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Complementarity of ResourceSat-1 AWiFS and Landsat TM/ETM+ sensors

S.N. Goward, G. Chander, M. Pagnutti, A. Marx, R. Ryan, N. Thomas, R. Tetrault
2012 Remote Sensing of Environment  
., "Complementarity of ResourceSat-1 AWiFS and Landsat TM/ETM+ sensors" (2012).  ...  Overall, we found that the AWiFS and Landsat TM/ETM+ imagery are comparable and in some ways complementary, particularly with respect to temporal repeat frequency.  ...  The support of the USDA Data Archive is much appreciated in accessing the AWiFS imagery.  ... 
doi:10.1016/j.rse.2012.03.002 fatcat:x5gskv3gvjc3ndbo75aqgz6rlm

Wheat Grain Protein Content Estimation Based on Multi-temporal Remote Sensing Data and Generalized Regression Neural Network [chapter]

Cunjun Li, Qian Wang, Jihua Wang, Yan Wang, Xiaodong Yang, Xiaoyu Song, Wenjiang Huang
2012 IFIP Advances in Information and Communication Technology  
GPC was estimated with multi-temporal remote sensing data and generalized regression neural network (GRNN) method.  ...  Wheat grain protein content (GPC) at maturity was measured and multi-temporal Landsat TM and Landsat ETM + images at key stages in 2003, 2004 growth stages were acquired in this study.  ...  In this research, Matlab was used to train GRNN for protein estimation using mutitemporal Landsat TM/ETM+ data.  ... 
doi:10.1007/978-3-642-27278-3_41 fatcat:yupg6ttuibdsdcqwicp45dzk2m

Estimating crop water stress with ETM+ NIR and SWIR data

Abduwasit Ghulam, Zhao-Liang Li, Qiming Qin, Hamid Yimit, Jihua Wang
2008 Agricultural and Forest Meteorology  
Four images of clear sky TM/ETM+ data were acquired over the Shunyi test site (Table 1) .  ...  That is why the correlation between EWT and TM/ETM+ water bands is stronger for band 5 than band 7.  ... 
doi:10.1016/j.agrformet.2008.05.020 fatcat:hv3fhjfuvjha5laegxbtsh2vwy

Mapping Croplands in the Granary of the Tibetan Plateau Using All Available Landsat Imagery, A Phenology-Based Approach, and Google Earth Engine

Yuanyuan Di, Geli Zhang, Nanshan You, Tong Yang, Qiang Zhang, Ruoqi Liu, Russell B. Doughty, Yangjian Zhang
2021 Remote Sensing  
Our first phenology-based cropland mapping algorithm (PCM1) used different thresholds of land surface water index (LSWI) by considering varied crop phenology along different elevations.  ...  To decrease the classification errors due to elevational differences in crop phenology, we developed two pixel- and phenology-based algorithms to map croplands using Landsat imagery and the Google Earth  ...  LSWI is sensitive to equivalent water thickness attributed to the SWIR band, which is sensitive to leaf water and soil moisture [52] .  ... 
doi:10.3390/rs13122289 fatcat:rmexeeo5bffftlogoczqkhrhay

Glacier Variations in the Fedchenko Basin, Tajikistan, 1992–2006: Insights from Remote-sensing Images

Qibing Zhang, Shichang Kang, Feng Chen
2014 Mountain Research and Development  
Considering all these factors, three areas were selected on a classification map for Landsat TM/ETM+; each area included 400 pixels.  ...  For Landsat TM/ETM+, strong shadows occurred on the images because of complicated relief, and mapping of the glacier boundaries had to be improved using NDSI 5 (band 2 2 band 5)/(band 2 + band 5).  ... 
doi:10.1659/mrd-journal-d-12-00074.1 fatcat:gs6b2fw7svevpmvdwsb4d4qkla

Assessment of Vegetation Trends in Drylands from Time Series of Earth Observation Data [chapter]

