Identification and mapping of the water-logged areas in Purba Medinipur part of Keleghai river basin, India: RS and GIS methods

Sahu, Abhay Sankar

doi:10.14419/ijag.v2i2.2452

Cited by 28 publications

(10 citation statements)

References 26 publications

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“…Based on previous studies (Jackson et al 2004, Chen et al 2005, Sahu 2014, it is known to be of great importance to correlate the results obtained by the two indices (NDVI and NDWI) in agricultural areas and in dense or scattered forest regions, where it is possible to quantify the chlorophyll and the moisture present in the vegetation cover.…”

Section: Geotechnologies Usedmentioning

confidence: 99%

Field and remote observations to determine the environmental impact of agrarian reform in the Brazilian Midwest

Bacarji

Vilpoux

Filho

2020

An. Acad. Bras. Ciênc.

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Brazil's Midwest is composed of four biomes, the Cerrado (Brazilian savannah), predominant in the region; the Pantanal, the largest irrigated plain on the planet; the Amazon biome; and the Atlantic Forest. The Midwest is the largest producer of grains and livestock in Brazil, activities that have a negative impact on environmental preservation. Agrarian reform redistributes land and reinforces small family farming, which many authors consider as favorable to environmental protection. The objective of this study is to characterize the impact of agrarian reform on environmental preservation and agriculture on each biome of the Brazilian Midwest. Fifty-four settlements were surveyed using direct observation and Landsat images available for the year 2014. QGIS software 2.8 Wien was applied to calculate NDVI and NDWI vegetation indices to classify areas of agriculture, pasture, and environmental preservation. Pasture and savannah land occupy the largest areas in all biomes, with the main human activity based on livestock. Most settlements in the Midwest lead to small-scale activities such as dairy farming and polyculture, practices that differ from large-scale farming based on monoculture, and are more favorable to environmental protection.

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Section: Geotechnologies Usedmentioning

confidence: 99%

Field and remote observations to determine the environmental impact of agrarian reform in the Brazilian Midwest

Bacarji

Vilpoux

Filho

2020

An. Acad. Bras. Ciênc.

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“…In addition, one vegetation index (Normalized Difference Vegetation Index) and two water content indexes (Normalized Difference Water Index and Normalized Difference Moisture Index) were used as a proxy of vegetation greenness and soil moisture, respectively. All these indexes were derived from Landsat 8 OLI/ TIRS satellite image acquired in 6 May 2016 (http://earthexplorer.usgs.gov/) using the following formula (Sahu, 2014): All the environmental layers used in the models had 30 m resolution. These layers were clipped to Nusakambangan boundary to be used in the modeling procedures.…”

Section: Environmental Variables Selectionmentioning

confidence: 99%

Predicting Habitat Distribution of Endemic and Critically Endangered Dipterocarpus Littoralis in Nusakambangan, Indonesia

Robiansyah¹

2017

REINWARDTIA

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ROBIANSYAH, I. 2017. Predicting habitat distribution of endemic and critically endangered Dipterocarpus littoralis in Nusakambangan, Indonesia. Reinwardtia 16(1): 11 - 18. - The tree species Dipterocarpus littoralis (Bl.) Kurz. is endemic to Nusakambangan and categorized as critically endangered. In the present study, the habitat suitability of the species in Nusakambangan was predicted using logistic regression analysis and Maxent model. Three topographic variables (elevation, slope, and aspect), distance from river and coastline, and one vegetation index (Normalized Difference Vegetation Index (NDVI)) as well as two water content indexes (Normalized Difference Water Index (NDWI) and Normalized Difference Moisture Index (NDMI)) were used as predictors of the models. Employing initial number of 82 presence and 250 absence data of D. littoralis, both models were able to predict the suitable areas for the species with fairly high success rate. The AUC and Kappa value for logistic regression were 0.77 ± 0.027 and 0.34 ± 0.058, respectively, while the respected values for Maxent were 0.91 ± 0.062 and 0.37 ± 0.025. Logistic regression analysis identified a total area of 26.13 km2 to be suitable for D. littoralis, while a smaller suitable area (7.85 km2) was predicted by Maxent model. Coastal areas in the west part of the island were predicted by both models as areas with high suitability for D. littoralis. Furthermore, distance from coastline and river, elevation, NDVI, NDWI and NDMI were suggested to be very important for the species ecology and distribution. The results of this study may serve as a basis for population reinforcement and reintroduction programs of D. littoralis and guide for ecosystem management of Nusakambangan Island as a whole.

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“…The geological location of Haryana with the Himalayan Mountains on the north-east and the Thar Desert on the south west leads to mainly inland drainage conditions and an extensively closed basin. Both surface and sub-surface water flow towards this depression and eventually stagnates thus resulting in problems of a rising water table, waterlogging, flooding after heavy rainfall and soil salinization (Sahu, 2014). This problem is further compounded by the leakages from unlined canals and surface drains.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Impact of Canal Network on Surface Waterlogging Using Remote Sensing Datasets in Rohtak District, Haryana

Kaushik

Dhote

Thakur

2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Remote Sensing is a very reliable and expeditious technique for assessment and mapping of surface waterlogged areas. In this study band ratio based NDWI index (Normalized Difference Water Index) was used for extracting water pixels from optical imageries. To overcome the limitation of false positives and cloud penetration associated with optical imageries waterlogged areas was also extracted using SAR (Synthetic Aperture Radar) images. Thresholding of NDWI for optical image and Sigma0 for SAR images was done using their respective histograms to distinguish water and terrestrial features. The total surface waterlogged areas in the district was calculated by integrating the results from both optical and SAR images. It was found that surface waterlogged areas varies temporally from pre-monsoon to post-monsoon period in Rohtak district, Haryana. The surface waterlogged area for pre monsoon period is around 9.7km2 and for post monsoon period is 17.86km2. The canal and surface drain network in the district was digitized using the high resolution Sentinel 2 MSS images. Since most of the canals in the area are unlined a buffer of 500m either side of the canals and surface drains was considered to assess the impact of seepage and leakage from canals and surface drains. It was found that more than 50% of the total surface waterlogged areas fall within this buffer, clearly indicating the contribution of leakages from canals and surface drains on surface waterlogging.

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Identification and mapping of the water-logged areas in Purba Medinipur part of Keleghai river basin, India: RS and GIS methods

Cited by 28 publications

References 26 publications

Field and remote observations to determine the environmental impact of agrarian reform in the Brazilian Midwest

Field and remote observations to determine the environmental impact of agrarian reform in the Brazilian Midwest

Predicting Habitat Distribution of Endemic and Critically Endangered Dipterocarpus Littoralis in Nusakambangan, Indonesia

Assessing the Impact of Canal Network on Surface Waterlogging Using Remote Sensing Datasets in Rohtak District, Haryana

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