Analyzing the degradation sequence of the meadow grassland in Xilin River basin, Inner Mongolia, using multi-temporal landsat TM/ETM+ sensor data

2004 ◽  
Author(s):  
Siqing Chen ◽  
Jiyuan Liu ◽  
Dafang Zhuang ◽  
Xiangming Xiao ◽  
Xinfang Yu ◽  
...  
Keyword(s):  
River Basin ◽  
Inner Mongolia ◽  
Landsat Tm ◽  
Sensor Data ◽  
Multi Temporal

scholarly journals Drought evolution characteristics and precipitation intensity changes during alternating dry-wet changes in the Huang-Huai-Hai River basin

2013 ◽  
Vol 10 (3) ◽  
pp. 2665-2696 ◽  
Author(s):  
D. H. Yan ◽  
D. Wu ◽  
R. Huang ◽  
L. N. Wang ◽  
G. Y. Yang
Keyword(s):  
River Basin ◽  
Inner Mongolia ◽  
Precipitation Intensity ◽  
Occurrence Frequency ◽  
Drought Frequency ◽  
Piedmont Plain ◽  
Daily Precipitation Data ◽  
Huai River ◽  
Increasing Trend ◽  
Frequency Changes

Abstract. According to the Chinese climate divisions and the Huang-Huai-Hai River basin digital elevation map, the basin is divided into seven sub-regions by means of cluster analysis of the basin meteorological stations using the self-organizing map (SOM) neural network method. Based on the daily precipitation data of 171 stations for the years 1961–2011, the drought frequency changes with different magnitudes are analyzed and the number of consecutive days without precipitation is used to identify the drought magnitudes. The first precipitation intensity after a drought period is analyzed with the Pearson-III frequency curve, then the relationship between rainfall intensity and different drought magnitudes is observed, as are the drought frequency changes for different years. The results of the study indicated the following: (1) the occurrence frequency of different drought level shows an overall increasing trend; there is no clear interdecadal change shown, but the spatial difference is significant. The occurrence frequencies of severe and extraordinary drought are higher on the North China Plain, Hetao Plains in Ningxia-Inner Mongolia, as well as on the Inner Mongolia and the Loess Plateaus, and in the Fen-Wei Valley basin. (2) As the drought level increases, the probability of extraordinary rainstorm becomes lower, and the frequency of occurrence of spatial changes in different precipitation intensities vary. In the areas surrounding Bo Sea, the Shandong Peninsula and the Huai River downstream, as the drought level increases, the occurrence frequency of different precipitation intensities first shows a decreasing trend, which becomes an increasing trend when extraordinary drought occurs. In the middle and upper reaches of the Huai River basin, on the Hai River basin piedmont plain and Hetao Plains in Ningxia-Inner Mongolia, Inner Mongolia and Loess Plateaus, and in the Fen-Wei Valley basin, the probability of the different precipitation intensities shows an overall decreasing trend. The mountains with high attitude and Tibetan Plateau are located at high altitudes where the variation of different precipitation intensities with the increase in drought level is relatively complex. (3) As the drought frequency increases, areas I, II and V which are located on the coastal and in the river basin are vulnerable to extreme precipitation processes; areas III, IV, VI and VII are located in the inland area where heavier precipitation is not likely to occur.

Remote sensing of Australian wetlands: An evaluation of Landsat TM data for inventory and classification

1993 ◽  
Vol 44 (2) ◽  
pp. 235 ◽  
Author(s):  
RM Johnston ◽  
MM Barson
Keyword(s):  
Remote Sensing ◽  
Water Regime ◽  
Landsat Tm ◽  
Classification Methods ◽  
Vegetation Types ◽  
Infrared Band ◽  
South Wales ◽  
Multi Temporal ◽  
Density Slicing ◽  
Remote Sensing Techniques

This study aimed to develop simple remote-sensing techniques suitable for mapping and monitoring wetlands, using Landsat TM imagery of inland wetland sites in Victoria and New South Wales. A range of classification methods was examined in attempts to map the location and extent of wetlands and their vegetation types. Multi-temporal imagery (winter/spring and summer) was used to display seasonal variability in water regime and vegetation status. Simple density slicing of the mid-infrared band (TM5) from imagery taken during wet conditions was useful for mapping the location and extent of inundated areas. None of the classification methods tested reproduced field maps of dominant vegetation species; however, density slicing of multi-temporal imagery produced classes based on seasonal variation in water regime and vegetation status that are useful for reconnaissance mapping and for examining variability in previously mapped units. Satellite imagery is unlikely to replace aerial photography for detailed mapping of wetland vegetation types, particularly where ecological gradients are steep, as in many riverine systems. However, it has much to offer in monitoring changes in water regime and in reconnaissance mapping at regional scales.

