基于决策树的辽宁省北部沙漠化信息提取研究

以沙漠化问题较突出的辽宁省北部地区为例,选取2007年Landsat 5 TM遥感影像作为基本数据源,通过对影像中耕地、林地、草地、水域等常见地物及典型沙漠化土地进行光谱特征分析和波段间的相互运算,将修改型土壤调整植被指数（MSAVI）、归一化差异水体指数（NDWI）和遥感图像缨帽变换后的土壤亮度指数（SBI）、绿度植被指数（GVI）及湿度指数（WVI）等特征变量融入决策树分类模型后进行分层分离,从而实现对沙漠化信息的高精度提取。结果显示,决策树分类法可排除提取地物时的干扰信息,是保证沙漠化土地信息快速自动提取的方法之一。     

1994—2008年河南省植被净第一性生产力及其时空变化

基于地理信息系统和卫星遥感技术,利用地面气象数据、遥感数据和土地分类等数据,根据河南省实际植被覆盖和自然地理情况,应用改进的CASA模型估算了1994—2008年间河南省植被净第一性生产力及其时空变化。结果表明：河南省植被净第一性生产力与年均温度的相关性好于植被年净第一性生产力与年降水量和年均太阳辐射之间的相关性,温度是限制河南省植被净第一性生产力的主要因子;15年来河南省植被净第一性生产力呈增加趋势,但不明显;河南省主要植被类型的净第一性生产力从大到小依次为林地、灌丛、耕地、草地、其它植被,它们随时间的变化趋势极为一致。     

基于植被指数和神经网络的热带人工林地上蓄积量遥感估测

热带森林作为陆地生态系统的组成成分之一,研究其蓄积量估测对我们了解其在全球碳循环中的地位和作用有很重要的意义.但遥感估测森林生态参数的精度如何,还是个不确定的问题.利用LANDSAT-TM数据,基于森林清查数据和遥感技术,以尾叶桉和加勒比松为例,对中国南方地区人工林蓄积量估测进行了尝试研究.首先,通过测量样方胸径、树高,建立森林蓄积量估算模型.其次,通过对比分析不同植被指数与森林蓄积量之间的关系,选择合适植被指数组合,建立多元回归和神经网络模型.结果表明:单波段TM数据和大多数植被指数与蓄积量相关性并不好.神经网络比回归分析模拟效果好.而多元回归和神经网络模型大大提高预测精度.本研究方法对大面积的森林蓄积量估测具有一定的参考价值.     

Monitoring of abandoned quarries by remote sensing and in situ surveying

In Italy quarrying causes relevant environmental damages and alterations to the land and the ecosystems. Despite the present Italian legislation requiring the restoration of the sites after exploitation, most of the quarries, both the abandoned and the still operational ones, are not restored.The objective of this work is to indicate a monitoring methodology in order to survey the present state of the quarry sites and their evolution in time, which are the basic data needed to implement an adequate land reclamation project.Such methodology has been applied to several abandoned limestone quarries in the Latina province (close to Rome), characterised by a typical Mediterranean vegetation, but it can be applied to any other kind of litology and vegetation.The land monitoring has been realised both by using remote sensing techniques, supported by a Geographic Information System of the studied area, and by in situ surveying. The in situ surveying was able to assess the capability of the remote sensing model to describe the state of each site.     

Application of Markov-chain model for vegetation restoration assessment at landslide areas caused by a catastrophic earthquake in Central Taiwan

The 921 earthquake caused a catastrophic disaster in Central Taiwan. Ten years have passed since the earthquake occurred. Vegetation succession is the basis for establishing a restoration reference which plays an important role in vegetation restoration at landslide sites. Generally, growth conditions for grass are easier and the growth rate is faster than that for trees. Therefore, grass can be considered a pioneer species or an important reference for the early vegetation succession stage. This is the reason why grass is required to be extracted from other land covers. Integrating remote sensing, geographic information system and image classification into vegetation succession models is very important. In this study, the Markov chain model was applied for vegetation restoration assessment and discussion. Chiufenershan and Ninety-nine peaks were selected as the study areas. Five SPOT satellite images are used for land cover mapping and vegetation restoration simulations. Four categories of land covers were extracted, including forest, grass, bare land and water, respectively. From the transitive probability matrix (derived from any two land covers), the results show that vegetation restoration at the Chiufenershan and Ninety-nine peaks landslide areas is ongoing, but that has been disturbed by natural disasters.     

