砒砂岩区土地利用与土地覆盖动态变化分析

本文应用TM影像,采用决策树方法进行遥感信息提取,对晋陕蒙砒砂岩区1998、2003和2008年的土地利用与土地覆盖格局进行了分析,结果表明,各景观类型中沙地景观面积变化最显著。研究结果为进一步开展研究区域景观动态变化模拟与预测提供了科学依据。     

基于Landsat影像的土地覆盖变化信息提取方法研究——以贵阳市为例

基于贵阳市中部地区2017年和2019年Landsat8 OIL地表反射率数据,采用图像差值法、归一化植被指数差值法、主成分分析差值法3种方法进行土地覆盖变化信息的提取.精度评价结果表明:主成分分析差值法虽然漏检率高于归一化植被指数差值法,但正检率和错检率均明显优于其他2种方法,是3种方法中更适合该研究区提取土地覆盖变...     

国际土地利用与土地覆盖变化对生态环境影响的研究

土地利用与土地覆盖变化作为全球变化的一个重要内容,对全球生态环境产生了巨大的影响,一方面通过影响气候、土壤、水文以及地貌而对自然环境产生了深刻的影响,另一方面则造成了生态系统的生物多样性、物质循环与能量流动以及景观结构的巨大变化,使得生态系统的结构和功能发生了改变。文中介绍了国际上土地利用与土地覆盖变化对生态环境影响的最新研究进展,并对相关研究在未来的发展进行了探讨。     

1985—2015年滦河下游典型区域土地覆盖/土地利用时空变化及其影响因素分析

为探究滦河下游典型区域土地覆盖/土地利用时空变化规律及其影响因素,利用1985—2015年每隔5年的遥感影像及其他辅助数据,采用监督分类的最大似然法提取不同时间段各土地类型,分析了滦河下游土地覆盖/土地利用的时空变化规律和影响因素。结果表明:1)耕地面积近30年呈高速率下降的趋势,但仍是滦河下游的主要土地覆盖类型。2)总体上,从1985—2015年林地与草地变化表现上升趋势,林地上升速率为15.78km2/5 a;草地上升速率为9.23 km2/5 a。3)耕地面积变化呈持续高速下降趋势,下降速率为103.8 km2/5 a。建筑用地呈上升趋势,2015年建筑用地面积为1985年的3倍多,其近30年来的整体增加速率为83.00km2/5 a;研究区水域面积呈波动下降的趋势,年变化率为-4.11km2/5 a。4)城镇扩张是影响滦河下游生态环境的主要因素。     

中国生态区划分与评价和保护建设的研究(Ⅳ)

生态区评价是国际上新近发展起来的一种科学方法和实践。有利解决资源开发利用保护生态环境的矛盾。中国生态区划分以地面景观为标准，并建立二级分类系统，区一亚区，同时充分利用政府行为。将全国共划分为10个一级生态区；天然林保护生态区、自然保护区生态区、水土保持生态区、防护林生态区、荒漠生态区、湿地生态区、林业生态区、草原生态区、农业生态区、青藏高原高寒生态区。     

内蒙古自治区呼伦贝尔沙地耕地(局部)变化分析

利用四期TM卫片,通过实地验证,对呼伦贝尔沙地境内的耕地变化进行研究、分析、为遏制草原开垦、防止草原荒漠化提供依据。     

中国生态区划分与评价和保护建设的研究(Ⅶ)

生态区评价是国际上新近发展起来的一种科学方法和实践。有利解决资源开发利用保护生态环境的矛盾。中国生态区划分以地面景观为标准，并建立二级分类系统，区一亚区，同时充分利用政府行为。将全国共划分为10个一级生态区；天然林保护生态区、自然保护区生态区、水土保持生态区、防护林生态区、荒漠生态区、湿地生态区、林业生态区、草原生态区、农业生态区、青藏高原高寒生态区。     

中国生态区划分与评价和保护建设的研究(Ⅱ)

生态区评价是国际上新近发展起来的一种科学方法和实践，有利解决资源开发利用保护生态环境的矛盾，中国生态区划分以地面景观为标准，并建立二级分类系统，区一亚区，同时充分利用政府行为，将全国共划分为10个一级生态区；天然林保护生态区，自然保护区生态区，水土保持生态区，防护林生态区，荒漠生态区，湿地生态区，林业生态区，草原生态区，农业生态区，青藏高原高寒生态区。     

基于CBERS影像的土地覆盖动态监测方法研究

准确地从遥感影像通过分类方法获取土地覆盖信息是一项基础性的重要课题.在建立土地覆盖分类体系的基础上,对株洲市1999年、2003年和2007年3个时相CBERS星CCD数据进行监督分类,提取土地覆盖信息,并分析其动态变化过程.结果表明:在我国中部丘陵地区,利用多时相CBERS星CCD数据开展土地覆盖变化遥感动态监测取得了较理想的效果;1999年至2007年间,株洲市林地、水体和城镇居民点面积所占比重逐渐提高,林地和城镇居民点面积增幅较大,增速呈放缓趋势,从而造成农用地和其他土地面积减少,这可为株洲市合理利用土地资源和地区可持续发展提供一定的科学依据.     

