Accuracy assessments of the GLOBCOVER dataset using global statistical inventories and FLUXNET site data

The spatio-temporal distribution of land cover provides fundamental data for global climate and environmental change research. In recent decades, five global land cover maps have been produced based on remote sensing data sources and methodologies. Related research have shown that the availability and quality of the first four global land cover datasets are poor at the regional or the continental scale for a variety of reasons. There is still no consensus on the accuracy of the latest global land cover map. Based on comparison of the land cover dataset with the statistical cropland data from FAO and the FLUXNET site data, this paper discusses the accuracy of the fifth global land cover map, namely, the GLOBCOVER dataset, at different spatial scales. At the global scale, the cropland area obtained from the GLOBCOVER dataset is greater than that of the FAO statistical data by 47.06–84.49%, and the land cover types of the GLOBCOVER dataset have a 65.02% consistency with that of the FLUXNET site data. At the continental scale, the difference between cropland areas obtained from the GLOBCOVER dataset and the statistical cropland area vary from ?43.42% to 502.36%; continents that have a more accurate cropland area compared to the FAO statistical data tend to be less consistent with the FLUXNET site data. In general, North America has a higher accuracy and Oceania has a lower accuracy. At the country scale, the accuracy estimates vary sharply over a wide range: between ?100.00% and 190670.37%. It is recommended that future studies should pay careful attention to the data validation step before using the GLOBCOVER dataset for any particular problem. Future studies are also required for the development of a universal land cover classification system and advanced algorithms for remote sensing classification of global land cover maps.     

Spatial and temporal dynamics of methane emissions from agricultural sources in China

Agricultural activities contribute significantly to the global methane budget. Agricultural sources of methane are influenced by land‐use change, including changes in agricultural area, livestock keeping and agricultural management practices. A spatially explicit inventory of methane emissions from agriculture is made for China taking the interconnections between the different agricultural sources into account. The influence of land‐use change on methane emissions is studied by linking a dynamic land‐use change model with emission calculations. The land‐use change model calculates changes in rice area and livestock numbers for a base‐line scenario. Emissions are calculated for 1991 based on land‐use statistics and for 2010 based on simulated changes in land‐use patterns. Emissions from enteric fermentation and manure management are based on emission factors, while emissions from rice paddies involve the calculation of total organic carbon added to rice paddy soils and assume that a constant fraction is emitted as methane. Spatial patterns of emissions are presented for the different sources. For the land‐use scenario considered it is expected that total methane emissions from agricultural sources in China increase by 11% while the relative contribution of rice fields to the emission decreases. Emissions from manure management are expected to become more important. These results indicate that agencies should anticipate changes in source strengths as a consequence of land‐use changes when proposing mitigation strategies and future national greenhouse gas budgets.     

敦煌市土地利用/覆盖变化特征及成因分析

利用ArcGIS9.2软件,结合野外调查,对敦煌市1987、1996和2007年3期Land-sat5-TM遥感影像进行解译,并分8个类型分析了土地利用/覆盖变化的特征及成因。结果表明:近20年来敦煌市呈现出植被覆盖程度不断降低、覆盖面积减小的趋势,其中耕作区、城建用地和无植被区面积净增,其他5类用地面积净减;8类用地类型之间互有转换,转移的主要方向是部分草地和无植被区转变为耕作区,水域湿地和灌木林地转变为草地,草地由高覆盖、中覆盖、低覆盖到无植被区逐次转变;除了耕作区边缘植被覆盖程度有所增加外,其他区域退化趋势明显;引起LUCC的自然因素中气温升高的影响较大,而人文因素中土地开垦、增加灌溉的影响较大。     

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km² area, whereas the increase in such depth reached only 10 mm/year in a 243-km² area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km² of land area by 2030, a significant decrease from the 747 km² they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities.     

