Autors: Evstatiev, B., Valova, I., Kaneva, T., Valov, N., Sevov, A., Stanchev, G., Komitov, G., Zhelyazkova, T., Gerdzhikova, M., Todorova, M., Grozeva, N., Saliev, D. N., Damyanov, I. S.
Title: Identification of Pasture Degradation Using Remote Sensing Data and Machine Learning: A Case Study of Obichnik
Keywords: unmanned aerial vehicle, visual spectrum images, pasture, degradation, random trees, support vector machine, machine learning

References

    Issue

    APPLIED SCIENCES-BASEL, vol. 14, 2024, , https://doi.org/10.3390/app14177599

    Цитирания (Citation/s):
    1. Xing, LW, Jin, DY, Shen, C, Zhu, MS, Wu, JZ, Integrated Remote Sensing Evaluation of Grassland Degradation Using Multi-Criteria GDCI in Ili Prefecture, Xinjiang, China, LAND, vol 14, 2025, eissn: 2073-445X, art_no: ARTN 1592, doi: 10.3390/land14081592 - 2025 - в издания, индексирани в Scopus и/или Web of Science
    2. Li J., Liang W., Xu M., Tian H., Gao X., Yang Y., Hu R., Zhang Y., Cao C., Threshold Extraction and Early Warning of Key Ecological Factors for Grassland Degradation Risk, 2025, Remote Sensing, issue 17, vol. 17, DOI 10.3390/rs17173098, eissn 20724292 - 2025 - в издания, индексирани в Scopus и/или Web of Science

    Вид: статия в списание, публикация в реферирано издание, индексирана в Scopus и Web of Science