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پیش‌بینی مکانی عملکرد گندم با استفاده از نقشه‌برداری رقومی خاک در منطقه گتوند استان خوزستان | ||
| تحقیقات آب و خاک ایران | ||
| مقاله 17، دوره 47، شماره 1، اردیبهشت 1395، صفحه 175-184 اصل مقاله (934.34 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2016.57989 | ||
| نویسندگان | ||
| روح اله تقی زاده مهرجردی* 1؛ سید علیرضا سید جلالی2؛ فریدون سرمدیان3 | ||
| 1دانشگاه اردکان | ||
| 2موسسه خاک و آب | ||
| 3دانشگاه تهران | ||
| چکیده | ||
| در پژوهش حاضر، مقدار 110 عملکرد مشاهداتی در منطقه گتوند (استان خوزستان) با استفاده از مدل برنامه‌ریزی ژنتیک، به داده‌های کمکی (مستخرج شده از مدل رقومی ارتفاع و تصویر ماهواره) ارتباط داده شد. سپس با استفاده از معادله بدست آمده برای نقاط فاقد مشاهده میزان عملکرد برآورد و نقشه تغییرات مکانی محاسبه گردید. الگوریتم رپر پارامترهای مولفه تصویر ماهواره، شاخص نسبت گیاهی، شاخص گیاهی تعدیل کننده اثر خاک، شاخص خیسی و سطح پایه شبکه زهکشی را به عنوان مهم‌ترین عوامل تولید شناخته است. میانگین ریشه مربعات خطا، ضریب همبستگی تطابق لاین و ضریب تبیین ارزیابی متقابل مدل برنامه‌ریزی ژنتیک (1) با همه داده‌های کمکی به ترتیب 11/525، 87/0 و 82/0 است. همچنین نتایج نشان داد که مدل برنامه‌ریزی ژنتیک (2) با داده‌های کمکی انتخاب شده توسط الگوریتم رپر نیز به خوبی (میانگین ریشه مربعات خطا، ضریب همبستگی تطابق لاین و ضریب تبیین به ترتیب 82/530، 86/0 و 79/0 است) قادر به پیش‌بینی عملکرد گندم است. لذا پیشنهاد می‌گردد در مطالعات آتی جهت برآورد مکانی عملکرد محصولات زراعی از مدل برنامه‌ریزی ژنتیک در قالب نقشه‌برداری رقومی خاک استفاده گردد. | ||
| کلیدواژه‌ها | ||
| داده‌های کمکی؛ الگوریتم رپر؛ برنامه‌ریزی ژنتیک؛ تغییرات مکانی | ||
| عنوان مقاله [English] | ||
| Spatial Prediction of wheat crop yield Using Digital Soil Mapping in Gotvand, Khuzestan Province | ||
| نویسندگان [English] | ||
| Roohollah Taghizadeh Merjerdi1؛ Seyed Alireza Seyed Jalali2؛ Fereydoon Sarmadian3 | ||
| چکیده [English] | ||
| A number of 110 observed crop yields were correlated with auxiliary variables (DEM and Landsat images) using genetic programming (GP) in Gotvand area (Khuzestan Province). The spatial prediction map of wheat crop yield was prepared using the obtained equation. Wrapper algorithm identified some more important auxiliary variables Nof: DVI, SAVI, and wetness index and channel network based level. RMSE, coefficient of determination and Lin's concordance coefficient of GP (1) with all the auxiliary data were obtained as 525.11, 0.87 and 0.82, respectively. Moreover, results indicated GP (2) with auxiliary data selected through wrapper algorithm could also reasonably predict wheat crop yield (RMSE, coefficient of determination and Lin's concordance coefficient, 530.82, 0.86 and 0.79, respectively). It can, therefore, be recommended to use the same approach to predict spatial distribution of crop yields in the future studies. | ||
| کلیدواژه‌ها [English] | ||
| Auxiliary variables, wrapper algorithm, Genetic programming, Spatial Variation | ||
| مراجع | ||
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