Effects of nitrogen mineralization on paddy rice yield under low nitrogen input conditions in irrigated rice-based multiple cropping with intensive cropping of vegetables in southwest China

The farm household responsibility system (FHRS) was adopted in Chinese rural areas during the economic reform in the early 1980s. Since then, many farm households have increased cropping intensity by using large quantities of nitrogen (N) fertilizers in their responsible fields to increase agricultural income. However, intensive cropping systems with low N input are still common in remote places of the southwestern region of China. Maintenance and improvement of soil quality in intensive cropping systems is critical for sustaining agricultural productivity and environmental quality for future generations. The effects of intensive cropping of vegetables on paddy rice (Oryza sativa L.) yield using small quantities of N fertilizers through N mineralization of paddy soil in irrigated rice-based multiple cropping systems were studied in 15 paddy fields in Sichuan Province, China for 3 years. Intensification of vegetable cropping with negative N balance and removal of vegetable crop residues has greatly decreased total N (TN) contents in paddy soil leading to low levels of effective cumulated soil temperature and thickness of plow layer. As a result, the N mineralization in paddy field during paddy rice growing period was decreased. In addition to the low levels of chemical fertilizer N input and residual mineral N input, the lower level of N mineralization in paddy fields and low N recovery efficiency decreased the amount of N accumulated in aboveground biomass of paddy rice at maturity, resulting in limited rice yields. The amount of mineralized N only correlated with TN (partial correlation analysis). Therefore, in paddy fields with very low N input, the N mineralization in paddy soil during the paddy rice-growing period was the major limiting factor affecting the total yield increases. In addition, a decline in soil fertility can be determined using TN as an indicator. To improve paddy rice yield and avoid soil deterioration, the development and adoption of rational soil management programs are needed. These include input of plant residues, conscientious soil tillage for the maintenance of soil temperature and thickness of the plow layer, and the split application of fertilizer for the improvement of N recovery efficiency.     

Assessing the application of a geographic presence-only model for land suitability mapping

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This paper assesses the adaptation and application of the presence-only geographic species distribution model, MaxEnt, for agricultural crop suitability mapping in a rural Thailand where lowland paddy rice and upland field crops predominant. To assess this modeling approach, three independent crop presence datasets were used including a social-demographic survey of farm households, a remote sensing classification of land use/land cover, and ground control points, used for geodetic and thematic reference that vary in their geographic distribution and sample size. Disparate environmental data were integrated to characterize environmental settings across Nang Rong District, a region of approximately 1300 sq. km in size. Results indicate that the MaxEnt model is capable of modeling crop suitability for upland and lowland crops, including rice varieties, although model results varied between datasets due to the high sensitivity of the model to the distribution of observed crop locations in geographic and environmental space. Accuracy assessments indicate that model outcomes were influenced by the sample size and the distribution of sample points in geographic and environmental space. The need for further research into accuracy assessments of presence-only models lacking true absence data is discussed. We conclude that the MaxEnt model can provide good estimates of crop suitability, but many areas need to be carefully scrutinized including geographic distribution of input data and assessment methods to ensure realistic modeling results.     

Land‐use change affects water recycling in Brazil's last agricultural frontier

Historically, conservation‐oriented research and policy in Brazil have focused on Amazon deforestation, but a majority of Brazil's deforestation and agricultural expansion has occurred in the neighboring Cerrado biome, a biodiversity hotspot comprised of dry forests, woodland savannas, and grasslands. Resilience of rainfed agriculture in both biomes likely depends on water recycling in undisturbed Cerrado vegetation; yet little is known about how changes in land‐use and land‐cover affect regional climate feedbacks in the Cerrado. We used remote sensing techniques to map land‐use change across the Cerrado from 2003 to 2013. During this period, cropland agriculture more than doubled in area from 1.2 to 2.5 million ha, with 74% of new croplands sourced from previously intact Cerrado vegetation. We find that these changes have decreased the amount of water recycled to the atmosphere via evapotranspiration (ET) each year. In 2013 alone, cropland areas recycled 14 km³ less (?3%) water than if the land cover had been native Cerrado vegetation. ET from single‐cropping systems (e.g., soybeans) is less than from natural vegetation in all years, except in the months of January and February, the height of the growing season. In double‐cropping systems (e.g., soybeans followed by corn), ET is similar to or greater than natural vegetation throughout a majority of the wet season (December–May). As intensification and extensification of agricultural production continue in the region, the impacts on the water cycle and opportunities for mitigation warrant consideration. For example, if an environmental goal is to minimize impacts on the water cycle, double cropping (intensification) might be emphasized over extensification to maintain a landscape that behaves more akin to the natural system.     