基于Landsat8的若尔盖县沙化监测区NDVI植被覆盖变化特征分析

以若尔盖县第五次沙化监测图斑区为研究区,采用2013年、2015年、2017年3个年度10月初的Landsat?8影像提取NDVI,通过像元二分模型反演植被覆盖度(FC),再将NDVI和FC进行分级后,进行各级别的面积转移矩阵分析,同时也与沙化程度进行相关性分析.研究表明:(1)NDVI和FC从2013年、2015年、...     

Dynamic of China’s cultivated land and landcover changes of its typical regions based on remote sensing data

Using the multi-temporal Landsat data and survey data of national resources, the authors studied the dynamics of cultivated land and landcover changes of typical ecological regions in China. The results of investigation showed that the whole distribution of the cultivated land shifted to Northeast and Northwest China, and as a result, the ecological quality of cultivated land dropped down. The seacoast and cultivated land in the area of Yellow River Mouth expanded by an increasing rate of 0.73 km·a⁻¹, with a depositing rate of 2.1 km·a⁻¹. The desertification area of the dynamic of Horqin Sandy Land increased from 60.02% of the total land area in 1970s to 64.82% in 1980s but decreased to 54.90% in early 1990s. As to the change of North Tibet lakes, the water area of the Namu Lake decreased by 38.58 km² from year 1970 to 1988, with a decreasing rate of 2.14 km²·a⁻¹. Foundation Item: This paper was supported by National Natural Science Foundation of China (Grant No. 39900084) and KZCX1-10-07. Biography: ZHANG Jia-hua (1966-), male, Ph. Doctor, Associate professor in START, Institute of Atmospheric Physics, Chinese Academy of Sciences. Responsible editor: Chai Ruihai     

Establishing evaluation index system for desertification of Keerqin sandy land with remote sensing data

科尔沁位于我国东北部,地处东北平原向内蒙古高原的过渡地带(42°41'-45°15'N,118°35'-123°30'E),是受荒漠化影响较重的地区。利用外业调查数据,依据地表形态和生态状况的变化,确定了植被盖度、裸沙地占地百分比和土壤质地3 项评价指标,并建立了基于遥感的科尔沁沙质荒漠化评价指标体系,其中裸沙地占地百分比用混合像元分解的方法获得。利用外业调查的数据对该指标体系进行验证,结果表明该指标体系适于研究区域的荒漠化评价。表4参11。     

基于RS的长株潭绿心区植被覆盖动态变化研究

以2000年、2005年、2011年3个时期的landsat5TM遥感影像为数据源,利用像元二分法模型反演三个时期的植被覆盖度,并研究3期植被覆盖度变化特征、植被覆盖度转移矩阵。结果表明:研究区植被覆盖状况良好,3期Ⅳ级和Ⅴ级植被覆盖度(f_c0.5)区域的面积和占总面积百分比均为79%以上。2000—2011年,研究区植被覆盖度总体呈下降趋势,2000年平均植被覆盖度为0.78,2005年平均植被覆盖度为0.72,2011年平均植被覆盖度为0.70。     

EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements

The overall objective of this study was to combine national forest inventory data and remotely sensed data to produce pan-European maps on growing stock and above-ground woody biomass for the two species groups “broadleaves” and “conifers”. An automatic up-scaling approach making use of satellite remote sensing data and field measurement data was applied for EU-wide mapping of growing stock and above-ground biomass in forests. The approach is based on sampling and allows the direct combination of data with different measurement units such as forest inventory plot data and satellite remote sensing data. For the classification, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used. Comprehensive field measurement data from national forest inventories for 98,979 locations from 16 countries were used for which tree species and growing stock estimates were available. The classification results were evaluated by comparison with regional estimates derived independently from the classification from national forest inventories. The validation at the regional level shows a high correlation between the classification results and the field based estimates with correlation coefficient r = 0.96 for coniferous, r = 0.94 for broadleaved and r = 0.97 for total growing stock per hectare. The mean absolute error of the estimations is 25 m³/ha for coniferous, 20 m³/ha for broadleaved and 25 m³/ha for total growing stock per hectare. Biomass conversion and expansion factors were applied to convert the growing stock classification results to carbon stock in above-ground biomass. As results of the classification, coniferous and broadleaved growing stock as well as carbon stock of the above-ground biomass is mapped on a wall-to-wall basis with a spatial resolution of 500 m × 500 m per grid cell. The mapped area is 5 million km², of which 2 million km² are forests, and covers the whole European Union, the EFTA countries, the Balkans, Belarus, the Ukraine, Moldova, Armenia, Azerbaijan, Georgia and Turkey.     

