کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4973021 | 1451253 | 2016 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing Detecting bugweed (Solanum mauritianum) abundance in plantation forestry using multisource remote sensing](/preview/png/4973021.png)
چکیده انگلیسی
The invasive weed Solanum mauritianum (bugweed) has infested large areas of plantation forests in KwaZulu-Natal, South Africa. Bugweed often forms dense infestations and rapidly capitalises on available natural resources hindering the production of forest resources. Precise assessment of bugweed canopy cover, especially at low abundance cover, is essential to an effective weed management strategy. In this study, the utility of AISA Eagle airborne hyperspectral data (393-994Â nm) with the new generation Worldview-2 multispectral sensor (427-908Â nm) was compared to detect the abundance of bugweed cover within the Hodgsons Sappi forest plantation. Using sparse partial least squares discriminant analysis (SPLS-DA), the best detection results were obtained when performing discrimination using the remotely sensing images combined with LiDAR. Overall classification accuracies subsequently improved by 10% and 11.67% for AISA and Worldview-2 respectively, with improved detection accuracies for bugweed cover densities as low as 5%. The incorporation of LiDAR worked well within the SPLS-DA framework for detecting the abundance of bugweed cover using remotely sensed data. In addition, the algorithm performed simultaneous dimension reduction and variable selection successfully whereby wavelengths in the visible (393-670Â nm) and red-edge regions (725-734Â nm) of the spectrum were the most effective.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 121, November 2016, Pages 167-176
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 121, November 2016, Pages 167-176
نویسندگان
Kabir Peerbhay, Onisimo Mutanga, Romano Lottering, Victor Bangamwabo, Riyad Ismail,