洪涝灾害监测是农情监测的主要任务之一,遥感监测可以弥补地面观测耗人、耗财、信息滞后等诸多不足,已成为洪涝灾害研究领域的重要发展方向。该文基于HJ-1A/1B-CCD数据,以海南岛为研究区,选取研究区内400个训练样本,利用区分度(division...洪涝灾害监测是农情监测的主要任务之一,遥感监测可以弥补地面观测耗人、耗财、信息滞后等诸多不足,已成为洪涝灾害研究领域的重要发展方向。该文基于HJ-1A/1B-CCD数据,以海南岛为研究区,选取研究区内400个训练样本,利用区分度(division degree,DD)对归一化差异水体指数(normalized difference water index,NDWI)、基于蓝光的归一化差异水体指数(normalized difference water index based on blue light,NDWI-B)和混合水体指数(combined index of NDVI and NIR for water body identification,CIWI)3种水体指数进行比较分析。分析结果显示,在应用HJ-1CCD数据进行纯水体、湿地识别时,NDWI-B模型效果最好(综合区分度分别为31.30%、28.13%),是海南岛洪涝灾害监测的最优模型。经验证,NDWI-B模型的水体识别总体精度达91.50%。通过对采样点的水体指数值与地物类型的反复对比确定NDWI-B模型的水体识别阈值为-0.015。利用NDWI-B模型对海南岛2010年9月25日至10月25日的洪涝灾情进行监测。结果表明,10月12日的灾情最为严重,全岛洪水淹没面积达到监测期内最高值,为120.22km2,除东方、昌江、乐东外所有市县均出现新增水体,新增水体主要分布于村庄、耕地、道路、城镇居民地等。从区域上看,东部的文昌、琼海、海口、定安为洪涝重灾区,西部的东方、昌江、乐东为洪涝轻灾区。全岛洪涝影响最大的土地利用类型为水田,其次为旱地。10月12日,水田、旱地的淹没面积分别为61.46和29.59 km2,耕地(水田和旱地)淹没面积占总淹没面积的比例为75.73%。NDWI-B模型具有水陆区分度较大和水体面积提取精度较高的优点外,还能够识别小范围水体和湿地,是海南岛洪涝灾害监测较为理想的模型。该文为海南岛水资源管理、洪涝灾害动态监测及防灾减灾提供参考。展开更多
基于风云3号(FY-3)卫星中分辨率成像光谱仪(medium resolution spectral imager,MERSI)数据的归一化差异水体指数(normalized difference water index,NDWI)和基于蓝光波段的归一化差异水体指数(normalized difference water index base...基于风云3号(FY-3)卫星中分辨率成像光谱仪(medium resolution spectral imager,MERSI)数据的归一化差异水体指数(normalized difference water index,NDWI)和基于蓝光波段的归一化差异水体指数(normalized difference water index based on blue light,NDWI-B),通过直方图分析获取了水体指数判识阈值,并对新疆北疆沿天山一带2009—2011年发生的融雪性洪水灾害天气进行了监测。对比基于环境1号卫星CCD数据的监测结果表明:利用FY-3/MERSI的250 m空间分辨率数据可实现对新疆融雪性洪水灾害的监测,其中利用FY-3/MERSI NDWI-BFY数据的判识效果最好。展开更多
The present study is inscribed within the framework of the geotechnical characterization of the soils of the Santchou plain, their classification for employment as pavement subgrade, various identification tests were ...The present study is inscribed within the framework of the geotechnical characterization of the soils of the Santchou plain, their classification for employment as pavement subgrade, various identification tests were carried out on the samples. The results obtained showed that with a wide range of different grain sizes, the studied soils showed low content in clay grains and dominance of either sand grains or silt grains, this can be explaining how most of these soil are poorly graded. According to the USDA textural classification, the grain size distribution of these soils makes them to be classified as Silty Loam types to Sandy Loam types. Despite of their organic matter content which is less than 10%, according to their respective methylene blue values, the soils studied along the section should be mainly loamy soil of medium plasticity to clayed soil, therefore showing a sensibility of its behavior to variation of water content. That last one is confirmed by the consistency parameters of these soils which show intermediate plasticity to highly plastic. Also, the bearing capacity proposed by these soils at their respective optimum dry densities is relatively small, although most of these experimental CBR values of the studied soils are more important than the ones prescribed by the AASHTO Classification system for A5, A6, and A7 types, and the French Highway Earthworks Manual Classifications system (GTR) for the corresponding A2 and A3 types.展开更多
