Estimating the Crop Acreage of Menthol Mint Crop from Remote Sensing Satellite Imagery Using ANN

被引:2
作者
Babu, Jampani Satish [1 ]
Ch, Smitha Chowdary [1 ]
Bhattacharyya, Debnath [1 ]
Byun, Yungcheol [2 ]
机构
[1] Koneru Lakshmaiah Educ Fdn, Dept Comp Sci & Engn, Vaddeswaram, Guntur 522302, India
[2] Jeju Natl Univ, Dept Comp Engn, 102 Jejudaehak Ro, Jeju Si 690756, Jeju Do, South Korea
来源
AGRONOMY-BASEL | 2023年 / 13卷 / 04期
关键词
precision data; smart agriculture; rainfall; crop acreage estimation; remote sensing; TIBETAN PLATEAU;
D O I
10.3390/agronomy13040951
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Acreage estimates are crucial for forecasting menthol mint acreage, as crop output figures fluctuate from year to year in response to fluctuations in the market price of menthol mint oil. Thus, there are yearly fluctuations in the maximum price that farmers can obtain. Since low production arises from low rates, and high production results from high prices, these acreage estimate studies may be useful in lowering uncertainty regarding menthol mints' output. The widespread adoption of remote sensing technologies for assessing crop acreage at both the national and international levels can be attributed to their low cost, ease of use, and flexibility. The extent of an area planted with menthol mint in the Vishakhapatnam district of Andhra Pradesh, India, was estimated using Sentinel-2A satellite data for that year. After conducting a comprehensive ground survey, the area of the menthol mint crop was estimated using an adaptive maximum chance-type set of rules for taluk-level statistics. According to the research, the Bheemunipatnam taluk in the Vishakhapatnam district was the most productive in growing menthol mint. Using customer and manufacturer accuracies of 89.13% and 87.23%, along with the average accuracy (90.67%) and kappa rate (0.9), the total acreage of menthol mint crop in the study region was estimated to be around 58,000,284.70 ha (0.844). A further aim in this study was to estimate the acreage planted with early and late menthol mint. Around 26,123.50 ha and 29,911.40 ha were found to be home to early menthol mint and late menthol mint, respectively. This method shows promise for early- and late-stage crop acreage assessment of menthol mint using a localised degree of precision.
引用
收藏
页数:18
相关论文
共 50 条
  • [21] Effect of measure units on estimating crop LEAF chlorophyll content with remote sensing
    Wang, Chao
    Bian, Changlin
    Xing, Hongyan
    Zhang, Xuehong
    Shen, Yi
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (23): : 8627 - 8631
  • [22] Estimation of emissions from crop residue burning using remote sensing data
    Bahsi, Kubra
    Salli, Betul
    Kilic, Dogushan
    Sertel, Elif
    INTERNATIONAL JOURNAL OF GLOBAL WARMING, 2019, 19 (1-2) : 94 - 105
  • [23] A Review of Crop Water Stress Assessment Using Remote Sensing
    Ahmad, Uzair
    Alvino, Arturo
    Marino, Stefano
    REMOTE SENSING, 2021, 13 (20)
  • [24] Integrated provincial crop monitoring system using remote sensing
    Meng J.
    Wu B.
    Li Q.
    Niu L.
    Zhang F.
    Du X.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2011, 27 (06): : 169 - 175
  • [25] Estimation of Hail Damage Using Crop Models and Remote Sensing
    Gobbo, Stefano
    Ghiraldini, Alessandro
    Dramis, Andrea
    Dal Ferro, Nicola
    Morari, Francesco
    REMOTE SENSING, 2021, 13 (14)
  • [26] Automated building extraction using satellite remote sensing imagery
    Hu, Qintao
    Zhen, Liangli
    Mao, Yao
    Zhou, Xi
    Zhou, Guozhong
    AUTOMATION IN CONSTRUCTION, 2021, 123
  • [27] Estimating soil available water capacity within a Mediterranean vineyard watershed using satellite imagery and crop model inversion
    Alkassem, Mohamed
    Buis, Samuel
    Coulouma, Guillaume
    Jacob, Frederic
    Lagacherie, Philippe
    Prevot, Laurent
    GEODERMA, 2022, 425
  • [28] Estimating and mapping the dynamics of soil salinity under different crop types using Sentinel-2 satellite imagery
    Cui, Xin
    Han, Wenting
    Zhang, Huihui
    Dong, Yuxin
    Ma, Weitong
    Zhai, Xuedong
    Zhang, Liyuan
    Li, Guang
    GEODERMA, 2023, 440
  • [29] Comparison of remote sensing-based energy balance methods for estimating crop evapotranspiration
    Gonzalez-Dugo, M. P.
    Neale, C. M. U.
    Mateos, L.
    Kustas, W. P.
    Li, F.
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY VIII, 2006, 6359
  • [30] Remote Sensing Assisted Multi-Level Crop Acreage Estimation -an Application of Small Area Estimation in Heilongjiang Province
    Zhou, Wei
    Zhang, Jinshui
    Pan, Yaozhong
    Zhu, Rong
    THIRD INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS 2014), 2014, : 178 - 183