典型文献
Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks
文献摘要：
In agricultural systems, the regular monitoring of Soil Organic Matter (SOM) dynamics is essential. This task is costly and time-consuming when using the conventional method, especially in a very fragmented area and with intensive agricultural activity, such as the area of Sidi Bennour. The study area is located in the Doukkala irrigated perimeter in Morocco. Satellite data can provide an alternative and fill this gap at a low cost. Models to predict SOM from a satellite image, whether linear or nonlinear, have shown considerable interest. This study aims to compare SOM prediction using Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). A total of 368 points were collected at a depth of 0–30 cm and analyzed in the laboratory. An image at 15 m resolution (MSPAN) was produced from a 30 m resolution (MS) Landsat-8 image using image pansharpening processing and panchromatic band (15 m). The results obtained show that the MLR models predicted the SOM with (training/ validation) R2 values of 0.62/0.63 and 0.64/0.65 and RMSE values of 0.23/0.22 and 0.22/0.21 for the MS and MSPAN images, respectively. In contrast, the ANN models predicted SOM with R2 values of 0.65/0.66 and 0.69/0.71 and RMSE values of 0.22/0.10 and 0.21/0.18 for the MS and MSPAN images, respectively. Image pansharpening improved the prediction accuracy by 2.60％ and 4.30％ and reduced the estimation error by 0.80％ and 1.30％ for the MLR and ANN models, respectively.
文献关键词：
中图分类号：
作者姓名：
Abdelkrim Bouasria;Khalid Ibno Namr;Abdelmejid Rahimi;El Mostafa Ettachfini;Badr Rerhou
作者机构：
Faculty of Sciences,Chouaib Doukkali University,El Jadida,Morocco;Agricultural Development Department,Doukkala Regional Agricultural Development Office,El Jadida,Morocco;Soil Science Department,Hassan Ⅱ Agronomic and Veterinary Institute,Rabat,Morocco
文献出处：
引用格式：
[1]Abdelkrim Bouasria;Khalid Ibno Namr;Abdelmejid Rahimi;El Mostafa Ettachfini;Badr Rerhou-.Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks)[J].地球空间信息科学学报（英文版）,2022(03):353-364
A类：
Sidi,Bennour,Doukkala,MSPAN,panchromatic
B类：
Evaluation,Landsat,pansharpening,estimating,soil,organic,matter,using,multiple,regression,artificial,neural,networks,In,agricultural,systems,regular,monitoring,Soil,Organic,Matter,SOM,dynamics,essential,This,task,costly,consuming,when,conventional,method,especially,very,fragmented,area,intensive,activity,such,study,located,irrigated,perimeter,Morocco,Satellite,data,can,provide,alternative,fill,this,gap,low,Models,from,satellite,whether,nonlinear,have,shown,considerable,interest,aims,compare,prediction,Multiple,Linear,Regression,MLR,Artificial,Neural,Networks,ANN,total,points,were,collected,depth,analyzed,laboratory,An,resolution,was,produced,processing,band,results,obtained,that,models,predicted,training,validation,values,RMSE,images,respectively,contrast,Image,improved,accuracy,by,reduced,estimation,error
AB值：
0.526467
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