 data: A review. Remote Sens., 12.","DOI":"10.3390\/rs12172760"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"111511","DOI":"10.1016\/j.rse.2019.111511","article-title":"Remote Sensing of Environment A review of vegetation phenological metrics extraction using time-series, multispectral satellite data","volume":"237","author":"Zeng","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"112197","DOI":"10.1016\/j.rse.2020.112197","article-title":"Satellite prediction of forest flowering phenology","volume":"255","author":"Dixon","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"112466","DOI":"10.1016\/j.rse.2021.112466","article-title":"Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests","volume":"260","author":"Moon","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"112716","DOI":"10.1016\/j.rse.2021.112716","article-title":"Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery","volume":"266","author":"Moon","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"108147","DOI":"10.1016\/j.ecolind.2021.108147","article-title":"Monitoring agroecosystem productivity and phenology at a national scale: A metric assessment framework","volume":"131","author":"Browning","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.rse.2012.04.001","article-title":"Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology","volume":"123","author":"Atkinson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1007\/s11258-015-0489-1","article-title":"Temporal trends in the enhanced vegetation index and spring weather predict seed production in Mediterranean oaks","volume":"216","author":"Garbulsky","year":"2015","journal-title":"Plant Ecol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"112004","DOI":"10.1016\/j.rse.2020.112004","article-title":"Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2","volume":"248","author":"Cheng","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"112278","DOI":"10.1016\/j.rse.2020.112278","article-title":"Landsat-based detection of mast events in white spruce (Picea glauca) forests","volume":"254","author":"Garcia","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Noumonvi, K.D., Obli\u0161ar, G., \u017dust, A., and Vilhar, U. (2021). Empirical approach for modelling tree phenology in mixed forests using remote sensing. Remote Sens., 13.","DOI":"10.3390\/rs13153015"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s12145-019-00380-5","article-title":"Change detection techniques for remote sensing applications: A survey","volume":"12","author":"Asokan","year":"2019","journal-title":"Earth Sci. Inform."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Panuju, D.R., Paull, D.J., and Griffin, A.L. (2020). Change detection techniques based on multispectral images for investigating land cover dynamics. Remote Sens., 12.","DOI":"10.3390\/rs12111781"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.isprsjprs.2019.08.006","article-title":"An enhanced bloom index for quantifying floral phenology using multi-scale remote sensing observations","volume":"156","author":"Chen","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.rse.2003.11.013","article-title":"The spatial distribution of indigenous forest and its composition in the Wellington region, New Zealand, from ETM+ satellite imagery","volume":"90","author":"Dymond","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_27","unstructured":"Landcare Research Ltd. (2014). EcoSat Forests (North Island), Landcare Research Ltd."},{"key":"ref_28","unstructured":"Landcare Research Ltd. (2014). EcoSat Forest (South Island), Landcare Research Ltd."},{"key":"ref_29","unstructured":"Department of Conservation (2019). Flowering and Fruit Production."},{"key":"ref_30","unstructured":"Department of Conservation (2019). Department of Conservation Te Papa Atawhai Annual Report 2019, Technical Report."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Shepherd, J.R.D., Schindler, J., and Dymond, J.R. (2020). Automated Mosaicking of Sentinel-2 Satellite Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12223680"},{"key":"ref_32","unstructured":"Rouse, W., Haas, H., and Deering, W. (1974). Monitoring vegetation systems in the Great Plains with ERTS, Goddard Space Flight Center 3d ERTS-1 Symposium."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and Photographic Infrared l, lnear Combinations for Monitoring Vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.3390\/rs2102369","article-title":"Applicability of Green-Red Vegetation Index for remote sensing of vegetation phenology","volume":"2","author":"Motohka","year":"2010","journal-title":"Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.rse.2014.06.012","article-title":"Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: An algorithm designed specifically for monitoring land cover change","volume":"152","author":"Zhu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_36","first-page":"137","article-title":"Monitoring scrub weed change in the Canterbury region using satellite imagery","volume":"60","author":"Shepherd","year":"2007","journal-title":"N. Z. Plant Prot."},{"key":"ref_37","first-page":"431","article-title":"Using Known Map Category Marginal Frequencies to Improve Estimates of Thematic Map Accuracy","volume":"48","author":"Card","year":"1982","journal-title":"Photgrammetric Eng. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Maxwell, A.E., Warner, T.A., and Guill\u00e9n, L.A. (2021). Accuracy assessment in convolutional neural network-based deep learning remote sensing studies\u2014Part 1: Literature review. Remote Sens., 13.","DOI":"10.3390\/rs13132450"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1890\/04-0863","article-title":"Climate and net carbon availability determine temporal patterns of seed production by Nothofagus","volume":"86","author":"Uscoe","year":"2005","journal-title":"Ecology"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Thapa, S., Millan, V.E.G., and Eklundh, L. (2021). Assessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, phenocam) and satellite (MODIS, sentinel-2) remote sensing. Remote Sens., 13.","DOI":"10.3390\/rs13081597"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"112133","DOI":"10.1016\/j.rse.2020.112133","article-title":"Investigation of land surface phenology detections in shrublands using multiple scale satellite data","volume":"252","author":"Peng","year":"2021","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1573\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:42:38Z","timestamp":1760136158000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1573"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,24]]},"references-count":41,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071573"],"URL":"https:\/\/doi.org\/10.3390\/rs14071573","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,3,24]]}}}