Fish assemblages respond to forest cover in small Amazonian basins     

《Limnologica》2020

The removal of native forest affects stream characteristics, processes, and organisms at the local scale. We compared the structure of fish assemblages between microbasins impacted by deforestation and those in pristine condition in the Amazonian Machado River basin, Brazil. Fish were collected with seine and dip nets along an 80-m stretch of 28 streams. At each site, we recorded physical, chemical, and land-water ecotone variables. We collected 6,586 specimens of 109 species, being 39 and 18 of them exclusively of forested and deforested streams, respectively. Non-significant differences were found for abundance and species richness between forested and deforested streams. A total of four main trophic groups were identified. Carnivores were more abundant in forested streams, whereas herbivores, omnivores and detritivores species were the most abundant in deforested streams. The deforested streams showed higher abundance and richness of algae and periphyton consumers, while forested streams presented higher abundance and richness of invertebrate consumers. Forested streams presented longer foodchains, higher occurrence and abundance of species that have more specialized habits and are intolerant to degraded environments, whereas generalist and tolerant species predominated in deforested streams. We conclude that species composition in Amazonian streams predictably responds to the degree of forest cover.  相似文献   

Update and spatial extension of strategic forest inventories using time series remote sensing and modeling     

《International Journal of Applied Earth Observation and Geoinformation》2020

Up-to-date forest inventory information relating the characteristics of managed and natural forests is fundamental to sustainable forest management and required to inform conservation of biodiversity and assess climate change impacts and mitigation opportunities. Strategic forest inventories are difficult to compile over large areas and are often quickly outdated or spatially incomplete as a function of their long production cycle. As a consequence, automated approaches supported by remotely sensed data are increasingly sought to provide exhaustive spatial coverage for a set of core attributes in a timely fashion. The objective of this study was to demonstrate the integration of current remotely-sensed data products and pre-existing jurisdictional inventory data to map four forest attributes of interest (stand age, dominant species, site index, and stem density) for a 55 Mha study region in British Columbia, Canada. First, via image segmentation, spectrally homogenous objects were derived from Landsat surface-reflectance pixel composites. Second, a suite of Landsat-based predictors (e.g., spectral indices, disturbance history, and forest structure) and ancillary variables (e.g., geographic, topographic, and climatic) were derived for these units and used to develop predictive models of target attributes. For the often difficult classification of dominant species, two modelling approaches were compared: (a) a global Random Forests model calibrated with training samples collected over the entire study area, and (b) an ensemble of local models, each calibrated with spatially constrained local samples. Accuracy assessment based upon independent validation samples revealed that the ensemble of local models was more accurate and efficient for species classification, achieving an overall accuracy of 72% for the species which dominate 80% of the forested areas in the province. Results indicated that site index had the highest agreement between predicted and reference (R² = 0.74, %RMSE = 23.1%), followed by stand age (R² = 0.62, %RMSE = 35.6%), and stem density (R² = 0.33, %RMSE = 65.2%). Inventory attributes mapped at the image-derived unit level captured much finer details than traditional polygon-based inventory, yet can be readily reassembled into these larger units for strategic forest planning purposes. Based upon this work, we conclude that in a multi-source forest monitoring program, spatially localized and detailed characterizations enabled by time series of Landsat observations in conjunction with ancillary data can be used to support strategic inventory activities over large areas.  相似文献   

基于无人机的用海项目施工期悬浮泥沙监测          下载免费PDF全文

孙芹芹  张加晋  罗美雪 《海洋技术学报》2019,38(3):34-38

为实现对用海项目施工期悬浮泥沙扩散的实时跟踪监测,尝试采用无人机携带可见光、多光谱传感器对古雷围填海项目的围堰区进行遥感探测。利用Pix4d软件对无人机携带的可见光及多光谱照片进行处理,结果表明,可见光及多光谱影像对水体中的悬浮泥沙分布均具有一定的识别能力。通过研究分析多光谱影像的光谱特征发现,近红外波段对悬浮泥沙含量的升高较为敏感,运用波段比值公式计算结果显示,围堰内含沙水体经溢流口排入海域后浓度明显降低,并可向南继续扩散约300 m。该方法可克服遥感卫星影像时空分辨率低的特点,为用海项目资源环境影响跟踪监测提供新的技术手段。  相似文献   

