三江源区“黑土滩”型退化草地时空变化

“黑土滩”型退化草地易引起三江源区生态环境的急剧恶化,准确及时地了解“黑土滩”型退化草地的时空分布,对三江源地区草地退化的治理和生态环境的保护具有重要作用。本研究以三江源区典型“黑土滩”型退化草地——青海达日县境内的项目试验区作为研究区,对比该区域2007年6月29日的QuickBird影像和7月1日的Landsat TM影像,结果表明,Landsat TM影像解译精度较低,但足以满足“黑土滩”退化草地的监测。利用Landsat TM资料分析了该区域2000、2007和2011年“黑土滩”退化草地的时空变化,结果显示,2000-2007年,非黑土滩总面积减小,草地呈现退化趋势,黑土滩总面积增大;2007-2011年,非黑土滩总面积增大,黑土滩总面积减小,草地退化和黑土滩扩展趋势得到有效遏制。说明三江源区生态保护和建设工程在“黑土滩”综合治理方面成效显著。     

基于TM影像的濮阳市生态系统多样性多层次分析

基于Landsat-8 TM影像,利用ENVI 50进行遥感影像解译并结合样地调查,在景观、生态系统、群落3个层次上对濮阳市生态系统多样性进行分析。结果表明：濮阳市以旱地农田及其防护林为景观基质,各景观斑块的破碎化程度较高,但形状变化不复杂,景观层次上的多样性指数为13167,均匀度指数为08181;生态系统类型较为丰富,多样性指数为17126,均匀度指数为07794,主要类型是旱作农田、居住地与片林;群落层次上的物种多样性在不同生态系统类型中变化较大,但均受草本层控制,森林群落基本上为杨树单优群落,多样性水平较自然群落低;未来应注重发展类型多样、结构丰富的农田防护林与林下复合经营体系,为生物多样性保持与生物防治以及农业高产、稳产等提供保障。     

Using Landsat Images and Spectral Mixture Analysis to Assess Drivers of 21‐Year LULC Changes in Sudan

Landsat images acquired in 1987, 1999 and 2008 were selected to evaluate land use and land cover changes in three different ecological zones in the Republic of the Sudan: savannah (North Kordofan), semi‐desert (River Nile) and desert (Northern State). Maps of soil, vegetation and non‐photosynthetic material were built by spectral mixture analysis using endmembers spectra derived from images. Multitemporal comparison techniques were then applied to vegetation and soil maps to estimate the long‐term land degradation/re‐growth dynamics and to emphasize land cover variation over time and in space. Multitemporal comparisons have shown that site‐specific interactions between natural processes, climate variation and human activity played a pivotal role in land use and land cover change. In savannah, human activities strongly affected degradation phenomena. Expansion of villages triggered a change in land use and mismanagement of the natural resources, mainly caused by deforestation to supply wood for domestic uses. The degradation then promoted sand encroachment and dune migration. On average, 48% of the total area was subjected to medium (25–50%) and high (50–75%) land degradation. Differently, climatic constraints drove increasing degradation processes in semi‐desert and desert zones. The phenomenon was particularly severe in the desert zone. In each site, an inversion of the general trend was due to a land use change where forestry or agricultural projects were established, partly sustained in savannah by the positive rainfall trend of the last two decades. Site‐specific strategies that take into account the interactions of the driving factors at local scale are thus necessary to combat land degradation. Copyright © 2016 John Wiley & Sons, Ltd.     

Mapping Prosopis juliflora in West Somaliland with Landsat 8 Satellite Imagery and Ground Information

Prosopis juliflora is a drought‐tolerant fast‐growing tree species originating from South and Central America with a high invasion potential in arid and semi‐arid areas in Africa. It was introduced in Somaliland in the 1980s and is reported to have spread vigorously since. Despite being recognized as a serious issue in the country, the actual scale of the problem is unknown. In this study, we mapped the species in a study area that includes the capital, Hargeisa, using Landsat 8 satellite imagery. During a field campaign in 2015, we collected canopy‐level spectral signatures of P . juliflora and native trees to analyse the potential use of spectral data in discriminating the invasive species. P. juliflora was found to be generally distinguishable because of its greater vigour during the dry season. We tested the accuracy of the random forest classifier and different classification set‐ups, varying the spatial resolution (original 30 m vs pan‐sharpened 15 m) and image acquisition dates (during the wet season, the dry season and a combination of the two). Best overall accuracy (84%) was achieved by using pan‐sharpened data from the two seasons. About 30 years since its introduction, the invasive species was detected in 9% of the total investigated area with highest occurrence in the proximity of human settlements and along seasonal water courses. © 2016 The Authors. Land Degradation and Development published by John Wiley & Sons, Ltd.     

