Thesis (M. Env. Sc.)--University of Adelaide, Mawson Graduate Centre for Environmental Studies, 1999. / Includes bibliographical references (leaves 183-191).

Thesis (M.Env.Sc.)--University of Wollongong, 2007. / Typescript. Includes bibliographical references: leaf 83-98.

Thesis (M. Sc.)--University of Canterbury, 2009. / Typescript (photocopy). Includes bibliographical references (leaves 103-115). Also available via the World Wide Web.

The monitoring of continental and global scale net primary production remains a major focus of satellite-based remote sensing. Potential benefits which follow are diverse and include contributions to, and improved scientific understanding of, ecological systems, rangeland management, famine warning, agricultural commodity trading, and the study of global climate change.A NOAA-AVHRR data set containing monthly observations of green vegetation cover over a ten year period was acquired and analysed, to extract information on seasonal conditions. The data were supplied as a vegetation index, commonly known as the Normalised Difference Vegetation Index (NDVI), with a spatial resolution of approximately five km. The data set was acquired from three different satellites, and calibration problems were known to exist. A new technique was developed to estimate, and subsequently remove, the calibration bias present in the data.Monthly rainfall measurements were used as surrogate ground truth to validate the NDVI data. For regions of native vegetation, linear models relating NDVI to previous rainfall were derived, using transfer function techniques in common use in systems engineering. The models demonstrate that, in mid-latitude regions, the NDVI is a linear function of rainfall recorded over the preceding seven or eight months.Annual summaries of the image data were developed to highlight the amount and timing of plant growth. Three fundamental questions were posed as an aid to the development of the summary technique: where, when and how much? These summaries highlight the extraordinary spatial and temporal variations in plant growth, and hence rainfall, over much of Western Australia each year.Standard analysis techniques used in time series analysis, such as classical decomposition, were successfully applied to the analysis of NDVI time series. These techniques highlighted ++ / structural differences in the image data, due to land use, climatic factors and vegetation type.Overall, the results of the research undertaken in this study, using NOAA-AVHRR data in Western Australia, demonstrate that vegetation indices acquired from satellite platforms can be used to monitor continental scale seasonal conditions in an effective manner. As a consequence of these results, further research using this type of data is proposed in rangeland management and climate change modelling.

Thesis (M.S.)--Oregon State University, 2007. / Printout. Includes bibliographical references (leaves 102-105). Also available on the World Wide Web.

Arizona Cooperative Extension Publication 190043 / Originally published 1990, revised 1995, revised 1997.

Arizona Cooperative Extension Publication 190043 / Originally published 1990, Revised 1995.

Thesis (M.Sc.). / Written for the Dept. of Geography. Title from title page of PDF (viewed 2008/05/28). Includes bibliographical references.

Thesis (M.A.)--University of Nevada, Reno, 2007. / "May 2007" Includes bibliographical references (leaves 138-151). Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2008]. 1 microfilm reel ; 35 mm. Online version available on the World Wide Web.