东北黑土地区稻田甲烷排放时空演变及排放潜力分析

稻田甲烷排放是农业源甲烷排放的主要来源。东北黑土地区是我国最大的粮食生产基地,农业温室气体减排是实现黑土地永续利用的关键议题之一。运用稻田甲烷排放模型(CH4MOD)核算并分析了2009-2018年东北黑土地区稻田甲烷排放的时空演变特征,结合GOSAT卫星遥感数据探究了水稻生产与区域甲烷排放的时空动态联系,进一步量化了稻田甲烷对区域甲烷排放的贡献程度及不同情景下的排放潜力。结果表明,受水稻生产面积扩张和排放强度提高的影响,东北黑土地区稻田甲烷排放总量从2009年的39.05万t增加到2018年的79.53万t。东北黑土地区区域甲烷排放在季节变化和栅格单元上表现出与稻田甲烷排放较为一致的时空动态,大规模的稻田耕作可能会增加水稻生产与区域甲烷排放直接相关的可能性。随着水稻持续扩种稳产,2018年东北黑土地区水稻生产贡献了区域甲烷排放总量的15.04%,其中黑龙江省的贡献率高达31.06%。在基准发展情景下,预计2035年东北黑土地区稻田CH₄排放量较2018年增加19.5%;在粮食供给保障情景下,维持当前稻田耕作面积,水稻生产集约化程度提高,预计其稻田CH₄排放量较2018年减少0.88%;在此基础上,采取促进秸秆还田、增施有机肥、实施节水间歇灌溉等稻田管理措施将使稻田CH₄排放量增加17.8%-63.6%。以满足膳食需求和供给保障为导向,优化水稻种植结构、控制稻田耕作面积,推动技术进步、品种改良以提升单产水平,采取化肥和有机肥搭配施用、节水间歇灌溉等途径能够缓解稻田甲烷排放。研究综合运用自上而下的遥感数据和自下而上的模型运算,刻画了水稻生产与区域甲烷排放的时空联系,进一步评估了稻田甲烷的排放潜力及减排措施的减排效果,为促进东北黑土地区农业甲烷减排和生产布局优化提供了理论依据和决策参考。     

Storage and sequestration potential of topsoil organic carbon in China's paddy soils

Carbon (C) storage and sequestration in agricultural soils is considered to be an important issue in the study of terrestrial C cycling and global climatic change. The baseline C stock and the C sequestration potential are among the criteria for a region or a state to adopt strategies or policies in response to commitment to the Kyoto Protocol. Paddy soils represent a large portion of global cropland. However, little information on the potential of C sequestration and storage is available for such soils. In this paper, an estimation of the topsoil soil organic carbon (SOC) pool and the sequestration potential of paddy soils in China was made by using the data from the 2nd State Soil Survey carried out during 1979–1982 and from the nationwide arable soil monitoring system established since then. Results showed that the SOC density ranged from 12 to 226 t C ha^?1 with an area‐weighted mean density of 44 t C ha^?1, which is comparable to that of the US grasslands and is higher than that of the cultivated dryland soils in China and the US. The estimated total topsoil SOC pool is 1.3 Pg, with 0.85 Pg from the upper plow layer and 0.45 Pg from the plowpan layer. This pool size is ～2% of China's total storage in the top 1 m of the soil profiles and ～4% of the total topsoil pool, while the area percentage of paddy soil is 3.4% of the total land. The C pool in paddy soils was found predominantly in southeast China geographically and in the subgroups of Fe‐accumulating and Fe‐leaching paddy soils pedogenetically. In comparison with dryland cultivation, irrigation‐based rice cultivation in China has induced significant enrichment of SOC storage (0.3 Pg) in paddy soils. The induced total C sequestration equals half of China's total annual CO₂ emission in the 1990s. Estimates using different SOC sequestration scenarios show that the paddy soils of China have an easily attainable SOC sequestration potential of 0.7 Pg under present conditions and may ultimately sequester 3.0 Pg. Soil monitoring data showed that the current C sequestration rate is 12 Tg yr^?1. The total C sequestration potential and the current sequestration rate of the paddy soils are over 30%, while the area of the paddy soils is 26% that of China's total croplands. Therefore, practicing sustainable agriculture is urgently needed for enhancing SOC storage to realize the ultimate SOC sequestration of rice‐based agriculture of China, as the current C sequestration rate is significantly lower than the potential rate.     

