Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disa...Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.展开更多
In recent years, the pressure of increasing coastal industries and tourism activities has, in some areas, led to the clearing of many coastal habitats along the Qatar＇s shorelines for the construction of tourist reso...In recent years, the pressure of increasing coastal industries and tourism activities has, in some areas, led to the clearing of many coastal habitats along the Qatar＇s shorelines for the construction of tourist resorts, tourism-related development and industrial facilities. Such threats are leading to the increasing demand for detailed mangrove maps for the purpose of measuring the extent of decline in mangrove ecosystems. Detailed mangrove maps at the community or species level are, however, not easy to produce, mainly because mangrove forests are very difficult to access. Without doubt, remote sensing is a serious alternative to traditional field-based methods for mangrove mapping, as it allows information to be gathered from the forbidding environment of mangrove forests, which otherwise, logistically and practically speaking, would be extremely difficult to survey. Remote sensing applications for mangrove mapping at the fundamental level are already well established but, surprisingly, a number of advanced remote sensing applications have remained unexplored for the purpose of mangrove mapping at a finer level. Consequently, the aim of this paper is to unveil the potential of some of the unexplored remote sensing techniques for mangrove studies. Temporal Landsat TM image of 1986, Landsat ETM image of 2000 and Resourcesat-1 LISS 3 image of 2008 are used to calculate percentage change in mangrove cover at AI Dhakira site using geometrically registered and radiometrically corrected historical Landsat and Resourcesat-1 images. Region masks are employed to isolate the unwanted area from the images. NDVI （normalized difference vegetation index） is used to detect mangroves using near-infrared and red bands which are computed from the satellite images. The ground-truthing visit to AI Dhakira site is conducted to confirm the results of the analysis. Change detection is applied and mangrove in the study area is found to have decreased by about 8.79% from 2000 to 2008.展开更多
基金Supported by Key Scientific and Technological Project of Henan Province(082102140009)~~
文摘Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.
文摘In recent years, the pressure of increasing coastal industries and tourism activities has, in some areas, led to the clearing of many coastal habitats along the Qatar＇s shorelines for the construction of tourist resorts, tourism-related development and industrial facilities. Such threats are leading to the increasing demand for detailed mangrove maps for the purpose of measuring the extent of decline in mangrove ecosystems. Detailed mangrove maps at the community or species level are, however, not easy to produce, mainly because mangrove forests are very difficult to access. Without doubt, remote sensing is a serious alternative to traditional field-based methods for mangrove mapping, as it allows information to be gathered from the forbidding environment of mangrove forests, which otherwise, logistically and practically speaking, would be extremely difficult to survey. Remote sensing applications for mangrove mapping at the fundamental level are already well established but, surprisingly, a number of advanced remote sensing applications have remained unexplored for the purpose of mangrove mapping at a finer level. Consequently, the aim of this paper is to unveil the potential of some of the unexplored remote sensing techniques for mangrove studies. Temporal Landsat TM image of 1986, Landsat ETM image of 2000 and Resourcesat-1 LISS 3 image of 2008 are used to calculate percentage change in mangrove cover at AI Dhakira site using geometrically registered and radiometrically corrected historical Landsat and Resourcesat-1 images. Region masks are employed to isolate the unwanted area from the images. NDVI （normalized difference vegetation index） is used to detect mangroves using near-infrared and red bands which are computed from the satellite images. The ground-truthing visit to AI Dhakira site is conducted to confirm the results of the analysis. Change detection is applied and mangrove in the study area is found to have decreased by about 8.79% from 2000 to 2008.