干旱是全球范围内的灾害。协同利用遥感数据和气象数据来研究植被对干旱的响应并进行干旱评估和监测，对于减少干旱损失，制定决策和农业管理都有重大的现实意义。 / 本研究提出了两种新的处理多时相遥感数据的方法：一种是基于无云影像频域分析的植被时间序列获取；另一种是基于时间序列主成份分析的MODIS混合象元信息提取。这两种方法可以分别用于时间序列数据的预处理和估算生态干扰发生时陆地植被覆盖的变化。 / 本研究开展了地面试验，用ASD地面高光谱仪和SPAD502叶绿素仪测定了在控制梯度干旱下的玉米叶片光谱和叶绿素含量的动态变化。研究表明：随着干旱的加剧, 叶片光谱反射率也会相应增加。统计分析表明叶片510 nm和690 nm处的反射率可以用于玉米干旱的预警。本研究基于不同干旱程度和玉米不同发育时期的光谱数据，全面探讨了光谱变量和光谱指数对干旱胁迫下叶绿素变化的敏感性。 / 本研究探讨了中国的作物长势与气象因子的关系，首先基于温度，降水，光照和NDVI数据将中国分为7个研究区，然后基于多元线性回归提取了每个研究区在19822006年间限制作物生长的关键气候因子。研究表明在春季和夏季，温度，降水, 光照对作物NDVI的影响（R²>=0.35）要大于秋季和冬季 (R²<=0.14). 在分区1-3（华北，东北）中，全年作物NDVI呈现显著增加的趋势(p<0.1)，而在华南地区则没有明显的趋势。 / 在西南干旱中，两类遥感干旱指数（基于空间特征的TVDI和基于时间序列的VHI）与气象干旱指数SPI进行了比较。本研究进行了气象干旱指数和遥感干旱指数的时空一致性分析。TVDI受制于特定研究区提取的‘干边’和‘湿边’，而VHI则受时间序列数据噪声的影响。SPI36和遥感干旱指数存在相对稳定的关系，这与研究区的主要的植被类型是森林有关。 / 本研究用模型碳参数结合遥感数据估算了干旱引起的森林生态系统碳存储的变化。估算的结果与遥感获取的植被净光合速率的变化进行了比较，两者的一致性较高（r=0.32 p<0.001）。研究表明卫星遥感数据结合生态模型可以有效反演在全球变化背景下植被参数的变化。 / Studies on monitoring vegetative responses to drought by integrating remote sensing and meteorological data sets are of great practical meaning in mitigating losses, making decisions and managing agriculture. / A field experiment was conducted to test the hyperspectral sensitivity of corn responses to drought in controlled gradients. Statistical analysis shows that leaf reflectance at 510 nm and 690 nm under artificial illumination mode can indicate early drought significantly. The sensitivity of different hyperspectral indices and position-based variables on vegetative chlorophyll change under drought was also comprehensively compared. / China was divided into 7 regions based on the monthly anomaly of NDVI, precipitation, temperature and sunshine duration from 1982 to 2006 with hierarchical clustering. The impact of precipitation, temperature and sunshine duration on crop NDVI in spring and summer (average R² >=0.35) is higher than that in autumn and winter (average R² < =0.14). The full-year crop NDVI trend for region 1-3 increases (p<0.1), which is related with temperature increase as temperature is the limiting climatic factor for crop growth in these regions. / Time-frequency domain analysis was conducted to denoise multi-temporal remotely sensed data. These methods can be used for retrieving cloud-free phenological curves from multi-temporal satellite data. The two drought indices TVDI and VHI were spatio-temporally compared with the meteorological drought index, SPI. TVDI was subjected to extracted ‘wet edge’ and ‘dry edge’ in the study area while VHI was subjected to noises on NDVI and LST time series. SPI36 and remotely sensed drought indices can reach relative stable relationship, which may be due to the fact that most areas in the present study were covered by forest. / Carbon dynamics for forest ecosystem in drought can be quantified with carbon parameters from models and multi-temporal MODIS NDVI data sets. Sub-pixel percent forest cover was extracted based on principle component analysis (PCA) to multi-temporal MODIS NDVI. The estimated carbon change is highly correlated with the remotely sensed PsnNet change (r=0.32 p<0.001). Satellite remote sensing in conjunction with ecological models can retrieve many important variables caused by global change. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wang, Hongshuo. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 102-120). