Mangrove Mapping Using Landsat Imagery and Aerial Photographs: Kemaman District, Terengganu, Malaysia

Classification and distribution of mangrove vegetation are vital information for the proper development of a mangrove management plan. In this study, classification for the mangroves of the district of Kemaman were done using both 1 : 5000 aerial photographs and Landsat TM imageries. The coverage by aerial photographs is limited to the coastal and estuarine areas only. Thus, for areas further upstream of the aerial photo coverage, Landsat TM imageries were used. Analysis of aerial photographs and remote sensing images revealed that the mangroves of Kemaman could be classified into 14 different classes of vegetation. All the 14 classes were identified from areas covered by the aerial photographs. For areas covered by the Landsat images only 7 classes of vegetation were identified. The accuracy for aerial photograph and Landsat images are 91.2% and 87.8%, respectively. It can be concluded that although both techniques are useful in determining the mangrove vegetation classes, the large 1 : 5000 aerial photographs are more accurate and provided more detailed information comparatively.     

基于无人机多传感吊舱系统的火点实时定位方法

林火定位是林火智能监测设备的核心技术。提出了一种基于激光雷达、红外热像仪及组合惯导多数据融合的火点定位方法。首先设计了一个通用的无人机吊舱系统,并基于ROS框架实现数据采集、数据处理和数据传输等功能;其次提出了一个基于无人机吊舱系统的火点全局定位方案,根据红外热像仪成像特性识别火点,同时将密集点云与红外图像进行数据融合,估计出火点的三维空间位置;然后根据无人机位姿提出了一种基于墨卡托投影的火点全局定位方案,得到了火点的GPS位置。最后通过试验得到了该方案的全局定位精度：在实验中经度最大误差为2.36×10^-5°,纬度最大误差为1.84×10^-5°,高程最大误差为0.926 1 m,为其他林火定位方案提供了技术支持。     

基于尾涡强度的无人机与民机纵向安全间隔评估研究

为了解决无人机频频入侵机场净空,与民航客机发生危险接近的问题,以碰撞风险为量化指标,对无人机与民机需要保持的纵向安全间隔进行评估研究。分析民机尾涡流场对无人机运行的影响,利用Crow近场涡强度消散理论,得到实际尾迹影响区改进Reich碰撞模板,据此建立CNS/GPS性能环境下的纵向间隔评估模型,通过Matlab进行间隔值求解。研究结果表明:模型可以较为准确地反映民机起飞初始爬升阶段无人机尾随运行时导航性能和尾涡迹对所需最小间隔值的影响,并得到给定安全目标水平的计算结果。     

Effectiveness of Africa's tropical protected areas for maintaining forest cover

The effectiveness of parks for forest conservation is widely debated in Africa, where increasing human pressure, insufficient funding, and lack of management capacity frequently place significant demands on forests. Tropical forests house a substantial portion of the world's remaining biodiversity and are heavily affected by anthropogenic activity. We analyzed park effectiveness at the individual (224 parks) and national (23 countries) level across Africa by comparing the extent of forest loss (as a proxy for deforestation) inside parks to matched unprotected control sites. Although significant geographical variation existed among parks, the majority of African parks had significantly less forest loss within their boundaries (e.g., Mahale Park had 34 times less forest loss within its boundary) than control sites. Accessibility was a significant driver of forest loss. Relatively inaccessible areas had a higher probability (odds ratio >1, p < 0.001) of forest loss but only in ineffective parks, and relatively accessible areas had a higher probability of forest loss but only in effective parks. Smaller parks less effectively prevented forest loss inside park boundaries than larger parks (T = ?2.32, p < 0.05), and older parks less effectively prevented forest loss inside park boundaries than younger parks (F_2,154 = ?4.11, p < 0.001). Our analyses, the first individual and national assessment of park effectiveness across Africa, demonstrated the complexity of factors (such as geographical variation, accessibility, and park size and age) influencing the ability of a park to curb forest loss within its boundaries.     

Diflubenzuron residue and persistence on an oak forest after aerial application

Abstract

A twenty hectare forest block in central Pennsylvania was aerially sprayed with diflubenzuron (Dimilin 25W®) at the dose of 33.23g A.I./ha in 9.4 litres/ha. Leaf samples were collected from the upper and lower canopies of 27 oaks and understory within this block on the day of spray, May 29, 1991. Canopy leaves were also collected on May 31, June 10, July 29 and September 26, 1991.

Recovery of diflubenzuron residues on fortified canopy‐leaf and litter‐leaf samples using analytical techniques employed in this study averaged 87.4% (SE = 7.5%) and 66.2% (SE = 8.2%), respectively.

