2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models

One of the challenges of remote sensing and computer vision lies in the three-dimensional (3-D) reconstruction of individual trees by using automated methods through very high-resolution (VHR) data sets. However, a successful and complete 3-D reconstruction relies on precise delineation of the trees in two dimensions. In this paper, we present an original approach to detect and delineate citrus trees using unmanned aerial vehicles based on photogrammetric digital surface models (DSMs). The symmetry of the citrus trees in a DSM is handled by an orientation-based radial symmetry transform which is computed in a unique way. Next, we propose an efficient strategy to accurately build influence regions of each tree, and then we delineate individual citrus trees through active contours by taking into account the influence region of each canopy. We also present two efficient strategies to filter out erroneously detected canopy regions without having any height thresholds. Experiments are carried out on eight test DSMs composed of different types of citrus orchards with varying densities and canopy sizes. Extensive comparisons to the state-of-the-art approaches reveal that our proposed approach provides superior detection and delineation performances through supporting a nice balance between precision and recall measures.     

Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2’s red-edge bands to land-use and land-cover mapping in Burkina Faso

The availability of freely available moderate-to-high spatial resolution (10–30 m) satellite imagery received a major boost with the recent launch of the Sentinel-2 sensor by the European Space Agency. Together with Landsat, these sensors provide the scientific community with a wide range of spatial, spectral, and temporal properties. This study compared and explored the synergistic use of Landsat-8 and Sentinel-2 data in mapping land use and land cover (LULC) in rural Burkina Faso. Specifically, contribution of the red-edge bands of Sentinel-2 in improving LULC mapping was examined. Three machine-learning algorithms – random forest, stochastic gradient boosting, and support vector machines – were employed to classify different data configurations. Classification of all Sentinel-2 bands as well as Sentinel-2 bands common to Landsat-8 produced an overall accuracy, that is 5% and 4% better than Landsat-8. The combination of Landsat-8 and Sentinel-2 red-edge bands resulted in a 4% accuracy improvement over that of Landsat-8. It was found that classification of the Sentinel-2 red-edge bands alone produced better and comparable results to Landsat-8 and the other Sentinel-2 bands, respectively. Results of this study demonstrate the added value of the Sentinel-2 red-edge bands and encourage multi-sensoral approaches to LULC mapping in West Africa.     

西昌市1989—2018年林地草地湿地动态变化特征分析

遥感技术已被广泛应用于生态环境调查与研究。为获取西昌市近30 a生态环境演化趋势,利用1989年、2000年、2010年的专题绘图仪(Thematic Mapper,TM)遥感影像和2018年的陆地成像仪(Operational Land Imager,OLI)遥感影像,通过图像处理、目视解译和野外验证等方法,获得了西昌市1989—2018年的土地利用/覆盖数据,并对林地、草地和湿地的动态变化特征进行了研究。结果表明: 1989—2018年,西昌市林地、湿地和草地面积持续增加,生态环境持续向好; 林地主要分布于安宁河谷和邛海盆地四周山地,在牦牛山、螺髻山一带形成主要林区; 草地主要呈星岛状分布于牦牛山、螺髻山一带林地之间; 湿地以河流湿地与湖泊湿地为主,主要沿安宁河及邛海分布。但仍存在一些问题: 森林存在针叶化现象较普遍、树种单一等问题,需要重点加强林区火灾防范; 草地多数呈零星片状分布,不具有完整的系统结构和良好的功能,多数草地承载力和生产力较低,不宜大规模开发利用,应通过封山育林促使其向森林转化; 湿地分布也比较局限,需要着力予以保护。研究成果可为西昌市生态保护修复措施的制定及经济社会可持续发展提供科学依据。     

海南岛天然橡胶林台风灾害风险评价

台风灾害是海南橡胶种植中影响最为严重和主要的灾害,为对其风险进行定量评估,本研究以海南岛天然橡胶林为研究对象,基于灾害风险评估理论,融合橡胶台风灾害、社会经济和气象数据,建立橡胶台风灾害危险性、暴露性和脆弱性评价模型,利用加权综合评价法开展天然橡胶林台风灾害风险评价。结果表明：海南橡胶种植高风险区位于沿海台风发生频繁市县,其中琼海、文昌、海口为海南岛橡胶灾害风险最高的地区,其次陵水、万宁、琼中、屯昌、东方等地区灾害风险也较高。风险最低地区位于中部五指山、保亭、乐东、三亚等地区,评价结果与实际灾害发生以及种植情况相符。评价结果表明,台风灾害危险性是风险的主导因子,但非单一决定因子,种植技术、品种改良等措施对脆弱性降低起到了较好的促进作用。评价结果可为橡胶林避灾防灾及种植布局提供依据。     

