تعيين سطح زير كشت محصول سيب زميني در استان همدان با استفاده از سري زماني تصاوير ماهواره IRSP6
محورهای موضوعی : آمایش سرزمینعلی شهبازی 1 , لقمان خداکرمی 2 , دکتر کامران نصیراحمدی 3
1 - دانشکده منابع طبیعی
2 - دانشکده فنی، دانشگاه کویا
3 - دانشکده مهندسی شیمی و صنایع
کلید واژه: سنجش از دور, طبقه¬بندي فازي, سيب زميني, SAVI , NDVI ,
چکیده مقاله :
این مطالعهبا هدف استفاده از تکنیک سنجش از دور و سري زماني تصاویر ماهواره ای برای شناسایی و تعیین سطح زیر کشت مزارع سيب زميني در استان همدان صورت گرفت. بدين ترتیب از سري زماني تصاوير ماهوارهIRSP6 سنجنده Awifs براي تعيين سطح زير کشت سيب زميني، استفاده شد. براي اين منظور در سه گذر زماني که همزمان با سبزينگي و زردشدگي گياه سيب زميني بوده تصاوير تهيه شد. پردازش هاي لازم از جمله آماد سازي تصاوير، تصحيح هندسي، شاخص گياهي، طبقه بندي نظارت نشده و طبقه بندي نظارت شده فازي بر روي تصاوير انجام شد. در نهايت با استفاده روش Overlay بر روي نقشه هاي حاصل از طبقه بندي نظارت شده فازي و شاخص هايNDVI, و SAVI سطح زيرکشت سيب زميني شناسايي شد. ضريب کاپا براي نقشه هاي سطح زير کشت سيب زميني حاصل از روش طبقه بندي فازي، شاخص-هايNDVI و SAVI به ترتيب90، 87 و 85 درصد به دست آمد. مساحت سطح زير کشت سيب زميني نيز به ترتيب حدود38740، 36728 و 36614 هکتار در سال 1387 تعيين شد. بر اساس نتایج اين مطالعه مشخص شد که مي توان از روش طبقه بندي فازي و سري زماني داده هاي سنجندهAWIFS براي تشخيص و تخمين سطح زير کشت سيب زميني با دقت تقريبا قابل قبول استفاده کرد و همچنين استفاده از شاخص هاي گياهي مذکور داراي سرعت بالا براي تفکيک سطح زيرکشت اين محصول است.
The aim of this study is to detect and quantify the cultivated area of potato fields in Hamadan Province using remote sensing methods and a time series of satellite photos. As a result, Awifs time-series imaging was used to determine the potato cropping area. For this purpose, pictures were taken at three different times when the potato plant turned green and yellow. Processing such as preparation, atmospheric and geometric correction, vegetation index, and unsupervised classification were performed on the images using appropriate training sites for supervised classification. Following the integration of these two layers, the studied area under the cropping map was prepared using the phase classification method. Additionally, by using the vegetation indices NDVI and SAVI, the area under cropping for the three main crop yields is determined first using the threshold level technique and in three temporal intervals. The kapa coefficient for potato under cropping area determined by phase classification, NDVI, and SAVI was 90, 87, and 85%, respectively. In 1998, the potato cropping area was determined to be 38740, 36728, and 36614 acres, respectively. This study clearly shows that the phase classification method and Awif data time series can be used to recognize and estimate potato under cropping area with acceptable precision and that vegetation indices distinguish potato under cropping area faster.
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