三峡库区土地覆被动态变化遥感分析

利用 1 995年和 2 0 0 0年TM卫星影像资料 ,对三峡库区 5年内的土地覆被动态变化进行了分析。结果表明 ,该时期库区土地覆被的变化主要表现为林地向草地和耕地转化 ,以及耕地向建设用地转化 ;其次是林地向建设用地转化 ,有林地向灌丛转化 ,以及草地向林地转化。土地覆被的这种变化说明 ,三峡库区近几年来生态环境在总体上呈现继续恶化的趋势 ,仅局部地区有所好转。     

Remote Sensing Change Detection and Process Analysis of Long-Term Land Use Change and Human Impacts

This study investigates environmental change over a 30-year period and attempts to gain a better understanding of human impacts on an arid environment and their consequences for regional development. Multi-temporal remotely sensed imagery was acquired and integrated to establish the basis for change detection and process analysis. Land cover changes were investigated in two categories, namely categorical change using image classification and quantitative change using a vegetation index. The results show that human-induced land cover changes have been minor in this remote area. However, the pace of growth of human-induced change has been accelerating since the early 1990s. The analysis of the multi-temporal vegetation index also shows no overall trend of rangeland deterioration, although local change of vegetation cover caused by human activities was noticeable. The results suggest that the current trend of rapid growth may not be sustainable and that the implementation of effective counter-measures for environmentally sound development is a rather urgent matter.     

鄱阳湖湿地出露草洲分布特征的遥感研究

利用鄱阳湖区46景不同时相的Landsat MSS/TM/ETM+遥感影像,分别提取鄱阳湖的出露草洲范围,并假定只要一个时期是出露草洲就属于草洲,形成鄱阳湖湿地草洲潜在分布图,并分析鄱阳湖湿地出露草洲的分布特征。研究结果表明：(1)利用出露草洲面积与星子水文站观测水位得到二者的关系,表明出露草洲分布及范围受水位的影响显著,高水位时,大部分草洲被水淹没;低水位时,出露草洲面积大。此外,也受气象因素、草洲植物生长期的水位过程等因素影响;(2)出露草洲面积的季节变化明显：随水位的升高而减少,随水位的下降而增加;在植被生长期的春季和夏季,出露草洲面积逐渐减少,在秋季和冬季,出露草洲面积却逐渐增加;出露草洲面积最大在1月,最小在7月;(3)鄱阳湖潜在草洲的面积达2 441 km2,草洲可能出现的范围占整个鄱阳湖面积的69.5%     

Spatial and temporal variations in NO2 distributions over Beijing,China measured by imaging differential optical absorption spectroscopy

During the CAREBEIJING campaign in 2006, imaging differential optical absorption spectroscopy (I-DOAS) measurements were made from 08:00 to 16:00 on September 9 and 10 over Beijing, China. Detailed images of the near-surface NO₂ differential slant column density (DSCD) distribution over Beijing were obtained. Images with less than a 30-min temporal resolution showed both horizontal and vertical variations in NO₂ distributions. For DSCD to mixing ratio conversion, path length along the lines of I-DOAS lines of sight was estimated using the light-extinction coefficient and Ångstrom exponent data obtained by a transmissometer and a sunphotometer, respectively. Mixing ratios measured by an in-situ NO₂ analyzer were compared with those estimated by the I-DOAS instrument. The obtained temporal and spatial variations in NO₂ distributions measured by I-DOAS for the two days are interpreted with consideration of the locations of the major NO_x sources and local wind conditions. I-DOAS measurements have been applied in this study for estimating NO₂ distribution over an urban area with multiple and distributed emission sources. Results are obtained for estimated temporal and spatial NO₂ distributions over the urban atmosphere; demonstrating the capability of the I-DOAS technique. We discuss in this paper the use of I-DOAS measurements to estimate the NO₂ distribution over an urban area with multiple distributed emission sources.     

Exploring the capacity of radar remote sensing to estimate wetland marshes water storage

This paper focuses on the use of radar remote sensing for water storage estimation in wetland marshes of the Paraná River Delta in Argentina. The approach followed is based on the analysis of a temporal set of ENVISAT ASAR data which includes images acquired under different polarizations and incidence angles as well as different environmental conditions (water level, precipitation, and vegetation condition). Two marsh species, named junco and cortadera, were monitored. This overall data set gave us the possibility of studying and understanding the basic interactions between the radar, the soil under different flood conditions, and the vegetation structure. The comprehension of the observed features was addressed through electromagnetic models developed for these ecosystems. The procedure used in this work to estimate water level within marshes combines a direct electromagnetic model, field work data specifically obtained to feed the model, the actual ASAR measurements and a well known retrieval scheme based on a cost function. Results are validated with water level evaluations at specific points. A map showing an estimation of the water storage capacity and its error in junco and cortadera areas for the date where the investigation was done is also presented.     

