According to FAO, cropping pattern is defined as the spatial representation of crop rotations, which embodies the spatial arrangement of crops and the yearly crop sequences. Cropping pattern plays an important role for effective and controllable agricultural management. Generally speaking, rational cropping pattern decides to a certain extent whether the planter can take beat advantage of the physical constraints of soil, climate and availability of irrigation to supplement rainfall and in part a response to market opportunities. Remote sensing data with its synoptic and frequently repeated coverage provides the undoubtedly best way to obtain this information and even the case especially with the development of spaceborne high-quality imaging spectrometers such as MODIS. However, studies have been restricted to crop phenology detection or extraction of multiple cropping index based on the multi-temporal high resolution images such as TM or coarse resolution satellite derived vegetation index time series. Few studies on remote sensing cropping system can be found in the literature. The objective of this dissertation is to make an attempt to extract cropping system information from temporal profile of optimized spectral index time-series (or temporal profile).
This dissertation begins with the study on key issues related to atmospheric correction based on image itself, spectral index development to characterize the crop growth and the denoising and normalization of the temporal profile of the spectral index. On this basis, the yearly 16-day composite MODIS Enhanced Vegetation Index (EVI) time series covering North China Plain are collected. Noise-reducing and phonological feature extraction are performed on this data. A brief but reasonable decision tree based on less features is built so that one accurate agriculture-oriented land cover map is gained with an overall accuracy of 75.5％. Winter wheat and maize is extracted by the optimized features from the spectral index profile, and the typical cropping pattern map is gained.
The main conclusions are drawn as follows:
1. The model-based atmospheric correction code ACORN is quite demanding for spectral and radiometric calibration performance of hyperspectral instrument. The new spaceborne imaging spectrometer CHRIS can’t meet the requirements of ACORN at least for bands beyond 750nm.
2. An atmospheric correction flow is designed for MODIS, the key atmospheric parameters could be inverted pixel by pixel. The corrected MODIS reflectance spectrum has good consistence in shape with the in-situ measured spectrum.
3. Three algorithms are utilized to develop nitrogen-sensible spectral index based on the rebuilt airborne hyperspectral image spectra and nitrogen mapping is carried out. The nitrogen map estimated by NDVI(dr745, dr699.2) as indicator is quite consistent with the value range of the ground truth data.
4. The sensibility analysis of the popular chlorophyll spectral indices is made by the canopy radiative transfer model PROSAIL simulation. An improvement is made on the integrated spectral index TCARI/OSAVI. Validation shows that the improved integrated index is sensitive to chlorophyll for crop and forest whether at foliar scale or canopy scale. Chlorophyll maps are gained successfully for two temporal CHRIS images.
5. Choosing biomass and leaf area index (LAI) as the best indicators of crop growth, the optimal NDVI-type spectral index of MODIS is explored by simulating the MODIS bands by long term ground measured wheat spectra. It turns out, NDSI(b19,b2）, NDSI（b19,b16）and NDSI(b19,b17）all have much stronger correlations with both biomass and LAI than the two MODIS vegetation indices, while MODIS_EVI is more sensible indeed to growth indicators than MODIS_NDVI.
6. The harmonic analysis algorithm for time series (HANTS) not only can reduce the noise effects in the MODIS EVI image cube, but also can reveal the periodical characteristics implied in the temporal EVI profile. The phenological stages determined by HANTS-processed EVI profiles agree with regular observations.
7. Based on temporal analysis of MODIS_EVI profile, five phenological features are extracted to measure the calendar difference, in combination with land surface temperature to measure interaction difference of surface-atmosphere, and slope to characterize the spatial variability of land cover classes, a brief but reasonable decision tree is built to make an accurate agriculture-oriented land cover map with an overall accuracy of 75.5% , obviously higher than that of NASA USGS product. Most of all, when compared with the cropland area from official statistics, our classification shows much higher consistence with an overall mean square root error of 34.0507 kilo-hektare versus 66.1205 kilo-hectare by USGS product.
Phenological features of winter wheat and its succession maize are extracted and analyzed. Re-green stage and peak stage(heading stage) are of great importance for winter wheat extraction, while peak stage (silking stage) and the skew parameter which characterizes the accumulated biomass difference before and after silking stage are most important for maize extraction. The overall accuracy of wheat mapping is 88.38% when compared with official statistics in county unit. The cropping system map of wheat-maize, wheat-rice, and wheat-other crop is quite consistent with the rotation feasible map regarding on climate distribution. The error is caused mostly by the coarse resolution of MODIS and the great spatial variability in regional scale.
Target detection and classification is one of primary tasks of hyperspectral imaging. In terms of the method of spectral expression, the style of unsupervised cluster, probability in the data, the geometrical construction of hyperspectral imaging in the band space and the it’s continuity in the image space, the dissertation draws some conclusion on feature extraction, unsupervised classification, endmember selection,
linear unmixing, target detection and anomaly detection as follows:
1. A method for spectral feature extraction was developed based on spectral recomposition. By arranging the spectra by the sort of their reflectance or DN, the spectral curves that are originally difficult to be extracted features from will usually produce some obvious features. It is helpful to feature extraction and father analysis and process.
