Classification of land cover from remote sensing fused image based on ICA-SVM and D-S evidence theory

2008 ◽  
Author(s):  
Mi Chen ◽  
Yingchun Fu ◽  
Tao Sun ◽  
Deren Li ◽  
Qianqing Qin
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Evidence Theory ◽  
Fused Image

scholarly journals Isolation Forests to Evaluate Class Separability and the Representativeness of Training and Validation Areas in Land Cover Classification

2019 ◽  
Vol 11 (24) ◽  
pp. 3000 ◽  
Author(s):  
Francisco Alonso-Sarria ◽  
Carmen Valdivieso-Ros ◽  
Francisco Gomariz-Castillo
Keyword(s):  
Remote Sensing ◽  
Random Forest ◽  
Land Cover ◽  
Classification Accuracy ◽  
Land Cover Classification ◽  
Landsat 8 ◽  
Commission Errors ◽  
Class Separability ◽  
Isolation Forest

Supervised land cover classification from remote sensing imagery is based on gathering a set of training areas to characterise each of the classes and to train a predictive model that is then used to predict land cover in the rest of the image. This procedure relies mainly on the assumptions of statistical separability of the classes and the representativeness of the training areas. This paper uses isolation forests, a type of random tree ensembles, to analyse both assumptions and to easily correct lack of representativeness by digitising new training areas where needed to improve the classification of a Landsat-8 set of images with Random Forest. The results show that the improved set of training areas after the isolation forest analysis is more representative of the whole image and increases classification accuracy. Besides, the distribution of isolation values can be useful to estimate class separability. A class separability parameter that summarises such distributions is proposed. This parameter is more correlated to omission and commission errors than other separability measures such as the Jeffries–Matusita distance.

scholarly journals Remote sensing appraisal of Lake Chad shrinkage connotes severe impacts on green economics and socio-economics of the catchment area

2017 ◽  
Vol 4 (11) ◽  
pp. 171120 ◽  
Author(s):  
Olapeju Y. Onamuti ◽  
Emmanuel C. Okogbue ◽  
Israel R. Orimoloye
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Catchment Area ◽  
Supervised Classification ◽  
Economic Status ◽  
Land Use Land Cover ◽  
Economic Activities ◽  
Lake Chad ◽  
Border Communities

Lake Chad commonly serves as a major hub of fertile economic activities for the border communities and contributes immensely to the national growth of all the countries that form its boundaries. However, incessant and multi-decadal drying via climate change pose greater threats to this transnational water resource, and adverse effects on ecological sustainability and socio-economic status of the catchment area. Therefore, this study assessed the extent of shrinkage of Lake Chad using remote sensing. Landsat imageries of the lake and its surroundings between 1987 and 2005 were retrieved from Global Land Cover Facility website and analysed using Integrated Land and Water Information System version 3.3 (ILWIS 3.3). Supervised classification of area around the lake was performed into various land use/land cover classes, and the shrunk part of its environs was assessed based on the land cover changes. The shrinkage trend within the study period was also analysed. The lake water size reduced from 1339.018 to 130.686 km 2 (4.08–3.39%) in 1987–2005. The supervised classification of the Landsat imageries revealed an increase in portion of the lake covered by bare ground and sandy soil within the reference years (13 490.8–17 503.10 km 2 ) with 4.98% total range of increase. The lake portion intersected with vegetated ground and soil also reduced within the period (11 046.44–10 078.82 km 2 ) with 5.40% (967.62 km 2 ) total decrease. The shrunk part of the lake covered singly with vegetation increased by 2.74% from 1987 to 2005. The shrunk part of the lake reduced to sand and turbid water showed 5.62% total decrease from 1987 to 2005 and a total decrease of 1805.942 km 2 in area. The study disclosed an appalling rate of shrinkage and damaging influences on the hydrologic potential, eco-sustainability and socio-economics of the drainage area as revealed using ILWIS 3.3.

scholarly journals Landuse Pattern and Landcover of Akure Forest Reserve and Its Environs

2019 ◽  
pp. 852-861
Author(s):  
O. O. Ojo ◽  
A. A. Shittu ◽  
T. J. Adebolu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Forest Reserve ◽  
Gis And Remote Sensing ◽  
Forestry Management ◽  
Ondo State ◽  
Cover Class ◽  
Broad Objective

This study investigated the pattern of land use and land cover of forest reserve in Akure, Ondo State, Nigeria. Currently, deforestation constitutes one of the global development challenges. The broad objective of this study is to identify land use and land cover class within the study area using satellite imagery (ies) to determine the rate/trend of change of this Forest Reserve from 1988 to 2018. The research method includes the use of Geographical Positioning System, and processing of field data through GIS and Remote sensing tool (ILWIS). The research was able to identify various land use and land cover within the Akure forest reserve with the help of GIS and remote sensing tools, the boundary of Akure forest reserve and its environs was delineated, and further result of the classification of Landsat shows that as at 2018 the forest reserve is covered with majorly light vegetation with 51.79%. The study recommended that there Department of Forestry and Ministry of Physical Planning and Urban Development must ensure Policy that will encourage local people and institutional participation in forestry management and conservation along with safeguarding indigenous people’s traditional rights and tenure with rightful sharing of benefits.

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