Monitoring land use changes associated with urbanization: An object based image analysis approach

Samal, Dipak R.; Gedam, Shirish S.

doi:10.5721/eujrs20154806

Cited by 67 publications

(25 citation statements)

References 34 publications

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“…Land use describes human operations such as landrelated agriculture, settlement, and industry, while as the land cover relates to features such as lakes, mountains, vegetation, and rocks on the surface of earth (Samal & Gedam, 2016). (LULC) regulates volume, timing, and recharge amount.…”

Section: Landuse Landcover (Lulc)mentioning

confidence: 99%

Delineation of potential groundwater recharge zones using analytical hierarchy process (AHP)

Dar

Rai

Bhat

2020

Geology, Ecology, and Landscapes

174

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In the present study, an effort was made in Kashmir Valley, NW-Himalayas to delineate potential groundwater areas using GIS and Analytical Hierarchy method (AHP) by incorporating remote sensing data with data from other sources. These data sets were used to prepare eight thematic layers of slope, soil texture, drainage density, land/land cover (LULC), lithology, geomorphology, lineament density, and rainfall. The analytical method of AHP pair wise matrix was used to evaluate the normalized weight of these thematic layers. All the thematic layers and their corresponding classes were allocated ranks and weights based on their impact on groundwater potential. The study area has been classified into five different potential groundwater recharge zonesexcellent (28.97%), good (19.99%), moderate (21.70%), poor (27.16%) and very poor (2.15%). The groundwater potential map prepared for the study area has been validated with 245 existing bore-wells and flow direction of basin. The validation of results was in agreement with the evidence obtained as Area Under Curve (AUC) was calculated to be 79.69% and flow computational investigations which suggest groundwater flows north-eastward from south of basin up to central Kashmir, and south-westward from North towards Jhelum River. The validation suggests that the applied method proves to give us a very significant and reliable result for the study area.

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Section: Landuse Landcover (Lulc)mentioning

confidence: 99%

Delineation of potential groundwater recharge zones using analytical hierarchy process (AHP)

Dar

Rai

Bhat

2020

Geology, Ecology, and Landscapes

174

View full text Add to dashboard Cite

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“…The global increase of agricultural and urban areas (Foley et al, 2005) results in a competition for land (Müller and Munroe, 2014). Previous research in the region has shown that cropland and urban area compete for similar areas (Samal and Gedam, 2015), resulting in a relocation of cropland due to urban growth in the study area (Wagner et al, 2013). This competition is well reflected in the R-G-B composite in Fig.…”

Section: Discussionmentioning

confidence: 81%

Importance of spatially distributed hydrologic variables for land use change modeling

Wagner

Waske

2016

Environmental Modelling & Software

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“…Object-based methods are commonly applied to images with high spatial resolution such as IKONOS, GeoEye, QuickBird and SPOT; however, this method has also been applied in land cover classification using medium resolution Landsat images [19,84,85]. For example, object-based classification was used on Landsat MSS, TM and ETM+ for land cover classification in Ethiopia and on urban sprawl in Eritrea [86,87].…”

Section: Object-based Approachmentioning

confidence: 99%

Developments in Landsat Land Cover Classification Methods: A Review

2017

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Land cover classification of Landsat images is one of the most important applications developed from Earth observation satellites. The last four decades were marked by different developments in land cover classification methods of Landsat images. This paper reviews the developments in land cover classification methods for Landsat images from the 1970s to date and highlights key ways to optimize analysis of Landsat images in order to attain the desired results. This review suggests that the development of land cover classification methods grew alongside the launches of a new series of Landsat sensors and advancements in computer science. Most classification methods were initially developed in the 1970s and 1980s; however, many advancements in specific classifiers and algorithms have occurred in the last decade. The first methods of land cover classification to be applied to Landsat images were visual analyses in the early 1970s, followed by unsupervised and supervised pixel-based classification methods using maximum likelihood, K-means and Iterative Self-Organizing Data Analysis Technique (ISODAT) classifiers. After 1980, other methods such as sub-pixel, knowledge-based, contextual-based, object-based image analysis (OBIA) and hybrid approaches became common in land cover classification. Attaining the best classification results with Landsat images demands particular attention to the specifications of each classification method such as selecting the right training samples, choosing the appropriate segmentation scale for OBIA, pre-processing calibration, choosing the right classifier and using suitable Landsat images. All these classification methods applied on Landsat images have strengths and limitations. Most studies have reported the superior performance of OBIA on different landscapes such as agricultural areas, forests, urban settlements and wetlands; however, OBIA has challenges such as selecting the optimal segmentation scale, which can result in over or under segmentation, and the low spatial resolution of Landsat images. Other classification methods have the potential to produce accurate classification results when appropriate procedures are followed. More research is needed on the application of hybrid classifiers as they are considered more complex methods for land cover classification.

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Monitoring land use changes associated with urbanization: An object based image analysis approach

Cited by 67 publications

References 34 publications

Delineation of potential groundwater recharge zones using analytical hierarchy process (AHP)

Delineation of potential groundwater recharge zones using analytical hierarchy process (AHP)

Importance of spatially distributed hydrologic variables for land use change modeling

Developments in Landsat Land Cover Classification Methods: A Review

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