Modeling spatially non-stationary land use/cover change in the lower Connecticut River Basin by combining geographically weighted logistic regression and the CA-Markov model   总被引：2，自引：0，他引：2  

Hui Wang  Scott R. Stephenson  Shijin Qu 《International journal of geographical information science》2019,33(7):1313-1334

Simulating land use/cover change (LUCC) and determining its transition rules have been a focus of research for several decades. Previous studies used ordinary logistic regression (OLR) to determine transition rules in cellular automata (CA) modeling of LUCC, which often neglected the spatially non-stationary relationships between driving factors and land use/cover categories. We use an integrated geographically weighted logistic regression (GWLR) CA-Markov method to simulate LUCC from 2001–2011 over 29 towns in the Connecticut River Basin. Results are compared with those obtained from the OLR-CA-Markov method, and the sensitivity of LUCC simulated by the GWLR-CA-Markov method to the spatial non-stationarity-based suitability map is investigated. Analysis of residuals indicates better goodness of fit in model calibration for geographically weighted regression (GWR) than OLR. Coefficients of driving factors indicate that GWLR outperforms OLR in depicting the local suitability of land use/cover categories. Kappa statistics of the simulated maps indicate high agreement with observed land use/cover for both OLR-CA-Markov and GWLR-CA-Markov methods. Similarity in simulation accuracy between the methods suggests that the sensitivity of simulated LUCC to suitability inputs is low with respect to spatial non-stationarity. Therefore, this study provides critical insight on the role of spatial non-stationarity throughout the process of LUCC simulation.  相似文献   

Riparian land use and stream habitat regulate water quality     

《Limnologica》2020

Riparian land use is a key driver of stream ecosystem processes but its effects on water quality are still a matter of debate when proposing measures to improve freshwater quality. The aim of this study was to examine the influence of riparian land use on stream habitat and water chemistry, and to assess in what extent stream habitat also affects water quality. To that end, we selected eight reaches in the Ave River basin (northwestern Portugal) and compared longitudinal variations in water chemistry and stream habitat between reaches with different land use (urban, agricultural and natural), and between reaches with natural riparian areas and different habitats. Stream habitat was assessed using the Fluvial Functional Index, the HABSCORE, and the Riparian Forest Quality Index. Longitudinal variations in water chemistry were determined measuring differences in concentrations of ammonium, nitrate, phosphate and oxygen, and conductivity, pH and temperature between the downstream and the upstream ends of each reach. Nitrate concentration tended to decrease along reaches with more natural riparian areas and to increase along reaches with more urban and agricultural land uses. Longitudinal variations in water chemistry also differed between reaches with natural riparian areas, suggesting that water quality also depends on stream habitat. Moreover, longitudinal variation in water chemistry was proven a simple, useful and low-cost approach to assess the influence of land cover and stream habitat on water quality. Overall results demonstrated that both riparian land use and stream habitat influence water quality and that riparian forests are essential to reduce nutrient export to downstream ecosystems.  相似文献   

Accuracy assessment of NLCD 2011 percent impervious cover for selected USA metropolitan areas     