文摘洪涝灾害监测是农情监测的主要任务之一,遥感监测可以弥补地面观测耗人、耗财、信息滞后等诸多不足,已成为洪涝灾害研究领域的重要发展方向。该文基于HJ-1A/1B-CCD数据,以海南岛为研究区,选取研究区内400个训练样本,利用区分度(division degree,DD)对归一化差异水体指数(normalized difference water index,NDWI)、基于蓝光的归一化差异水体指数(normalized difference water index based on blue light,NDWI-B)和混合水体指数(combined index of NDVI and NIR for water body identification,CIWI)3种水体指数进行比较分析。分析结果显示,在应用HJ-1CCD数据进行纯水体、湿地识别时,NDWI-B模型效果最好(综合区分度分别为31.30%、28.13%),是海南岛洪涝灾害监测的最优模型。经验证,NDWI-B模型的水体识别总体精度达91.50%。通过对采样点的水体指数值与地物类型的反复对比确定NDWI-B模型的水体识别阈值为-0.015。利用NDWI-B模型对海南岛2010年9月25日至10月25日的洪涝灾情进行监测。结果表明,10月12日的灾情最为严重,全岛洪水淹没面积达到监测期内最高值,为120.22km2,除东方、昌江、乐东外所有市县均出现新增水体,新增水体主要分布于村庄、耕地、道路、城镇居民地等。从区域上看,东部的文昌、琼海、海口、定安为洪涝重灾区,西部的东方、昌江、乐东为洪涝轻灾区。全岛洪涝影响最大的土地利用类型为水田,其次为旱地。10月12日,水田、旱地的淹没面积分别为61.46和29.59 km2,耕地(水田和旱地)淹没面积占总淹没面积的比例为75.73%。NDWI-B模型具有水陆区分度较大和水体面积提取精度较高的优点外,还能够识别小范围水体和湿地,是海南岛洪涝灾害监测较为理想的模型。该文为海南岛水资源管理、洪涝灾害动态监测及防灾减灾提供参考。
文摘基于风云3号(FY-3)卫星中分辨率成像光谱仪(medium resolution spectral imager,MERSI)数据的归一化差异水体指数(normalized difference water index,NDWI)和基于蓝光波段的归一化差异水体指数(normalized difference water index based on blue light,NDWI-B),通过直方图分析获取了水体指数判识阈值,并对新疆北疆沿天山一带2009—2011年发生的融雪性洪水灾害天气进行了监测。对比基于环境1号卫星CCD数据的监测结果表明:利用FY-3/MERSI的250 m空间分辨率数据可实现对新疆融雪性洪水灾害的监测,其中利用FY-3/MERSI NDWI-BFY数据的判识效果最好。
文摘The present study is inscribed within the framework of the geotechnical characterization of the soils of the Santchou plain, their classification for employment as pavement subgrade, various identification tests were carried out on the samples. The results obtained showed that with a wide range of different grain sizes, the studied soils showed low content in clay grains and dominance of either sand grains or silt grains, this can be explaining how most of these soil are poorly graded. According to the USDA textural classification, the grain size distribution of these soils makes them to be classified as Silty Loam types to Sandy Loam types. Despite of their organic matter content which is less than 10%, according to their respective methylene blue values, the soils studied along the section should be mainly loamy soil of medium plasticity to clayed soil, therefore showing a sensibility of its behavior to variation of water content. That last one is confirmed by the consistency parameters of these soils which show intermediate plasticity to highly plastic. Also, the bearing capacity proposed by these soils at their respective optimum dry densities is relatively small, although most of these experimental CBR values of the studied soils are more important than the ones prescribed by the AASHTO Classification system for A5, A6, and A7 types, and the French Highway Earthworks Manual Classifications system (GTR) for the corresponding A2 and A3 types.