Effects of changing landscape pattern and U. S. G. S. land cover data variability on ecoregion discrimination across a forest-agriculture gradient

We examined the use of coarse resolution land cover data (USGS LUDA) to accurately discriminate ecoregions and landscape-scale features important to biodiversity monitoring and management. We used land cover composition and landscape indices, correlation and principal components analysis, and comparison with finer-grained Landsat TM data, to assess how well LUDA data discriminate changing patterns across an agriculture-forest gradient in Minnesota, U.S.A. We found LUDA data to be most accurate at general class levels of agriculture and forest dominance (Anderson Level I), but in consistent and limited in ecotonal areas of the gradient and within forested portions of the study region at finer classes (Anderson Level II). We expected LUDA to over-represent major (matrix) cover types and under-represent minor types, but this was not consistent with all classes. 1) Land cover types respond individualistically across the gradient, changing landscape grain as well as their spatial distribution and abundance. 2) Agriculture is not over-represented where it is the dominant land cover type, but forest is over-represented where it is dominant. 3) Individual forest types are under-represented in an open land matrix. 4) Within forested areas, mixed deciduous-coniferous forest is over-represented by several orders of magnitude and the separate conifer and hardwood types under-represented. Across gradual, transitional agriculture-forest areas, LUDA cover class dominance changes abruptly in a stair-step fashion. In general, rare cover types that are discrete, such as forest in agriculture or wetlands or water in forest, are more accurately represented than cover classes having lower contrast with the matrix. Northward across the gradient, important changes in the proportions of conifer and deciduous forest mixtures occur at scales not discriminated by LUDA data. Results suggest that finer-grained data are needed to map within-state ecoregions and discriminate important landscape characteristics. LUDA data, or similar coarse resolution data sources, should be used with caution and the biases fully understood before being applied in regional landscape management. This revised version was published online in July 2006 with corrections to the Cover Date.     

A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning

The quantification of evapotranspiration (ET) from irrigated projects is important for water rights management, water resources planning and water regulation. Traditionally, ET has been estimated by multiplying a weather-based reference ET by crop coefficients (K_c) determined according to the crop type and the crop growth stage. However, there is typically question regarding whether crops grown compare with the conditions represented by the K_c values, especially in water short areas. In addition, it is difficult to estimate the correct crop growth stage dates for large populations of crops and fields. METRIC (Mapping Evapotranspiration at high Resolution and with Internalized Calibration) is an image-processing model for calculating ET as a residual of the surface energy balance. METRIC is a variant of SEBAL, an energy balance process developed in the Netherlands by Bastiaanssen and was extended to provide tighter integration with ground-based reference ET. METRIC was applied with Landsat images in southern Idaho to predict monthly and seasonal ET for water rights accounting and for operation of ground water models. ET “maps” (i.e., images) provide the means to quantify, in terms of both the amount and spatial distribution, the ET on a field by field basis. The ET maps have been used in Idaho to quantify net ground-water pumpage in areas where water extraction from underground is not measured and to estimate recharge from surface-irrigated lands. Application and testing of METRIC indicates substantial promise as an efficient, accurate, and relatively inexpensive procedure to predict the actual evaporation fluxes from irrigated lands throughout a growing season.     

乌鲁木齐市2000-2018年“三生”空间格局演变及其风险评价

[目的] 剖析生产—生活—生态（“三生”）空间转变对绿洲城市生态风险变化的影响,实现“三生”空间的协调发展,为解决经济快速发展和社会转型中带来的国土开发秩序混乱及资源环境问题提供科学依据。[方法] 基于乌鲁木齐市2000,2010和2018年3期“三生”空间矢量数据,借助GIS空间分析、地统计分析等方法,分析“三生”空间演变特征,并构建网格尺度下的生态风险指数,对该地区生态风险时空分异特征进行定量评价。[结果] ①研究期间,研究区生活生产空间面积增加明显,增长率高达169.78%,生态生产空间面积平缓上升,生态空间和生产生态空间面积下降率达到4.27%和21.79%。“三生”空间综合动态度为0.40%,均呈现重心南移趋势。②2000—2018年生态空间区域内以高、较高风险等级为主,比例达92.15%,其他空间内风险等级相对较低;生活生产空间及生产生态空间区域内风险等级上升。③2010—2018年,该区域的生态风险程度有所减缓,生态风险等级变化以下降为主,是风险等级上升面积的1.95倍。④研究区生态风险对“三生”空间变化的响应弹性降低,表明影响生态风险的因素呈现多样化的特征。[结论] ①近20 a来该区域生活生产空间面积明显扩张,增加了606.99 km²,主要由其周边的生态空间以及生产生态空间转入; ②该区域生态安全状况后期趋于好转,但依旧属于中高风险地区,需要对生态系统极不稳定的生态空间加强管理。     