基于MODIS数据的河南省冬小麦产量遥感估算模型

小麦是世界上最重要的粮食作物,小麦生产对中国的粮食保障起着十分重要的作用,及时、准确、大范围对小麦产量进行监测预报,对于农学经济发展和粮食政策制定具有极为重要的现实意义。对作物产量进行遥感监测的原理是建立在其遥感特征基础之上的,通过建立作物长势指标与遥感信息的定量关系,可实现对作物产量的监测预报。文章基于2009年MODIS遥感数据和气象数据,利用Arcgis和ENVI提取纯小麦像元,并提取纯小麦像元对应的NDVI、NPP和LAI,获取分县NDVI、NPP和LAI均值,利用统计软件对产量数据和分县遥感参数均值进行数据整理和分析,建立了河南省冬小麦产量估算模型。以往研究多采用遥感图像上某像元和地面调查点进行研究,具有很大的不确定性,文章以县为单位,对冬小麦平均单产和县域内冬小麦种植像元遥感参数的均值进行相关研究,提高了模型模拟精度。同时文章选用多种遥感参数和多项气象因子建立估产模型,避免了针对一个参数进行估产的局限性。在最佳时相的选择上,根据冯美辰（2010）以往的研究结果,从4月以后,5月8日和4月20Et植被指数和产量相关性最大,4月份之前冬小麦处于返青到拔节期,对产量来说还有很多不确定闪素,因此文章选用5月8El和4月20日进行冬小麦估产研究。结果表明,5月8日的估产模型优于4月20日,加入气象冈子的遥感气象估产模型优于只采用遥感参数进行估产的遥感模型。利用2010年产量数据对模型精度进行检验,遥感气象模型预测精度在70．2％N99．7％之间,平均精度为90．7％;遥感模型预测精度在68．1％到95．5％之间,平均精度为83．9％。表明遥感气象模型模拟精度更高,其精度可以满足大面积估产要求,可以对产量预报提供科学参考。     

Evaluating the environmental flows of China's Wolonghu wetland and land use changes using a hydrological model, a water balance model, and remote sensing

Environmental flows are critical to sustaining a variety of plant and animal communities in wetlands. However, evaluation of environmental flows is hampered by the problem of hydrological and ecological data shortage, especially in many developing countries such as China. Based on a hydrological model, a water balance model and remote sensing data, we assessed the environmental flows of China's Wolonghu wetland with limited data. The hydrological model provides input data for the water balance model of the wetland, and the remote sensing data can be used to assess land use changes. Integration of these two models with the remote sensing data revealed both the environmental flows of the Wolonghu wetland and the relationships between these environmental flows and land use changes. The results demonstrate that environmental flows have direct and indirect influences on the wetland ecosystem and should be linked to sustainable wetland management.     

临策铁路沿线土地沙漠化敏感性评价

以临河至策克铁路为研究对象,选择土壤、地貌、植被类型作为沙漠化敏感性评价因子,根据TM遥感影像,参考铁路沿线有关资料,并结合现场调查,编制了铁路沿线地貌、土壤和植被图.采用图层权重 - 级别打分叠加模型,对铁路沿线土地沙漠化敏感性进行评价.结果表明,临策铁路大部分位于沙漠化高度敏感区,占全线长度的54.5%;极度敏感区占4.4%.这些区域也是风沙流主要分布地区,在铁路工程施工期及运营期应该采取有效保护措施,防止沙漠化土地的扩大与蔓延以及风沙流的加剧.     

