Different management modes can influence land-use and land-cover changes (LULCC), resulting in changes in ecosystem service values (ESV). However, few studies compared the differences in ESV under different management modes. The objective was to analyze the impact of different management modes on ESV. Multisource remote sensing images were used to obtain the LULCC data for Fujin City over four periods (1986, 1995, 2005, and 2015). We modified the equivalent value factors method by crop yield to estimate the ESV in different years. Statistics show that paddy increased from 59.2 to 1341.8 km2 in the agricultural region, whereas it increased from 60.1 to 2236.3 km2 in the reclamation region during 1986 to 2015. The total ESV decreased by 49.0% and 43.4%, respectively, in the agricultural region and reclamation region. The agricultural products function exhibited a larger increase and the freshwater supply function exhibited a greater decrease in the reclamation region than in the agricultural region. Two regions can learn from each other and carry out innovations in land management approaches to promote common developmental goals.
As the resolution of the interferometer is rapidly increasing, the higher requirement is proposed to the interferometry. For avoiding losing of the useful information of the actual interferogram, an algorithm is presented based on singular value decomposition (SVD) which is more stable than other algorithms to some extent. The weight coefficients of the orthogonal polynomials can be worked out directly, which can eliminate the computational error. Then an evaluation criterion is developed to choose the optimum Zernike polynomial number. The computer simulations of this algorithm are also made. The simulation experiments have proved that it is an efficient algorithm and can reconstruct the wavefront accurately and stably.
Songnen Plain is located in the intersection area of agriculture and forestry in Jilin Province and Heilongjiang Provinces of Northeast China. In recent years, grasslands in the area have gradually decreased year by year due to the unplanned use in a large scale, being the most typical pattern in study on regional land use and cover change. This paper has well utilized the remote sensing imagery and regional feature analysis approach (referred to as geoanalysis) to model its dynamic change based on the survey data. Combination of remote sensing information and field investigation data, we did an analysis on its driving force in light of the regional characteristics and the policies of rapid economic development put forward by Chinese Government. In practice, mapping the grasslands in 1986, 1996 and 2002 respectively was carried out to overlay each other and extract these varied patches with a feature, and thus a trend map of its development was compiled towards a decade to come. Finally, author brought up an idea how to better utilize grasslands in the area on the basis of the regional feature of China.
Northeast China is the national commercial grain base of China. It provides the critical food supply for other areas of the country every year. In this region dramatic changes, such as population increase, deforestation, grass land degeneration, wetland shrinking and so on, have taken place in recent several decades. The changes in resources and environment in this region have significant impacts on human living, social economy and many other aspects of the regional development. In this study uses Remote Sensing (RS), GIS and other information technology to reconstruct a digital Northeast China of the
last 100 years from year 1900 to 2000. This paper first introduces the Digital Northeast China of this 100 years which includes the system targets, data foundation and design frame. Then as a case study, the woodland resource changes after 1980s based on the completed dataset are analyzed. This Digital Northeast China is based on satellite remote sensing images (Landsat TM and ETM) and topology maps and can help people solve problems related to population, natural resources and environment. On the other hand, the Digital Northeast China system can help farmers make wise use of land, increase production and preserve environment simultaneously. Furthermore, using data contained in the system, geographical
scientists can analyze the resource and environment changes and make certain forecasts of the future development.
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