Uncertainties in the 20th century carbon budget associated with land use change

Uncertainties in the 20th century carbon budget associated with the treatment of land use change (LUC) are assessed using the Canadian Centre for Climate Modelling and Analysis (CCCma) first‐generation Earth System Model (CanESM1). Eight coupled climate carbon cycle simulations are performed using different reconstructions of 1850–2000 land cover derived from historical information on changes in cropland and pasture area. The simulations provide estimates of the emissions associated with LUC, the relative contribution of changes in cropland and pasture to LUC emissions and the uncertainty associated with differences among historical data sets of crop area as well as in the manner in which the historical land cover data are constructed. The resulting estimates of the amount of biomass deforested over the 1850–2000 period range from 63 to 145 Pg C with cumulative implied LUC emissions ranging from 40 to 77 Pg C. These values of LUC emissions are considerably lower than Houghton's estimate of 156 Pg C. The year 2000 atmospheric CO₂ concentration ranges between 371.1 ± 3.7 ppm depending on the data set used and the manner in which historical land cover is constructed. This compares to the observed value of 369.6 ppm at Mauna Loa and is 17.3 ± 6.3 ppm larger than for simulations without LUC. Although increases in cropland result in the expected increase in LUC emissions, changes in pasture area decrease these emissions because of carbon sequestration in soils.     

基于RS和转移矩阵的泾河流域生态承载力时空动态评价

利用泾河流域1986、1995、2000、2008年4期遥感数据和转移矩阵分析方法,在GIS平台上,对该流域近23a的生态承载力时空变化进行了定量评价和空间化表达,结果表明,泾河流域生态承载力空间分布极不均匀,整体呈南高北低,并由东南向西北递减,由上游向下游递增的空间变化趋势,表现出与流域地貌特征,土地利用/覆被和环境禀赋相关联的地理特性和空间异质性;随着时间的推移,全流域生态承载力呈逐年降低趋势,尤其以2000年以后下降趋势明显,但流域内部不同区域的生态承载力及其各类土地生态承载力的变化幅度与趋势各有不同;3个时段内(1986-1995年、1995-2000年、2000-2008年)流域各类土地生态承载力转换频繁,转向趋势明显,且以2000年为拐点,前两时段以林地和草地生态承载力向耕地和建筑用地生态承载力转移为主,后一时段以耕地和建筑用地生态承载力向林地和草地生态承载力转移为主,导致近23a来泾河流域生态承载力及其内部组成变化均较大,说明土地利用/覆被的变化是流域生态承载力变化的主导因素,而1999年以后国家实施的退耕还林还草生态工程则是2000-2008年该流域生态承载力变化的主要驱动力。     

