کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6962496 | 1452270 | 2016 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A platform for crowdsourcing the creation of representative, accurate landcover maps
ترجمه فارسی عنوان
یک پلتفرم برای جمع آوری اطلاعات نمایندگی، نقشه های نقشه برداری دقیق
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کلمات کلیدی
سنجش از دور، پوشش زمین، جمع آوری منابع، ارزیابی دقیق، نمونه گیری نمایشی، استخراج شی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
چکیده انگلیسی
Accurate landcover maps are fundamental to understanding socio-economic and environmental patterns and processes, but existing datasets contain substantial errors. Crowdsourcing map creation may substantially improve accuracy, particularly for discrete cover types, but the quality and representativeness of crowdsourced data is hard to verify. We present an open-sourced platform, DIYlandcover, that serves representative samples of high resolution imagery to an online job market, where workers delineate individual landcover features of interest. Worker mapping skill is frequently assessed, providing estimates of overall map accuracy and a basis for performance-based payments. A trial of DIYlandcover showed that novice workers delineated South African cropland with 91% accuracy, exceeding the accuracy of current generation global landcover products, while capturing important geometric data. A scaling-up assessment suggests the possibility of developing an Africa-wide vector-based dataset of croplands for $2-3 million within 1.2-3.8 years. DIYlandcover can be readily adapted to map other discrete cover types.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Environmental Modelling & Software - Volume 80, June 2016, Pages 41-53
Journal: Environmental Modelling & Software - Volume 80, June 2016, Pages 41-53
نویسندگان
L.D. Estes, D. McRitchie, J. Choi, S. Debats, T. Evans, W. Guthe, D. Luo, G. Ragazzo, R. Zempleni, K.K. Caylor,