Spectral sensitivity of ALOS,ASTER, IKONOS,LANDSAT and SPOT satellite imagery intended for the detection of archaeological crop marks

This study compares the spectral sensitivity of remotely sensed satellite images, used for the detection of archaeological remains. This comparison was based on the relative spectral response (RSR) Filters of each sensor. Spectral signatures profiles were obtained using the GER-1500 field spectroradiometer under clear sky conditions for eight different targets. These field spectral signature curves were simulated to ALOS, ASTER, IKONOS, Landsat 7-ETM+, Landsat 4-TM, Landsat 5-TM and SPOT 5. Red and near infrared (NIR) bandwidth reflectance were re-calculated to each one of these sensors using appropriate RSR Filters. Moreover, the normalised difference vegetation index (NDVI) and simple ratio (SR) vegetation profiles were analysed in order to evaluate their sensitivity to sensors spectral filters. The results have shown that IKONOS RSR filters can better distinguish buried archaeological remains as a result of difference in healthy and stress vegetation (approximately 1–8% difference in reflectance of the red and NIR band and nearly 0.07 to the NDVI profile). In comparison, all the other sensors showed similar results and sensitivities. This difference of IKONOS sensor might be a result of its spectral characteristics (bandwidths and RSR filters) since they are different from the rest of sensors compared in this study.     

基于农作物食用安全的土壤重金属风险阈值

采用单项超标指数法对德兴铜矿区土壤和农作物重金属含量进行评价,发现土壤中与农作物中的重金属超标不一致,尤其是Pb、Cd在土壤中不超标或超标很少,但在农作物中超标极其严重。为了解决土壤超标与农作物超标不匹配问题,依据国家食品卫生标准,提出基于农作物安全的土壤重金属风险阈值方法,给出德兴地区农田土壤重金属超标风险阈值。该方法解决了国家标准评价时出现的超标界限偏差和考虑土壤使用情况单一的问题。很好地为德兴铜矿地区水稻和小白菜种植地点的选择和超标土壤的治理提供科学依据,更加灵活地应用于农业生产过程中。     

Influences of international agricultural trade on the global phosphorus cycle and its associated issues

Industrial phosphorus (P) fertilizer has substantially improved global food production, but has also led to environmental impacts. Intensive global agricultural trade has increased and the impacts of trade on aggravating or alleviating future P scarcity must be examined, especially for the most vulnerable countries. We combined data to estimate the global P trade among countries and its impacts on global P flows, based on global agricultural trade, cropland soil P budgets and crop P fertilizer footprints (the amount of industrial P fertilizer applied for producing one unit of P in the harvested crop). The global agricultural P trade represented a fraction of 16% of P in harvested crops in 2014, half of which was exported from the United States of America, Brazil and the European Union and one fifth imported by China. Virtual P fertilizer flows (about 2.60 Tg P y^-1) referred to industrial P fertilizers applied to traded crops by exporting countries; thus, 1/3 of global virtual P fertilizer flows were associated with the international soybean trade. P use efficiency (PUE), the ratio of the harvested crop-P to the total external P inputs, is a larger problem for tropical than temperate countries. Global crop trade had brought in a net 0.2 Tg P y^-1 savings of industrial P fertilizers globally, compared to crop production in export and import countries. >0.50 Tg y^-1 of the gross global accumulation of soil P and P in freshwater were associated with global agricultural trade. Global PUE, however, could be improved considerably, and thus global cooperation and improving PUE could help to solve the problem of future P scarcity. Vulnerable countries should also propose urgent national plans to address their own situations of P scarcity or low PUE.     

棉花和大豆等效散射反照率估算

本文以棉花和大豆为例,基于车载多频率微波辐射计的观测数据,利用最小二乘原理实现对两种典型农作物等效散射反照率的估算,研究了植被层等效散射反照率随观测角度、频率以及植被浓密程度的变化规律,对不同覆盖度情况下植被层的等效散射反照率进行了定性的分析。这一研究结果在以零阶模型为基础进行地表参数反演时,对于植被层等效散射反照率的确定具有重要的理论参考价值。     

Water‐Saving Crop Planning Using Multiple Objective Chaos Particle Swarm Optimization for Sustainable Agricultural and Soil Resources Development