苏南典型城镇耕地景观动态变化及其影响因素

基于高分辨率遥感影像获得3期土地利用数据,引入景观动态度和缩减强度指数分析了辛庄镇各村水田景观减少的速度和强度;利用转移矩阵和GIS地图叠加方法分析了辛庄镇水田景观变化的时空特征;应用冗余分析方法,直观地展现了主要的水田转变方式与各影响因子的定量关系。结果表明:1991-2009年间,研究区水田景观面积比例减少了30.5%,且呈加速下降趋势;各村水田景观缩减的规模、速度和强度差异明显;减少的水田主要被工业用地、鱼塘和居住用地占用,且这种现象集中发生在主要道路与河流周围。社会经济因子和区位因子对水田变化的空间差异具有很好的解释作用,且各因子对解释不同时段水田变化的空间分异的贡献率差异显著。     

基于遥感的湿地景观格局季相分析

以中国东北地区三江平原北部为研究区域,利用2012年多季相遥感影像作为数据源,结合野外调查数据,应用面向对象的分类方法,根据影像的物候、时相等特征,提取不同月份的湿地信息,进行景观格局季相分析。结果表明:(1)研究区湿地面积、类型格局在同一年不同季节不同月份会有不同幅度的变化,总体呈现缓增骤减的态势。湿地主要分布在低洼地区,主要湿地类型为草本沼泽,其次为河流,其他湿地占总面积比例较小。(2)研究区各阶段湿地都有转化,主要发生在湿地和非湿地之间,多数表现在草本沼泽和草地之间的转化。(3)湿地分布和湿地转化面积主要集中在低海拔区域和低坡度区域,其中海拔100 m和坡度5°以下范围内的湿地分布面积和湿地转化面积占湿地总面积及湿地转化面积的绝大部分。(4)年内季节性湿地转化与降水、温度和湿地植被物候关系密切。     

Changes in soil carbon sequestration and soil respiration following afforestation on paddy fields in north subtropical China

Aims Although many studies have reported net gains of soil organic carbon (SOC) after afforestation on croplands, this is uncertain for Chinese paddy rice croplands. Here, we aimed to evaluate the effects of afforestation of paddy rice croplands on SOC sequestration and soil respiration (R s). Such knowledge would improve our understanding of the effectiveness of various land use options on greenhouse gas mitigation in China.Methods The investigation was conducted on the Chongming Island, north subtropical China. Field sites were reclaimed from coastal salt marshes in the 1960s, and soils were homogeneous with simple land use histories. SOC stocks and R s levels were monitored over one year in a paddy rice cropland, an evergreen and a deciduous broad-leaved plantation established on previous paddy fields and a reference fallow land site never cultivated. Laboratory incubation of soil under fast-changing temperatures was used to compare the temperature sensitivity (Q 10) of SOC decomposition across land uses.Important findings After 15–20 years of afforestation on paddy fields, SOC concentration only slightly increased at the depth of 0–5cm but decreased in deeper layers, which resulted in a net loss of SOC stock in the top 40cm. Seasonal increase of SOC was observed during the rice-growing period in croplands but not in afforested soils, suggesting a stronger SOC sequestration by paddy rice cropping. However, SOC sequestered under cropping was more labile, as indicated by its higher contents of dissolved organic carbon and microbial biomass. Also, paddy soils had higher annual R s than afforested soils; R s abruptly increased after paddy fields were drained and plowed and remained distinctively high throughout the dry farming period. Laboratory incubation revealed that paddy soils had a much higher Q 10 of SOC decomposition than afforested soils. Given that temperature was the primary controller of R s in this region, it was concluded that despite the stronger SOC sequestration by paddy rice cropping, its SOC was less stable than in afforested systems and might be more easily released into the atmosphere under global warming.     

