Woody vegetation cover,height and biomass at 25-m resolution across Australia derived from multiple site,airborne and satellite observations

Detailed spatial information on the presence and properties of woody vegetation serves many purposes, including carbon accounting, environmental reporting and land management. Here, we investigated whether machine learning can be used to combine multiple spatial observations and training data to estimate woody vegetation canopy cover fraction (‘cover’), vegetation height (‘height’) and woody above-ground biomass dry matter (‘biomass’) at 25-m resolution across the Australian continent, where possible on an annual basis. We trained a Random Forest algorithm on cover and height estimates derived from airborne LiDAR over 11 regions and inventory-based biomass estimates for many thousands of plots across Australia. As predictors, we used annual geomedian Landsat surface reflectance, ALOS/PALSAR L-band radar backscatter mosaics, spatial vegetation structure data derived primarily from ICESat/GLAS satellite altimetry, and spatial climate data. Cross-validation experiments were undertaken to optimize the selection of predictors and the configuration of the algorithm. The resulting estimation errors were 0.07 for cover, 3.4 m for height, and 80 t dry matter ha^-1 for biomass. A large fraction (89–94 %) of the observed variance was explained in each case. Priorities for future research include validation of the LiDAR-derived cover training data and the use of new satellite vegetation height data from the GEDI mission. Annual cover mapping for 2000–2018 provided detailed insight in woody vegetation dynamics. Continentally, woody vegetation change was primarily driven by water availability and its effect on bushfire and mortality, particularly in the drier interior. Changes in woody vegetation made a substantial contribution to Australia’s total carbon emissions since 2000. Whether these ecosystems will recover biomass in future remains to be seen, given the persistent pressures of climate change and land use.     

2013年—2017年主要农业区秸秆焚烧时空特征及影响因素分析

中国作为农业大国,每年面临大规模的露天秸秆焚烧现象,近十几年来,秸秆焚烧在突发和极端雾霾事件中发挥了显著的作用,导致大气能见度下降,危害人类健康。本文为探究中国“大气十条”实施第一阶段（2013年—2017年）以来中国秸秆焚烧时空变化情况,并探究秸秆禁烧政策对秸秆焚烧时空变化的影响,借助2013年—2017年Terra、Aqua卫星MODIS热异常产品,利用土地利用与覆盖变化数据,通过提取白天农田范围内的热异常点,获取全国范围秸秆焚烧结果,分析了2013年—2017年秸秆焚烧时空变化特征,并深入讨论了全国和区域禁烧政策对秸秆焚烧治理的影响,有助于为今后针对重点焚烧区制定相关政策提供科学依据。研究结果显示“大气十条”颁布之后5年期间全国秸秆焚烧年总量呈先增加后减小的总趋势,最低值2016年比最高值2014年降低34.48%,2017年较2013年秸秆焚烧数量减少的区域面积约为增加区域面积的2倍。秸秆焚烧治理成效最为显著的为河南省、安徽省和湖北省,其中,河南省在严格的禁烧政策、集中约谈、经济处罚、推广秸秆综合利用产业等多种措施共同影响下,2016-06和2016-10两个秸秆焚烧高峰期的秸秆焚烧数量分别较2015年同期下降86.66%和98.93%,且后期未出现反弹。黑龙江省虽然在一定程度上控制了秋季秸秆焚烧情况,但由于秸秆产量大且缺乏处理手段,会导致次年春季出现大规模反弹,并未从根本上解决秸秆焚烧控制问题。因此,除了进一步强化秸秆焚烧重点区域和重点时段禁烧措施,不断提高禁烧监管水平,还必须鼓励秸秆还田,秸秆能源化,提高秸秆综合利用率,“禁”“用”结合、因地制宜,形成管控秸秆焚烧的长效科学措施。     

