Small farm ponds: overlooked features with important impacts on watershed sediment transport

Despite their size, small farm ponds are important features in many landscapes. Yet hydrographical databases often fail to capture these ponds, and their impacts on watershed processes remain unclear. For a 230‐km² portion of central Texas, United States (U.S.), we created a historical inventory of ponds and quantified the accuracy of automated detection methods under varying drought conditions. In addition, we documented pond dredging/enlargement events and identified sites that had been abandoned. We also analyzed sediment cores from downstream reservoirs to track changes in watershed sediment transport. Over 75 years, pond densities increased more than 350% — to among the highest documented in the U.S. — and the ability of automated methods to detect these ponds was highly dependent on drought severity (R² = 0.96). Approximately 5% of ponds present in the 1950s were no longer present in 2012, while 33% were dredged between 1937 and 2012. Downstream reservoir sedimentation has decreased by an average of 55% as ponds have increased in number. These findings suggest that small ponds and the maintenance of trapping efficiency have large‐scale impacts on sediment dynamics. Accurately accounting for these storage effects is vital to water resource planning efforts.     

基于DEM的SAR图像洪水水体的提取

星载雷达遥感已广泛应用于洪水灾害的监测和评估中。但是由于其阴影与水体严重混淆 ,使得从雷达图像中提取洪水水体较为困难。为此 ,本文探讨了在地形数据的支持下 ,实现星载SAR图像洪水水体半自动提取的方法。主要包括以下几步 :首先 ,对雷达图像进行滤波处理 ,并将其与地形数据匹配 ,从雷达图像中提取出初步的洪水水体范围 ;其次 ,利用地形数据生成DEM ,并根据雷达图像的成像参数和DEM生成相应的模拟雷达图像 ;最后 ,利用模拟雷达图像上的阴影 ,剔除被误提为洪水水体的阴影 ,从而实现洪水水体的准确提取。研究表明 ,该方法能有效地、半自动地将星载雷达图像上的洪水水体提取出来 ;同时 ,该方法可以用于多种星载多模式的雷达图像的洪水水体的识别提取 ,尤其对含山区的大范围洪水水体的半自动提取 ,更为适用。     

Mapping Invasive Aquatic Vegetation in the Sacramento-San Joaquin Delta using Hyperspectral Imagery

The ecological and economic impacts associated with invasive species are of critical concern to land managers. The ability to map the extent and severity of invasions would be a valuable contribution to management decisions relating to control and monitoring efforts. We investigated the use of hyperspectral imagery for mapping invasive aquatic plant species in the Sacramento-San Joaquin Delta in the Central Valley of California, at two spatial scales. Sixty-four flightlines of HyMap hyperspectral imagery were acquired over the study region covering an area of 2,139 km² and field work was conducted to acquire GPS locations of target invasive species. We used spectral mixture analysis to classify two target invasive species; Brazilian waterweed (Egeria densa), a submerged invasive, and water hyacinth (Eichhornia crassipes), a floating emergent invasive. At the relatively fine spatial scale for five sites within the Delta (average size 51 ha) average classification accuracies were 93% for Brazilian waterweed and 73% for water hyacinth. However, at the coarser, Delta-wide scale (177,000 ha) these accuracy results were 29% for Brazilian waterweed and 65% for water hyacinth. The difference in accuracy is likely accounted for by the broad range in water turbidity and tide heights encountered across the Delta. These findings illustrate that hyperspectral imagery is a promising tool for discriminating target invasive species within the Sacramento-San Joaquin Delta waterways although more work is needed to develop classification tools that function under changing environmental conditions.     

基于环境一号卫星的自然保护区生态系统健康评价

以生态系统健康及压力－状态响应模型作为研究方法,设计了一套基于环境一号卫星CCD数据的自然保护区生态系统健康评价评价方法、指标体系和技术流程.同时选择向海湿地自然保护区为示范区,以环境一号卫星CCD影像为数据源, 对指标, 对其生态系统健康现状进行了评价.结果表明,向海湿地自然保护区生态系统相对不健康、中等健康、较健康和相对健康的区域面积分别占整个自然保护区总面积的46.49%、18.02%、21.18%、14.31%,整个自然保护区生态系统健康水平一般,人类干扰严重,组织结构不太合理.向海湿地自然保护区生态系统健康水平一般的主要原因是人类活动日益增强和年降水量明显减少.     

Effects of Coffee Management on Deforestation Rates and Forest Integrity

Knowledge about how forest margins are utilized can be crucial for a general understanding of changes in forest cover, forest structure, and biodiversity across landscapes. We studied forest‐agriculture transitions in southwestern Ethiopia and hypothesized that the presence of coffee (Coffea arabica)decreases deforestation rates because of coffee's importance to local economies and its widespread occurrence in forests and forest margins. Using satellite images and elevation data, we compared changes in forest cover over 37 years (1973–2010) across elevations in 2 forest‐agriculture mosaic landscapes (1100 km² around Bonga and 3000 km² in Goma‐Gera). In the field in the Bonga area, we determined coffee cover and forest structure in 40 forest margins that differed in time since deforestation. Both the absolute and relative deforestation rates were lower at coffee‐growing elevations compared with at higher elevations (?10/20% vs. ?40/50% comparing relative rates at 1800 m asl and 2300–2500 m asl, respectively). Within the coffee‐growing elevation, the proportion of sites with high coffee cover (>20%) was significantly higher in stable margins (42% of sites that had been in the same location for the entire period) than in recently changed margins (0% of sites where expansion of annual crops had changed the margin). Disturbance level and forest structure did not differ between sites with 30% or 3% coffee. However, a growing body of literature on gradients of coffee management in Ethiopia reports coffee's negative effects on abundances of forest‐specialist species. Even if the presence of coffee slows down the conversion of forest to annual‐crop agriculture, there is a risk that an intensification of coffee management will still threaten forest biodiversity, including the genetic diversity of wild coffee. Conservation policy for Ethiopian forests thus needs to develop strategies that acknowledge that forests without coffee production may have higher deforestation risks than forests with coffee production and that forests with coffee production often have lower biodiversity value. Efectos de la Administración Cafetalera sobre las Tasas de Deforestación y la Integridad de los Bosques     