1980-2010年北京市农用地碳储量对土地利用变化的响应

分析北京市农用地碳储量对土地利用变化的响应,对快速城市化和工业化区域及全国农用地低碳利用调控具有重要意义。利用1980年第二次土壤普查数据与2010年测土配方施肥项目成果土壤数据核算北京市农用地表层土壤碳储量,利用生物量遥感信息（NDVI）模型反演林地、草地植被碳储量,对北京市土地利用变化造成的农用地碳储量变化进行研究,结果表明：1）1980-2010年,北京市农用地碳储量由75.29 Tg-C增至81.13Tg-C,增加5.83 Tg-C,其中,土壤碳储量减少7.51 Tg-C,植被碳储量增加13.34 Tg-C;2）30年间,北京市农用地面积减少14.11×10⁴ hm²,其中,耕地流失最为显著,主要去向为建设用地和林地,林地面积略有增加;3）北京市用地类型保持不变的农用地土壤碳储量减少297.63×10⁴ t,植被碳储量增加1095.21×10⁴ t,共计增加797.58×10⁴ t,其中,用地类型保持不变的耕地、林地碳储量增加,草地碳储量减少;4）30年间,土地利用类型转化使北京市农用地土壤碳储量减少75.71×10⁴ t,植被碳储量增加212.49×10⁴ t,共计增加136.78×10⁴ t,其他用地类型转为林地使碳储量增加,有利于碳汇的形成,林地转出为其他用地类型均会造成一定碳排放;5）平原造林、退耕还林等工程有利于增加北京市农用地固碳量。未来北京市可通过控制农用地面积减少量,优化农用地内部结构,降低用地类型间的转换频率以提高农用地碳储量。研究可为其他区域及全国在快速城市化工业化过程中提升农用地碳储量提供一定参考。     

洞庭湖退田还湖区不同土地利用方式下土壤微生物数量与酶活性特征

以钱粮湖垸为例,研究了洞庭湖退田还湖区林地(Ⅰ)、园地(Ⅱ)、旱地(Ⅲ)、水田(Ⅳ)和荒地(Ⅴ)等不同土地利用方式下的土壤微生物数量、酶活性及其典范相关关系。结果表明:5种土地利用方式下不同土层细菌、放线菌数量均以旱地最高,真菌数量以荒地最高;细菌是土壤微生物的主要类群,占全部微生物的比例为44.42%～92.93%,其次为真菌数量,所占比例为4.89%～42.76%,放线菌数量最少,所占比例为1.71%～24.52%;不同土地利用方式下0～50cm土层磷酸酶、脲酶、蛋白酶和脱氢酶活性变化范围为0.01～0.07mg.g-1.d-1、0.01～0.05mg.g-1.d-1、0.92～7.11mg.kg-1.d-1和0.01～0.38μl.g-1.d-1;土壤磷酸酶、脲酶、脱氢酶活性分别以园地、荒地、水田最低,而旱地土壤蛋白酶活性总体最低;土壤微生物典范变量(U)中,放线菌数量与之呈正相关,回归系数最大(0.174),其次为细菌数量(0.003),而真菌数量则出现负相关(-0.215);土壤酶活性典范变量(V)中,脲酶活性与之呈正相关,回归系数最大(10.557),其次为脱氢酶活性(1.616),而磷酸酶活性(-17.275)与蛋白酶(-0.041)则出现负相关。不同层次土壤微生物数量及酶活性在典范变量上的聚集趋势可为该区域土壤健康诊断与立地类型划分提供依据。     

长江三峡库区生态环境变化遥感研究进展

长江三峡库区是我国最重要的生态敏感区之一,受三峡水利工程和相关人类活动影响,其生态环境变化显著.揭示三峡库区生态系统结构、功能和生态过程的变化对于维护库区生态安全具有重要意义.生态环境遥感为此提供了关键途径,并在三峡库区生态环境研究中受到重视.现有的三峡库区生态环境变化遥感研究往往存在较大差异,难以有效反映生态环境变化和响应特征,加之生态本底和人类干扰活动的复杂性,三峡库区生态环境变化遥感研究仍面临诸多挑战.本文对库区环境变化遥感研究的发展阶段、研究尺度、遥感数据和方法等进行了系统总结,并从土地利用/覆盖变化、植被变化、水土安全、生态服务价值评价、生态系统健康与生态规划5个方面对库区生态环境变化遥感研究进展进行综述,在此基础上探讨了当前三峡库区生态环境变化遥感研究存在的问题,并提出未来研究中需重点关注的主要科学问题,以期为三峡库区生态环境管理和类似地区生态环境变化遥感研究提供参考.
     