热带西太平洋M4海山超微型浮游生物的生态分布特点

获取并分析了2017年8月热带西太平洋M4海山水体中的超微型浮游生物样品,根据流式细胞术的散射光和荧光信号,检测到M4海山各水层中普遍存在四个超微型自养浮游生物类群(聚球藻、原绿球藻、微微型真核浮游生物、微型真核浮游生物)和两个超微型异养原核生物类群(低核酸含量和高核酸含量异养原核生物)。聚球藻丰度高值出现在100m以浅;原绿球藻和微微型真核浮游生物丰度高值区在深层叶绿素最大值附近(75—150m);微型真核浮游生物和异养原核生物分布范围较广,150m以浅丰度较高。异养原核生物的生物量(1.68—11.25μgC/L)高于自养浮游生物(0.05—6.02μgC/L)的生物量。在超微型自养浮游生物中,原绿球藻生物量在100—150m水层占优势(53.83%±6.32%),微型真核浮游生物的生物量在75m以浅(58.62%±8.53%)和200—300m水层占优势(46.18%±7.82%)。在异养原核生物中,高核酸含量异养原核生物的生物量所占百分比(61.05%±3.98%)高于低核酸含量异养原核生物(38.95%±3.98%),然而在海山附近DCM层低核酸含量异养原核生物比例最高可达58.64%。冗余分析表明,超微型浮游生物的丰度与温度呈正相关,与深度和营养盐呈负相关关系。在M4海山超微型自养浮游生物分布没有明显的"海山效应",但海山的存在会对异养原核生物两个类群生物量的比例产生影响。     

南海北部陆架和陆坡区小型底栖动物群落的比较研究

为了解南海北部陆架与陆坡区小型底栖动物的群落特征,以及影响群落特征的环境因素,2015年6月对南海北部海域(19.3°—21.4°N, 112.4°—115.1°E)7个站位的小型底栖动物及环境因子进行了采样,并对陆架和陆坡区小型底栖动物群落的丰度、生物量、类群组成和群落结构进行比较。结果表明,在陆架站位,小型底栖动物由13个类群组成,平均丰度为(132±130)ind./10cm2,平均生物量为(169±79)μgdwt/10cm2;在陆坡站位由8个类群组成,平均丰度为(33±14)ind./10cm2,平均生物量为(56±35)μgdwt/10cm2。单因素方差分析结果表明,陆坡区小型底栖动物的总丰度和总生物量以及线虫和多毛类的丰度均显著低于陆架区,但优势类群的相对丰度组成没有显著不同,海洋线虫占总丰度的83%,其次为多毛类和桡足类,分别占7%和3%。环境因子的主成分分析(Principal ComponentsAnalysis,PCA)将陆架和陆坡站位沿第一主分量轴分开,小型底栖生物丰度和生物量与沉积物叶绿素a和脱镁叶绿酸含量以及底层水温呈最大正相关,与水深呈负相关;聚类(Cluster)和排序(non-metric Multidimensional Scaling, MDS),以相似性系数65%将7个站位划分为2组,与按照水深划分的陆架和陆坡组基本吻合;单因素相似性分析(one-way ANOSIM)显示陆架和陆坡区小型底栖动物群落结构差异显著;生物-环境分析(Biota-Environment,BIOENV)表明影响群落结构的最佳环境因子组合为叶绿素a和底层水温。综上可知,随水深增加的食物减少和底层水温的下降是限制南海北部研究海域小型底栖动物丰度和生物量及影响群落组成和结构的主要因素。     

Crop characterization using an improved scattering power decomposition technique for compact polarimetric SAR data