Establishing a water‐saving planting structure is necessary for the arid, water‐deficient regions of northern China and of the world. Optimizing and adjusting a water‐saving agricultural planting structure is a typical semi‐structured, multi‐level, multi‐objective group decision‐making problem. Therefore, optimization can be best achieved with a swarm intelligence algorithm. We build an optimization model for a water‐saving planting structure with four target functions: (1) maximum total net output, (2) total grain yield, (3) ecological benefits, and (4) water productivity. The decision variable is the yearly seeded area of different crops, and its restrictions are the farmland area, the agricultural water resources, and the needs of the people and other farming‐related industries. Multiple objective particle swarm optimization (MOPSO) is an efficient optimization method, but its main shortcoming is that it can easily fall into a local optimum. Multiple objective chaos particle swarm optimization (MOCPSO) will greatly improve the searching performance of the algorithm by placing chaos technology with the advantages of ergodicity into MOPSO. When MOCPSO is used to solve the multi‐objective optimization model in the middle portion of the Heihe River basin, the results show that MOCPSO has the advantages of a high convergence speed and a tendency not to fall easily into a local optimum. After adopting a water‐saving agricultural planting structure, irrigation water would be reduced by about 7%, which would provide tangible economic, social, and ecological benefits for sustainable agricultural development.     

西北地区特色作物对气候变化响应及应对技术的研究进展

总结了白兰瓜、 大樱桃、 酿酒葡萄、 苹果、 桃、 当归、 党参、 黄芪、 甘草、 枸杞等10种特色作物的生长发育、 种植区域、 气象灾害、 生物量、 产量与品质等对现代气候暖干化的响应特征. 结果表明: 气候暖干化使多年生特色作物萌芽或返青提早, 生长发育速度提前加快; 瓜果类作物全生育期缩短, 根类作物全生育期延长; 使种植区的高度提高150 m左右, 向更高纬度扩展, 种植面积迅速扩大. 对旱作农业区的特色作物气候产量下降, 对灌溉农业区的影响较少, 有利于喜温凉特色作物气候产量增加, 对较耐旱的影响较轻, 对不够耐旱受到较大的影响.有利于提高瓜果类作物的品质, 尤其含糖量提高. 提出了建立特色作物种植基地或示范区, 实现农工商产业系列服务, 创建现代农业发展模式和管理新模式适应气候变化; 制定精细化综合农业自然资源区划, 合理调整种植结构; 根据未来气候预测和不同气候年型调整作物种植比例; 加强气象灾害监测、 评估、 预警与防御工作等4个方面的措施应对气候暖干化.     

作物水生产力评估方法研究

农业用水作为消耗水资源最多的部分, 在全球和区域水资源消耗中占据很大比例. 农业水生产力的评价对于改进区域农业水资源利用方式, 促进农业经济发展具有重要意义, 尤其是在水资源匮乏地区. 首先阐述了作物水生产力的基本概念, 分析了影响作物水生产力的核心要素; 其次总结了作物水生产力的评价方法, 将其分为收获方法、 模型方法和集成遥感或GIS的模型方法, 并分析了这三类方法优缺点; 最后对作物水生产力研究发展趋势进行了展望, 认为将RS或GIS与模型结合用来估算作物水生产力的方法, 将是目前研究的发展方向.     

A methodology for estimating Leaf Area Index by assimilating remote sensing data into crop model based on temporal and spatial knowledge

In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.     

Hargreaves公式在塔克拉玛干沙漠腹地的适用性

对运用Hargreaves公式计算参考作物蒸散量(ET0)在干旱区的适用性存在不同观点。为了求证Hargreaves公式在极端干旱区塔克拉玛干沙漠腹地的适用性,利用2005-2010年塔克拉玛干沙漠研究站的气象资料,以利用Penman-Monteith公式计算的结果为标准,对利用Hargreaves公式计算的ET0进行了对比分析,并对两种计算结果差异的成因进行了阐释。结果表明:在年时间尺度上,利用Hargreaves公式计算的结果略大于利用Penman-Monteith公式计算的结果,标准差介于32.86~35.00 mm,年参考作物蒸散量计算结果呈现弱变异程度;在月时间尺度上,用两种方法计算的参考作物蒸散量呈现中等变异程度,蒸散量绝对偏差介于-3.26~8.73 mm,相对偏差介于-12.20%~29.02%,除了10月与11月,其余月份相对偏差均保持在10%之内。用两种方法计算的10月与11月份ET0产生差异的最主要原因在于有较高的温度较差。最后,经过对年、月参考作物蒸散量进行t-检验及建立回归方程,表明Hargreaves公式适用于极端干旱的塔克拉玛干沙漠腹地。     

土壤—大宗农产品中Cd的分配及其环境意义

基于多目标地球化学调查成果,以土地生态效应为重点,研究成都经济区大宗农产品——水稻、玉米、小麦籽实中Cd元素的含量,同时讨论了农产品籽实与土壤中Cd含量的关系。结果表明大宗农产品籽实中Cd元素的累积状况为小麦>水稻>玉米;土壤酸碱度(pH值)环境对土壤中Cd元素的转移和在农作物籽实中积累影响较大,酸性土壤中Cd元素更容易进入植物体并积累下来,从而形成环境生态危害。