| 本论文的创新点 | 第1-5页 |
| 摘要 | 第5-13页 |
| Abstract | 第13-15页 |
| Table of contents | 第15-18页 |
| 1 General introduction | 第18-54页 |
| ·Land resource and land resource management:sketching a background | 第20-22页 |
| ·Land resource and land resource management | 第20-21页 |
| ·Land resource management and natural resource management | 第21-22页 |
| ·"3S" techniques for land/natural resources management | 第22页 |
| ·The principle of remote sensing and its applications on land/natural resource management | 第22-30页 |
| ·Principles of remote sensing | 第22-24页 |
| ·Spectral reflectance curve | 第24-26页 |
| ·Applications of remote sensing on land/natural resource management | 第26-30页 |
| ·Remote sensing of vegetation parameters | 第30-38页 |
| ·Remote sensing of forests | 第30-32页 |
| ·Remote sensing of grasslands | 第32-33页 |
| ·Remote sensing on precision agriculture | 第33-37页 |
| ·New opportunity brought by hyperspectral remote sensing | 第37-38页 |
| ·Hyperspectral remote sensing of vegetation parameters | 第38-50页 |
| ·The advent and advantage of hyperspectral remote sensing | 第38-39页 |
| ·Utility of physically-based models | 第39-40页 |
| ·Utility of empirical models | 第40-50页 |
| ·Research objectives | 第50-51页 |
| ·Study area | 第51-52页 |
| ·Thesis outline | 第52-54页 |
| 2 Literature review of hyperspectral remote sensing and foliar chemistry | 第54-62页 |
| ·Laboratory near infrared spectroscopy (NIRS) for dried powders | 第56-58页 |
| ·Field spectrometer for living plants | 第58-59页 |
| ·Imaging spectrometer for living plants | 第59-62页 |
| 3 Lab-spectroscopy of tea biochemistry-tea powders and fresh tea leaves | 第62-78页 |
| ·Introduction | 第64-66页 |
| ·Material and Methods | 第66-70页 |
| ·Sampling design | 第66页 |
| ·Spectral measurements | 第66-67页 |
| ·Biochemical assay | 第67-68页 |
| ·Data analysis | 第68-70页 |
| ·Results | 第70-75页 |
| ·Data description | 第70-71页 |
| ·Observed versus predicted values for total tea polyphenols | 第71-72页 |
| ·Observed versus predicted values for free amino acids | 第72页 |
| ·Prediction results of total tea polyphenols and free amino acids using different pre-processing methods | 第72-73页 |
| ·Influential wavelength channels | 第73-75页 |
| ·Discussion | 第75-76页 |
| ·Conclusion | 第76-78页 |
| 4 Foliar biochemistry detection for tea powders, fresh tea leaves and living tea plants acrossvarious tea varieties | 第78-96页 |
| ·Introduction | 第80-82页 |
| ·Methods and materials | 第82-87页 |
| ·Study area | 第82页 |
| ·Sampling design | 第82-83页 |
| ·Data collection | 第83-85页 |
| ·Data pre-processing | 第85-86页 |
| ·Partial least squares regression | 第86-87页 |
| ·Results | 第87-93页 |
| ·Spectral measurements of tea powders, fresh tea leaves and tea plant canopies | 第87-88页 |
| ·Measured versus predicted chemical concentrations | 第88-89页 |
| ·Retrieval accuracy of total tea polyphenols, free amino acids and soluble sugars at different levels | 第89-90页 |
| ·Important wavebands selection | 第90-93页 |
| ·Discussions and conclusions | 第93-96页 |
| 5 Estimating tea quality as a response to different soil nutrient levels, using narrow bandvegetation indices and red-edge position-an greenhouse experiment | 第96-112页 |
| ·Introduction | 第98-100页 |
| ·Methods | 第100-105页 |
| ·Greenhouse setup | 第100-101页 |
| ·Canopy spectral measurement | 第101页 |
| ·Spectral pre-processing and transformation | 第101-104页 |
| ·Chemical analysis | 第104页 |
| ·Statistical analysis | 第104-105页 |
| ·Results | 第105-110页 |
| ·Chemical concentration differences between soil treatments | 第105-106页 |
| ·Chemical concentrations retrieval using normalized ratio indices (NRI) | 第106-109页 |
| ·Chemical concentrations retrieval using red-edge position | 第109页 |
| ·Canopy spectra differences between soil treatments | 第109-110页 |
| ·Discussion and collusions | 第110-112页 |
| 6 Integrating neural networks and genetic algorithms for a better estimation of the foliarbiochemicals of tea | 第112-136页 |
| ·Introduction | 第114-117页 |
| ·Materials and methods | 第117-123页 |
| ·Plant material and growing conditions | 第117页 |
| ·Data collection | 第117-118页 |
| ·Selecting the input data set for ANN | 第118-121页 |
| ·The algorithm and parameters of ANN | 第121-123页 |
| ·Results | 第123-132页 |
| ·Band selection using genetic algorithms | 第124-125页 |
| ·Band selection using principle component analysis | 第125-127页 |
| ·Band selection using principle component analysis in combination with continuum removal | 第127-128页 |
| ·Band selection using re-sampling every 10 nm | 第128-130页 |
| ·Comparison of the perdition results between genetic algorithms and other methods | 第130-132页 |
| ·Discussion and conclusions | 第132-136页 |
| 7 Synthesis | 第136-146页 |
| ·Introducing to the synthesis | 第138-140页 |
| ·Main findings and conclusions | 第140-142页 |
| ·Creative points of this research | 第142-143页 |
| ·Looking towards the future:scaling up from hand-held spectrometer to imagingspectrometer | 第143-146页 |
| References | 第146-164页 |
| 博士期间所发表的论文 | 第164-166页 |
| Acknowledgements | 第166-168页 |
| 致谢 | 第168-170页 |