On the day of spray, diflubenzuron residues on the upper canopy, lower canopy and understory averaged 81.18, 39.65 and 8.35 ng/cm², respectively. Diflubenzuron residues on canopy‐leaf samples collected 2, 12, 61 and 120 days post‐spray averaged 14.83 (SE = 10.19), 16.75 (SE = 9.95), 12.84 (SE = 8.25) and 11.20 (SE = 7.52) ng/cm², respectively. Diflubenzuron residues on litter‐leaf samples collected after leaf senescence ‐ 169 and 323 days post spray contained measurable amounts of diflubenzuron in 51 and 59% of the samples, respectively. Of the samples with measurable amounts of diflubenzuron, residues averaged 1.36 (SE = 2.44) and 0.65 ng/cm² (SE = 0.73) respectively.     

Monitoring Australian Rangeland Sites Using Landscape Function Indicators and Ground- and Remote-Based Techniques

If the goal for managing rangelands is to achieve a balance between production and conservation, then monitoring is essential to detect change and apply corrective action. In some range-land areas of northern Australia, monitoring has detected a tilt in the production-conservation balance towards excessive production. How big is this imbalance? Can it shift back? Robust monitoring is needed to answer these questions. The aim is to know what to monitor, and where. For example, to detect changes caused by livestock on rangeland forage production and soil erosion, indicators linking grazing disturbances to landscape function are needed, that is, indicators that signal how well landscapes are capturing, concentrating, and utilizing scarce water, nutrient, and organic resources. Studies in Australia and the USA document that simple vegetation and soil patch attributes can be measured as indicators of the 'state of health' of landscape function. For example, field and remote sensing-based grazing studies in Australia document that landscapes with a high cover of perennial plant patches function effectively to capture runoff water and nutrients in sediments, whereas landscapes with a low cover of these patches do not — they are dysfunctional — as indicated by large patches of bare soil. Aerial videography is proving to be a robust technique for measuring indicators of landscape function such as small patches of vegetation and the extent of bare soil. These indicators typically have a sigmoidal response to grazing impacts. We illustrate that if these indicators are measured on monitoring sites established near the sigmoidal 'point of inflection’ then small changes in these indicators can be detected.     

广元飞播造林成效与流域生态环境效益研究

运用川北广元历年飞播成效调查以及固定标准地观测的结果,结合笔者从事飞播造林技术与管理工作的经验,得出：飞播造林是速度快、省劳力、投资少、成本低、效益高的造林方式,推广飞机播种造林是绿化川北山地,迅速治理流域生态环境和实现山区经济可持续发展的有效措施     

基于无人机高光谱遥感在太湖蓝藻水华监测中的一次应用

采用机载高光谱视频相机,在4个季节对太湖蓝藻进行7次、18个架次的有效拍摄。对拍摄到的高光谱影像进行辐射定标、几何拼接等预处理后,提取不同浓度蓝藻和水草等其他物体的高光谱数据,发现不同浓度的蓝藻光谱在680 nm后表现出较大差异。采用主成分分析（PCA）对高光谱数据降维后,结合k-近邻（kNN）分类算法,可实现对蓝藻的精准定位。定性识别结果经光谱预处理后,采用连续投影算法（SPA）进行特征波段提取,发现蓝藻光谱的季节差异主要表现在450 nm~570 nm和760 nm~910 nm波段。     

基于无人机影像的城市植被精细分类

针对传统植被资源调查方法工作量大、成本高、效率低的问题,利用高分辨率无人机遥感影像,联合地物光谱-纹理-空间信息,构建了一种适用于描述城市不同植被种类的多维特征空间,在此基础上对三种应用广泛的分类算法(基于像素的、面向对象的支持向量机及深度学习Mobile-Unet语义分割模型)开展了对比分析研究.结果表明:本文提出的联合地物光谱-纹理-空间信息的特征空间构建方法能够有效地描述城市不同类型植被的特征差异,提升影像分割、植被分类的精度;在分类精度上,基于像素和面向对象的支持向量机分类结果的总体精度均超过90%,深度学习方法的总体分类精度为84%;在算法效率上,传统机器学习方法也优于深度学习方法.因此,得出结论针对城市小区域、小样本的植被精细分类,传统机器学习分类方法比深度学习方法效果更好.     

某型号无人机环境试验技术策划

根据某型无人机结构特性与使用环境,对其气候环境与力学环境试验进行技术策划,确定其环境试验内容、试验条件与方法。采用经验总结与气候、力学环境载荷分析的方法,分析环境因素对无人机工作可靠性的影响和该型无人机飞行环境,总结工作使用状态下的环境载荷,并确定其气候与环境试验内容、条件与方法。总结确定了该型无人机的主要环境载荷,确定了该型无人机环境试验项目与试验条件,并最终进行了环境可靠性试验实施。