scholarly journals Forest cover change and carbon stock assessment in Swat valley using remote sensing and geographical information systems

2017 ◽  
Vol 6 (3) ◽  
Author(s):  
Sajid Ali
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Carbon Stock ◽  
Geographical Information Systems ◽  
Forest Cover ◽  
Stock Assessment ◽  
Geographical Information ◽  
Forest Cover Change ◽  
Swat Valley

scholarly journals Forest cover monitoring of Bara district (Nepal) using remote sensing and geographic information systems

1970 ◽  
Vol 20 (1) ◽  
pp. 30-36
Author(s):  
CM Kandel ◽  
M Caetano ◽  
P Cabral
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Forest Cover ◽  
Driving Forces ◽  
Forest Area ◽  
Geographical Information ◽  
Forest Cover Change ◽  
Change Analysis ◽  
Spatial Metrics ◽  
Land Cover Maps

This study uses Landsat TM of 1989 and ETM+ of 1999 and 2005 imagery to evaluateforest cover dynamics during 1989-2005 in the Bara district of Nepal. The aim of thestudy was to analyse the extent and trend of forest cover dynamics, spatial pattern offorest and their driving forces. Forest cover change analysis was performed using objectorientedclassification approach applying a standard nearest neighbour algorithm to classifythe image in recognition. The overall classification accuracies were 85.71% and 88.23%for the year 1999 and 2005, respectively. Land cover maps were produced with sevenland cover categories and were further reclassified as forest and non-forest areas toanalyse the forest cover dynamics. Post-classification and time series analysis were carriedout to detect the changes. Spatial metrics were computed for detecting the spatial patternof forest. The classifications suggested that the amount of forest land had decreased by11.56% during 1989-2005. Spatial metrics revealed that forest area has been fragmentedand deforested with an annual rate of 0.72%. The overall result demonstrates that forestarea has experienced a significant shrinkage and mostly transferred into agricultural andbare land. Expected change for the year 2021 was projected using Markov Chain Analysis(MCA). The MCA result showed that forest area would decrease by 8.5% in the period of2005-2021.Key words: Forest cover dynamics; geographical information systems; landsat; remotesensing; spatial metricsDOI: 10.3126/banko.v20i1.3506Banko Janakari, Vol. 20, No. 1 pp.30-36

Modeling air pollution-related hospital admissions employing remote sensing and geographical information systems.

2021 ◽  
pp. 118502
Author(s):  
Tavera Busso Iván ◽  
Rodríguez Núñez Martín ◽  
Amarillo Ana Carolina ◽  
Mettan Fabricio ◽  
Carreras Hebe Alejandra
Keyword(s):  
Remote Sensing ◽  
Air Pollution ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Hospital Admissions ◽  
Geographical Information

scholarly journals Numerical Modeling for Gully Erosion in the North of Algeria based on Data of Remote Sensing and Geographic Information Systems

2017 ◽  
Vol 25 (1) ◽  
pp. 37-63
Author(s):  
mohammad abbas daoudi mohammad abbas daoudi
Keyword(s):  
Remote Sensing ◽  
Multivariate Analysis ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Univariate Analysis ◽  
Probabilistic Approach ◽  
Geographical Information ◽  
Rainfall Erosivity ◽  
Erosion Risk ◽  
The North

The problems of soil erosion are largely widespread in the countries of the Mediterranean basin. The process of gullying is a complex phenomenon with disastrous consequences. It particularly affects northern Algeria, decreasing the potentialities of the water tanks, reducing cultivable lands availability and degrading infrastructures. Therefore, this work studies the analysis and the prediction of gullying erosion by using a probabilistic approach based on multisource data. The objective of this search is to answer to the three following questions: i) which factors support the process of gullying ? ii) how does a process of gullying develop? iii) which are the zones favourable to gullying ? Works are undertaken on the catchment area of the Isser River. We focused the applications on the upstream part of the basin. In this research, we study a North-South transect which corresponds to three under-basins slopes. The choice of these tests areas answers to four criteria defined in our method: the representativeness, the homogeneity, the availability of former data and, finally, the accessibility. After the completion of the multisource data, modelling and multivariate analysis for the prediction of gullying. The combination factor-process by the univariate analysis allows on the one hand, to highlight the variables controlling the process of gullying, and on the other hand, to analyse the variables on a hierarchical basis and to know their degree of influence. The multivariate analysis, by the logistic regression model (LRM), enabled us to select the significant variables and to locate the most favourable zones for the process of gullying. The validation of the models is evaluated using the curves of lift spin. The results suggest that the factors highlighted by the model to be most influential on gullying erosion are: the lithology, the slope, the morphopedology, the rainfall erosivity and the land cover. The synthesis of this approach is illustrated in the form of charts of gullying erosion risk maps in four classes of probability. The assessment of the study shows the fundamental interest of this approach using geographical information systems and remote sensing, in particular for the watersheds of the southern Mediterranean, with the possibility of extending this methodology to other regions.

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