半干旱黄土区退耕还林十年植被恢复变化分析——以陕西吴起县为例

黄土高原退耕还林（草）政策实施已逾10 a,了解植被恢复变化状况及存在的问题,对于制定和完善生态环境治理方略具有重要意义。以吴起县为例,基于实地调查及遥感等数据,对退耕还林（草）以来植被覆盖度、主要植被类型变化及不同立地条件下植被恢复变化的差异进行了定量分析。结果表明：2000年至2009年,植被覆盖度大于30%的面积在全县总面积中的比例由不足1%上升至91.96%;其中缓坡立地类型上的乔灌林地类型面积增长最为显著,而阳向陡坡等恶劣生境下的植被恢复缓慢;有林地、灌木林地及疏林地均呈现规模增大趋势,属扩张状态;中覆盖度草地、低覆盖度草地、坡耕地及耕地呈现规模减少趋势,属缩减状态。     

崇明东滩景观格局的生态学分析与评价

在崇明岛功能区划的基础上,利用2006年的遥感影像对崇明东滩的景观类型进行解译,并对景观格局变化和植被覆盖度进行了分析与评价。结果表明:崇明东滩的景观面貌已经由原始潮滩演化出目前多达11种斑块类型。从景观空间形态指标和景观组分指标分析结果来看,崇明东滩的生境破碎化趋势已经显现,但从景观空间关系指标和Shannon均匀性指标分析结果来看,景观聚集度和连通度尚处于较高水平(分别为96.27和99.15),均匀度尚较大(0.59)。崇明东滩的植被覆盖度主要集中在0.3至0.9之间,植被覆盖度整体上尚处于较高水平。     

Temporal-spatial dynamics of vegetation variation on non-point source nutrient pollution

The temporal-spatial interaction of land cover and non-point source (NPS) nutrient pollution were analyzed with the Soil and Water Assessment Tool (SWAT) to simulate the temporal-spatial features of NPS nutrient loading in the upper stream of the Yellow River catchment. The corresponding land cover data variance was expressed by the normalized difference vegetation index (NDVI) that was calculated from MODIS images. It was noted that the temporal variation of land cover NDVI was significantly correlated with NPS nutrient loading. The regression analysis indicated that vegetation not only detained NPS nutrient pollution transportation, but also contributed to sustainable loading. The temporal analysis also confirmed that regional NDVI was an effective index for monthly assessment of NPS nitrogen and phosphorus loading. The spatial variations of NPS nutrient loading can be classified with land cover status. The high loadings of NPS nitrogen in high NDVI subbasins indicated that forestry and farmland are the main critical loss areas. Farmland contributed sustainable soluble N, but the loading of soluble and organic N from grassland subbasins was much lower. Most P loading came from the areas covered with dense grassland and forestry, which cannot directly discharge to local water bodies. However, some NPS phosphorus from suburban farmland can directly discharge into adjacent water bodies. The interactions among nutrient loading, NDVI, and slope were also analyzed. This study confirmed that the integration of NPS modeling, geographic information systems, and remote sensing is needed to understand the interactive dynamics of NPS nutrient loading. Understanding the temporal-spatial variation of NPS nutrients and their correlations with land cover will help NPS pollution prevention and water quality management efforts. Therefore, the proposed method for evaluating NPS nutrient loading by land cover NDVI can be an effective tool for pollution evaluation and watersheds planning.     

Global burned-land estimation in Latin America using MODIS composite data.

This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.     

Satellite detection of bird communities in tropical countryside.