Crop characterization using Compact-Pol Synthetic Aperture Radar (CP-SAR) data is of prime interest with the rapid advancements of SAR systems towards operational applications. It is noteworthy that as a good compromise between the dual and quad-polarized SAR systems, the CP-SAR offer advantages in terms of the larger swath and lower data rate. The m − χ CP decomposition considers two out of the three Stokes child parameters: degree of polarization (m), ellipticity (χ), and orientation angle (ψ) to describe the polarized part of the quasi-monochromatic partially polarized wave. An improvement in the scattering powers was proposed in the S − Ω decomposition, which takes into accounts both the transmitted and received wave ellipticities (χ_t, χ_r) and the orientation angles (ψ_t, ψ_r). In this decomposition, S denotes the Stokes vector and Ω is the polarized power fraction. However, it may be noted that the S − Ω decomposition intrinsically ignores dominance in the target scattering mechanism while calculating the powers. In this work, improvement is proposed for the S − Ω decomposition by utilizing the degree of dominance in the scattering mechanism. The improved S − Ω (named as iS − Ω) decomposition powers are first compared with the existing m − χ and S − Ω powers for elementary (viz., trihedral and dihedral corner reflectors) and distributed targets using simulated CP-SAR data from quad-pol RADARSAT-2 data. An increase of ∼2% for odd and even-bounce powers obtained from the iS − Ω decomposition is observed for the trihedral and dihedral corner reflectors respectively. The analysis of the scattering powers for distributed targets shows that an increase of 15% and 12% in the even and odd-bounce powers is observed from iS − Ω for urban and bare soil areas respectively as compared to the m − χ and S − Ω decompositions. Besides, temporal variations in the scattering powers obtained from the iS − Ω decomposition are also analyzed for rice, cotton, and sugarcane crops at different growth stages.     

Crop classification from full-year fully-polarimetric L-band UAVSAR time-series using the Random Forest algorithm

Accurate and timely information on the distribution of crop types is vital to agricultural management, ecosystem services valuation and food security assessment. Synthetic Aperture Radar (SAR) systems have become increasingly popular in the field of crop monitoring and classification. However, the potential of time-series polarimetric SAR data has not been explored extensively, with several open scientific questions (e.g. the optimal combination of image dates for crop classification) that need to be answered. In this research, the usefulness of full year (both 2011 and 2014) L-band fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data in crop classification was fully investigated over an agricultural region with a heterogeneous distribution of crop categories. In total, 11 crop classes including tree crops (almond and walnut), forage crops (grass, alfalfa, hay, and clover), a spring crop (winter wheat), and summer crops (corn, sunflower, tomato, and pepper), were discriminated using the Random Forest (RF) algorithm. The SAR input variables included raw linear polarization channels as well as polarimetric parameters derived from Cloude-Pottier (CP) and Freeman-Durden (FD) decompositions. Results showed clearly that the polarimetric parameters yielded much higher classification accuracies than linear polarizations. The combined use of all variables (linear polarizations and polarimetric parameters) produced the maximum overall accuracy of 90.50 % and 84.93 % for 2011 and 2014, respectively, with a significant increase of approximately 8 percentage points compared with linear polarizations alone. The variable importance provided by the RF illustrated that the polarimetric parameters had a far greater influence than linear polarizations, with the CP parameters being much more important than the FD parameters. The most important acquisitions were the images dated during the peak biomass stage (July and August) when the differences in structural characteristics between most crops were the largest. At the same time, the images in spring (April and May) and autumn (October) also contributed to the crop classification since they respectively provided unique information for discriminating fruit crops (almond and walnut) as well as summer crops (corn, sunflower, and tomato). As a result, the combined use of only four acquisitions (dated May, July, August, and October for 2011 and April, June, August, and October for 2014) was adequate to achieve a nearly-optimal overall accuracy. In light of the promising classification accuracies demonstrated in this research, it becomes increasingly viable to provide accurate and up-to-date crops inventories over large areas based solely on multitemporal polarimetric SAR.     

