协同多源遥感数据的北亚热带森林蓄积量贝叶斯分层估测

精确估算森林蓄积量是国家实现2060年前碳中和目标的迫切需求,而基于遥感的森林蓄积量定量反演是当前遥感应用领域面临的重要挑战和研究热点.光学遥感数据由于无法获取森林高度信息并存在信号饱和问题,反演森林蓄积量的精度较低,而机载Lidar数据能获取高度信息,但成本高、观测范围有限.本研究利用Sentinel-2多光谱、资源...     

利用车载激光扫描的城市森林三维绿量估算

针对城市森林绿量估算研究不足的现状,该文提出了结合高分辨率航空遥感影像和车载激光扫描技术估算城市森林三维绿量的方法:首先从车载激光扫描数据中提取道路两侧单株树的生物物理参数,再结合从航空遥感影像中提取的植被分布,对均质城市森林片区进行三维绿量的拟合计算;最后以上海市滨江森林公园为例进行了方法验证。结果表明,该方法能够拓展车载激光扫描系统应用的领域,为城市绿化信息的获取提供参考。     

Predicting the spatial distribution of hunted and non-hunted Sable antelope (Hippotragus niger niger) using remotely sensed woody cover in a Southern African savanna

From remotely sensed woody cover, we tested whether sables under hunting pressure preferred closed woodland habitats and whether those not under hunting preferred more open woodland habitats. We applied a two factorial logistic regression analysis to model the probability of occurrence of sable antelope in hunted and non-hunted areas of northwest Zimbabwe as a function of vegetation cover density (estimated by a normalized difference vegetation index (NDVI)). We validated the results by high-spatial resolution imagery derived tree canopy area. We subsequently compared the predictions from the two models in order to compare sable cover selection between hunted and non-hunted areas. Our results suggest that hunted sables are likely to select closed woodland, while non-hunted ones would prefer more open woodland habitats. We also established a significant positive relationship between NDVI and tree canopy cover, thus emphasizing the importance of remote sensing in studies that measure the impact of hunting on habitat selection of targeted species.     

Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC)

The Normalized Area Over reflectance Curve (NAOC) is proposed as a new index for remote sensing estimation of the leaf chlorophyll content of heterogeneous areas with different crops, different canopies and different types of bare soil. This index is based on the calculation of the area over the reflectance curve obtained by high spectral resolution reflectance measurements, determined, from the integral of the red–near-infrared interval, divided by the maximum reflectance in that spectral region. For this, use has been made of the experimental data of the SPARC campaigns, where in situ measurements were made of leaf chlorophyll content, LAI and fCOVER of 9 different crops – thus, yielding 300 different values with broad variability of these biophysical parameters. In addition, Proba/CHRIS hyperspectral images were obtained simultaneously to the ground measurements. By comparing the spectra of each pixel with its experimental leaf chlorophyll value, the NAOC was proven to exhibit a linear correlation to chlorophyll content. Calculating the correlation between these variables in the 600–800 nm interval, the best correlation was obtained by computing the integral of the spectral reflectance curve between 643 and 795 nm, which practically covers the spectral range of maximum chlorophyll absorption (at around 670 nm) and maximum leaf reflectance in the infrared (750–800 nm). Based on a Proba/CHRIS image, a chlorophyll map was generated using NAOC and compared with the land-use (crops classification) map. The method yielded a leaf chlorophyll content map of the study area, comprising a large heterogeneous zone. An analysis was made to determine whether the method also serves to estimate the total chlorophyll content of a canopy, multiplying the leaf chlorophyll content by the LAI. To validate the method, use was made of the data from another campaign ((SEN2FLEX), in which measurements were made of different biophysical parameters of 7 crops, and hyperspectral images were obtained with the CASI imaging radiometer from an aircraft. Applying the method to a CASI image, a map of leaf chlorophyll content was obtained, which on, establishing comparisons with the experimental data allowed us to estimate chlorophyll with a root mean square error of 4.2 μg/cm², similar or smaller than other methods but with the improvement of applicability to a large set of different crop types.     

水合铁离子及铁络合物吸收系数光谱(400-900 nm)测量

测量铁化合物溶解物的吸收光谱曲线是水中铁离子含量遥感反演的关键。采用自主设计的水体透射光测量装置,利用ASD光谱仪测量相同厚度不同浓度铁离子溶液的透射光辐亮度,然后运用比值法计算出水中3种铁化合物(硫酸铁、氯化铁和铁氰化钾)的消光系数和吸收系数,最终得到400—900 nm波长范围内3种铁离子吸收系数光谱。该方法可以较好地消除实验装置和水中悬浮物的影响。结果表明,水中3种铁离子均在紫蓝光波段吸收作用较大,绿光次之,逐渐减少至红光波段后,吸收系数变化很小呈平缓直线。测量结果可作为水体铁离子浓度遥感反演模型所需的基础参数。     

Comparative assessment of the relationship of satellite data with the above ground biomass of Sal trees (<Emphasis Type="Italic">Shorea robusta</Emphasis>) determined from phenologically different time periods

The Above Ground Biomass(AGB) estimates of vegetation comprise both the bole biomass determined through a volumetric equation and litter biomass collected from the ground.For mature trees,the AGB estimated in phenologically different time periods is directly affected by the litter biomass since the Diameter at Breast Height(DBH) and height(H) of such trees that are used in the estimation of bole biomass would remain unchanged over a reasonable time period.In the present study,we have determined the AGB of Sal trees(Shorea robusta) in two contrasting seasons:the peak green period in October being devoid of lit-ter on the ground and the leaf shedding period in February with abundant amount of litter present on the ground.Estimation of AGB for the month of February included the litter biomass.In contrast,the AGB for October represented only the bole biomass.AGB was estimated for ten different plots selected in the study area.The AGB estimated from ten sampling plots for each time period was re-gressed with the individual tree parameters such as the average DBH and height of trees measured from the corresponding plots.The regression analysis exhibited a significantly stronger relationship between the AGB and DBH for the month of October as compared to February.Furthermore,the correlation between the remotely sensed derived data and AGB was also found to be significantly higher for the month of October than February.This observation indicates that inclusion of the litter biomass in AGB will tend to decrease the re-gression relationship between AGB and DBH and also between the remotely sensed data and AGB.Therefore,these conclusions invite careful consideration while estimating AGB from satellite data in phenologically different time periods.