基于TM影像的兰州市热岛效应及预测分析

近些年来随着城市建设的高速发展,热岛效应越来越被人们所重视。采用2007年的TM遥感影像,分析了兰州市热岛效应热场强度的分布规律,并应用灰色模型对其未来发展趋势进行了预测。研究发现：兰州市热岛效应明显且稳定存在,热岛中心主要分布在城关区、七里河区人口密度大以及西固区工业聚集的地方;植被和水体有减弱热岛效应的作用。灰色关联度分析表明：人为因素对兰州城市热岛强度效应的影响相对突出;其次,在气象因子中,风速对城市热岛效应的形成和加重也起到重要的作用。灰色预测结果表明：兰州市热岛强度将会持续波动上升,2012年将达到3.826℃。     

利用RADARSAT SWA SAR和LANDSAT TM的互补信息确定洪水水体范围

从RADARSAT SAR图像中自动提取洪水水体,一直是一个急需解决而又未能得到解决的问题。主要困难是由于阴影与水体严重相混淆。为此,本文研究发现,通过RADARSAT SWA SAR图像和LANDSAT TM图像上的互补信息,利用RADARSAT SWA SAR图像和LANDSAT TM图像上的水体和阴影进行复合处理,可以从RADARSAT SWA SAR图像上准确、半自动提取洪水水体范围。研究结果表明,该方法不仅适用于平地洪水水体范围的半自动提取,而且更适用于包含山区的大范围洪水水体的半自动提取。     

Landsat5 TM遥感影像上太湖蓝藻水华反射光谱特征研究

利用ENVI遥感软件的FLAASH工具对2005年10月17日大规模蓝藻水华暴发的太湖Landsat5 TM影像进行大气校正处理,反演获得蓝藻水华和其他地物类型的遥感反射率图像,提取了不同集聚程度蓝藻水华的可见波段至近红外波段反射率数据,并与陆生植被、无蓝藻水面等地物的光谱反射率进行了比较。研究表明,与陆生植被、无蓝藻水面相比,蓝藻水华在TM2波段和TM4波段具有更高的反射率,在可见光波段整体反射率略高于陆生植被,在TM5、TM7波段则受水的影响反射率很低。从蓝藻水华、陆生植被的细胞生理结构、生长环境、复杂的遥感反射、散射及透射模型方面初步讨论了光谱差异的原因。     

天津市热环境时空演变及影响因素分析

随着城市化进程加快,城市热环境发生显著变化,对人类活动造成很大影响。为探究天津市城市热环境时空变化及其影响因素,基于2005—2020年四期Landsat遥感数据,利用辐射传输方程法反演地表温度,计算城市热岛比例指数,用标准差椭圆法分析城市热环境发展和布局,利用地表温度并结合土地利用分类研究城市地物覆盖类型与地表温度的响应关系,并采用地理探测器探究高程、绿地、建筑用地和水体对地表温度变化的影响差异。结果表明：天津市热岛足迹沿主干道由市内六区向环城四区发展,天津城市热环境呈现先增高后降低的趋势;由标准差椭圆分析可知,城市热岛呈现发展主轴维持在东北—西南方向,整体空间格局呈现放射状分布;天津市中心城区建筑用地面积占比逐年增加,水体面积占比逐年降低,各类型地物平均温度排序为：建筑用地＞绿地＞水体;地理探测器分析表明：NDBI和NDVI是影响地表温度变化的主要因子,NDVI和MNDWI对LST交互作用最强,是城市热环境驱动作用最强的因子组合。     

Measuring Plant Cover in Sagebrush Steppe Rangelands: A Comparison of Methods

Methods that are more cost-effective and objective are needed to detect important vegetation change within acceptable error rates. The objective of this research was to compare visual estimation to three new methods for determining vegetation cover in the sagebrush steppe. Fourteen management units at the US Sheep Experiment Station were identified for study. In each unit, 20 data collection points were selected for measuring plant cover using visual estimation, laser-point frame (LPF), 2 m above-ground-level (AGL) digital imagery, and 100-m AGL digital imagery. In 11 of 14 management units, determinations of vegetation cover differed (P < 0.05). However, when combined, overall determinations of vegetation cover did not differ. Standard deviation, corrected sums of squares, coefficient of variation, and standard error for the 100 m AGL method were half as large as for the LPF and less than the 2-m AGL and visual estimate. For the purpose of measuring plant cover, all three new methods are as good as or better than visual estimation for speed, standard deviation, and cost. The acquisition of a permanent image of a location is an important advantage of the 2 and 100 m AGL methods because vegetation can be reanalyzed using improved software or to answer different questions, and changes in vegetation over time can be more accurately determined. The reduction in cost per sample, the increased speed of sampling, and the smaller standard deviation associated with the 100-m AGL digital imagery are compelling arguments for adopting this vegetation sampling method.