Microphytobenthic biomass and species composition in intertidal flats of the Nakdong River estuary, Korea

Intertidal microphytobenthos (MPB) were investigated monthly from August 2006 to March 2008 at four different sites in the sand flats of Nakdong River estuary, Korea. Samples of surface sediment (ca. 1 cm) were collected, and chlorophyll a was extracted as biomass estimation. Species identification and enumeration were carried out by light microscopy, assisted where necessary by scanning electronic microscopy. Biomass varied between 0.47 and 16.58 μg cm⁻³, abundance changed from 5.25 to 414.75 × 10³ cells cm⁻³, while the Shannon diversity indexes ranged between 0.69 and 2.35 H′. Thirty-nine MPB taxa were identified, primarily composed of epipelic diatoms, among which Amphora and Navicula were the most abundant genera. Based on the biomass, abundance, species composition and their dynamics, MPB assemblages of sampling sites were grouped into three distinct communities corresponding to their sediment composition characteristics. Multivariate correlation analysis revealed that biomass was positively related to mud and very fine sand, negatively related to fine and medium sand, but not significantly related to environmental factors such as pore water nutrients, light intensity and salinity, which fluctuated rapidly during emersion period. Cluster analysis corroborated the division of MPB communities according to site types on seasonal scales, and also showed seasonality between sites by cluster of all summer groups. Principal component analysis identified that variability in species composition was significantly affected by mud, very fine sand, fine sand, light intensity, and sediment temperature. This study suggests that sediment composition plays an important role in the functioning of intertidal MPB communities in estuarine ecosystems.     

厦门东海域和安海湾小型底栖动物的密度和生物量

2007年6月对厦门东海域5个站位和晋江安海湾4个站位进行了小型底栖动物调查,分析了小型底栖动物的类群组成、密度和生物量．结果表明,从这两个海域样品中共鉴定出12个小型底栖动物类群,厦门东海域和安海湾自由生活海洋线虫分别占总数量的84．56％和98．19％．生物量组成和密度组成不同,厦门东海域多毛类（37．80％）、海洋线虫（33．32％）和底栖桡足类（18．64％）共同组成了小型底栖动物的生物量优势类群;安海湾生物量优势类群是由海洋线虫（67．64％）和多毛类（30．46％）组成．厦门东海域小型底栖动物的平均密度为72．67±10．21ind／cm^2,平均生物量为23．01±10．41μg/cm^2;安海湾的平均密度为31．48±45．58ind／cm^2,平均生物量为18．28±25．69μg/cm^2．     

基于空间抽样的农作物面积遥感测量

传统的农作物面积统计通常采用人工统计的方法,费时费力,并且精确度不高,实时性不强。为了快速、准确地获取农作物面积,本文根据实际业务需求,充分利用遥感技术,同时结合地理信息技术,与基于PPS二阶空间抽样主法提出了一套切实可行的农作物面积遥感测量方法和流程。     

黄海中南部头足类的群落结构与生物多样性

为掌握黄海中南部头足类的群落结构及数量分布,作者根据2010~2011年间春、秋、冬3个季节的底拖网调查资料,对黄海中南部头足类的种类组成、生物量分布及生物多样性进行了研究。结果显示:3个季节共捕获头足类13种,隶属3目6科6属。各季节的优势种及其生物量比重分别为:春季——双喙耳乌贼(Sepiola birostrata)50.07%、秋季——针乌贼(Sepia esculenta)40.88%、冬季——枪乌贼(Loligo spp.)68.20%。各季节头足类平均资源密度分别为春季4.85 kg/km2、秋季2.52 kg/km2、冬季12.72 kg/km2,春秋两季间差异性不显著(P0.05),冬季与其他两季差异性显著(P0.05)。黄海中南部不同季节头足类的生物量分布变化较大,春季以西南及东北部密度最高,秋季以西南部密度最高,冬季以中部及东北部密度最高。头足类在各水深的垂直分布随季节变化。无论根据生物量还是丰度,种类丰富度指数、均匀度指数及Shannon-Wiener指数等多样性指数均以冬季最高,其次是春季,秋季最低。春季与冬季群落结构相似性较高,秋季与其他两个季节的群落结构相似性均较低。与1998~2000年同期相比,头足类种类数增加5种,相对资源密度增长了12%,枪乌贼类的生物量比重仍最高,耳乌贼类的比重提高,太平洋褶柔鱼的比重则大幅下降。