Assessment of land use/land cover dynamics vis-à-vis hydrometeorological variability in Wular Lake environs Kashmir Valley, India using multitemporal satellite data

2013 ◽  
Vol 7 (11) ◽  
pp. 4707-4715 ◽  
Author(s):  
Fayma Mushtaq ◽  
Arvind Chandra Pandey
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Data ◽  
Land Use Land Cover ◽  
Kashmir Valley ◽  
Wular Lake ◽  
Land Cover Dynamics

scholarly journals IMPACT OF FLOODING ON LAND USE/ LAND COVER TRANSFORMATION IN WULAR LAKE AND ITS ENVIRONS, KASHMIR VALLEY, INDIA USING GEOINFORMATICS

2017 ◽  
Vol IV-4/W4 ◽  
pp. 13-18 ◽  
Author(s):  
T. Ahmad ◽  
A. C. Pandey ◽  
A. Kumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Aquatic Vegetation ◽  
Satellite Image ◽  
Water Bodies ◽  
Land Use Land Cover ◽  
Terrestrial Vegetation ◽  
Kashmir Valley ◽  
Wular Lake ◽  
Classified Image

Wular lake, located at an elevation of 1520&amp;thinsp;m above sea level in Kashmir valley, India. In the present study, the immediate and long term impact of flood (2014) over the Wular lake environs was analyzed by using satellite images and employing supervised classification technique in GIS environment. The LULC classification was performed on the images of 25th August 2014 (pre flood) and 13th September 2015 (post flood) and was compared, which indicated marked decrease in terrestrial vegetation (23.7&amp;thinsp;%), agriculture (43.7&amp;thinsp;%) and water bodies (39.9&amp;thinsp;%). Overlaying analysis was performed with pre and post flood classified images with reference to the satellite image of 10th September 2014(during flood) which indicated total area inundated during flood was 88.77&amp;thinsp;km<sup>2</sup>. With the pre-flood situation, the aquatic vegetation of 34.06&amp;thinsp;km<sup>2</sup>, 13.89&amp;thinsp;km<sup>2</sup> of agriculture land and terrestrial vegetation of 3.13&amp;thinsp;km<sup>2</sup> was inundated. In the post flood situation, it was also came into focus that more than the half of the area under water bodies was converted into sand deposits (22.76&amp;thinsp;km<sup>2</sup>) due to anomalous increase in siltation. The overlay analysis on post flood classified image indicated that aquatic vegetation followed by agriculture and sand deposits lie within the flood inundated area. Further spatial analysis was performed within the flood inundated area (88.77&amp;thinsp;km<sup>2</sup>) with pre and post classified image to understand the situation before and after the flood and to calculate the changes. These land use-land cover transformations signifies the ill effect of flooding on the biodiversity of Wular Lake.

scholarly journals Land use land cover dynamics and fragmentation-induced changes in woody plant community structure in a mining landscape, Ghana

2021 ◽  
Vol 4 ◽  
pp. 100070 ◽  
Author(s):  
Samuel Kumi ◽  
Patrick Addo-Fordjour ◽  
Bernard Fei-Baffoe ◽  
Ebenezer J.D. Belford ◽  
Yaw Ameyaw
Keyword(s):  
Land Use ◽  
Community Structure ◽  
Land Cover ◽  
Plant Community ◽  
Woody Plant ◽  
Plant Community Structure ◽  
Land Use Land Cover ◽  
Land Cover Dynamics ◽  
Induced Changes

scholarly journals Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid Hydrologic Modeling and Basin Planning

2018 ◽  
Vol 10 (12) ◽  
pp. 1910 ◽  
Author(s):  
Joseph Spruce ◽  
John Bolten ◽  
Raghavan Srinivasan ◽  
Venkat Lakshmi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Data ◽  
Reference Data ◽  
Assessment Tool ◽  
Deciduous Forest ◽  
Land Use Land Cover ◽  
Modis Ndvi ◽  
Mekong Basin ◽  
Lower Mekong Basin

This paper discusses research methodology to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB) for basin planning, using both MODIS and Landsat satellite data. The 2010 MODIS MOD09 and MYD09 8-day reflectance data was processed into monthly NDVI maps with the Time Series Product Tool software package and then used to classify regionally common forest and agricultural LULC types. Dry season circa 2010 Landsat top of atmosphere reflectance mosaics were classified to map locally common LULC types. Unsupervised ISODATA clustering was used to derive most LULC classifications. MODIS and Landsat classifications were combined with GIS methods to derive final 250-m LULC maps for Sub-basins (SBs) 1–8 of the LMB. The SB 7 LULC map with 14 classes was assessed for accuracy. This assessment compared random locations for sampled types on the SB 7 LULC map to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data, and Mekong River Commission data (e.g., crop calendars). The SB 7 LULC map showed an overall agreement to reference data of ~81%. By grouping three deciduous forest classes into one, the overall agreement improved to ~87%. The project enabled updated regional LULC maps that included more detailed agriculture LULC types. LULC maps were supplied to project partners to improve use of Soil and Water Assessment Tool for modeling hydrology and water use, plus enhance LMB water and disaster management in a region vulnerable to flooding, droughts, and anthropogenic change as part of basin planning and assessment.

scholarly journals Multi-Temporal Landsat8 Satellite Data Based Crops and Other Land Use Spatial Estimation in Okara District of Pakistan

2018 ◽  
Author(s):  
Ibrar ul Hassan Akhtar ◽  
Athar Hussain ◽  
Kashif Javed ◽  
Hammad Ghazanfar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Data ◽  
Urban Areas ◽  
Integrated Approach ◽  
Kappa Statistics ◽  
Digital Information ◽  
Land Use Land Cover ◽  
Land Utilization ◽  
Cropping Patterns

Developing countries like Pakistan is among those where lack of adoption to science and technology advancement is a major constraint for Satellite Remote Sensing use in crops and land use land cover digital information generation. Exponential rise in country population, increased food demand, limiting natural resources coupled with migration of rural community to urban areas had further led to skewed official statistics. This study is an attempt to demonstrate the possible use of freely available satellite data like Landsat8 under complex cropping system of Okara district of Punjab, Pakistan. An Integrated approach has been developed for the satellite data based crops and land use/cover spatial area estimation. The resultant quality was found above 96% with Kappa statistics of 0.95. Land utilization statistics provided detail information about cropping patterns as well as land use land cover status. Rice was recorded as most dominating crop in term of cultivation area of around 0.165 million ha followed by autumn maize 0.074 million ha, Fallow crop fields 0.067 million ha and Sorghum 0.047 million ha. Other minor crops observed were potato, fodder and cotton being cultivated on less than 0.010 million ha. Population settlements were observed over an area of around 0.081 million ha of land.&nbsp;

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