The Taihang Mountains area is an area in North China where serious mudflow hazards take place frequently. The hazards often obstrust traffic and make it difficult to carry out conventional ground investigations of the...The Taihang Mountains area is an area in North China where serious mudflow hazards take place frequently. The hazards often obstrust traffic and make it difficult to carry out conventional ground investigations of the mudflow hazards. This paper introduces the feasibility study of mudflow hazards by using Landsat-5TM data. The study has achieved a great success through adopting both the faint spectral enhancement technique for mudflow fans (or other depositional areas) and comprehensive study of the environmental background of pregnant mudflows. Thus, remote sensing as a fast, convenient, low-cost and effective technical method can be used to recognise the situation of mudflow hazards so that effective rescue can be provided.展开更多
Successful biological monitoring depends on judicious classification. An attempt has been made to provide an overview of important characteristics of marsh wetland. Classification was used to describe ecosystems and l...Successful biological monitoring depends on judicious classification. An attempt has been made to provide an overview of important characteristics of marsh wetland. Classification was used to describe ecosystems and land cover patterns. Different spatial resolution images show different landscape characteristics. Several classification images were used to map and monitor wetland ecosystems of Honghe National Nature Reserve （HNNR） at a plant community scale. HNNR is a typical inland wetland and fresh water ecosystem in the North Temperate Zone. SPOT-5 10 m ×10 m, 20 m × 20 m, and 30 m×30 m images and Landsat -5 Thematic Mapper （TM） images were used to classify based on maximum likelihood classification （MLC） algorithms. In order to validate the precision of the classifications, this study used aerial photography classification maps as training samples because of their high accuracy. The accuracy of the derived classes was assessed with the discrete multivariate technique called KAPPA accuracy. The results indicate： （1） training samples are important to classification results. （2） Image classification accuracy is always affected by areal fraction and aggregation degree as well as by diversities and patch shape. （3） The core zone area is protected better than buffer zone and experimental zone wetland. The experimental zone degrades fast because of irrational development by humans.展开更多
文摘The Taihang Mountains area is an area in North China where serious mudflow hazards take place frequently. The hazards often obstrust traffic and make it difficult to carry out conventional ground investigations of the mudflow hazards. This paper introduces the feasibility study of mudflow hazards by using Landsat-5TM data. The study has achieved a great success through adopting both the faint spectral enhancement technique for mudflow fans (or other depositional areas) and comprehensive study of the environmental background of pregnant mudflows. Thus, remote sensing as a fast, convenient, low-cost and effective technical method can be used to recognise the situation of mudflow hazards so that effective rescue can be provided.
基金jointly supported by the National Science and Technology Support Program(No.2013BAC03B05)Ecological environment evaluation of disaster area(No.O7M73120AM)
文摘Successful biological monitoring depends on judicious classification. An attempt has been made to provide an overview of important characteristics of marsh wetland. Classification was used to describe ecosystems and land cover patterns. Different spatial resolution images show different landscape characteristics. Several classification images were used to map and monitor wetland ecosystems of Honghe National Nature Reserve （HNNR） at a plant community scale. HNNR is a typical inland wetland and fresh water ecosystem in the North Temperate Zone. SPOT-5 10 m ×10 m, 20 m × 20 m, and 30 m×30 m images and Landsat -5 Thematic Mapper （TM） images were used to classify based on maximum likelihood classification （MLC） algorithms. In order to validate the precision of the classifications, this study used aerial photography classification maps as training samples because of their high accuracy. The accuracy of the derived classes was assessed with the discrete multivariate technique called KAPPA accuracy. The results indicate： （1） training samples are important to classification results. （2） Image classification accuracy is always affected by areal fraction and aggregation degree as well as by diversities and patch shape. （3） The core zone area is protected better than buffer zone and experimental zone wetland. The experimental zone degrades fast because of irrational development by humans.
