کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4458969 1621272 2013 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Integration of in situ measured soil status and remotely sensed hyperspectral data to improve plant production system monitoring: Concept, perspectives and limitations
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
Integration of in situ measured soil status and remotely sensed hyperspectral data to improve plant production system monitoring: Concept, perspectives and limitations
چکیده انگلیسی

A common problem in agricultural remote sensing is the sub-pixel spectral contribution of background soils, weeds and shadows which impedes the effectiveness of spectral vegetation indices to monitor site-specific variations in crop condition. To address this mixture problem, the present study combines in situ measured soil status and remotely sensed hyperspectral data in an alternative spectral unmixing algorithm. The model driven approach, referred to as Soil Modeling Mixture Analysis (SMMA), combines a general soil reflectance model and a modified spectral mixture model providing as such the opportunity to simultaneously extract the sub-pixel cover fractions and spectral characteristics of crops. The robustness of the approach was extensively tested using ray-tracer data (PBRT) from a virtual orchard, and results showed an improved monitoring of the crop's chlorophyll, water content and Leaf Area Index (LAI). A significant increase in the R2 between vegetation indices and the biophysical parameters was observed when index values were calculated from the pure vegetation signals as extracted by SMMA as opposed to index values calculated from the original (mixed) image pixels (GM1: ΔR2 = 0.19; MDWI: ΔR2 = 0.38; sLAIDI: ΔR2 = 0.14).


► A Signal Unmixing approach is presented minimizing background effects in VI.
► MESMA was combined with a soil reflectance model to extract pure crop signals.
► A virtual citrus orchard was used to create a realistic simulation of the test site.
► Signal Unmixing significantly improved crop status monitoring.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 128, 21 January 2013, Pages 197–211
نویسندگان
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