Rasmus Fensholt, Stephanie Horion, Torbern Tagesson, Andrea Ehammer, Kenneth Grogan, Feng Tian, Silvia Huber, Jan Verbesselt, Stephen D. Prince, Compton J. Tucker, Kjeld Rasmussen
2015 Remote Sensing Time Series  
Acknowledgement We highly appreciate that all MODIS, Landsat and DEM data were provided free of charge by the National Aeronautics and Space Administration(NASA), the National Oceanic and Atmospheric Administration  ...  This chapter is part of research framed by the USGS-NASA Landsat Science Team 2012-2016.  ...  For optical instruments it is already common to combine two or several data sets retrieved from Landsat TM, ETM+, and OLI.  ... 
doi:10.1007/978-3-319-15967-6_8 fatcat:2cl5kwf33zg7hl2k3syukjpa6q

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data

Geli Zhang, Xiangming Xiao, Jinwei Dong, Weili Kou, Cui Jin, Yuanwei Qin, Yuting Zhou, Jie Wang, Michael Angelo Menarguez, Chandrashekhar Biradar
2015 ISPRS journal of photogrammetry and remote sensing (Print)  
Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions.  ...  This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and  ...  Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.isprsjprs.2015.05. 011.  ... 
doi:10.1016/j.isprsjprs.2015.05.011 pmid:27667901 pmcid:PMC5034934 fatcat:flrdtaayyrbm3o42hk57p7x2qa

Satellite observed rapid green fodder expansion in northeastern Tibetan Plateau from 2010 to 2019

Tong Yang, Geli Zhang, Yuzhe Li, Jiangwen Fan, Danfeng Sun, Jie Wang, Yuanyuan Di, Nanshan You, Ruoqi Liu, Qiang Zhang, Russell B. Doughty
2021 International Journal of Applied Earth Observation and Geoinformation  
water content in the late growing season than other vegetation.  ...  A total of 858 Landsat images were used to generate green fodder maps in northeastern Tibetan Plateau (including Zeku, Guinan, and Tongde Counties) in three periods (circa 2010, 2015, and 2019).  ...  The harmonization algorithm used the OLS regression coefficients to harmonize TM/ETM + to OLI, because TM/ETM + has a different spectral band setting from OLI (Roy et al., 2016) .  ... 
doi:10.1016/j.jag.2021.102394 fatcat:53ulzhtqdbajpoqkefjzoue4tq

Uncertainty assessment of surface net radiation derived from Landsat images

Maria Mira, Albert Olioso, Belén Gallego-Elvira, Dominique Courault, Sébastien Garrigues, Olivier Marloie, Olivier Hagolle, Pierre Guillevic, Gilles Boulet
2016 Remote Sensing of Environment  
Results show a substantial 42 underestimation of Landsat-7 albedo (up to 0.024), particularly for estimates retrieved 43 using the middle infrared, which could be due to different sources: the calibration  ...  Surface albedo is estimated from spectral reflectances using a narrow-to-34 broadband conversion method.  ...  This was not the case for albedo (Fig. 2) and surface temperature (Fig. 4) . 765 Estimations of albedo from Landsat data were obtained by applying the NTB 766 conversion method using different coefficient  ... 
doi:10.1016/j.rse.2015.12.054 fatcat:zk2kaf7ohzeurgemlz2ircacye

Recent glacier mass balance and area changes in the Kangri Karpo Mountain derived from multi-sources of DEMs and glacier inventories

Wu Kunpeng, Liu Shiyin, Jiang Zongli, Xu Junli, Wei Junfeng, Guo Wanqin
2017 The Cryosphere Discussions  
Glacier area and length changes were derived from Topographical Maps and Landsat TM/ETM+/OLI images between 1980 and 2015.  ...  Hence, Landsat 1 TM/ETM+ scenes were used to validate and update the CGI2 and GAMDAM glacier inventory, 2 and generated the 2000 inventory of the detailed study area. 3 A semi-automated approach using  ...  Glacier area and length changes were derived from 23 Topographical Maps and Landsat TM/ETM+/OLI images between 1980 and 2015.  ... 
doi:10.5194/tc-2017-153 fatcat:ato7f6ukrjcvzl67j6j3dzjy7q

