Carbon forestry in West Africa: The politics of models,measures and verification processes     

Melissa Leach  Ian Scoones 《Global Environmental Change》2013,23(5):957-967

In a context of neo-liberal environmental governance, imperatives for global climate change mitigation are motivating a new round of policy initiatives and projects aimed at carbon forestry: conserving and enhancing forest carbon stocks, and trading these values in emerging carbon markets. In this context modelling and measurement, always significant in framing and justifying forest policy initiatives, are of renewed importance, with a growing array of protocols focused on counting and accounting for forest carbon as a commodity. This article draws on perspectives from science and technology studies and environmental discourse analysis to explore how these modelling and measurement processes are being co-constructed with forest carbon policies and political economies, and applied in project design in local settings. Document analysis and key informant interviews are used to track and illustrate these processes in a pair of case studies of forest carbon projects in Sierra Leone and Ghana. These are chosen to highlight different project types – focused respectively on forest reserve and farm-forestry – in settings with multi-layered histories of people-forest relations, landscape change and prior project intervention. The analysis shows how longer established framings and assessments of deforestation are being re-invoked and re-worked amidst current carbon concerns. We demonstrate that measurement processes are not just technical but social and political, carrying and thus cementing particular views of landscape and social relations that in turn make likely particular kinds of intervention pathway, with fortress style conservation or plantations becoming the dominant approach. In the process, other possibilities – including alternative pathways that might treat and value carbon as part of complex, lived-in landscapes, or respond more adaptively to less equilibrial people–forest relations, are occluded.  相似文献   

Maintaining accurate,current, rural road network data: An extraction and updating routine using RapidEye,participatory GIS and deep learning     

《International Journal of Applied Earth Observation and Geoinformation》2020

Accurate and current road network data is fundamental to land management and emergency response, yet challenging to produce for unpaved roads in rural and forested regions using traditional cartographic approaches. Automatic extraction of roads from satellite imagery using deep learning is a promising alternative gaining increasing attention, however most efforts have focused on urban paved roads and used very high spatial resolution imagery, which is less frequently available for rural regions. Additionally, road extraction routines still struggle to produce a fully-connected, vectorized road network. In this study covering a large forested area in Western Canada, we developed and evaluated a routine to automatically extract unpaved road pixels using a convolutional neural network (CNN), and then used the CNN outputs to update a pre-existing government road network and evaluate if and how it would change. To cover the large spatial extent mapped in this study, we trained the routine using moderately high-resolution satellite imagery from the RapidEye constellation and a ground-truth dataset collected with smartphones by organizations already operating and driving in the region. Performance of the road extraction was comparable to results achieved by others using very high-resolution imagery; recall accuracy was 89–97%, and precision was 85–91%. Using our approach to update the pre-existing road network would result in both removals and additions to the network, totalling over 1250 km, or about 20 % of the roads previously in the network. We discuss how road density estimates in the study area would change using this updated network, and situate these changes within the context of ongoing efforts to conserve grizzly bears, which are listed as a Threatened species in the region. This study demonstrates the potential of remote sensing to maintain current and accurate rural road networks in dynamic forest landscapes where new road construction is prevalent, yet roads are also frequently de-activated, reclaimed or otherwise not maintained.  相似文献   

High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Forest canopy height is an important indicator of forest carbon storage, productivity, and biodiversity. The present study showed the first attempt to develop a machine-learning workflow to map the spatial pattern of the forest canopy height in a mountainous region in the northeast China by coupling the recently available canopy height (H_canopy) footprint product from ICESat-2 with the Sentinel-1 and Sentinel-2 satellite data. The ICESat-2 H_canopy was initially validated by the high-resolution canopy height from airborne LiDAR data at different spatial scales. Performance comparisons were conducted between two machine-learning models – deep learning (DL) model and random forest (RF) model, and between the Sentinel and Landsat-8 satellites. Results showed that the ICESat-2 H_canopy showed the highest correlation with the airborne LiDAR canopy height at a spatial scale of 250 m with a Pearson’s correlation coefficient (R) of 0.82 and a mean bias of -1.46 m, providing important evidence on the reliability of the ICESat-2 vegetation height product from the case in China’s forest. Both DL and RF models obtained satisfactory accuracy on the upscaling of ICESat-2 H_canopy assisted by Sentinel satellite co-variables with an R-value between the observed and predicted H_canopy equalling 0.78 and 0.68, respectively. Compared to Sentinel satellites, Landsat-8 showed relatively weaker performance in H_canopy prediction, suggesting that the addition of the backscattering coefficients from Sentinel-1 and the red-edge related variables from Sentinel-2 could positively contribute to the prediction of forest canopy height. To our knowledge, few studies have demonstrated large-scale vegetation height mapping in a resolution ≤ 250 m based on the newly available satellites (ICESat-2, Sentinel-1 and Sentinel-2) and DL regression model, particularly in the forest areas in China. Thus, the present work provided a timely and important supplementary to the applications of these new earth observation tools.  相似文献   

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

《International Journal of Applied Earth Observation and Geoinformation》2020

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.  相似文献   

大小兴安岭林区风场动力降尺度对比研究     

孟莹莹  曹殿斌  吴岩  王子洋 《气象与环境学报》2019,35(4):8-15

对2017年春季黑龙江省大、小兴安岭林区的6个代表站点10 m风场进行降尺度分析,并结合观测数据对比分析了WRF模式和CALMET降尺度模式的10 m风速、风向预报结果。结果表明：两模式逐小时风速预报与观测的相关系数为0.5-0.7,且随着风速的增加,模式的预报准确率逐渐提高,夜间的风速预报偏差较大,进入白天后,偏差明显减小。WRF模式对风速变化趋势的预报效果优于CALMET模式,与观测的风速相关性更高,而CALMET模式对较大风速的预报效果优于WRF模式。在风向预报方面,WRF和CALMET的风向模拟与观测风向均有较好的一致性,模式预报准确率较高的两个风向也刚好对应各站的盛行风向。同时,本文用回归方法对日平均风速进行订正发现,订正后各站的日平均风速预报准确率平均提高了50%,具有较好的业务应用价值。  相似文献   

