基于遥感在土地利用与土地覆盖中的应用研究

介绍了遥感技术的发展以及土地利用与土地覆盖遥感信息的获取和应用,为我国土地保护和合理利用提供了新的技术支持。     

Applying Local Measures of Spatial Heterogeneity to Landsat-TM Images for Predicting Wildfire Occurrence in Mediterranean Landscapes

In mountainous Mediterranean regions, land abandonment processes in past decades are hypothesized to trigger secondary vegetal succession and homogenization, which in recent years has increased the size of burned areas. We conducted an analysis of temporal changes in landscape vegetal spatial pattern over a 15-year period (1984–1998) in a rural area of 672.3 km² in Eastern Spain to investigate the relationship between local landscape heterogeneity and wildfire occurrence. Heterogeneity was analyzed from textural metrics derived from non-classified remote sensing data at several periods, and was related to wildfire history in the study area. Several neural network models found significant relationships between local spatial pattern and future fire occurrence. In this study, sensitivity analysis of the texture variables suggested that fire occurrence, estimated as probability of burning in the near future, increased where local homogeneity was higher.     

应用MODIS-NDVI对草原植被变化监测研究--以锡林郭勒盟为例

利用新一代卫星遥感数据MODIS,进行草原植被专题信息的提取,同时结合地面调查数据,分析2002、2003年5月30日归一化植被指数(NDVI),并根据其分级图,对天然草原植被长势的时间和空间变化特征和变化规律进行研究,从而对引起草原植被发生变化的可能原因,特别是由于禁牧、休牧的影响进行分析评价.     

Monitoring forage production for farmers’ decision making

Objective management of grazing livestock production systems needs monitoring of forage production at the managerial unit level. Our objectives were to develop a system that routinely estimates forage above-ground net primary production (ANPP) at the spatial and temporal resolution required by farmers in the Pampas of Argentina, and to facilitate adoption of the system by end users as a managerial support tool. Our approach was based on the radiation use efficiency (RUE) logic, which proposes that ANPP is determined by the amount of photosynthetically active radiation absorbed by the canopy (APAR), and the efficiency with which that energy is transformed in above-ground dry matter (radiation use efficiency, RUE). APAR is the product of incoming photosynthetically active radiation (PAR) and the fraction absorbed by the canopy (fPAR). We estimated fPAR as a non-linear function of MODIS normalized difference vegetation index (NDVI). RUE was empirically estimated for the two principal forage resources of the region, yielding the following relations: ANPP = 0.6 × APAR + 12, (R² = 0.86; p < 0.001; n = 18) for the upland sown pastures, and ANPP = 0.27 × APAR + 26, (R² = 0.74; p < 0.001; n = 18) for the lowland naturalized pastures, with ANPP in g/m²/60 days and APAR in MJ/m²/60 days. The models were able to predict independent ANPP values with acceptable accuracy. Computational procedures were automated and run in a Relational Data Base Manager System that stored and managed all the information. The system is currently monitoring 212,794 ha in 83 farms and provides monthly ANPP values for the previous month and a history of the last 6 years. The data so generated show ANPP differences between the two major forage resources, considerable variability of a given month’s ANPP among years and paddocks, and contrasting among-farm differences in the efficiency of conversion of ANPP and forage supplements into beef production. The system was well accepted by end users who utilize it mainly for making near real time decisions according to last month ANPP, and explaining results of previous production cycles by incorporating ANPP as an explicative variable. However, there were differences among farmers in the degree of utilization, apparently related to the advisor’s attitude toward this new technology. Our results indicate that (1) forage production of large extensions can be monthly monitored at the paddock level by a small laboratory with capabilities in geographic information systems, and (2) advisors and farmers apply this information to their managerial decisions.     

