Future land use land cover scenario simulation using open source GIS for the city of Warangal, Telangana, India

Satya, B. Aneesha; Shashi, M.; Pratap, Deva

doi:10.1007/s12518-020-00298-4

Cited by 81 publications

(20 citation statements)

References 9 publications

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“…It is an important transformation tool in land use change modeling. However, the following prerequisites must be fulfilled [54][55][56]: (1) In a certain area, different types of land use should be transformable into each other, (2) the conversion between different types of land use can include many events, which are difficult to describe with a specific formula, and (3) within the time limit of the study, the conversion status of the land use structure is relatively stable, which meets the requirements of the Markov chain. Moreover, the area ratio of the mutual conversion between the types of land uses equals the state transition probability.…”

Section: Land Use Scenario Modeling For Reference Levelsmentioning

confidence: 99%

Framework for Accounting Reference Levels for REDD+ in Tropical Forests: Case Study from Xishuangbanna, China

et al. 2021

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The United Nations’ expanded program for Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to mobilize capital from developed countries in order to reduce emissions from these sources while enhancing the removal of greenhouse gases (GHGs) by forests. To achieve this goal, an agreement between the Parties on reference levels (RLs) is critical. RLs have profound implications for the effectiveness of the program, its cost efficiency, and the distribution of REDD+ financing among countries. In this paper, we introduce a methodological framework for setting RLs for REDD+ applications in tropical forests in Xishuangbanna, China, by coupling the Good Practice Guidance on Land Use, Land Use Change, and Forestry of the Intergovernmental Panel on Climate Change and land use scenario modeling. We used two methods to verify the accuracy for the reliability of land classification. Firstly the accuracy reached 84.43%, 85.35%, and 82.68% in 1990, 2000, and 2010, respectively, based on high spatial resolution image by building a hybrid matrix. Then especially, the 2010 Globeland30 data was used as the standard to verify the forest land accuracy and the extraction accuracy reached 86.92% and 83.66% for area and location, respectively. Based on the historical land use maps, we identified that rubber plantations are the main contributor to forest loss in the region. Furthermore, in the business-as-usual scenario for the RLs, Xishuangbanna will lose 158,535 ha (158,535 × 104 m2) of forest area in next 20 years, resulting in approximately 0.23 million t (0.23 × 109 kg) CO2e emissions per year. Our framework can potentially increase the effectiveness of the REDD+ program in Xishuangbanna by accounting for a wider range of forest-controlled GHGs.

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Section: Land Use Scenario Modeling For Reference Levelsmentioning

confidence: 99%

Framework for Accounting Reference Levels for REDD+ in Tropical Forests: Case Study from Xishuangbanna, China

et al. 2021

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“…Four sets of orthorectified Images of Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) with 10-year intervals (images of 1990, 2000, 2010, and 2020) were downloaded from the United States Geological Survey (USGS) Glovis (http://glovi s.usgs.gov) website [14,15] and used for identification of the agricultural changes in KMA (Table 1). All of these images had UTM projection and WGS84 datum [21]. In order to obtain cloud free images (< 10% cloud cover), the month of January had been preferred and, accordingly, two scenes had been downloaded for each year to cover the whole study area.…”

Section: Data Acquisitionmentioning

confidence: 99%

“…However, the small concretized pools and reservoirs were classified under built-up area. Several training signatures within the RoI were also collected from standard false color composites for each year based on pixel color, tone, texture, and association to aid the supervised classification procedure [13,14,21]. After preparing all LULC maps, accuracy assessments were carried out for each one.…”

Section: Image Classificationmentioning

confidence: 99%

Long-term monitoring of cropland transformation in Kolkata Metropolitan Area, India using open-source geospatial technologies

Mazumder

Saha²,

Nandi

et al. 2021

SN Appl. Sci.

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Urban and peri-urban agricultural practices are degrading throughout the developing world owing to unprecedented urban sprawling and consequent expansion of built-up areas. This study attempted to assess the changing land use/land cover patterns of Kolkata Metropolitan Area, India from 1990 to 2020 with special emphasis on the transformation trajectories of its urban and peri-urban agriculture as a case study using free and open-source software and multi-temporal geospatial database. It also aimed to project the transformation scenario of croplands in 2030 through application of the artificial neural network algorithm of the freely available Modules for Land Use Change Evaluation plugin. Results revealed a persistent spread of built-up areas by engulfing croplands, wetlands, vegetation and water bodies throughout the assessment period. An overall loss of 181.11 sq. km of croplands between 1990 and 2020 was estimated and found to be more prominent in the northern, eastern, and south-eastern parts of the study area. If the existing socio-economic framework and administrative mechanism would prevail as usual, then the projected land use patterns of 2030 would predict a further decrease of 15.46 sq. km in cropland area thereby culminating to a total 37.39% of it original extent since 1990. A theoretical three-stage model of land use conversion was developed from the empirical results as well as field observations and validated with the findings of the projected scenario. It indicated two primary conversion patterns for the study area, viz. (1) natural area to cropland to fallow land and then to built-up, and (2) natural area to fallow land to built-up. Few necessary management measures were suggested to mitigate this persistent loss of croplands and other natural areas.

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“…On the other hand, GIS software offers a unique set of capabilities for applying location-based analytics to hydrological process practices. It produces the results via maps, apps, and reports [3,16,33,36,47,58].…”

Section: Introductionmentioning

confidence: 99%

Investigating impact of land-use and land cover changes on hydro-ecological balance using GIS: insights from IIT Bombay, India

Srivastava

Chinnasamy

2021

SN Appl. Sci.

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The present study, for the first time, examined land-use land cover (LULC), changes using GIS, between 2000 and 2018 for the IIT Bombay campus, India. Objective was to evaluate hydro-ecological balance inside campus by determining spatio-temporal disparity between hydrological parameters (rainfall-runoff processes), ecological components (forest, vegetation, lake, barren land), and anthropogenic stressors (urbanization and encroachments). High-resolution satellite imageries were generated for the campus using Google Earth Pro, by manual supervised classification method. Rainfall patterns were studied using secondary data sources, and surface runoff was estimated using SCS-CN method. Additionally, reconnaissance surveys, ground-truthing, and qualitative investigations were conducted to validate LULC changes and hydro-ecological stability. LULC of 2018 showed forest, having an area cover of 52%, as the most dominating land use followed by built-up (43%). Results indicated that the area under built-up increased by 40% and playground by 7%. Despite rapid construction activities, forest cover and Powai lake remained unaffected. This anomaly was attributed to the drastically declining barren land area (up to ~ 98%) encompassing additional construction activities. Sustainability of the campus was demonstrated with appropriate measures undertaken to mitigate negative consequences of unwarranted floods owing to the rise of 6% in the forest cover and a decline of 21% in water hyacinth cover over Powai lake. Due to this, surface runoff (~ 61% of the rainfall) was observed approximately consistent and being managed appropriately despite major alterations in the LULC. Study concluded that systematic campus design with effective implementation of green initiatives can maintain a hydro-ecological balance without distressing the environmental services.

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Future land use land cover scenario simulation using open source GIS for the city of Warangal, Telangana, India

Cited by 81 publications

References 9 publications

Framework for Accounting Reference Levels for REDD+ in Tropical Forests: Case Study from Xishuangbanna, China

Framework for Accounting Reference Levels for REDD+ in Tropical Forests: Case Study from Xishuangbanna, China

Long-term monitoring of cropland transformation in Kolkata Metropolitan Area, India using open-source geospatial technologies

Investigating impact of land-use and land cover changes on hydro-ecological balance using GIS: insights from IIT Bombay, India

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