Using multi-source data to map and model the predisposition of forests to wind disturbance

Natural disturbances such as wind are known to cause threats to ecosystem services as well as sustainable forest ecosystem management. The objective of this research was to better understand and quantify drivers of predisposition to wind disturbance, and to model and map the probability of wind-induced forest disturbances (P_DIS) in order to support forest management planning. To accomplish this, we used open-access airborne light detection and ranging (LiDAR) data as well as multi-source National Forest Inventory (NFI) data to model P_DIS in southern Finland. A strong winter storm occurred in the study area in December 2011. High spatial resolution aerial images, acquired after the disturbance event, were used as reference data. Potential drivers associated with P_DIS were examined using a multivariate logistic regression model. The model based on LiDAR provided good agreement with detected areas susceptible to wind disturbance (73%); however, when LiDAR was combined with multi-source NFI data, the results were more promising: prediction accuracy increased to 81%. The strongest predictors in the model were mean canopy height, mean elevation, and stem volume of the main tree species (Norway spruce and Scots pine). Our results indicate that open-access LiDAR data can be used to model and map the probability of predisposition to wind disturbance, providing spatially detailed, valuable information for planning and mitigation purposes.     

秦淮河流域土地利用/覆被变化对蒸散量变化的贡献

为评估城市化造成的土地利用/覆被类型变化（Land use/cover change,LUCC）对流域尺度蒸散量变化的影响,选取长三角地区秦淮河流域为研究区,基于Landsat系列卫星数据和站点气象数据,构建决策树模型,提取2000年和2013年土地利用/覆被类型数据,同时借助SEBAL模型估算研究区四季典型日（春季：2014-05-26、夏季：2013-08-11、秋季：2013-10-14、冬季：2014-01-02）栅格尺度蒸散,探讨2000?2013年秦淮河流域主要土地利用/覆被类型间转化过程对流域尺度日蒸散量变化的贡献。结果表明：（1）相较于2000年,2013年秦淮河流域不透水面增加183.8%,而水稻田、旱地、林地和水域分别减少19.1%、10.7%、12.8%和9.5%。2000-2013年主要土地利用/覆被类型转化方向包括水稻田→不透水面、旱地→不透水面、水稻田→旱地和旱地→水稻田,转化面积分别为208、168、282和232km2;（2）仅考虑LUCC的影响,对比2000年,2013年研究区流域尺度日蒸散总量在四季典型日分别减少134万、109万、60万和5万m3。在春、夏、秋三季典型日,水稻田和旱地向不透水面转化过程造成的贡献率分别为-58.5%、-59.5%、-54.4%和-35.1%、-36.3%、-39.8%,负贡献会抵消旱地向水稻田转化过程造成的正贡献（分别为16.8%、16.3%、5.7%）,导致春、夏、秋三季典型日流域尺度日蒸散量下降;而在冬季典型日,水稻田向不透水面、旱地向不透水面和水稻田向旱地转化过程造成的负贡献（分别为-48.8%、-20.5%和-31.8%）会抵消旱地向水稻田转化过程造成的正贡献（26.1%）,导致冬季典型日流域尺度日蒸散量下降。总体而言,2000?2013年秦淮河流域城市化带来土地利用/覆被的显著变化,使蒸散较高的水稻田和旱地向蒸散较低的不透水面大面积转化,导致流域尺度日蒸散量在四季均呈下降趋势。     

Object-based forest biomass estimation using Landsat ETM+ in Kampong Thom Province, Cambodia

Information about forest biomass distribution is important for sustainable forest management and monitoring fuelwood supply. The objective of this study is to develop an accurate forest biomass map for Kampong Thom Province, Cambodia. We used a new technique (object-based approach) and a conventional technique (pixel-based approach) for the estimation of forest biomass using Landsat Enhanced Thematic Mapper Plus (ETM+). The object-based approach created segments of images, and calculated statistical and textural attributes. Our results showed that estimation accuracy of the object-based approach, with the use of band 1 and an exponential fit, was the best (R ² = 0.76), and this accuracy was comparable to that of the pixel-based approach (R ² = 0.67). Although several textural variables were related to forest biomass, they did not contribute significantly to improvement of estimation accuracy. However, the object-based method can be used for image segmentation so that the image objects are spectrally more homogeneous within individual regions than with their neighbors. Hence, they can be regarded as management units for policy-related spatial decisions. Therefore, it is possible to select either of the two methods depending upon what the situation demands.