نتایج جستجو برای: modis و avhrr

تعداد نتایج: 768857  

2003
L. G. Ferreira H. Yoshioka A. Huete E. E. Sano

The Brazilian Cerrado biome comprises a vertically structured mosaic of grassland, shrubland, and woodland physiognomies with distinct phenology patterns. In this study, we investigated the utility of spectral vegetation indices in differentiating these physiognomies and in monitoring their seasonal dynamics. We obtained high spectral resolution reflectances, during the 2000 wet and dry seasons...

Journal: :Remote Sensing 2014
Liying Geng Mingguo Ma Xufeng Wang Wenping Yu Shuzhen Jia Haibo Wang

s: More than 20 techniques have been developed to de-noise time-series vegetation index data from different satellite sensors to reconstruct long time-series data sets. Although many studies have compared Normalized Difference Vegetation Index (NDVI) noise-reduction techniques, few studies have compared these techniques systematically and comprehensively. This study tested eight techniques for ...

2017
Xiaoyi Guo Hongyan Zhang Zhengfang Wu Jianjun Zhao Zhengxiang Zhang

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resoluti...

2006
A.C.T. Pinheiro R. Mahoney

We developed a new 6-year daily, daytime and nighttime, NOAA-14 AVHRR based land surface temperature (LST) dataset over continental Africa for the period 1995 through 2000. The processing chain was developed within the Global Inventory Modeling and Mapping System (GIMMS) at NASA's Goddard Space Flight Center. This paper describes the processing methodology used to convert the Global Area Covera...

Journal: :Remote Sensing 2014
Gang Bao Zhihao Qin Yuhai Bao Yi Zhou Wenjuan Li Amarjargal Sanjjav

The response of vegetation to regional climate change was quantified between 1982 and 2010 in the Mongolian plateau by integrating the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) (1982–2006) and the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI (2000–2010). Average NDVI values f...

2004
Adrian Hauser David Oesch Stefan Wunderle

[1] Soufflet, V., D. Tanre, A. Royer, and N.T. O'Neill, (1997) Remote sensing of aerosols over boreal forest and lake water from AVHRR data. Remote Sensing of Environment, 60, pp: 22-34. [2] Goodrum, G., K.B. Kidwell, and W. Winston, (1999) NOAA KLM user's guide, National Environmental Satellite, Date, and Information Services (NESDIS). [3] Key, J., (2002) The Cloud and Surface Parameter Retrie...

2016

1 لوئسم هدنسیون : ناریا ،نارهت ،نارهت هاگشناد ،یمیش یسدنهم هدکشناد ،يژولونکتویب هورگ ،رایشناد . یکینورتکلا تسپ : [email protected] 2 ناریا ،يراس ،ناردنزام تاقیقحت و مولع یملاسا دازآ هاگشناد ،ییاذغ عیانص و مولع هدکشناد ،دشرا سانشراک . 3 ناریا ،نارهت ،نارهت هاگشناد ،یمیش یسدنهم هدکشناد ،يژولونکتویب هورگ ،دشرا سانشراک . 4 و مولع یملاسا دازآ هاگشناد ،یمیش هدکشناد ،رایداتسا ناریا ،يراس ،نار...

Journal: :Journal of the Indian Society of Remote Sensing 2021

Aerosol Optical Depth (AOD) is one of the important parameters to characterize physical properties atmospheric aerosol, which used describe extinction characteristics and also calculate aerosol content, assess degree air pollution study climate effect. To historical change in long-time series, advanced very high resolution radiometer (AVHRR) data earliest for research was this study. Due lack s...

2016
Nasibeh Roozbeh Fatemeh Nahidi Sepideh Hajiyan

تعمج تانايبلا . ةيجهنم ةعجارم تناك ةساردلا هذه :هقیرطلا و ةصالخا تاملكلا لامعتساو تانايبلا ةدعاق يف ثحبلا للاخ نم زجالحا " :یتلاا تناك ةصالخا تاملكلا .ثحبلا یف قمعتلا ريياعلما . " ةطبثلما لماوعلا " و "ءاسنلل ةدلاولا لبق ةياعرلا " لوصو" ٬" یف قمعتلا وةساردلا دعب .OR ،AND تناك ةيقطنلما لماوعلا تلااقم تددحو تضفر ةطبارتم ريغ تلااقم ، هفلتخلما تلااقلما تلااقلما رايتخلاا رايعم .تلااقلما لذل اصخلم اها...

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