The future of biodiversity hinges partly on realizing the potentially high conservation value of human-dominated countryside. The characteristics of the countryside that promote biodiversity preservation remain poorly understood, however, particularly at the fine scales at which individual farmers tend to make land use decisions. To address this problem, we explored the use of a rapid remote sensing method for estimating bird community composition in tropical countryside, using a two-step process. First, we asked how fine-grained variation in land cover affected community composition. Second, we determined whether the observed changes in community composition correlated with three easily accessible remote sensing metrics (wetness, greenness, and brightness), derived from performing a tasseled-cap transformation on a Landsat Enhanced Thematic Mapper Plus image. As a comparison, we also examined whether the most commonly used remote sensing indicator in ecology, the Normalized Difference Vegetation Index (NDVI), correlated with community composition. We worked within an agricultural landscape in southern Costa Rica, where the land comprised a complex and highly heterogeneous mosaic of remnant native vegetation, pasture, coffee cultivation, and other crops. In this region, we selected 12 study sites (each < 60 ha) that encompassed the range of available land cover possibilities in the countryside. Within each site, we surveyed bird communities within all major land cover types, and we conducted detailed field mapping of land cover. We found that the number of forest-affiliated species increased with forest cover and decreased with residential area across sites. Conversely, the number of agriculture-affiliated species using forest increased with land area devoted to agricultural and residential uses. Interestingly, we found that the wetness and brightness metrics predicted the number of forest- and agriculture-affiliated species within a site as well as did detailed field-generated maps of land cover. In contrast, NDVI and the closely correlated greenness metric did not correlate with land cover or with bird communities. Our study shows the strong potential of the tasseled-cap transformation as a tool for assessing the conservation value of countryside for biodiversity.     

Ecological modelling of nitrate pollution in small river basins by spreadsheets and GIS

With the increasing importance and awareness of water quality in the small basins, the modelling system is developed for monitoring and predictions of surface water pollution. The compartment model deals with basin characteristics extended by land cover attributes. The parameters of the model are estimated by experimental data of water quality together with land cover types that serve as nutrient detention media or transformers. The study examines methodology to determine the potential areas of nitrate pollution from point and non-point sources by remote sensing techniques. Classification of water, agricultural, forest and urban areas is processed with satellite images (LANDSAT 7). Whereas the agricultural and urban areas act as sources of pollution, forest zones operate as sinks. The nitrate levels are decreased downstream, if the proportion of the forest inside contribution zones increases. The modelling system is used to simulate amounts of nitrates in each compartment of the stream during the monitored period of one year. The number of compartments and their lengths are estimated on the basis of morphology of the basin. Simulation of the dynamic model is carried out with the TabSim. Geographic information system (GIS) and remote sensing tools are used to manage and estimate nitrate inflows from point and non-point sources of pollution. The article presents the spatial and time variation of the nitrate (NO₃⁻) within the basin of the stream Rakovnický (the west part of Bohemia, the whole area of 368 km²). It is shown that the model approach extended by the GIS and remote sensing can support decision-making process for better management practices in the basins.     

Changes in wetland landscape patterns on Yinchuan Plain,China

Wetlands, with their many values and important functions, are precious resources. They have, however, undergone great changes during economic development and population growth. Relying on recent advances in remote sensing and geographic information system (GIS) techniques, this paper probes changes in wetland landscapes on Yinchuan Plain during 1978–2006. A series of remote sensing images was used to identify wetland landscape types. Landscape pattern indices, such as patch number, patch density, landscape shape, and Shannon's diversity, evenness, and contagion indices were calculated with GIS and landscape analysis software. Changes in wetland landscape patterns on Yinchuan Plain were analyzed. The analysis show that the total area of wetlands on Yinchuan Plain decreased from 391,540,239 m² in 1978 to 267,979,957 m² in 2006, a significant change over 28 years. The area of rivers and lakes has shrunk, and the area of paddies has increased consistently, with increasing wetland fragmentation and heterogeneity. The number of patches, patch density, and landscape shape index shows that wetland landscape patterns have undergone great changes. The landscape diversity, landscape evenness, and contagion indices indicate that wetland landscapes have become less heterogeneous. We discuss the causes of these changes and the sustainable development of wetland ecosystems.     

