Subjects: Geosciences >> Geography submitted time 2023-12-16 Cooperative journals: 《干旱区研究》
Abstract： Chlorophyll content is a crucial indicator for characterizing vegetation growth. In this study, we utilized high-spectral technology to rapidly monitor the chlorophyll contents of cotton leaves. We collected 125 cotton leaf seedling samples from Xinjiang and measured their chlorophyll content and spectral data. To achieve this, we employed various spectral preprocessing techniques and used a combination of vegetation indices. Subsequently, we constructed a whale optimization algorithm/random forest regression (WOA-RFR) quantitative inversion model for cotton leaf chlorophyll content. Finally, we conducted a comparative analysis, contrasting the results of the WOA-RFR model with those obtained from the support vector regression (SVR) and RFR models. The results indicated that the spectral transformation methods (logarithm transformation, fractional order differentiation, and wavelet transformation) effectively improved the correlation between the vegetation indices and the chlorophyll content. We also found that the best inversion performance was achieved with the WOA-RFR model using a fractional order differentiation with a transformation order of 0.9 and the Vogelmann3, RVI, DVI, SR 675-700 , Mndvi705, ND, VOG1, NVI, TVI, VOG2 combined vegetation indices. The model exhibited R2 values of 0.920 and 0.955 for the training set and validation set, respectively. The corresponding RMSE values were 0.987 and 0.986, while the MRE values were 0.013 and 0.014. Compared to the RFR and SVR models, the WOA-RFR model demonstrated higher predictive accuracy, and the optimization effect of the WOA algorithm was evident. As a result, this study provides valuable decision- making support for accurately quantifying cotton leaf chlorophyll content.
Subjects: Geosciences >> Geography submitted time 2023-11-13 Cooperative journals: 《干旱区地理》
Abstract：作物水分生产率的准确和定量化评价是提高干旱区作物产量的基础，对缓解水资源短缺和农业可持续发展具有重要意义。以塔里木盆地北岸的渭干河-库车河绿洲（渭库绿洲）为典型区域，基于Google Earth Engine（GEE）云平台，通过建立20092020年流域SEBAL遥感蒸散发模型、棉花分布识别模型及估产模型，对流域棉花水分生产率进行评价。结果表明：（1） 渭库绿洲棉花产量从2009年的1610.10 kghm-2增长到2020年的1855.05 kghm-2，增长率为13.20%，棉花种植面积逐年向绿洲边缘延伸，棉花产量重心整体自西向东移动2485 m。（2） 棉花生长期2009年蒸散发均值为686.80 mm，2020年为738.66 mm，整体呈上升趋势，其增长率为7.02%，棉花生长期蒸散发最大值为花铃期和吐絮期，蒸散发较高值主要分布在绿洲内部与塔里木河北岸边缘。（3） 2009年水分生产率均值为0.21 kgm-3，2020年均值为0.25 kgm-3，12 a间水分生产率均值增长率为16%。在空间上，渭库绿洲水分生产率重心在红旗镇自东北向西南移动1832 m，年均移动速度为152.67 ma-1。绿洲棉花水分生产率呈现东西方向大于南北方向扩张趋势，空间分布方向趋势增强，空间格局趋向集聚化。（4） 12 a间产量的增长速度超过了蒸散发的上升速度，促使水分生产率提高。其次，水分生产率与棉花种植面积和合理的水量灌溉技术密切相关，水分生产率高值主要分布于沙雅县新垦农场和新和县桑塔木农场，由于农场规模化种植和集约化管理，促进了棉花增产、农业水资源的稳定分配和高效利用。
Hits
Hits
Downloads
Comment