GIS-based spatial and temporal changes of land occupation caused by mining activities-a study in eastern part of Hubei Province

By using multi-source and multi-temporal high resolution remote sensing data and related techniques of remote sensing and geographic information systems, this paper analyzes the spatial and temporal changes of land occupation caused by mine development in four mining areas of eastern Hubei Province from 2011 to 2014, including Chengchao-Tieshan iron-copper polymetallic deposit area, Daye-Yangxin iron-copper polymetallic deposit area, E-Nan mining area, and Wuxue-Yangxin non-metallic mining area along the Yangtze River. The results show that: In the research area, land occupation of energy mine exploitation is small and in scattered distribution, with coal mine occupying the largest area, showing a downward trend in four years; land occupation of metal mines is large and in centralized distribution, with iron mine and copper mine occupying the largest area, showing a downward trend in four years; non-metallic mines are large and in great quantity, with mines of limestone for building and limestone occupying the largest area, showing a upward trend in four years.

Changes of net primary productivity in China during recent 11 years detected using an ecological model driven by MODIS data

Net primary productivity （NPP） is an important component of the terrestrial carbon cycle. Accurately mapping the spatial-temporal variations of NPP in China is crucial for global carbon cycling study. In this study the process-based Boreal Ecosystem Productivity Simulator （BEPS） was employed to study the changes of NPP in China＇s ecosystems for the period from 2000 to 2010. The BEPS model was first validated using gross primary productivity （GPP） measured at typical flux sites and forest NPP measured at different regions. Then it was driven with leaf area index （LAI） inversed from the Moderate Resolution Imaging Spectroradiometer （MODIS） reflec- tance and land cover products and meteorological data interpolated from observations at753 national basic meteorological stations to simulate NPP at daily time steps and a spatial resolution of 500m from January 1, 2000 to December 31, 2010. Validations show that BEPS is able to capture the seasonal variations of tower-based GPP and the spatial variability of forest NPP in different regions of China. Estimated national total of annual NPP varied from 2.63 to 2.84Pg C.yr-1, averaging 2.74Pg C.yr-1 during the study period. Simulated terrestrial NPP shows spatial patterns decreasing from the east to the west and from the south to the north, in association with land cover types and climate. South-west China makes the largest contribution to the national total of NPP while NPP in the North-west account for only 3.97% of the national total. During the recent 11 years, the temporal changes of NPP were heterogamous. NPP increased in 63.8% of China＇s landmass, mainly in areas north of the Yangtze River and decreased in most areas of southern China, owing to the low temperature freezing in early 2008 and the severe drought in late 2009.

Conversion of savanna rangelands to bush dominated landscape in Borana,Southern Ethiopia

Introduction:Analyzing trends of land use systems and the changes occurred overtime is an effective way of assessing the impacts of land use/land cover(LULC)changes on ecosystem function.It provides important insights for understanding the spatial patterns of land use processes.The rangelands of southern Ethiopia are adversely affected by increased human population pressure,encroachment of crop cultivation,and bush encroachment.Hence,it is vital to understand the trends of rangeland vegetation cover dynamics.Methods:This paper evaluates land use/land cover changes and spatial patterns between 1987 and 2003 in Yabelo(5426 km2),Borena rangelands of southern Ethiopia.We used a combination of three Landsat Thematic Mapper(TM)1987,Landsat TM 1995 and Enhanced Thematic Mapper Plus(ETM+)2003,and local perceptions.A pixelbased supervised classification with maximum likelihood classifier was used to classify images.The accuracy of classification was assessed for 1987(81.8%),1995(84.6%),and 2003(81.3%).Results:The results showed that the Borana rangelands had undergone substantial changes during the last 16 years.Between 1987 and 2003,we observed a considerable increase in woodland cover(11.7%),bushland cover(17%),cultivated land(72.5%),and settlements(79.8%).The results showed a rapid decline in grassland cover(7.7%),shrubby grassland cover(86%),and bareland(0.7%).The spatial pattern analysis indicate that the Borana rangeland was fragmented and characterized by the proliferation of large numbers of patches with a decline in patch index,increased patch density,and irregular shape of patches within a landscape.Local communities’perceptions indicate that recurrent drought,increased human population size,and expansion of cultivation were largely responsible for the observed LULC changes in the study area.Conclusions:LULC changes contribute to rangeland degradation and weaken the traditional practices of rangeland management.We suggest appropriate management measures to halt the impact of disturbances on LULC dynamics and its implication on the livelihoods of the Borana pastoralists.