Impact of a volcanic eruption on the sediment connectivity of a Chilean river basin: the Calbuco study case

2021 ◽  
Author(s):  
Marco Andreoli ◽  
Lorenzo Martini ◽  
Marco Cavalli ◽  
Andrés Iroumé ◽  
Lorenzo Picco
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Volcanic Eruption ◽  
Overland Flow ◽  
Volcanic Eruptions ◽  
Landsat 8 ◽  
Strong Impact ◽  
Low Resolution ◽  
Multi Temporal ◽  
Sediment Connectivity

<p>Volcanic eruptions are natural disturbances capable of introducing large quantities of sediment into river systems as to upset the transport regime for several years. Such a disturbance can have a strong impact on the water and sediment flows and consequently on the transport capacity. Moreover, changes in morphological settings and land cover lead to an alteration of the sediment connectivity within the catchment. This study aims to investigate the changes of sediment connectivity in a catchment affected by an explosive volcanic eruption using the Index of Connectivity (IC) with a multi-temporal approach. Potential variations were analyzed at the catchment scale over a period of 6 years, before and after the eruption. The study area, located in southern Chile, is the Blanco Este River basin (39,6 km²), affected by the eruption of the Calbuco volcano (April 2015, total volume of sediment expelled of about 0,28 km³) which profoundly changed its vegetation cover, geomorphology and hydrology. IC analyses were based on low-resolution and freely available data (i.e., GDEM, Landsat 8 satellite images). Through supervised image classification and field data survey, a Manning's n coefficient for overland flow is derived as weighting factor (W) due to its suitability to represent the impedance to sediment flows in catchments characterized by land cover variations. Following the eruption, bare soil cover on the basin doubled (from 5% to 10% of total basin area). Consequently, the multi-temporal analysis results in an overall increase of IC with the median value ranges from -3,58 to -3,26 in pre-eruptive (2015) and first post-eruptive scenario (2016), respectively. The connectivity maps show that the higher IC values (i.e. range from -1,23 to 1,66) are persistently located in three areas: at the base of the volcanic dome, on the steepest slopes near the main channel and in a sub-basin on the right side of the catchment. Moreover, the Difference of IC (DoIC) among different scenarios highlighted the major variations. Such changes are found along the volcano slopes, in a flat area located in the upper part of the basin and along the lower valley of the Rio Blanco Este. The study proposes a useful methodology to evaluate the sediment connectivity, and its evolutionary trends, in environments affected volcanic eruptions starting from low-resolution data and field survey. These results may help to better define types, location and typologies of interventions to improve the river management approaches, considering the ongoing cascading processes. This research is funded by the Fondecyt 1200079 project.</p>

Comparing the MLC and JavaNNS Approaches in Classifying Multi-Temporal LANDSAT Satellite Imagery over an Ephemeral River Area

2015 ◽  
Vol 6 (4) ◽  
pp. 83-102 ◽  
Author(s):  
Eufemia Tarantino ◽  
Antonio Novelli ◽  
Mariella Aquilino ◽  
Benedetto Figorito ◽  
Umberto Fratino
Keyword(s):  
Land Cover ◽  
A Priori ◽  
Sensor Data ◽  
Network Simulator ◽  
Research Activity ◽  
The Past ◽  
Time Space ◽  
Multi Temporal ◽  
Study Case ◽  
Landsat Satellite

This paper analyzes two pixel-based classification approaches to support the analysis of land cover transformations based on multitemporal LANDSAT sensor data covering a time space of about 24 years. The research activity presented in this paper was carried out using Lama San Giorgio (Bari, Italy) catchment area as a study case, being this area prone to flooding as proved by its geological and hydrological characteristics and by the significant number of floods occurred in the past. Land cover classes were defined in accordance with on the CN method with the aim of characterizing land use based on attitude to generate runoff. Two different classifiers, i.e. Maximum Likelihood Classifier (MLC) and Java Neural Network Simulator (JavaNNS) models, were compared. The Artificial Neural Networks (ANN) approach was found to be the most reliable and efficient when lacking ground reference data and a priori knowledge on input data distribution.

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