矿区土地覆盖变化信息的高精度提取,是区域资源环境保护和地质灾害防治领域的关键问题。以SPOT-5高分辨率卫星影像为数据源,以分类后比较法为变化信息提取方法,利用分类性能良好的支持向量机(SVM)为分类算法,分别设置不同SVM核函数及参...矿区土地覆盖变化信息的高精度提取,是区域资源环境保护和地质灾害防治领域的关键问题。以SPOT-5高分辨率卫星影像为数据源,以分类后比较法为变化信息提取方法,利用分类性能良好的支持向量机(SVM)为分类算法,分别设置不同SVM核函数及参数对实验样区进行分类,并评价分析不同核函数及参数对分类效果的影响。实验发现在4种核函数中高斯核函数分类精度最高,为87.1%;Sigmoid和多项式核函数分类精度适中,线性核函数分类精度最低,为78.7%。因此,利用高斯核函数分别对3个时相的大屯矿区影像进行分类,提取出变化信息空间分布并定量统计分析其变化特征。结果表明:矿区植被覆盖面积在近十年内持续减少18.539 km 2,塌陷面积共扩大4.379 km 2,而矿区厂矿增加、煤矿开采规模扩大、采煤塌陷区面积扩大以及耕地占用面积增大等人为因素,是威胁大屯矿区生态环境的主要因素。展开更多
Recently land-use change has been the main concern for worldwide environment change and is being used by city and regional planners to design sustainable cities. Nakuru in the central Rift Valley of Kenya has undergon...Recently land-use change has been the main concern for worldwide environment change and is being used by city and regional planners to design sustainable cities. Nakuru in the central Rift Valley of Kenya has undergone rapid urban growth in last decade. This paper focused on urban growth using multi-sensor satellite imageries and explored the potential benefits of combining data from optical sensors (Landsat, Worldview-2) with Radar sensor data from Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for urban land-use mapping. Landsat has sufficient spectral bands allowing for better delineation of urban green and impervious surface, Worldview-2 has a higher spatial resolution and facilitates urban growth mapping while PALSAR has higher temporal resolution compared to other operational sensors and has the capability of penetrating clouds irrespective of weather conditions and time of day, a condition prevalent in Nakuru, because it lies in a tropical area. Several classical and modern classifiers namely maximum likelihood (ML) and support vector machine (SVM) were applied for image classification and their performance assessed. The land-use data of the years 1986, 2000 and 2010 were compiled and analyzed using post classification comparison (PCC). The value of combining multi-temporal Landsat imagery and PALSAR was explored and achieved in this research. Our research illustrated that SVM algorithm yielded better results compared to ML. The integration of Landsat and ALOS PALSAR gave good results compared to when ALOS PAL- SAR was classified alone. 19.70 km2 of land changed to urban land-use from non-urban land-use between the years 2000 to 2010 indicating rapid urban growth has taken place. Land-use information is useful for the comprehensive land-use planning and an integrated management of resources to ensure sustainability of land and to achieve social Eq- uity, economic efficiency and environmental sustainability.展开更多
In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise...In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.展开更多
文摘矿区土地覆盖变化信息的高精度提取,是区域资源环境保护和地质灾害防治领域的关键问题。以SPOT-5高分辨率卫星影像为数据源,以分类后比较法为变化信息提取方法,利用分类性能良好的支持向量机(SVM)为分类算法,分别设置不同SVM核函数及参数对实验样区进行分类,并评价分析不同核函数及参数对分类效果的影响。实验发现在4种核函数中高斯核函数分类精度最高,为87.1%;Sigmoid和多项式核函数分类精度适中,线性核函数分类精度最低,为78.7%。因此,利用高斯核函数分别对3个时相的大屯矿区影像进行分类,提取出变化信息空间分布并定量统计分析其变化特征。结果表明:矿区植被覆盖面积在近十年内持续减少18.539 km 2,塌陷面积共扩大4.379 km 2,而矿区厂矿增加、煤矿开采规模扩大、采煤塌陷区面积扩大以及耕地占用面积增大等人为因素,是威胁大屯矿区生态环境的主要因素。
文摘Recently land-use change has been the main concern for worldwide environment change and is being used by city and regional planners to design sustainable cities. Nakuru in the central Rift Valley of Kenya has undergone rapid urban growth in last decade. This paper focused on urban growth using multi-sensor satellite imageries and explored the potential benefits of combining data from optical sensors (Landsat, Worldview-2) with Radar sensor data from Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for urban land-use mapping. Landsat has sufficient spectral bands allowing for better delineation of urban green and impervious surface, Worldview-2 has a higher spatial resolution and facilitates urban growth mapping while PALSAR has higher temporal resolution compared to other operational sensors and has the capability of penetrating clouds irrespective of weather conditions and time of day, a condition prevalent in Nakuru, because it lies in a tropical area. Several classical and modern classifiers namely maximum likelihood (ML) and support vector machine (SVM) were applied for image classification and their performance assessed. The land-use data of the years 1986, 2000 and 2010 were compiled and analyzed using post classification comparison (PCC). The value of combining multi-temporal Landsat imagery and PALSAR was explored and achieved in this research. Our research illustrated that SVM algorithm yielded better results compared to ML. The integration of Landsat and ALOS PALSAR gave good results compared to when ALOS PAL- SAR was classified alone. 19.70 km2 of land changed to urban land-use from non-urban land-use between the years 2000 to 2010 indicating rapid urban growth has taken place. Land-use information is useful for the comprehensive land-use planning and an integrated management of resources to ensure sustainability of land and to achieve social Eq- uity, economic efficiency and environmental sustainability.
文摘In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.