Spatial distribution of an ancient agricultural oasis in Juyan, northwestern China

Activities related to agricultural cultivation are some of the major human drivers of landscape change on the Earth＇s surface. Archaeological remains can provide qualitative evidence for studies of past agricultural development and environmental conditions. The ancient Juyan Oasis, which once flourished along the historic Silk Road, was a typical oasis of downstream inland river basins in the arid zone of northwestern China. Historical records and archaeological discoveries have qualitatively shown that the oasis supported extensive agricultural activities in this historical period from the Hart Dynasty to the early Ming Dynasty （B.C. 202-A.D. 1375）, which can be traced back to 2,000 years ago. In this study, different types of archaeological remains （including archaeological sites, ground surface artifacts, ancient cultivation ruins, and agricultural irrigation canals） that were obtained and identified from previous archaeological reports, field inspections, and remote sensing imagery were used to determine the spatial extent of the agricultural oasis in the historical period of interest. Our approach used multiple data sources in order to increase the accuracy and reliability of the results compared to previous studies. Our results distinctly suggested that much of the oasis was cultivated during the historical periods considered. Additionally, the arable land area in the historical period considered was roughly estimated to be approximately （3.39-4.75） × 10^4 ha. These findings regarding the spatial distribution of this ancient agricultural oasis and its arable land were reasonably determined to represent the ancient agricultural development that occurred in the Juyan Oasis better than results obtained from single sources of data.

Effects of ultraviolet radiation on marine primary production with reference to satellite remote sensing

Incubation experiments have shown that ultra- violet radiation （UVR） has significant influences on marine primary production （MPP）. However, existing satellite remote sensing models of MPP only consider the effects of visible light radiation, ignoring the UVR. Additionally, the ocean color satellite data currently used for MPP estimation contain no UV bands. To better understand the mechanism of MPP model development with reference to satellite remote sensing, including UVR＇s effects, we first reviewed recent studies of UVR＇s effects on phytoplankton and MPP, which highlights the need for improved satellite remote sensing of MPP. Then, based on current MPP models using visible radiation, we discussed the quantitative methods used to implement three key model variables related to UVR： the UVR intensity at the sea surface, the attenuation of UVR in the euphotic layer, and the maximum or optimal photosynthetic rate, con- sidering the effects of UVR. The implementation of these UVR-related variables could be useful in further assessing UVR＇s effects on the remote sensing of MPP, and in re- evaluating our existing knowledge of MPP estimation at large spatial scales and long-time scales related to global change.

A remote-sensing image-retrieval model based on an ensemble neural networks

With the rapid development of remote-sensing technology and the increasing number of Earth observation satellites,the volume of image datasets is growing exponentially.The management of big Earth data is also becoming increasingly complex and difficult,with the result that it can be hard for users to access the imagery that they are interested in quickly,efficiently and intelligently.To address these challenges,this paper proposes a remote-sensing image-retrieval model based on an ensemble neural networks.This model can make full use of existing training data to improve the efficiency and accuracy of the initial retrieval of remotesensing images and keep model simple.The retrieval of aerial images using the proposed model is compared with the results obtained using ten individual neural networks and two ensemble neural networks and the results show that the proposed approach has a high degree of precision.In addition,the coverage rate and mean precision show a dramatic improvement of more than 40%compared with existing methods based on normal way.And,the coverage ratio gets 86%for the top 10 return results.