Remote sensing and GIS for wetland inventory, mapping and change analysis

A multiple purpose wetland inventory is being developed and promoted through partnerships and specific analyses at different scales in response to past uncertainties and gaps in inventory coverage. A partnership approach is being promoted through the Ramsar Convention on Wetlands to enable a global inventory database to be compiled from individual projects and analyses using remote sensing and GIS. Individual projects that are currently part of this global effort are described. They include an analysis of the Ramsar sites' database to map the distribution of Ramsar sites across global ecoregions and to identify regions and wetland types that are under-represented in the database. Given the extent of wetland degradation globally, largely due to agricultural activities, specific attention is directed towards the usefulness of Earth Observation in providing information that can be used to more effectively manage wetlands. As an example, a further project using satellite data and GIS to quantify the condition of wetlands along the western coastline of Sri Lanka is described and trends in land use due to changes in agriculture, sedimentation and settlement patterns are outlined. At a regional scale, a project to map and assess, using remote sensing, individual wetlands used for agriculture in eight countries in southern Africa is also described. Land cover and the extent of inundation at each site is being determined from a multi-temporal data set of images as a base for further assessment of land use change. Integrated fully within these analyses is the development of local capacity to plan and undertake such analyses and in particular to relate the outcomes to wetland management and to compile data on the distribution, extent and condition of wetlands globally.     

A Calibrated,High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration1

Paech, Simon J., John R. Mecikalski, David M. Sumner, Chandra S. Pathak, Quinlong Wu, Shafiqul Islam, and Taiye Sangoyomi, 2009. A Calibrated, High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration. Journal of the American Water Resources Association (JAWRA) 45(6):1328‐1342. Abstract: Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10‐year period (1995‐2004). These insolation estimates were developed into well‐calibrated half‐hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2‐week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground‐based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three‐step process: (1) comparison with ground‐based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station‐averaged model error of 2.2 MJ m^?2/day (13%). Calibration reduced errors to 1.7 MJ m^?2/day (10%), and also removed temporal‐related, seasonal‐related, and satellite sensor‐related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2‐km resolution maps of estimated daily reference and potential evapotranspiration for water management‐related activities.     

Understanding large-scale deforestation in southern Jinotega, Nicaragua from 1978 to 1999 through the examination of changes in land use and land cover

Nicaragua, home to the largest remaining extent of rainforest in Central America (total surface area) and to a significant indigenous population, has lost approximately half of its forest cover since 1950. This major and rapid loss of forest cover has been explained as the consequence of an eastward moving agricultural frontier that cuts through the region of Jinotega. If the current deforestation rate continues, the country could lose its remaining forest cover over the course of the next two decades; therefore, it is essential that the dynamics and relationships of land-use and land-cover change (LUCC) in this region are understood. To examine LUCC in Nicaragua over time, Landsat imagery from the southern portion of the region of Jinotega, taken in 1978, 1987, and 1999 was utilized. A remote-sensing method, supervised classification, which allows for the grouping of spectrally similar values for each year, followed by an image change detection analysis (postclassification comparison) was conducted. Groundtruthing (field validation) was conducted in 2006 to validate the data, which yielded increasing overall accuracy rates of 71.68% for 1978, 82.35% for 1987, and 84.38% for 1999. The classification and change detection results showed that if the agricultural cultivation overtook this region, it happened before 1978. Therefore, the possibility that either deforestation did not actually occur along an agricultural frontier or that it was located further east exists; this would be an interesting subject for future studies. There was, however, clear evidence of increased forest cover from 1987 to 1999 near the urban center, correlating with the enforced reforestation law in the city of Jinotega.     

利用混合水体指数模型(CIWI)提取滨海湿地水体的信息

根据对滨海湿地区域光谱特性分析和背景信息的反射特点,对主要的水体信息提取方法进行比较分析,将混合水体指数模型（CIWI）应用于TM遥感影像,针对滨海湿地区域水体信息进行提取实验,并与近年得到广泛应用和承认的水体指数模型：归一化差异水体指数（NDWI）、改进的归一化差异水体指数（MNDWI）等进行比较。实验证明CIWI的区分度最高,水体与植被、水体与城镇、植被与城镇之间的区分度分别为505%、292%与267%;水体、植被、城镇像元之间的差异比NDWI和MNDWI增大,减少了混淆信息的影响,对江苏盐城滨海湿地研究区的水体信息提取精度达到949%,实现了滨海湿地区域水体信息的准确快速提取。