Wild fire of forest and grassland is one of the major natural disasters in the world. The fire of forest and grassland occurs
frequently due to global changing and uneven precipitation distribution, which may affect large areas and cause great
economic loss. With the advantages of wide-coverage, high spatio-temporal resolution, remote sensing technology has
been used for the wild fire monitoring activities. In this paper, the fire point detection model and burned area monitoring
model, for HJ-1A/B data, have been developed and applied for the southeast Australian wild fire monitoring in 2009.
The application shows that the models and the data are efficient for the wild fire monitoring.
On August 8, 2010 morning, a large debris flow occurred in Zhouqu County, Gannan Tibetan
Autonomous Prefecture, Gansu Province, China, which has damaged Zhouqu County and its
surrounding area seriously. An UAV and airplane were sent there the day after to acquire images of
disaster area; UAV image of 0.2 meter resolution and aerial remote sensing image of 1 meter
resolution were acquired. NDRCC compared pre-disaster and post-disaster remote sensing images of
disaster area, preliminary analyzed and judged the damage condition and disaster trend. We
partitioned the coverage and affected area of debris flow into 2457 girds in high resolution remote
sensing images, hazard assessment expert group were sent to implement field investigation
according to each grid. The disaster scope and extent of loss were defined again combined with field
investigation data. Then we assessed the physical quantity of housing, infrastructure, land resource
in detail and assessed the direct economic losses. It is for the first time that remote sensing images
are integrated into the national catastrophe assessment flow of China as a major data source.
Vegetation coverage and its changes are one of the hottest research branches in regional ecological environment change.
An important research content of vegetation coverage is vegetation fraction. Hydropower exploitation cascade in a river
basin inevitably makes vegetation fraction change. In this paper, the sub-pixel decomposition model and NDVI have
been applied to quantitatively estimate vegetation fraction change of Qingjiang River downstream based on remotely
sensed data. The results show that the overall vegetation environment has been greatly improved and the hydropower
cascade development has a greater influence on vegetation fraction change in Qingjiang River basin form 1987 to 2004.