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Crop mapping without labels: Investigating temporal and spatial transferability of crop classification models using a 5-year sentinel-2 series and machine learning
Title Crop mapping without labels: Investigating temporal and spatial transferability of crop classification models using a 5-year sentinel-2 series and machine learning Title translation Mapovanie plodín bez označení: Skúmanie časovej a priestorovej prenositeľnosti klasifikačných modelov plodín pomocou 5-ročnej série Sentinel-2 a metód strojového učenia Author Rusňák Tomáš 1990 SAVKREKO - Ústav krajinnej ekológie SAV Co-authors Kasanický Tomáš 1978- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Malík Peter SAVINFO - Ústav informatiky SAV Mojžiš Ján 1985- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Zelenka Ján 1983 SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Sviček Michal Abrahám Dominik Halabuk Andrej 1976 - SAVKREKO - Ústav krajinnej ekológie SAV Source document Remote Sensing : Open Access Journal. Vol. 15 (2023), article no. 3 414 Language eng - English Country CH - Switzerland URL URL link Document kind rozpis článkov z periodík (rbx) Keywords multitemporal classification * Google Earth Engine * within-season crop mapping * domain adaptation * agricultural monitoring * crop monitoring Citations PANDZIC, Milos - PAVLOVIC, Dejan - MATAVULJ, Predrag - BRDAR, Sanja - MARKO, Oskar - CRNOJEVIC, Vladimir - KILIBARDA, Milan. Interseasonal transfer learning for crop mapping using Sentinel-1 data. In INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, vol. 128, no., pp. ISSN 1569-8432. Dostupné na: https://doi.org/10.1016/j.jag.2024.103718. ARRIETA-PRIETO, Mario - SCHELL, Kristen R. Spatially transferable machine learning wind power prediction models: v-logit random forests. In RENEWABLE ENERGY, 2024, vol. 223, no., pp. ISSN 0960-1481. Dostupné na: https://doi.org/10.1016/j.renene.2024.120066. HOPPE, Hauke - DIETRICH, Peter - MARZAHN, Philip - WEISS, Thomas - NITZSCHE, Christian - VON LUKAS, Uwe Freiherr - WENGEREK, Thomas - BORG, Erik. Transferability of Machine Learning Models for Crop Classification in Remote Sensing Imagery Using a New Test Methodology: A Study on Phenological, Temporal, and Spatial Influences. In REMOTE SENSING, 2024, vol. 16, no. 9, pp. Dostupné na: https://doi.org/10.3390/rs16091493. ZHANG, Hongchi - LOU, Zihang - PENG, Dailiang - ZHANG, Bing - LUO, Wang - HUANG, Jianxi - ZHANG, Xiaoyang - YU, Le - WANG, Fumin - HUANG, Linsheng - LIU, Guohua - GAO, Shuang - HU, Jinkang - YANG, Songlin - CHENG, Enhui. Mapping annual 10-m soybean cropland with spatiotemporal sample migration. In SCIENTIFIC DATA, 2024, vol. 11, no. 1, pp. Dostupné na: https://doi.org/10.1038/s41597-024-03273-5. WIJESINGHA, Jayan - DZENE, Ilze - WACHENDORF, Michael. Evaluating the spatial-temporal transferability of models for agricultural land cover mapping using Landsat archive. In ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2024, vol. 213, no., pp. 72-86. ISSN 0924-2716. Dostupné na: https://doi.org/10.1016/j.isprsjprs.2024.05.020. LI, Mengmeng - FENG, Xiaomin - BELGIU, Mariana. Mapping tobacco planting areas in smallholder farmlands using Phenological-Spatial-Temporal LSTM from time-series Sentinel-1 SAR images. In INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, vol. 129, no., pp. ISSN 1569-8432. Dostupné na: https://doi.org/10.1016/j.jag.2024.103826. SOURAV - KAUR, Navneet - KAUR, Bobbinpreet. Crop Classification using Sentinel-1 and Sentinel-2: A Machine Learning Method. In 2nd IEEE International Conference on Data Science and Information System, ICDSIS 2024, 2024-01-01, pp. Dostupné na: https://doi.org/10.1109/ICDSIS61070.2024.10594331. Category ADCA - Scientific papers in foreign journals registered in Current Contents Connect with IF (impacted) Category of document (from 2022) V3 - Vedecký výstup publikačnej činnosti z časopisu Type of document článok Year 2023 Registered in WOS Registered in SCOPUS Registered in CCC DOI 10.3390/rs15133414 
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rok CC IF IF Q (best) JCR Av Jour IF Perc SJR SJR Q (best) CiteScore A rok vydania rok metriky IF IF Q (best) SJR SJR Q (best) 2023 2022 5 Q1 1.136 Q1
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