Minneapolis and Its Environs     

《The Journal of geography》2012,111(6):249-262

Abstract

University students participated in a research project on communities and conservation on Mount Kilimanjaro in Tanzania. Students contributed by gathering data with various methods that will be compiled in a GIS. Living in three villages at different elevations on the mountain, students facilitated GPS mapping, a random survey of over 90 households, and recording of observations and interviews with the people of these villages. While the inclusion of students in the research project brought greater logistical demands, their participation allowed quick collection of data on a broad scale, more intimate knowledge of the three villages and the communities in them, and provided a valuable learning experience for the students with opportunities to develop and carry-out a research project in an international setting.  相似文献   

Influences of forest roads on the spatial patterns of human- and lightning-caused wildfire ignitions   总被引：1，自引：0，他引：1  

Ganapathy Narayanaraj  Michael C. Wimberly 《Applied geography (Sevenoaks, England)》2012,32(2):878-888

Understanding the spatial patterns of fire ignitions and fire sizes is essential for understanding fire regimes. Although previous studies have documented associations of human-caused fire ignitions with road corridors, less consideration has been given to understanding the multiple influences of roads on the fire regime at a broader landscape-scale. Therefore, we examined the difference between lightning- and human-caused fire ignitions in relation to forest road corridors and other anthropogenic and biophysical factors in the eastern Cascade Mountains of Washington State. We used geographical information systems and case-control logistic regression models to assess the relative importance of these explanatory variables that influence the locations of lightning versus human-caused ignitions.We found that human-caused ignitions were concentrated close to roads, in high road density areas, and near the wildland-urban interface (WUI). In contrast, lightning-caused ignitions were concentrated in low road density areas, away from WUI, and in low population density areas. Lightning-caused ignitions were also associated with fuels and climatic and topographic factors. A weak but significant relationship between lightning-caused fire and proximity to gravel roads may be related to fuels near roads or to bias in detection and reporting of lightning-caused fires near roads. Although most small fires occurred in roaded areas, they accounted for only a small proportion of the total burned area. In contrast, the large fires in roadless and wilderness areas accounted for most of the burned area. Thus, from the standpoint of the total area burned, the effect of forest roads on restricting fire size is likely greater than the impact of roads on increasing fire ignitions. The results of our study suggest that roads and their edge effect area should be more widely acknowledged as a unique type of landscape effect in fire research and management.  相似文献   

On the Anomalous Behaviour of Scalar Flux–Variance Similarity Functions Within the Canopy Sub-layer of a Dense Alpine Forest     

D. Cava  G. G. Katul  A. M. Sempreviva  U. Giostra  A. Scrimieri 《Boundary-Layer Meteorology》2008,128(1):33-57

Within the canopy sub-layer (CSL), variability in scalar sources and sinks are known to affect flux–variance (FV) similarity relationships for water vapour (q) and carbon dioxide (C) concentrations, yet large-scale processes may continue to play a significant role. High frequency time series data for temperature (T), q and C, collected within the CSL of an uneven-aged mixed coniferous forest in Lavarone, Italy, are used to investigate these processes within the context of FV similarity. This dataset suggests that MOST scaling describes the FV similarity function of T even though the observations are collected in the CSL, consistent with other studies. However, the measured FV similarity functions for q and C appear to have higher values than their temperature counterpart. Two hypotheses are proposed to explain the measured anomalous behaviour in the FV similarity functions for q and C when referenced to T. Respired CO₂ from the forest floor leads to large positive excursions in the C time series at the canopy top thereby contributing significantly to both C variance increase and C vertical flux decrease—both leading to an anomalous increase in the FV similarity function. For q, transport of dry air from the outer-layer significantly increases both the variance and the water vapour flux. However, the expected flux increase is much smaller than the variance increase so that the net effect remains an increase in the measured FV similarity function for water vapour above its T counterpart. The hypothesis here is that identifying these events in the temporal and/or in the frequency domain and filtering them from the C and q time series partially recovers a scalar flow field that appears to follow FV similarity theory scaling. Methods for identifying both types of events in the time and frequency domains and their subsequent effects on the FV similarity functions and corollary flow variables, such as the relative transport efficiencies, are also explored.  相似文献   

植被生态动力学模式中萌衍方案的研究进展     

宋翔  曾晓东 《气候与环境研究》2014,19(1):117-126

萌衍模块是植被生态动力学模式中群体动力学方案的重要组成部分,主要用于描述种子的生产、萌芽以及最终发展成新个体等一系列过程,对植被群落结构和演替起着至关重要的作用。然而,目前其参数化方案较不成熟,不同模式的方案差异较大,且存在众多不确定性。因此,为了提出更加合理的萌衍方案,作者首先从观测角度总结了影响种子生产和传播、种子库以及种子萌发和幼苗存活的各种因素;然后围绕森林林窗模型和全球植被动力学模式的萌衍方案进行较为全面的介绍和评述,重点关注对幼苗个体数增量的计算方案;最后讨论其中存在的不确定性和今后的发展方向。  相似文献   

Evaluation of hydrologic equilibrium in a mountainous watershed: incorporating forest canopy spatial adjustment to soil biogeochemical processes     

D. Scott Mackay   《Advances in water resources》2001,24(9-10)

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