Remote sensing of biotic and abiotic stress for irrigation management of cotton

The applicability of commercially available remote sensing instrumentation was evaluated for site-specific management of abiotic and biotic stress on cotton (Gossypium hirsutum L.) grown under a center pivot low energy precision application (LEPA) irrigation system. This study was conducted in a field where three irrigation regimes (100%, 75%, and 50% ET_c) were imposed on areas of Phymatotrichum (root rot) with the specific objectives to (1) examine commercial remote sensing instrumentation for locating areas showing biotic and abiotic stress symptomology in a cotton field, (2) compare data obtained from commercial aerial infrared photography to that collected by infrared transducers (IRTs) mounted on a center pivot, (3) evaluate canopy temperature changes between irrigation regimes and their relationship to lint yield with IRTs and/or IR photography, and (4) explore the use of deficit irrigation and the use of crop coefficients for irrigation scheduling. Pivot-mounted IRTs and an IR camera were able to differentiate water stress among irrigation regimes. The IR camera distinguished between biotic (root rot) and abiotic (drought) stress with the assistance of groundtruthing. The 50% ET_c regime had significantly higher canopy temperatures than the other two regimes, which was reflected in significantly lower lint yields when compared to the 75% and 100% ET_c regimes. Deficit irrigation down to 75% ET_c had no impact on lint yield, indicating that water savings were possible without reducing yield.     

An entropy approach to spatial disaggregation of agricultural production

While agricultural production statistics are reported on a geopolitical – often national – basis we often need to know the status of production or productivity within specific sub-regions, watersheds, or agroecological zones. Such re-aggregations are typically made using expert judgments or simple area-weighting rules. We describe a new, entropy-based approach to making spatially disaggregated assessments of the distribution of crop production. Using this approach, tabular crop production statistics are blended judiciously with an array of other secondary data to assess the production of specific crops within individual ‘pixels’ – typically 25–100 square kilometers in size. The information utilized includes crop production statistics, farming system characteristics, satellite-derived land cover data, biophysical crop suitability assessments, and population density. An application is presented in which Brazilian state level production statistics are used to generate pixel level crop production data for eight crops. To validate the spatial allocation we aggregated the pixel estimates to obtain synthetic estimates of municipality level production in Brazil, and compared those estimates with actual municipality statistics. The approach produced extremely promising results. We then examined the robustness of these results compared to short-cut approaches to allocating crop production statistics and showed that, while computationally intensive, the cross-entropy method does provide more reliable estimates of crop production patterns.     

灌区计算机监控系统与灌溉优化调度模型集成应用研究

大型灌区实施计算机监控是提高灌区管理水平的重要手段,灌区轮灌分组优化模型旨在求解干渠各出水口运行时调度的最优组合方案,而灌溉优化调度方案在实施过程中往往仍然采用的是计算机远程人工调度.为此研究了一种灌区轮灌分组优化模型,并得出了灌溉优化调度方案,同时采用OPC（即OLE for Process Control）技术,使灌溉优化调度方案数据与计算机控制系统有效地结合起来,提高了灌区灌溉管理自动化水平。     

基于可变移动窗口方法估算太湖泥沙环流运动的本征尺度

基于遥感反演获得的太湖悬浮泥沙浓度数据,利用移动窗口方法,分析探讨了平均局部方差和移动窗口尺寸的关系。在90～1 860 m移动窗口尺寸变化范围内,太湖悬浮泥沙浓度的平均局部方差随着移动窗口尺寸的增大而增大,且抛物线模型能较好的描述2者的关系,回归系数0.9959。通过对抛物线模型求最大值可知,局部方差最大值所对应的移动窗口尺寸为2 308.33 m,根据当时的风速和风向,考虑泥沙浓度空间分布与水体运动之间的相关性,该尺寸可以解释为太湖逆时针环流的本征尺度。     

冬小麦播期遥感监测研究现状与展望

播期是影响小麦产量与品质的一个重要因素,冬小麦生产管理对播期的及时和准确监测有强烈需求。遥感数据源的日趋丰富及遥感定量化水平的日益提高,为大面积、低成本监测小麦播期提供了可能。本文对冬小麦播期遥感监测的研究进展进行了回顾,系统归纳了当前国内外播期遥感监测方法,分析了目前冬小麦播期遥感监测中存在的问题。推进高时空分辨率遥感数据的使用、强化多尺度传感器遥感数据融合算法的应用、开展冬小麦生长前期不同播期光谱数据的挖掘、探索冬小麦生长前期光谱与上茬作物时序遥感数据的综合及尝试遥感数据与作物模型同化方法的借鉴是冬小麦播期遥感监测的未来发展方向。