Results 111 to 120 of about 159,878 (310)

پهنه‌بندی خطر سرمازدگی در مراحل مختلف رشد برنج (.Oryza sativa L) با استفاده از داده‌های ماهواره‌ای [PDF]

تنش های محیطی در علوم زراعی
پدیده سرمازدگی منجر به خسارات جبران‌ناپذیری به شالیزارهای استان گیلان می‌شود. در کشورهای درحال‌توسعه مانند ایران، ایستگاه‌های هواشناسی معمولاً پراکنده هستند به همین دلیل از سنجنده و حسگرهایی مانند MODIS که به‌صورت رایگان در دسترس هستند استفاده می‌کنند که
لیلا صدوقی, علی اکبر نوروزی, علی محمدی ترکاشوند, ابراهیم پذیرا   +3 more
doaj   +1 more source

Global aerosol climatology from the MODIS satellite sensors [PDF]

, 2008
L. A. Remer, R. G. Kleidman, R. C. Levy, Yoram J. Kaufman, D. Tanré, S. Mattoo, J. Vanderlei Martins, Charles Ichoku, Ilan Koren, Hongbin Yu, B. N. Holben   +10 more
openalex   +1 more source

EOS Science Poster Series: LAND- Our Changing Earth [PDF]

, 2007
This poster, one in a four-part series, highlights recent images from select NASA Earth Science spacecraft and showcases related research results. The back gives a brief overview of the science and missions behind NASA's study of LAND. Educational levels:

core  

Correction of "Cloud Removal By Fusing Multi-Source and Multi-Temporal Images"

, 2017
Remote sensing images often suffer from cloud cover. Cloud removal is required in many applications of remote sensing images. Multitemporal-based methods are popular and effective to cope with thick clouds.
Cheng, Qing, Li, Xinghua, Li, Zhiwei, Shen, Huanfeng, Zhang, Chengyue   +4 more
core   +1 more source

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

Remote Sensing in Ecology and Conservation, EarlyView.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law, Yi‐Fei Gu, Shuwen Liu, Guangqin Song, Aland H. Y. Chan, Cham Man Tse, Zhonghua Liu, Martha J. Ledger, Billy C. H. Hau, Sawaid Abbas, Jin Wu   +10 more
wiley   +1 more source

A feasible method on atmospheric correction to channel 1 and 2 for MODIS(MODIS通道1和通道2大气订正的一种快速实用方法)

Zhejiang Daxue xuebao. Lixue ban, 2004
提出了利用气象资料对MODIS影像进行大气校正的一种快速实用方法.读取MODIS前两个通道250 min的反射率，采用常用的黑色目标扣除法(Dark-object subtraction)计算天空程辐射，通过卫星过境时刻的气象能见度和水汽资料计算大气造过率，表后推导出目标物的反射率. 通过比较两个邻近日期MODIS影像校正前后的归一化植被指数(NDVI)值，得出利用本文提出的方法对MODIS进行大气校正所得到的NDVI值更接近实际情况.
CHENGQian(程乾), HUANGJing-feng(黄敬峰), WANGRen-chao(王人潮), GUJun-qiang(顾俊强)   +3 more
doaj   +1 more source

Validation of MODIS aerosol retrieval over ocean [PDF]

, 2002
L. A. Remer, D. Tanré, Yoram J. Kaufman, Charles Ichoku, S. Mattoo, R. C. Levy, D. A. Chu, B. N. Holben, Оleg Dubovik, A. Smirnov, J. Vanderlei Martins, R.‐R. Li, Z. Ahmad   +12 more
openalex   +1 more source

Estimating Hourly Full-Coverage PM2.5 Concentrations Based On MODIS Data Over The Northeast of Thailand. [PDF]

, 2022
Wilawan Kumharn, Oradee Pilahome, Wichaya Ninsawan, Yuttapichai Jankondee   +3 more
openalex   +1 more source

Comparative Trends of Sociality Among Terrestrial Carnivores: A Multivariate Analysis 陆生食肉动物社会性的比较趋势:一项多变量分析

Wildlife Letters, EarlyView.
In this study we analyze the role of phylogeny, environment, and community structure on sociality. Using structural equation modeling (SEM) we aim to quantify the direct and indirect impacts of variables on behaviors including social grouping, reproduction, and space use among Carnivora species.
Jessica Ward, Aileen C. Mill, Chris Carbone, Steve Rushton   +3 more
wiley   +1 more source

Changes of Potential Suitable Areas for Lynx Under Climate Change in Mohe Area, Daxing'anling Mountains, China

Wildlife Letters, EarlyView.
Climate change drives shifts in suitable habitats for Eurasian lynx and its prey (hare, roe deer) in Mohe, Daxing'anling Mountains. Under RCP scenarios, moderate warming (RCP4.5) promotes substantial habitat expansion, while high‐emission conditions (RCP8.5) lead to strong expansion in the 2050s but slower gains and partial contraction by the 2070s ...
Binglian Liu, Dan Ju, Hong Chen, Qi Qi, Geng Liu, Shaochun Zhou   +5 more
wiley   +1 more source