Estimation of soil organic carbon based on remote sensing and process model

The estimation of the soil organic carbon content (SOC) is one of the important issues in the research of the global carbon cycle. However, there are great differences among different scientists regarding the estimated magnitude of SOC. There are two commonly used methods for the estimation of SOC, with each method having both advantages and disadvantages. One method is the so called direct method, which is based on the samples of measured SOC and maps of soil or vegetation types. The other method is the so called indirect method, which is based on the ecosystem process model of the carbon cycle. The disadvantage of the direct method is that it mainly discloses the difference of the SOC among different soil or vegetation types. It can hardly distinguish the difference of the SOC in the same type of soil or vegetation. The indirect method, a process-based method, is based on the mechanics of carbon transfer in the ecosystem and can potentially improve the spatial resolution of the SOC estimation if the input variables have a high spatial resolution. However, due to the complexity of the process-based model, the model usually simplifies some key model parameters that have spatial heterogeneity with constants. This simplification will produce a great deal of uncertainties in the estimation of the SOC, especially on the spatial precision. In this paper, we combined the process-based model (CASA model) with the measured SOC, in which the remote sensing data (AVHRR NDIV) was incorporated into the model to enhance the spatial resolution. To model the soil base respiration, the Van’t Hoff model was used to combine with the CASA model. The results show that this method could significantly improve the spatial precision (8 km spatial resolution). The results also show that there is a relationship between soil base respiration and the SOC as the influence of environmental factors, i.e., temperature and moisture, had been removed from soil respiration which makes the SOC the most important factor of soil base respiration. The statistical model of soil base respiration and the SOC shows that the determinant coefficient (R ²) is 0.78. As the method in this paper contains advantages from both direct and indirect methods, it could significantly improve the spatial resolution and, at the same time, keep the estimation of SOC well matched with the measured SOC. __________ Translated from Journal of Remote Sensing, 2007, 11(1): 127–136 [译自: 遥感学报]     

利用迁移学习进行长时序遥感影像分类的影响因素和策略

长时间序列遥感影像分类是研究区域自然资源和土地利用时空变迁的重要基础.传统的区域长时序遥感影像分类,需要逐景影像选取样本进行分类,存在样本复用性低、人工工作繁复等问题;而迁移学习作为一种将已有知识应用到不同任务中的机器学习方法,可以实现遥感影像特征信息的重复利用.但长时序遥感影像由于时间跨度和物候等差异,地物光谱存在不...     

Effects of changes in land use and land cover on sediment discharge of runoff in a typical watershed in the hill and gully loess region of northwest China

Land use plays a much more important role than other factors, such as climate, soil properties, topographic features, vegetation coverage, human activities and others, in affecting soil erosion and sediment discharge. In order to understand the effects of changes in land use on sediment discharge and to provide a theoretical basis for land use planning, management and ecological restoration, we used the controlled Qiaozidong watershed and the uncontrolled Qiaozixi watershed in the third sub-region of the Loess Plateau as examples and analyzed the effects of land use and land cover on the discharge of sediments. The results show that the impact of land use and land cover on the annual amount of sediment discharge is significant. Compared with the uncontrolled watershed during similar periods, the amount of sediment discharged from the controlled watershed was reduced by 44%, 75% and 86%, respectively, in wet, normal and dry years. In the controlled watershed, compared with the period from 1986 to 1994, the amount of sediments discharged was less during the period from 1995 to 2004. The impact of land use and land cover on sediment discharge demonstrated characteristics of seasonal fluctuation. The effects of sediment reduction in the controlled watershed were greater than those in the uncontrolled watershed in May and September. In the controlled watershed, the reduction effect coincided with the distribution of rainfall. The amount of discharged flood sediments is closely correlated with rainfall, rainfall intensity in a 60 min period and the volume of flood. The rainstorm-runoff process and the rainstorm-sediment discharge process demonstrate that land cover has a strong regulatory and control function in the flood process and sediment discharge in rainstorms. For the controlled watershed, given the same precipitation frequency distribution, the average amount of sediment discharged during the land use period from 1995 to 2004 was less than that during the earlier land use period from 1986 to 1994 under every recurrent period. __________ Translated from Journal of Beijing Forestry University, 2007, 29(6): 115–122 [译自: 北京林业大学学报]     

