Land use cover change (LUCC) provide important information for environmental management and planning. It is one of
the most prominent characteristics in globe environment change, and not only limited by natural factor, but also affected
by the factor of social, economics, technique and histories. Traditionally, field surveys of land cover and land use are
time consuming and costly and provide tabular statistics with out geographic location information. Remote sensing and
GIS are the most modern technologies which have been widely used in the field of natural resource management and
monitoring. Change detection in land use and updating information on the distribution and dynamics of land use have
long term significance in policy making and scientific research. In this paper, we use multistpectral images of Spot period
two different of time 2002 and 2007 for detection on LUCC base on Scale Invariant Feature Transform (SIFT) method.
An automatic image matching technique based on SIFT was proposed by using the rotation and scale invariant property
of SIFT. Keypoints are first extracted by searching over all scales and image locations, then the descriptors defined on
the keypoint neighborhood are computed. The proposed algorithm is robust to translation, rotation, noise and scaling.
Experimental results, urban is the most part of Huangpi area which have been changed.
Forest resource is the important material foundation of national sustainable development. And it need to master the status
and change of forest resource timely for reasonable exploitation of forest and its renewal. Laos is located in the heart of
the Indochinese peninsular, in southeast Asia, latitude 14° to 23 °north and longitude 100°to 108°east, covered a total
236, 800 square kilometers, and country of nearly 6 million people. The forest of Laos dropped from close to two-third
in the 1970's to less than half by the 1990's. This deforestation has been attributed to two human activities : a
traditional of shifting cultivation or slash and burn farming, and logging without reforestation. Remote sensing and GIS
are the most modern technologies which have been widely used in the field of natural resource management and
monitoring. These technologies provide very powerful tools to observe and collect information on natural resources
and dynamic phenomenon on the earth surface, and ability to integrate different data and present data in different formats.
In this study, using forest cover map and Landsat 7 ETM data, we analyze and compare forest cover change from
1997 to 2002. And the maximum likelihood method of supervised classification was used to classify the remote
sensing data, we processed Spectral Enhancement, including Normalized Difference Vegetation Index (NDVI) ,and
re-classify data again base on Principle Components Analysis (PCA) and NDVI.