基于WRF模式的风电场短期风速集成预报方法研究

风能始源于大气的运动,具有很大的随机性和间歇性。风速预测是风电场风功率预测的基础,其准确性具有重要的意义。对于复杂地形条件下,风速的预报一直是各国研究的难点和重点。为了提高风电场短期风速预报的准确性,本研究采用多种边界层参数化方案来集成预报风速,将各单一边界层参数化方案预报的风速及相应的实测风速数据,应用随机森林算法建立集成预报模型,对风电场的短期风速进行集成预报研究。试验结果表明,采用集成预报风速方法,预报的风速误差相比于单一边界层参数化方案预报的风速误差明显减小,对研究区域的风速、风向等气象要素有着较好的模拟效果,能够有效提高风速预报的准确率。     

MULTIVARIATE GEOMORPHIC ANALYSIS OF FOREST STREAMS: IMPLICATIONS FOR ASSESSMENT OF LAND USE IMPACTS ON CHANNEL CONDITION

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10 disturbed from 13 undisturbed reaches with 90 per cent and 92 per cent correct classification respectively. These variables are the total number of pools per reach, the ratio of mean residual pool depth to mean bankfull depth, and the ratio of critical shear stress of the median surface grain size to bankfull shear stress. The last variable can be dropped without a decrease in rate of correct classification; however, the resulting two-variable model may be less robust. Analysis of the distribution of channel units, including pool types, can also be used to discriminate disturbed from undisturbed reaches and is particularly useful for assessment of aquatic habitat condition. However, channel unit classification and inventory can be subject to considerable error and observer bias. Abundance of pool-related large woody debris is highly correlated with pool frequency and is an important factor determining channel morphology. Results of this study yield a much needed, objective, geomorphic discrimination of pristine and disturbed channel conditions, providing a reference standard for channel assessment and restoration efforts.     

大兴安岭火烧迹地土壤动物生态地理分析

不同恢复年份森林火烧迹地的土壤动物群落特征明显不同。火烧过后的前1³年,大型土壤动物的种类和数量很少,特别是常见类群中的线蚓所占的比例很小,但运动能力较强的蜈蚣、蜘蛛等所占比例较高。火烧3⁵年后,土壤中线蚓数量才逐渐增多并趋于稳定。中小型土壤动物中的原尾虫只出现在16年迹地和对比样地中,表明原尾虫确是稳定生境的指示动物。火烧过后,土壤环境中最先侵入的是运动能力较强的大型土壤动物,之后中小型土壤动物才逐渐得到恢复。火烧后6⁷年是中小型土壤动物发展的盛期,随后土壤动物种类和数量开始减少并趋于稳定。火烧的强度对土壤动物群落的恢复有一定的影响,轻度火烧影响地区的土壤动物恢复较快,经过6⁷年,土壤动物种类和数量能超过未受火烧影响的地区;而中、重度火烧地区,土壤动物恢复到正常水平则需要超过16年的更长的时间。     

区域性森林大火的真正成因

森林大火真正起因于地球排气中易燃还原性气体在腐殖层的临界积聚(气体体积分数大约为5%~6%)。现场气体(H2,CO)系统测量结果证实了这一点。测量结果显示,该林区腐殖层中H2、CO质量分数分别为(10~170)×10-6(本底值为0·5×10-6)和(2~60)×10-6(本底值为0·5×10-6),二者均远高于大气本底值数十到数百倍,而且未燃区的测值显然高于1998年燃区。     

基于GIS和RS的西藏森林火险等级计算方法

基于遥感技术(RS)和地理信息系统(GIS),利用由基于DEM演算的地面最高温度、最小相对湿度和最大风速等格点化气象要素,FY2静止气象卫星逐日降水反演产品和AVHRR积雪监测产品计算网格森林火险天气等级,结合由植被类型、NDVI、地形要素和公路、人口聚居地等要素评估的森林火险风险等级,综合计算得到网格化的西藏森林火险等级。该项业务程序基于MeteoInfo组件建立,能够实现全自动化业务运行。对于森林火灾事件,通过与基于气象站的森林火险天气等级相比,该方法的准确性更高,能为西藏林区森林防火工作提供有效参考。     

地震荷载下土层变形等级预测方法研究

以计算结果可靠的土层反应结果为基础数据,基于随机森林算法(Random Forest,简称"RF"),建立地震动、场地土层参数特征量与土层变形特征的关系,提出一种依据常规地震动和场地土层参数为特征量的地震荷载下土层变形等级预测新方法,给出了典型场地土体发生大应变的地震动阈值.结果表明:基于RF模型对土体的变形程度预测结...