基于NDVI假彩色合成法的土地覆被变化监测

土地覆被变化监测对区域生态系统保护、环境变化研究具有重要的作用,研究旨在提供一种基于归一化植被指数(NDVI)的假彩色合成法的土地覆被变化监测方法。该研究以黄河三角洲为研究区,以3期 Landsat TM影像(成像时间分别为1987年5月7日,1998年5月5日,2009年5月3日)为数据源,在进行相对辐射校正的基础上,生成3期NDVI图像,然后分别以三期的NDVI图像作为红、绿和蓝波段生成假彩色合成图像。基于彩色合成原理,对黄河三角洲的1987-2009年间的土地覆被变化进行了分析。结果表明:(1) 假彩色合成图像上的灰白色区域表示其土地覆被状态稳定,三个时期的NDVI值均较大,黑色区域的土地覆被状态也较稳定,但是三个时期的NDVI值均较小,而青色、绿色、红色则反映相应地区的NDVI处在不稳定状态;(2)不同的颜色反映了不同的土地覆被变化方式,较为直观地反映了土地覆被的变化特点,尤其是自然植被与农田之间的转换;(3)限于NDVI的瞬时性,该方法需要与基于遥感影像分类的方法相结合,才能更好地监测土地覆被变化。     

2000—2015年西南地区土地利用与植被覆盖的时空变化

西南地区是我国重要的生态资源区和生态脆弱区,在国家“绿水青山”战略发展中具有重要地位。本研究基于1 km空间分辨率的土地利用数据集,结合土地利用转移矩阵,定量分析2000—2015年间西南地区土地利用变化特征及其驱动力。并基于MODIS遥感植被指数,利用像元二分模型计算西南地区植被覆盖度,分析归一化植被指数(NDVI)和植被覆盖度的变化规律。结果表明: 研究期间,西南地区的主要地类是林地、农田和草地。建设用地面积增加5874 km²,增长率为55.8%;农田面积减少最多,下降6211 km²,其次是草地,减少2099 km²。2000—2015年间,西南地区建设用地的转入面积最多,主要由农田(贡献率68.2%)、林地(贡献率19.2%)和草地(贡献率13.1%)转化而来,转化的区域多靠近城区。农田的转出面积和转出率分别为7079 km²和2.2%,占所有转出类型面积的46.0%。林地多由草地(贡献率61.8%)转化而来,转化区域多分布在贵州中南部和云南西部等地。全区NDVI和植被覆盖度均呈显著增加趋势,说明研究区整体呈变绿趋势。其中,自然植被和农田的NDVI均显著增长,建设用地扩张地区的NDVI下降,说明自然植被和农田主导了该地区植被变化。通过残差分析发现,气候变化和人类活动对研究区变绿趋势的贡献显著。     

Remote sensing imagery for resource inventories in central Africa: The importance of detailed field data

The rate of rain forest clearing throughout central Africa is of national and international interest because it affects both the region's contribution to global warming and impacts the sustainable productive capacity of its natural resource base. The size and inaccessibility of much of central Africa makes remote sensing imagery the most suitable data source for regional land cover mapping and land transformation monitoring. Present image availability is poor. Most regional studies have had to rely on coarse resolution AVHRR 1 km data that fails to detect the small-scale agricultural clearings that are the primary cause of land cover change throughout the region. This study demonstrates that higher spatial resolution Landsat MSS imagery, which comprises the most available, geographically comprehensive and longest time series dataset, is too coarse to map land cover in low population density areas typical of most of central Africa. Furthermore, this study cautions that the use of high resolution imagery without detailed collateral field data on population density and land use practices while generating superficially plausible results, will most probably produce highly inaccurate estimates of land cover and land transformation. Policies for future regional remote sensing surveys of central Africa should focus on acquisition of higher spatial, spectral, and radiometric resolution imagery and must be accompanied by detailed, systematic field data collection.