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| 1 | 基于时间序列Landsat影像的棉花估产模型显示文摘为提高棉花遥感估产精度,该文选取加州San Joaquin Valley地区2个棉花地块作为研究区,利用时间序列Landsat_5_TM、Landsat_7_ETM遥感影像数据,结合野外实测产量数据,进行棉花产量遥感预测模型研究。结果表明:基于Landsat影像纯像元的植被指数时间序列准确地揭示了棉花整个生长期的长势情况,不同长势的棉花植被指数随时间变化在花铃期差异比较显著;整个花铃期植被指数与产量之间的相关系数均大于0.80,最大相关系数达0.90,花铃期NDVI平均值建模决定系数为0.82,均方根误差为463.69,证明花铃期比其他生长期更适用于棉花产量预测;单一时期最优模型为第206天(7月25日),多时期最优模型以NDVI最大值前三期NDVI平均值为自变量;整个花铃期NDVI最大值建模决定系数为0.81,均方根误差为477.82,该模型具有普适性。该文的研究成果为基于MODIS_NDVI最大值合成法的相关研究提供了理论依据,并且为其他农作物的估产模型建立提供借鉴。 | 刘焕军 孟令华 张新乐 Susan Ustin 宁东浩 孙思雨 | 2015 | 农业工程学报2015，31，17： | 21 |
| 2 | 基于时间序列高光谱遥感影像的田块尺度作物产量预测显示文摘在精准农业领域,田块尺度土壤理化性质、作物长势、产量等存在极显著的空间异质性。高光谱遥感侧重于光谱维度信息的提取,未充分利用空间与时相信息,限制了植被长势、生物量与产量的监测精度。传统格网采样与地统计空间插值方法,耗时费力、成本高,难以推广;而遥感技术可以获取农作物生理参数的时空异质性信息,可以用于田块尺度的精准管理分区(SSMZ)。以田块尺度棉花地为研究对象,获取时间序列航空高光谱遥感影像,分析不同长势棉花的反射光谱特征,构建光谱指数,综合光谱、时相、空间维度信息,利用面向对象方法进行精准管理分区,建立产量遥感预测模型。结果表明:综合多维信息的面向对象分割方法优于基于象元的方法,可以部分消除遥感与产量数据噪声,提高棉花估产精度;不同植被指数与棉花产量的相关系数排序为一阶微分、NDVI、OSAVI、二阶微分;对于同一尺度、单一时相,一阶微分产量预测模型精度较高,多时相多光谱植被指数也可以得到较高精度;对于同一输入量、不同尺度,较少SSMZ个数的棉花产量预测模型精度更高、稳定性更好,这是由于影像与产量数据的空间定位存在一定的误差造成。研究成果将丰富作物长势、估产方法,提高遥感监测精度,加速无人机遥感在相关领域的应用。 | 刘焕军 康苒 Susan Ustin 张新乐 付强 盛磊 孙天一 | 2016 | 光谱学与光谱分析2016，36，8： | 17 |
| 3 | 基于NDVI时间序列数据的施肥方式遥感识别方法显示文摘农产品生产过程时空动态监测是有机/绿色农产品认证亟待解决的问题,不同施肥方式的时空精准识别是解决该问题的关键。本文以美国加州大学戴维斯分校长期定位实验为基本材料,利用时间序列Landsat 8和Sentinel-2影像研究长期施肥实验下不同施肥处理轮作地块的植被指数时间序列,对比分析不同施肥处理NDVI的差异以及NDVI与产量的相关性。结果表明:1)不同施肥处理下的NDVI时间序列曲线总体趋势相似,有机肥与化肥处理NDVI时间序列曲线差异较大;2)不同施肥处理NDVI随作物生长期呈现规律变化,生长初期和后期有机肥处理NDVI均值高于化肥处理,生长中期化肥处理高于有机肥处理;3)不同施肥处理下的NDVI与产量之间相关系数随作物生长期有规律变化,应用植被指数进行遥感估产需要考虑不同施肥处理的影响。研究成果初步探讨了利用不同施肥处理NDVI时间序列差异、NDVI与产量相关性差异区分有机肥与其他施肥方式,有望为有机/绿色农业的时空动态监测与认证提供遥感技术支持,深化遥感技术在农业领域应用。 | 刘焕军 武丹茜 孟令华 Susan Ustin 崔杨 杨昊轩 张新乐 | 2019 | 农业工程学报2019，35，17： | 5 |
| 4 | Reflectance properties and physiological responses of Salicornia virginica to heavy metal and petroleum contamination显示文摘 | Pablo H. Rosso James C. Pushnik Mui Lay Susan L. Ustin | 2005 | Environmental Pollution2005，，2： | 3 |
| 5 | Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models显示文摘 | D.A. Roberts M. Gardner R. Church S. Ustin G. Scheer R.O. Green | 1998 | Remote Sensing of Environment1998，，3： | 2 |
| 6 | Evaluation of carotid intima media thickness in impaired fasting glucose and impaired glucose tolerance显示文摘 | Aydin Y Berker D Ustin I | 2011 | Minerva Endocrinol2011，36，3： | 1 |
| 7 | Estimation of tree canopy leaf area index by gap fraction analysis显示文摘 | Martens S N Ustin S L Rousseau R A | 1993 | Forest Ecology and Management1993，61，12： | 1 |
| 8 | Estimating leaf biochemistry using the PROSPECT leaf optical properties model显示文摘 | Jacquemoud S Ustin S L Verdebout J | 1996 | Remote Sensing of Environment1996，，56： | 1 |
| 9 | Application of AVIRIS data indetection of oil-induced vegetation stress and cover change atJornada,New Mexico 显示文摘 | Li L Ustin S L Lay M | 2005 | Remote Sensing of Environment2005，94，： | 1 |
| 10 | Winter rainfall interception by two mature open-grown trees in dsvis,California显示文摘 | Xiao Q F Mcpherson E G Ustin S L | | 0，，04： | 1 |
| 11 | Predicting Water Content Using Gaussian Model on Soil Spectra显示文摘 | Whiting M L Li L Ustin S L | 2004 | Remote Sensing o{ Environment2004，89，4： | 1 |