Assessing landscape structure and pattern fragmentation in semiarid ecosystems using patch-size distributions

Spatial vegetation patterns are recognized as sources of valuable information that can be used to infer the state and functionality of semiarid ecosystems, particularly in the context of both climate and land use change. Recent studies have suggested that the patch-size distribution of vegetation in drylands can be described using power-law metrics, and that these scale-free distributions deviate from power-law linearity with characteristic scale lengths under the effects of increasing aridity or human disturbance, providing an early sign of desertification. These findings have been questioned by several modeling approaches, which have identified the presence of characteristic scale lengths on the patch-size distribution of semiarid periodic landscapes. We analyze the relationship between fragmentation of vegetation patterns and their patch-size distributions in semiarid landscapes showing different degree of periodicity (i.e., banding). Our assessment is based on the study of vegetation patterns derived from remote sensing in a series of semiarid Australian Mulga shrublands subjected to different disturbance levels. We use the patch-size probability density and cumulative probability distribution functions from both nondirectional and downslope analyses of the vegetation patterns. Our results indicate that the shape of the patch-size distribution of vegetation changes with the methodology of analysis applied and specific landscape traits, breaking the universal applicability of the power-law metrics. Characteristic scale lengths are detected in (quasi) periodic banded ecosystems when the methodology of analysis accounts for critical landscape anisotropies, using downslope transects in the direction of flow paths. In addition, a common signal of fragmentation is observed: the largest vegetation patches become increasingly less abundant under the effects of disturbance. This effect also explains deviations from power-law behavior in disturbed vegetation which originally showed scale-free patterns. Overall, our results emphasize the complexity of structure assessment in dryland ecosystems, while recognizing the usefulness of the patch-size distribution of vegetation for monitoring semiarid ecosystems, especially through the cumulative probability distributions, which showed high sensitivity to fragmentation of the vegetation patterns. We suggest that preserving large vegetation patches is a critical task for the maintenance of the ecosystem structure and functionality.     

Modelling the spatial distribution of montane and subalpine forests in the central Alps using digital elevation models

The analysis of complex interactions between spatial distribution patterns of site factors and vegetation types is crucial for understanding high mountain ecosystems, especially in the view of a changing climate. Therefore, in the present study, a GIS and remote sensing-based approach is followed to produce a vegetation map for a study area in the Western Alps (Switzerland). Two major forest alliances are chosen for analysis: subalpine coniferous forest Vaccinio-Piceion/Larici-Pinetum cembrae and montane oak forest Quercion pubescenti-petraeae. As spatial information on site factors is commonly lacking in mountain areas, the use of a digital elevation model (DEM) is a potential substitute for use in vegetation analyses: it highly correlates with temperature, moisture, geomorphological processes and disturbance factors. Thus, it is important to analyse the capabilities of a DEM for indicating habitat conditions in a landscape characterised by high topodiversity and a patchwork of microclimatic habitats.For the purpose of identifying the potential of landform parameters for the indication of forest habitat structures in the present study, 24 primary and secondary landform parameters have been derived, indicating temperature and moisture distribution, exposure towards wind, snow, etc. Quantitative analyses were performed using statistical means such as contingency correlation coefficients and principal components analysis. The results formed the basis for the development of parallel-epiped-vegetation models (PED) used to simulate the spatial distribution patterns of the subalpine coniferous and the montane oak forest. It can be shown that topographic variables derived from a DEM at a spatial resolution of 25 m are very useful for indicating habitats of large forest types. Additionally potential forest sites in the cultural landscape, removed by human logging, can be reconstructed.Inaccuracies within the simulation results can partly be attributed to the insufficient parameterisation of geomorphologic activity and to poor spatial resolution of the DEM as compared to the vegetation data. Although the lack of information on the human dimension leads to some uncertainties in the interpretation of spatial patterns of vegetation, the exclusive use of topographic variables in vegetation models for the indication of forest habitats is very promising.     

