Monitoring changes in land use land cover of Yamuna riverbed in Delhi: a multi-temporal analysis

2011 ◽  
Vol 32 (24) ◽  
pp. 9547-9558 ◽  
Author(s):  
Rucha R. Joshi ◽  
Mangesh Warthe ◽  
Sharad Dwivedi ◽  
Ritesh Vijay ◽  
Tapan Chakrabarti
2017 ◽  
Vol 10 (2) ◽  
pp. 201-213
Author(s):  
Surya Prakash Pattanayak ◽  
Sumant Kumar Diwakar

Digital change detection is the process that helps in determining the changes associated with Land use and Land cover properties with reference to geo-referenced multi-temporal remote sensing data. It helps in identifying change between two or more dates that is uncharacterized of normal variation. This work is an attempt to assess the district-wise changes in land use/land cover in Delhi, India. The study made use of LISS -III imageries of 2008 and 2012 year. The images were classified using Maximum Likelihood classification method. The output can be useful in many applications such as Land use changes, habitat fragmentation, rate of deforestation, urban sprawl and other cumulative changes through spatial and temporal analysis. The study shows that Delhi land cover from 2008 to 2012 a major rapid changes in the landscape as there is high growth in the fallow and built up area. Agriculture land and forest area has reduced marginally and water body is showing almost stagnant condition over time.


2021 ◽  
Vol 12 ◽  
pp. 100536
Author(s):  
Erica Zanardo Oliveira-Andreoli ◽  
Mayra Cristina Prado de Moraes ◽  
Alexandre da Silva Faustino ◽  
Anaí Floriano Vasconcelos ◽  
Carlos Wilmer Costa ◽  
...  

2017 ◽  
Vol 10 (2) ◽  
pp. 201-213
Author(s):  
Surya Prakash Pattanayak ◽  
Sumant Kumar Diwakar

Digital change detection is the process that helps in determining the changes associated with Land use and Land cover properties with reference to geo-referenced multi-temporal remote sensing data. It helps in identifying change between two or more dates that is uncharacterized of normal variation. This work is an attempt to assess the district-wise changes in land use/land cover in Delhi, India. The study made use of LISS -III imageries of 2008 and 2012 year. The images were classified using Maximum Likelihood classification method. The output can be useful in many applications such as Land use changes, habitat fragmentation, rate of deforestation, urban sprawl and other cumulative changes through spatial and temporal analysis. The study shows that Delhi land cover from 2008 to 2012 a major rapid changes in the landscape as there is high growth in the fallow and built up area. Agriculture land and forest area has reduced marginally and water body is showing almost stagnant condition over time.


2020 ◽  
Vol XIX (1) ◽  
pp. 72-77
Author(s):  
Sushma Shastri ◽  
Prafull Singh ◽  
Pradipika Verma ◽  
Praveen Kumar Rai ◽  
A. P. Singh

2013 ◽  
Vol 39 (4) ◽  
pp. 59-70 ◽  
Author(s):  
Fredrick Ao Otieno ◽  
Olumuyiwa I Ojo ◽  
George M. Ochieng

Abstract Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.


Author(s):  
Antonio Tomao ◽  
Barbara Ermini ◽  
Marcela Prokopov ◽  
Adriano Conte

Negative environmental changes generally addressed as ‘syndromes’ are evaluated in the context of Soil Degradation (SD) and interpreted by using a ‘Land-Use/Land Cover Changes’ (LULCCs) framework in order to disentangle ‘past trajectories’, ‘present patterns’, and ‘future changes’. This approach allows to discuss the potential impact on SD processes and it represents an informed basis for identifying measurable outcomes of SD. This study focuses on the case of Emilia Romagna, a region located in the North of Italy with high-value added agricultural productions. A multi-temporal analysis of land-use changes between 1954 and 2008 has been proposed, discussing the evolution of associated SD syndromes in Emilia Romagna. The contributing information have been used as a baseline for Sustainable Land Management (SLM) strategies. This framework of analysis provides useful tools to investigate and to monitor the effects of SD in the Mediterranean basin where several regions underwent common development patterns yelding global pathological symptoms of environmental degradation.


2020 ◽  
Vol 4 (2) ◽  
pp. 55-78
Author(s):  
Modibbo Babagana-Kyari ◽  
Babagana Boso

The fragile Sudano-Sahelian ecological zone of Nigeria has been classified as a hotspot of land cover change (LCC) that has been suffering from serious anthropogenic and biophysical stresses. Damaturu, being the fastest growing town situated in the region happened to be a victim of this negative development. The purpose of this study is to remotely observe and assess the prevailing land-use/land-cover (LULC) dynamics of Damaturu town and its delicate surrounding lands from the year 1987-2017 study periods. To achieve this, a supervised image classification technique with Maximum Likelihood Classifier (MLC) algorithm was used in ERDAS Imagine version 15 software to classify the three epochs multi-temporal and multi-spectral Landsat imageries (TM 1987, ETM+7 2000 and OLI 2017). The classified LULC maps and their resulting statistics were then used to assess the spatio-temporal aspects of the observed changes by placing the results within the wider context of previous related literature and evidences. Findings revealed that the built-up area has been expanding since 1987 with an annual change rate of 4.5% between 1987-2000, and 5.3% during 2000-2017 respectively. The growth of the town is being accompanied by massive farmlands expansion and vegetal cover (trees and shrubs) lost making the surrounding arable lands seriously disturbed. Thus, if the observed trends continue, the entire studied region will be subjected to severe environmental hazard such as desertification. Overall, the study provides valuable information required for sustainable  environmental management.


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