2. The concept of spatial continuity was proposed and successfully applied to image classification, spectral optimization, redundancy reduction and real-time endmember determination.
3. A unsupervised classification method was proposed based on universal gravitation. Each pixel that was taken as a star in the universe would move with the gravitation of all the other pixels. The last formed galaxy is corresponding to the result of classification.
4. Two approaches of autonomous spectral endmember determination were developed. Based on the convex nature of hyperspectral data in its characteristic space, Gram–Schmidt Orthonormalization process, high dimensional analytic geometry and distance between pixels were introduce to find a unique set of purest pixels in an image; A new volume formula of simplex which was independent of dimension of the data was introduced to find all the endmembers which are larger than any other volume formed from any other combination of pixels. The concept of endmember constrution function was first proposed, so the weightiness of each endmember is depended on it’s influence to the simplex contruction, but not it’s information magnitude. It’s significant to the small target extraction.
5. A method of target extraction based on endmember projection vector was developed. Based on the convex nature of hyperspectral data in its band space, a series of vectors named endmember projection vector are produced for use of object extraction. The technique is based on the fact that in band space, any endmember is the farthest point from the hyperplane consisted of all the other endmembers.
6. A new theorem about the nature of simplex was proposed and applied to spectral linear unmixing. Once all the endmembers were found, the image cube can be "unmixed" into fractional abundances of each material in each pixel by a simple ratio of volume.
7. The idea of weighted sample correlation(covariance) matrix was proposed and applied to the small target detection and anomalous target detection. The general target detection algorithm with low probability was based on the abundance of image information. The method of target detection based on weighted sample correlation(covariance) matrix not only can reduce false alarm rate to small target , but can extract target with high probability.
8. A small and anomalous target detection method with low probability which can effectively suppress background and other small target was developed. because of not taking into account the influence of other small target and abnormity, the general small target detectors have high false alarm rate. The method developed in this dissertation perform effectively in extracting small target and abnormity with low false alarm rate.
9. A method of abnormal detection based on distance of pixels in the whiten image was developed. RX detector can’t find the abnormity which was in major components in the original image. After image was whiten, it’s simplex construction in the band space gradually transforms to “sphere”, the abnormal pixels lie outside the sphere, so we can find them by distances to the center of a sphere.
Satellite on-orbit test is a useful way to monitor satellite platform, on-orbit status and attenuation degree of sensors, and is the premise and base for satellite data’s processing and application. The article studies the contents and methods of small satellite on-orbit test from systems engineering in our country, which is used to direct our DMC（Disaster Monitoring Constellation）small satellite on-orbit test, and also as a reference for other similar satellite in our country.
The satellite studied in the article participates in international satellite constellation network. Compared with other satellites of our country, this satellite has its own characteristics and operation manner. The satellite is developed and launched by SSTL（Surrey Satellite Technology Limited，Surrey Space Centre University），which is handed over to China when on-orbit test period. The on-orbit test not only evaluates satellite platform, on-orbit status and attenuation degree of sensors, which provides the necessary parameters for satellite data’s processing and applications, but also the technical base for our checking and accepting the small satellite. So this requires the systematization, standardization, and internationalization of the DMC small satellite on-orbit test in our country. At same time, this job is also a part of Demonstration Center for Spaceborne Remote Sensing, CNSA, which is helpful to establish the system of our spaceborne remote sensing demonstration.
Based on above points, the article aims to establish the system of the contents and methods of our DMC small satellite on-orbit test, and also as a reference for other similar satellite in our country. We think that the DMC small satellite on-orbit test includes four aspects: geometic characteristics of sensor’s image, radiomatic characteristics of image, spectral characteristics of image, image general quality and its application potential.The evaluation of s geometric characteristics of its image includes: satellite pose, evaluation and adjustment of orbit parameters, directing precision of camera and its wavering performance, interior and exterior geometry precision of image, band matching, image resolution, and so on. The evaluation of radiomatic characteristics includes: MTF, SNR, relative radiometric calibration, absolute calibration, radiometric stability, dynamic range, the linearity of spectral response, and uniformity of CCD etc,. Because of few bands and low spectral resolution of our DMC small satellite, we only analyze band setting of sensors and change of spectral responding function qualitatively when evaluating the spectral performance of image. In addition, the article brings forward technical guideline for evaluating general image quality from data application, and analyzes application potential of our DMC small satellite image data.
The most contribution of the article is to establish the contents and method system of our DMC small satellite on-orbit test based on the characteristics and performance parameter design of our DMC small satellite, and summary of foreign similar satellite on-orbit test. It is the first system in our country that is applicable to push-broom, earth observing satellite, and has great directive significance for similar satellite on-orbit test. Furthermore, the article makes deep research in test methods, and advances some creative test methods, mainly including: a highly precise matching algorithm to test errors of bands matching; a method to calculate relative radiometric calibration.The aim of the article is to establish the system of the contents and methods of our DMC small satellite on-orbit, not an innovation of evaluation methods. Because our DMC small satellite is planned to be launched in May, 2005, it is impossible to get necessary test data. So the article is focused on experiment and analysis of some content and method of evaluation. However, the article summarizes the necessary data and documents in our DMC small satellite on-orbit, and advances the whole scheme and implementing method, which is meaningful to actual satellite on-orbit test.