Optimising three-band spectral indices to assess aerial N concentration,N uptake and aboveground biomass of winter wheat remotely in China and Germany

Remotely and accurately quantifying the canopy nitrogen status in crops is essential for regional studies of N budgets and N balances. In this study, we optimised three-band spectral algorithms to estimate the N status of winter wheat. This study extends previous work to optimise the band combinations further and identifies the optimised central bands and suitable bandwidths of the three-band nitrogen planar domain index (NPDI) for estimating the aerial N uptake, N concentration and aboveground biomass. Analysis of the influence of bandwidth change on the accuracy of estimating the canopy N status and aboveground biomass indicated that the suitable bandwidths for optimised central bands were 37 nm at 846 nm, 13 nm at 738 nm and 57 nm at 560 nm for assessing the aerial N uptake and were 37 nm at 958 nm, 21 nm at 696 nm and 73 nm at 578 nm for the assessment of the aerial N concentration and were 49 nm at 806 nm, 17 nm at 738 nm and 57 nm at 560 nm for the estimation of aboveground biomass. The optimised three-band NPDI could consistently and stably estimate the aerial N uptake and aboveground biomass of winter wheat in the vegetative stage and the aerial N concentration in the reproductive stage compared to the fixed band combinations. With suitable bandwidths, the broadband NPDI demonstrated excellent performance in estimating the aerial N concentration, N uptake and biomass. We conclude that the band-optimised algorithm represents a promising tool to measure the improved performance of the NPDI in estimating the aerial N uptake and biomass in the vegetative stage and the aerial N concentration in the reproductive stage, which will be useful for designing improved nitrogen diagnosis systems and for enhancing the applications of ground- and satellite-based sensors.     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

Detecting tents to estimate the displaced populations for post-disaster relief using high resolution satellite imagery

Estimating the number of refugees and internally displaced persons is important for planning and managing an efficient relief operation following disasters and conflicts. Accurate estimates of refugee numbers can be inferred from the number of tents. Extracting tents from high-resolution satellite imagery has recently been suggested. However, it is still a significant challenge to extract tents automatically and reliably from remote sensing imagery. This paper describes a novel automated method, which is based on mathematical morphology, to generate a camp map to estimate the refugee numbers by counting tents on the camp map. The method is especially useful in detecting objects with a clear shape, size, and significant spectral contrast with their surroundings. Results for two study sites with different satellite sensors and different spatial resolutions demonstrate that the method achieves good performance in detecting tents. The overall accuracy can be up to 81% in this study. Further improvements should be possible if over-identified isolated single pixel objects can be filtered. The performance of the method is impacted by spectral characteristics of satellite sensors and image scenes, such as the extent of area of interest and the spatial arrangement of tents. It is expected that the image scene would have a much higher influence on the performance of the method than the sensor characteristics.     

杭州湾南北两岸岸线变迁遥感动态调查

以多时相遥感资料为基础,利用遥感数据的时间和空间特点,对杭州湾南北两岸的岸线进行了遥感调查,查明了岸线变迁规律及影响因素,为杭州湾合理开发、管理和保护提供了依据。     

大比例尺卫片在土地利用动态变化监测中的应用——以黑龙江省阿城监测区为例

以黑龙江省阿城市为监测试验区,采用1:5万的TM假彩色合成图像,对该市土地利用现状进行解译调查,并与历史资料比较,对该市土地利用动态变化情况进行监测,同时对这种方法的可行性和该市地类变化情况以及监测结果进行了分析。     

地球空间信息技术在新一轮国土资源大调查中的应用探讨

从分析全球变化和社会可持续发展研究的要求出发,提出地球空间信息技术的形成背景和应用基础。针对新一轮国土资源大调查的性质和任务,探讨了地球空间信息技术在新一轮国土资源大调查中的应用。     

浙江省海宁市TM图像土地利用自动分类精度评价方法的试验研究

按照国家土管局土地利用现状分类标准,利用叠合的海宁市长安镇１∶１万同时期土地详查电子地图的全域地面实况数据,在遥感图像处理常规分类方法的范畴内,采取最大程度利于提高分类精度的措施,所得的分类精度上限为６５％。研究表明,通常在试验区的小块局部中选择训练样本和选择评价分类精度的参考像元,对精度评价有显著影响,参考像元质量和数量的限制很可能是这些年来一些同类研究报道了较高分类精度结果的主要原因     

全国土地动态监测系统总体研究——全国耕、林、草地总量和土地动态监测分析决策支持系统

讨论了全国土地动态监测系统的目标、任务和可行性,提出了系统总体设计思路和土地利用分类编码标准。     

环境遥感的未来十年——祝贺中国地理学会环境遥感分会成立10周年

过去十年,随着卫星航空信息日渐丰富,作为国家重点攻关项目的遥感技术不断开拓了应用的新领域,初步形成了一个新的高科技信息服务行业。“八五”期间,遥感又列为重点项目,预期气象卫星信息的开发与应用,将会再次出现高潮。在资源卫星群星灿烂,航空遥感持续发展的形势下,需要充分利用现有设备潜力和所取得的技术进步,集中力量,研制大容量存储,实时传输和快速处理功能的智能化技术系统。这样才能适应防灾,估产为主要目标,并兼顾开放城市及全球研究的需求。     

Single frequency processing of Ørsted GPS radio occultation measurements

The Global Positioning System (GPS) radio occultation measurements obtained using the TurboRogue GPS receiver on the Danish satellite Ørsted have been processed using the single frequency method. Atmospheric profiles of refractivity and temperature are derived and validated against numerical weather prediction data from the European Centre for Medium-Range Weather Forecast (ECMWF). Results from the Ørsted GPS measurement campaign in February 2000 indicate that the single frequency method can provide retrievals with accuracy comparable to that of using two frequencies. From comparisons between measured dry temperature profiles and corresponding dry temperature profiles derived from ECMWF analysis fields, we find a mean difference of less than 0.5 K and a standard deviation of 2–4 K between 500 and 30 hPa in height. Above 30 hPa the impact of the ionosphere becomes more dominant and more difficult to eliminate using the single frequency method, and the results show degraded accuracy when compared to previous analysis results of occultation data from other missions using the dual frequency method. At latitudes less than 40° (denoted low latitudes), the standard deviation is generally smaller than at latitudes higher than 40° (denoted high latitudes). A small temperature bias is observed centered at 200 hPa for low latitudes and at 300 hPa for high latitudes. This indicates that the ECMWF analyses do not adequately resolve the tropopause temperature minimum. In the lowest part of the troposphere an observed warm bias is thought to be due to erroneous tracking of the GPS signal in cases of atmospheric multipath propagation.