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.I / Table of contents --- p.IV / List of figures and tables --- p.VII / Acknowledgement --- p.XI / Chapter CHAPTER 1 --- Introduction --- p.1 / Chapter 1.1 --- Significance of the research --- p.1 / Chapter 1.2 --- Objectives of the study --- p.4 / Chapter 1.3 --- Dissertation structure --- p.4 / Chapter CHPATER 2 --- Literature Review --- p.6 / Chapter 2.1 --- Review on denoising multi-temporal data with time-frequency domain analysis --- p.6 / Chapter 2.2 --- Review on sub-pixel information extraction with multi-temporal NDVI --- p.9 / Chapter 2.3 --- Review on sensitivity of hyperspectral data in drought monitoring --- p.11 / Chapter 2.4 --- Review on spatio-temporal crop responses to climate change in China --- p.15 / Chapter 2.5 --- Review on spatio-temporal assessment of remotely- sensed drought indices --- p.18 / Chapter 2.5.1 --- Meteorological drought monitoring --- p.18 / Chapter 2.5.2 --- LST/NDVI space and its significance in drought monitoring --- p.20 / Chapter 2.6 --- Review on retrieving terrestrial carbon flux in drought --- p.23 / Chapter CHAPTER 3 --- Sensitivity of Hyperspectral Data in Monitoring Corn Responses to Drought --- p.25 / Chapter 3.1 --- Experiment --- p.25 / Chapter 3.2 --- Data analysis --- p.28 / Chapter 3.2.1 --- Sensitivity of hyerpspectral data to drought severity --- p.28 / Chapter 3.2.2 --- Comparison of different vegetation indices under drought --- p.30 / Chapter 3.3 --- Chlorophyll gradient under the threat of drought --- p.35 / Chapter 3.4 --- Discussion and conclusion --- p.36 / Chapter CHAPTER 4 --- Spatio-temporal Crop Responses to Climate Change in China --- p.39 / Chapter 4.1 --- Data description and preprocessing --- p.39 / Chapter 4.1.1 --- Data sets --- p.39 / Chapter 4.1.2 --- Data preprocessing --- p.40 / Chapter 4.1.3 --- Data standardization --- p.41 / Chapter 4.2 --- Conducting clustering analysis --- p.41 / Chapter 4.3 --- Regionalization result --- p.44 / Chapter 4.4 --- Crop responses to climate change --- p.44 / Chapter 4.4.1 --- Full-year crop responses to climate change --- p.48 / Chapter 4.4.2 --- Seasonal crop responses to climate change --- p.48 / Chapter 4.5 --- Drought trend of different scales and its potential influences on crop production --- p.54 / Chapter 4.6 --- Conclusion --- p.55 / Chapter CHAPTER 5 --- Spatio-temporal Assessment of Remotely-sensed Drought Indices a Case Study in Drought of Southwest China --- p.57 / Chapter 5.1 --- Denoising Multi-temporal data with frequency-time domain analysis --- p.57 / Chapter 5.1.1 --- Data Description --- p.57 / Chapter 5.1.2 --- Methods --- p.59 / Chapter 5.1.3. --- Comparison among Different Methods --- p.64 / Chapter 5.2. --- Drought indices --- p.65 / Chapter 5.2.1 --- data preprocessing --- p.67 / Chapter 5.2.2 --- VHI --- p.68 / Chapter 5.2.3 --- TVDI --- p.68 / Chapter 5.2.4 --- Spatial consistency between TVDI and VHI --- p.75 / Chapter 5.3 --- Conclusion and Discussion --- p.76 / Chapter CHAPTER 6 --- Monitoring Carbon Dynamic during Drought in Southwest China with MODIS --- p.78 / Chapter 6.1 --- Sub-pixel information retrieval based on multi-temporal MODIS NDVI --- p.78 / Chapter 6.1.1 --- Data collection and processing --- p.78 / Chapter 6.1.2 --- Methods --- p.82 / Chapter 6.1.3 --- Results and analysis --- p.86 / Chapter 6.2 --- Determining drought period --- p.89 / Chapter 6.3 --- Quantifying vegetative responses to drought with vegetation indices --- p.91 / Chapter 6.4 --- Quantifying carbon change of forest ecosystem during drought --- p.92 / Chapter 6.5 --- Conclusions and Discussions --- p.95 / Chapter CHAPTER 7 --- Innovations and Future Works --- p.98 / Chapter 7.1 --- Summary --- p.98 / Chapter 7.2 --- Innovations --- p.99 / Chapter 7.3 --- Future work --- p.101 / Reference --- p.102