Open Access
Monitoring Vegetation Systems in the Great Plains with Erts
J. W. Rouse,R. H. Haas,J. A. Schell,D. W. Deering +3 more
- Vol. 351, pp 309
TLDR
In this paper, a method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 spectral bands 5 and 7, corrected for sun angle, which is shown to be correlated with aboveground green biomass on rangelands.Abstract:
The Great Plains Corridor rangeland project utilizes natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. A method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 MSS data. Radiance values recorded in ERTS-1 spectral bands 5 and 7, corrected for sun angle, are used to compute a band ratio parameter which is shown to be correlated with aboveground green biomass on rangelands.read more
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Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale
TL;DR: In this paper, the capability of high-resolution (6m) multi-spectral satellite imagery, SPOT-6, in disease mapping was assessed and validated using field survey data.
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Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan
Shinya Tanaka,Kensuke Kawamura,Masayasu Maki,Yasunori Muramoto,Kazuaki Yoshida,Tsuyoshi Akiyama +5 more
TL;DR: The results indicate that the linear regression model based on the narrow-band and broad-band DSIR760–R739 is a simple but accurate method for timely and nondestructive monitoring of LAI.
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Remote prediction of yield based on LAI estimation in oilseed rape under different planting methods and nitrogen fertilizer applications
Yi Peng,Ting’e Zhu,Ting’e Zhu,Yucui Li,Can Dai,Shenghui Fang,Yan Gong,Xianting Wu,Renshan Zhu,Kan Liu +9 more
TL;DR: In this article, the authors developed a method to predict yield based entirely on remotely sensed data in oilseed rape under different planting methods and nitrogen fertilizer applications, which can be used to predict field-scale yield.
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Combining airborne laser scanning data and optical satellite data for classification of alpine vegetation
TL;DR: Overall accuracy when using the combination of laser data metrics, elevation derivatives and SPOT 5 data increased by 6% as compared to classification of SPOT and elevation derivatives only, and increased by 14.2% compared to SPot 5 data alone.
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Mapping flooding regimes in Camargue wetlands using seasonal multispectral data
TL;DR: In this article, a regression model was used for predicting the presence and levels of water, independently of vegetation type and density in shallow marshes in the Rhone river delta (Camargue) in 2005 and 2006.