| 12 | Predicting water content using Gaussian model on soil spectra显示文摘 | Whiting M L Li L Ustin S L | 2004 | Remote Sensing of Environment2004，89，： | 1 |
| 13 | Shadow Allometry: Estimating Tree Structural Parameters Using Hyperspatial Image Analysis显示文摘 | Greenberg J A Dobrowski S Z Ustin S L | 2005 | Remote Sensing of Environment2005，97，1： | 1 |
| 14 | Remote sensing of biological soil crust under simulated climate change显示文摘 | Ustin S L Santos M J Kefauver S C | 2009 | Re mote Sensing of Environment2009，113，： | 1 |
| 15 | Water content estimation in vegetation with MODIS reflectance data and model inversion methods显示文摘 | ZARCO-TEJADA P J RUEDA C A USTIN S L | 2003 | Remote Sensing of Environment2003，85，1： | 1 |
| 16 | Mapping of Freshwater Lake Wetlands Using Object-Relations and Rule-based Inference显示文摘Inland freshwater lake wetlands play an important role in regional ecological balance.Hongze Lake is the fourth biggest freshwater lake in China.In the past three decades,there has been significant loss of freshwater wetlands within the lake and at the mouths of neighboring rivers,due to disturbance,primarily from human activities.The main purpose of this paper was to explore a practical technology for differentiating wetlands effectively from upland types in close proximity to them.In the paper,an integrated method,which combined per-pixel and per-field classification,was used for mapping wetlands of Hongze Lake and their neighboring upland types.Firstly,Landsat ETM+ imagery was segmented and classified by using spectral and textural features.Secondly,ETM+ spectral bands,textural features derived from ETM+ Pan imagery,relative relations between neighboring classes,shape features,and elevation were used in a decision tree classification.Thirdly,per-pixel classification results from the decision tree classifier were improved by using classification results from object-oriented classification as a context.The results show that the technology has not only overcome the salt-and-pepper effect commonly observed in the past studies,but also has improved the accuracy of identification by nearly 5%. | RUAN Renzong Susan USTIN | 2012 | Chinese Geographical Science2012，22，4： | 1 |
| 17 | Measuring in vivo animal soft tissue properties for haptic modeling in surgical simulation 显示文摘 | Brouwer I Ustin J Bentley L | 2001 | Stud Health Technol Inform2001，81，： | 1 |
| 18 | Shadowallometry:estimating tree structural parameters using hyperspatialimage analysis显示文摘 | GREENBERG J A DOBROWSKI S Z USTIN S L | 2005 | Remote Sensing of Environment2005，97，1： | 1 |
| 19 | Application of multiple endmember spectral mixture analysis(MESMA)to AVIRIS im- ageryforcoastalsaltmarshmappingacasestudyinChinaCamp, CA, USA 显示文摘 | LI L USTIN S L LAY M | 2005 | IntJ RemoteSens2005，26，23： | 1 |
| 20 | Active canopy sensing of winter wheat nitrogen status: An evaluation of two sensor systems显示文摘 | Qiang Cao Yuxin Miao Guohui Feng Xiaowei Gao Fei Li Bin Liu Shanchao Yue Shanshan Cheng Susan L. Ustin R. Khosla | 2014 | Computers and Electronics in Agriculture2014，，： | 1 |
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