Glacier mass and area changes on the Kenai Peninsula, Alaska, 1986–2016

Ruitang Yang, Regine Hock, Shichang Kang, Donghui Shangguan, Wanqin Guo
2020 Journal of Glaciology  
Glacier mass loss in Alaska has implications for global sea level rise, fresh water input into the Gulf of Alaska and terrestrial fresh water resources.  ...  We map all glaciers (>4000 km2) on the Kenai Peninsula, south central Alaska, for the years 1986, 1995, 2005 and 2016, using satellite images.  ...  A red/short-wave infrared (R/SWIR) band ratio with a threshold of 2-2.5 (TM3/TM5 of Landsat TM and ETM+, TM4/TM6 of Landsat OLI imagery) and an additional threshold on the blue band (band 1 of TM/ETM+  ... 
doi:10.1017/jog.2020.32 fatcat:l7ppsr2tcnch5n35nj4vccvluy

Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales

Martha C. Anderson
2009 Journal of Applied Remote Sensing  
This paper describes a novel physically-based approach for estimating leaf area index (LAI) and leaf chlorophyll content (C ab ) at regional scales that relies on radiance data acquirable from a suite  ...  While the empirical-statistical approach that links vegetation indices (VI) and vegetation variables using experimental data is less affected by e.g. radiometric calibration accuracy and atmospheric factors  ...  We would like to acknowledge Wayne Dulaney and Principal Investigator Brent Holben of the AERONET sites for making sun photometer data available.  ... 
doi:10.1117/1.3141522 fatcat:mu6av5cdxfdznfn6ch57kowlbu

Multispectral classification and reflectance of glaciers: in situ data collection, satellite data algorithm development, and application in Iceland & Svalbard

Allen J. Pope, Apollo-University Of Cambridge Repository, Apollo-University Of Cambridge Repository
2013
Glaciers and ice caps (GIC) are central parts of the hydrological cycle, are key to understanding regional and global climate change, and are important contributors to global sea level rise, regional water  ...  Multispectral (visible and near-infrared) remote sensing has been used for studying GIC and their changing characteristics for several decades.  ...  Band 2 TM/ETM+ and Band 4 TM/ETM+ are valid for TM and ETM+; for MSS, Bands 4 MSS and 6 MSS were used.  ... 
doi:10.17863/cam.16313 fatcat:geolexhjvfha5kpbofrd2c546y

An overview of MATISSE-v2.0

Luc Labarre, Karine Caillault, Sandrine Fauqueux, Claire Malherbe, Antoine Roblin, Bernard Rosier, Pierre Simoneau, Karin Stein, John D. Gonglewski
2010 Optics in Atmospheric Propagation and Adaptive Systems XIII  
for providing the Radarsat-2, TerraSAR-X and weather data respectively.  ...  This gives us a background correlation that we use as reference to subtract from the spatial correlation in both image and far-field measurements.  ...  Landsat TM/ETM+ images of these sites within the corresponding periods have been obtained from NASA/USGS data portal (http://glovis.usgs.gov).  ... 
doi:10.1117/12.868183 fatcat:5anlqspzzzcftfufaxvlr45zve

Vertical distribution of stable isotopic composition in atmospheric water vapor and subsurface water in grassland and forest sites, eastern Mongolia

Maki Tsujimura, Lisa Sasaki, Tsutomu Yamanaka, Atsuko Sugimoto, Sheng-Gong Li, Dai Matsushima, Ayumi Kotani, Mijiddorj Saandar
2007 Journal of Hydrology  
The results are organized in five relevant categories comprising (i) hydrologic cycle including precipitation, groundwater, and surface water, (ii) hydrologic cycle and ecosystem, (iii) surface-atmosphere  ...  Note that JGH and KBU stations are the meteopost and only the data three times a day (8, 14, 20 MST) were available and were used for the calculation, while others are the meteostation.  ...  Also in some months, data are completely missing in some stations.  ... 
doi:10.1016/j.jhydrol.2006.07.025 fatcat:i6irn2rplfby3mvsticrvqrkq4
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