半干旱区人工封育草场植物群落物种多样性与复杂性研究──以宁夏盐池为例

围栏封育促进植被恢复效果研究方法很多,其中通过研究植被的群落特征及物种多样性来阐述恢复状况仍是比较常用和有效的手段,但多样性测度对生物群落的自组织及有序性方面的特征描述欠缺,鉴于此,多样性与复杂性测度结合起来研究群落结构与功能显得更有意义。研究人工封育对植被恢复过程中群落的多样性与复杂性的影响,必然有助于揭示生态恢复过程机理。目前,利用多样性与复杂性测度相结合来对群落结构进行量化研究不多,用于对草原生态系统植物群落结构研究更少。本文通过样地调查,利用多样性和复杂性指数相结合定量研究半干旱区人工封育草场植物群落物种多样性、复杂性随封育年限的变化规律,并对比分析复杂性与物种多样性之间的相关性。结果表明,（1）老封育区、新封育区丰富度指数整体高于对照区,说明封育有利于物种丰富度的增加。但随封育时间的延长,封育区的优势种占据主要的资源空间,丰富度指数降低。长时间封育,草场植被丰富度将发生规律性波动变化,低峰值和高峰值出现频率均约为4~5年/次。老封育区、新封育区的SW、SP多样性指数值大部分也高于对照区,说明封育措施增加草场植被的多样性。物种多样性指数受降水影响显著,当降水量增加或减少时,多样性指数也相应出现增加或减少,但降水影响效应具有一定的滞后性。老封育区、新封育区均匀度变化比较平稳,且指数值高于对照区,说明封育有利于均匀度的增加。（2）老封育区、新封育区总复杂性指数、无序结构复杂性指数值大部分比对照区指数值高,且指数波动相对平稳,说明封育区群落结构比对照区稳定,更适合荒漠草原植被的生长,封育增加了群落总复杂性、无序结构复杂性。封育也提高群落有序结构复杂性,但?     

遥感与GIS支持下的城市绿地信息提取方法研究--以深圳市为例

城市绿地作为城市结构中的自然生产力主体，在城市系统中起着重要作用。传统的城市绿地调查多采用人工普查并结合统计学方法进行城市绿地调查，需要投入大量的人力和资金，但得到的数据精度和现时性都较差，而采用高分辨率遥感卫星数据与地理信息系统相结合的方法，可以达到对城市绿地遥感数据的快速特征提取和准确的空间统计分析。文章采用基于遥感和GIS相结合的方法，并以深圳市为例，进行了城市绿地特征提取方法的研究和应用分析。     

Optimizing model for land use/land cover retrieval from remote sensing imagery based on variable precision rough sets

The suitable spectral mode in remote sensing is often desirable to facilitate the inversion of ecological environment and landscape. This paper put forward an optimizing model based on variable precision rough sets (VPRS) for the land cover discrimination in wetland inventory. In the case study of Lake Baiyangdian which has important ecological functions to the northern China, this model is established successfully according to the domain-experts knowledge. The procedure is as follows. First step is data collection, including remote-sensing data (e.g., Landsat-5 TM bands), the digitized relief maps, and statistical yearbooks. Second, the remote sensing imagery (RSI) and relief maps are co-registered into the same resolution. Third, a condition set, including various attributes is derived from spectral bands, band math or ratio indices based on previous studies, at the same time, the decision set is derived from true land types after investigation and validation. Then, the remote sensing decision table (RSDT) is constructed by linking condition set with decision set according to the sequential pixels in RSI. Fourth, we create one forward greedy searching algorithm based on VPRS to handle this RSDT. After adjusting parameters such as β and knowledge granularity diameter (KGD), we obtain the stable optimized results. Comparative experiments and evaluation show that the discrimination or retrieval accuracy of VPRS model is satisfying (overall accuracy: 87.32% and KHAT: 0.84) and better than original data. Moreover, data dimension has been decreased dramatically (from 12 to 3) and key attributes found by the model may be useful for specific retrieval in wetland inventories.