Assessment of structural and functional characteristics of cropping systems using advanced terrestrial, air-, and spaceborne remote sensing applications

该项目的总体目标是建立遥感应用程序，以便能够在班加罗尔的土壤和气候条件下评估农作物和种植制度的重要结构特征(作物高度、作物种类)和功能特征(产量、质量)。具体目标是：1.根据UASB田间试验的参考数据(生物量、叶面积指数、氮和纤维浓度、N营养指数)校准各种遥感数据(近端高光谱辐射计；陆地高分辨率3D激光扫描仪；全画幅高光谱成像光谱仪)，其中包括大多数相关作物物种在不同水分和氮素有效性水平下的独特变异性；2.测试传感器组合用于评估作物特征的潜力。主要目的是证明陆地高分辨率三维激光扫描技术能否在较高水平的农作物叶面积指数上用光谱来补偿饱和效应；3.将陆地高光谱光谱与星载多光谱图像的结果进行比较，并建立高光谱图库，使用n维角将卫星图像像素与参考光谱相匹配，这有望提高星载光谱的性能；4.开发作物种类和作物管理强度的识别和分类程序，这是生成班加罗尔更大面积的时空清晰作物地图的前提；5.使用位于班加罗尔样带的农场试验田的独立数据验证模型的准确性；模型的开发及其彻底验证，以及支持空间遥感性能的数据的产生，将使C01能够为大规模评估种植制度创造方法学基础。因此，C01的结果是对班加罗尔城乡交界处种植系统时空动态的设想评估和FOR2432分析的基本要素。

The overarching objective of the project is to establish remote sensing applications, which allow the assessment of important structural (crop height, crop species) and functional characteristics (yield, quality) of agricultural crops and cropping systems under the soil and climate conditions of Bangalore. Specific objectives are: 1. To calibrate various remote sensors (proximal hyperspectral radiometer; terrestrial high-resolution 3D laser scanner; full-frame hyperspectral imaging spectrometer) based on reference data (biomass, leaf area index, nitrogen and fibre concentration, N nutrition index) from the field experiment at UASB, which comprises a unique variability of most relevant crop species at different levels of water and nitrogen availability; 2. To test the potential of sensor combinations for the assessment of crop characteristics. The main aim is to prove if terrestrial high-resolution 3D laser scanning techniques can compensate saturation effects with spectrometry at higher levels of crop leaf area index; 3. To compare results from terrestrial hyperspectral spectrometry with space-borne multi-spectral imagery and to create hyper-spectral libraries, using an n-dimensional angle to match satellite image pixels to reference spectra, which is expected to improve the performance of space-borne spectrometry; 4. To develop identification and classification procedures for crop species and crop management intensity, which is a prerequisite for the generation of spatio-temporal explicit crop maps of the larger area of Bangalore; 5. To validate the models accuracy using independent data from on-farm experimental fields located on the transects of Bangalore; The development of models and their thorough validation, and the generation of data supporting the performance of space-borne remote sensing will allow C01 to create the methodological basis for a large-scale assessment of cropping systems. Thus, the outcomes of C01 are essential elements for the envisaged assessment of spatio-temporal dynamics of cropping systems along the rural-urban interface in Bangalore and the analysis within FOR2432.