Assessing inconsistency in global land cover products and synthesis of studies on land use and land cover dynamics during 2001 to 2017 in the southeastern region of Bangladesh

Islam, Md. Shahidul; Zhang, Miao; Yang, Hong; Ma, Mingguo

doi:10.1117/1.jrs.13.048501

Cited by 10 publications

(10 citation statements)

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“…According to the conditions of TR, the streamflow of Alar station is divided into three grades with Q < 50 m 3 /s, 50-500 m 3 /s, and >500 m 3 /s, and the streamflow of Xinquman station is divided into three grades with Q < 40 m 3 /s, 40-400 m 3 /s, and >400 m 3 /s, respectively representing the low flow process, medium flow process, and large flow process by Yu et al [34]. Considering there is no clear river boundary in the mainstream of TR, the annual occurrence days of the large flow process in Alar (Q > 500 m 3 /s) and Xinquman station (Q > 400 m 3 /s) are defined as the yearly overflow days in this paper. Since 2000, an ecological water transport project was launched by the local government, the cumulative eco-water transport value is the sum of the total eco-water transport amount up to a certain year.…”

Section: Correlation Analysismentioning

confidence: 99%

“…Recent years have witnessed increasing concern for vegetation dynamics and landscape ecological risk on the environment and society [1][2][3]. The increasing population pressure and intense human activities have changed the water circulation process in many basins, resulting in various ecological problems, thus the fragile environment is facing unprecedented challenges [4].…”

Section: Introductionmentioning

confidence: 99%

“…The downstream vegetation coverage showed a trend of increasing-decreasing-increasing-decreasing. Comparing the vegetation coverage with the ecological water transport, it was found that the ecological water transport decreased significantly from 6.25 to 1.02 million m3 in 2003-2004, which corresponds to a turning point of vegetation coverage from increasing to decreasing. From 2009 to 2010, the amount of ecological water transport increased significantly from 0.11 to 3.64 million m 3 , corresponding to a turning point of vegetation coverage decreasing to increasing.…”

mentioning

confidence: 99%

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Assessing Vegetation Dynamics and Landscape Ecological Risk on the Mainstream of Tarim River, China

Hui

Xue

Wei³

et al. 2020

Water

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The Tarim River (TR), the longest inland river at an arid area in China, plays a critical role in the sustainable development of the regional ecological environment. This study presents the spatial-temporal variations in the vegetation coverage at regional and pixel scales and its driving factors on the TR mainstream. The latest dataset of normalized difference vegetation index (NDVI) and a vegetation coverage index (fc) over the period from 2000–2015 were analyzed with the unary linear regression and the partial correlation. On the basis of land use data, we further built the landscape ecological risk index and assessed the ecological risk level of the mainstream. Our results suggest that the vegetation coverage index demonstrated fluctuations but denoted a generally upward trend in the TR mainstream, the vegetation improvement areas are far greater than the degraded areas during the study period. Apparently, the overflow days in the TR mainstream and the cumulative amount of water transport are the two main factors that dominate the vegetation coverage. The ecological risk level varies throughout the TR with a high-to-low spatial distribution from upstream to downstream, and the overall landscape ecological risk of the whole basin exhibits an upward tendency. Above all, our study provides a framework with the remote sensing data to assess vegetation coverage and landscape ecological risk which can help design and implement reliable strategies for the ecological management and vegetation restoration in the Tarim River Basin.

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Section: Correlation Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Assessing Vegetation Dynamics and Landscape Ecological Risk on the Mainstream of Tarim River, China

Hui

Xue

Wei³

et al. 2020

Water

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“…Added together, they come to 100. Islam et al (2019) proposed the overall areal inconsistency (OAI), the individual areal inconsistency (AIC) and the overall spatial inconsistency (OSI) metrics. They are formulated as follows:…”

Section: Descriptionmentioning

confidence: 99%

“…Available tools QGIS has no specific tool for calculating the metrics proposed by Yang et al (2017) and Islam et al (2019). However, these can be easily calculated using the cross-tabulation matrix via the formulae set out above.…”

Section: Qgis Exercisesmentioning

confidence: 99%

Metrics Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps

Mas

García-Álvarez

Paegelow

et al. 2022

Land Use Cover Datasets and Validation Tools

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The overlaying of two map layers is a standard GIS procedure. As we saw in the previous chapter, it enables us to compute the intersection between two feature classes and cross-tabulate either the area or the pixel count of the intersecting features depending on whether raster or vector data are being used. Cross-tabulation can be used to evaluate different topics depending on the nature of the input data. In this chapter, cross-tabulation is used to assess land cover changes, the spatial agreement between maps and map accuracy. In Sect. 1, Land use/cover changes (LUCC) are quantified by comparing two LUC maps, computing different indices of change and creating a change matrix. In Sect. 2, we used various metrics to evaluate the spatial agreement between two maps. This procedure was applied to compare a LUC map with a reference map, a simulated LUC map with a reference map and a simulated LUCC map with a reference map of changes. Section 3 introduces the Kappa indices, which allow us to assess the agreement between two datasets, given the agreement expected by random coincidence. We used the indices to compare observed or simulated maps with a reference map. In Sect. 4 we evaluate the agreement between maps at a global level (the entire map) by focusing on a specific feature such as a smaller area or a particular category (stratum level). Finally, in Sect. 5, the cross-tabulation between a map and reference sample data is used to assess the thematic accuracy of the map by calculating various different accuracy indices. We present examples of analyses based on cross-tabulation for four different cases: To validate a series of maps with two or more time points, to validate a map against a reference map, to validate a simulation against a reference map and to validate simulated changes against a reference map of changes. In the example exercises, we use CORINE and SIOSE maps from the Asturias Central Area and Ariège Valley datasets and maps of the Marqués de Comillas region of south-eastern Mexico (MarquesLUC dataset). The cross-tabulation techniques proposed by Robert Gilmore Pontius Jr. are applied in Chapter “Pontius Jr. Methods Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps”.

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Temporal Evaluation of Climate Change on Land Use and Land Cover Changes in the Southeastern Region of Bangladesh from 2001 to 2016

Islam

Hossain

et al. 2021

Climate Change Management

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Assessing inconsistency in global land cover products and synthesis of studies on land use and land cover dynamics during 2001 to 2017 in the southeastern region of Bangladesh

Abstract: Assessing inconsistency in global land cover products and a synthesis of studies on land use and land cover dynamics during 2001-2017 in the southeastern region of Bangladesh. Journal of Applied Remote Sensing, 13 (4). 048501.

Cited by 10 publications

References 44 publications

Assessing Vegetation Dynamics and Landscape Ecological Risk on the Mainstream of Tarim River, China

Assessing Vegetation Dynamics and Landscape Ecological Risk on the Mainstream of Tarim River, China

Metrics Based on a Cross-Tabulation Matrix to Validate Land Use Cover Maps

Temporal Evaluation of Climate Change on Land Use and Land Cover Changes in the Southeastern Region of Bangladesh from 2001 to 2016

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