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Uncovering process domains in large rivers: Patterns and potential drivers of benthic substrate heterogeneity in two North American riverscapes
rivers North American benthic
2021/7/23
Identifying and understanding functional process domains (sensu Montgomery, 1999) in rivers is paramount for linking the physical habitat template to ecosystem structure and function.
MONITORING AND ANALYZING THE GEOSPATIAL PATTERNS OF THE PEARL RIVER DELTA (PRD) FROM 1960 TO 2012
Geographical Spatial Patterns Coastal Environment Landuse Coastline
2018/5/15
The Geospatial Patterns Pearl River Delta (PRD), one of the most economically-important and fastest-growing regions in China, have changed remarkably and continuously during the past decades. In this ...
Changes and spatial patterns of eco-environment in the farming-pastoral region of northern China
2007/8/24
This paper firstly selects 10 kinds of indexes to reflect eco-environment background condition and builds the multi-subject spatial database by using ground meteorological data, remote sen...
The role of remote sensing in phenological studies is increasingly regarded as a key to understand large area seasonal phenomena. This paper describes the application of Moderate Resolutio...
Based on the information from forest resources distribution maps of Luoning County of 1983 and 1999, six indices were used to analyze spatial patterns and dynamics of forest landscapes of ...
In this paper, we use CEVSA, a process-based model, which has been validated on regional and global scales, to explore the temporal and spatial patterns of Net Primary Productivity (NPP) a...
With the objectives to acquire the fundamental data of the territorial resource, understand the impacts of human activities on the land use and cover patterns and evaluate the potential of...
By using digitized land use maps of Beijing in 1982, 1992 and 1997 and employing GIS spatial analysis techniques, this paper conducts an empirical study on the spatial differentiation and ...
Abstracts: The case study based on Qinling Mountains in Shaanxi Province of China, in virtue of the information from TM image, classifies the land types and analyzes their spatial and temp...