《International Journal of Applied Earth Observation and Geoinformation》2020

The emergence of high-resolution land cover data has created the opportunity to assess the accuracy of impervious cover (IC) provided by the National Land Cover Database (NLCD). We assessed the accuracy of the 900 m² NLCD2011 %IC for 18 metropolitan areas throughout the conterminous United States using reference data from 1 m² land cover data developed as part of the United States Environmental Protection Agency’s EnviroAtlas project. Agreement was assessed from two perspectives: 1) sensitivity to the size of the assessment unit used for the comparison, and 2) utility of NLCD %IC to serve as a proxy for high-resolution IC. The former perspective was considered because statistical relationships can be sensitive to assessment unit size and shape, and the latter perspective was considered because high resolution (reference) %IC data are not available nationwide. The utility of NLCD %IC as a proxy for the high resolution data was assessed for seven lattice (square) cell sizes ranging from 1 ha to 200 ha using four EnviroAtlas IC indicators: 1) %IC per 100 ha (1 km²); 2) %IC by Census block group; 3) %IC within a 15 m (radius) of the riparian zone, and; 4) %IC within a 50 m (radius) of the riparian zone. Agreement was quantified as per assessment unit deviation (NLCD %IC – reference %IC) and summarized as Mean Absolute Deviation (MAD) and Mean Deviation (MD) both within and across the 18 metropolitan areas. Ordinary least squares (OLS) regression (y = reference %IC and x = NLCD %IC) was also used to evaluate the quality of the NLCD %IC data. MAD was ≤ 5% for six of the seven lattice cell sizes. MAD was also ≤ 5% for Census block groups > 100 ha and for both riparian units. These results suggest that uncertainty attributable to the measurement of %IC was no greater than the uncertainty related to the effect of IC on aquatic resources that have been derived from studies of aquatic condition (e.g., benthic fauna) over a range of %IC. Overall, agreement was variable from one metropolitan area to the next. Agreement improved as assessment unit size increased and declined as the level of urbanization (NLCD %IC) increased. NLCD %IC tended to underestimate reference %IC overall, but NLCD %IC was sometimes greater than reference %IC in urbanized settings.  相似文献   

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing     

《International Journal of Applied Earth Observation and Geoinformation》2020

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.  相似文献   

Integration of remote sensing,county-level census,and machine learning for century-long regional cropland distribution data reconstruction     

《International Journal of Applied Earth Observation and Geoinformation》2020

The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 10⁴ km² in 1850 to 6.64 × 10⁴ km² in 1980 and then decreased to 6.16 × 10⁴ km² in 2018. Cropland expansion rate was the largest in the 1960s (749 km² yr⁻¹) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km² yr⁻¹ in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.  相似文献   

陆地可控源电磁法探测效果的频率响应          下载免费PDF全文

万伟  唐新功  黄清华 《地球物理学报》2019,62(12):4846-4859

陆地可控源电磁法的观测资料可依据频段范围近似地划分为近区场、中间区场及远区场,但采用测量相互正交电、磁分量,并计算视电阻率的资料处理方式只适用于远区场数据.为更有效地利用陆地可控源电磁法不同区间场的观测资料,本文结合三维数值模拟技术并采用电场分量直接进行反演的策略,对不同区间电场的响应特征与探测效果进行了分析.数值模拟结果表明:近区电场的异常响应最明显,异常响应不随频率发生显著变化,但纵向分辨能力差;远区电场异常响应随频率发生显著变化,其探测深度取决于频率的高低;中间区场较为复杂,地表电场异常响应的等值线中心并不是位于异常体中心正上方,而是在沿场传播方向上向异常体与围岩的分界面处偏移,并且发现中间区场资料的加入会影响反演结果的准确性.综合合成数据和野外实测资料的反演结果,发现结合近区场和远区场资料而舍弃中间区场资料的反演效果更佳,这为陆地可控源电磁法资料的反演解释提供了一种有效途径.  相似文献   

山东省地面沉降监测与防治工作进展          下载免费PDF全文

张永伟  邵明  肖敏 《山东国土资源》2018,34(8)

近年来,山东省地面沉降监测与防治工作取得了重要进展,初步建立了以二等水准路线、全球定位系统(GPS)、基岩标分层标和地下水监测为基础的"四网合一"地面沉降监测体系,INSAR监测实现了山东全省覆盖。监测成果显示,山东省地面沉降主要位于东营市广饶县、滨州市博兴县、聊城市茌平县,沉降速率呈加快趋势,造成建筑物地基下沉、房屋开裂、地下管道破损等一系列地质环境问题。  相似文献