中国东北样带植被净初级生产力时空动态及其对气候变化的响应

根据净初级生产力(NPP)遥感估算模型,重建了中国东北样带(NECT)1982–2000 年间每月的 NPP 时空序列,分析了研究时段内 NPP 的时空格局特征及其与气候因子的关系。结果表明:(1)NECT 样带植被 NPP 的空间变化趋势同降水量的空间变化十分相似,由东到西逐渐降低,二者在空间上的相关性达到了 0.84(P<0.01),说明 NECT 样带的植被 NPP在空间分布上主要受水分趋动;(2)NECT 样带植被 NPP 的年际变化主要是由各年份夏季 NPP 的变化造成的,夏季对NECT 样带植被 NPP 的年际增长贡献率最大(67.6%),二者之间的相关性达到了 0.95(P<0.01);(3)NECT 样带的植被NPP 积累期主要发生在 5–9 月份,这 5 个月的 NPP 占了全年NPP 总量的 89.8%,整个夏季(6–8 月份)的 NPP 占了全年的 65.9%,冬季(12–2 月份)的 NPP 最低,基本为 0;(4)近 19 年来的气候变化促进了 NECT 样带的植被生长,从 1980年代到 1990 年代,NPP 显著增加,年代际相对增长率为 14.3%,平均年际绝对增长趋势为 4.6 gC m-2 a-1,相对增长趋势为 1.17%,这主要是由温度升高引起的。图 6 表 1 参 36。     

Linking physical, economic and institutional constraints of land use change and forest conservation in the hills of Nepal

This paper analyses the changes in spatial patterns of agricultural land use during the period 1976–2000 along the altitudinal gradients in a watershed in Nepal. Land change patterns during this period were examined using information on land use derived from satellite images from 1976, 1990 and 2000. During the 24-year period from 1976 to 2000 agricultural land use increased by 35% at a cost of loss of forestland. Agricultural expansion was most conspicuous at higher elevations (1150–2000-m). About 36%, 18% and 6% of forestland was converted into agricultural activities from higher, middle and lower elevations respectively in the period from 1990 to 2000. Spatial distribution of living standard parameters, including farm family income and, food availability obtained from family surveys, shows a decreasing trend as the elevation increases whereas percentage of food bought shows an increasing trend. In this way it was found that, lost forest areas were smaller when located around high-income areas with good quality agricultural land and near an administrative centre as compared to areas located around low-income areas with low quality agricultural land and far from an administrative centre. Additionally, a regression model is constructed, to link the socioeconomic variables with the conversion of forestland into agricultural activities, breaking the study area into smaller zones. The spatial trajectories of these zones are then contrasted, paying particular attention to the socioeconomic conditions and institutional arrangements governing access to land resources. The study finds that while overall land change patterns in the region are largely explained by elevation and the socioeconomic conditions of people living adjacent to the forestland, more specifically, in sub-regional areas, trajectories reflect the signatures of institutions governing access to land. As sustainability of the watershed is dependent on forests, continued depletion of forest resources will result in poor economic returns from agriculture for local people together with loss of ecosystem services.     

青海湖及其周围地区沙化土地变化动态研究

青海湖地区生态环境的变化对中国乃至全球的生态变化都有指示意义,为了定期掌握本省荒漠化土地和沙化土地的现状及动态变化信息,为国家和本省制定防沙治沙与防治荒漠化的政策和长远发展规划,保护、改良和合理利用国土资源提供基础资料。本研究采用高分辨率遥感数据判读与地面调查相结合,在现状调查统计的基础上,统计各类型荒漠化和沙化土地面积的监测方法。与1994年、1999年、2004年、2009年连续四次沙化土地监测结果进行对比分析,青海湖及其周围地区从最近20年5次沙化土地监测结果看,在1999年之前的5年沙化土地是发展的,年均速率达到了2.7%,是有监测数据以来沙化土地发展速度最快的。在其之后的15年保持持续逆转的态势,逆转速率在0.25%~2.3%之间,逆转速度逐步减缓,小有起伏。同时尽管沙化土地总体在逆转,但局部地段仍在扩大,而且沙化土地面积占到区域陆地面积21.4%,流动沙地和半固定沙地占沙化土地总面积的42.6%,而露沙地和有明显沙化趋势的土地面积较大,比例较高,沙化土地的逆转具有很大的脆弱性,可逆性高。