Land cover changed object detection in remote sensing data with medium spatial resolution

Yang, Xiao; Liu, Huiping; Gao, Xiaoyang

doi:10.1016/j.jag.2014.12.015

Cited by 21 publications

(11 citation statements)

References 38 publications

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“…However, the extra features certainly provide more information that should improve the accuracy of change detection in remote sensing imagery (e.g., for NDVI see Ward et al [48] and for textural features see Im et al [49], even though different methods were used). An improvement in overall accuracy with additional information on entropy was observed by Yang et al [13] using an object-based method, although adding NDVI had a detrimental effect on the accuracy. Further improvements in OBCD would therefore require an improved change detection method that was able to take advantage of additional information such as textural information.…”

Section: The Lack Of Accuracy Improvement With Additional Featuresmentioning

confidence: 76%

“…In the second step, multiresolution segmentation [28] was applied separately to a number of different band combinations to generate a variety of different units of analysis even at the same scale (see Figure 2). In the third step, in order to identify changed objects using feature information (see Section 3.3), chi-square transformation [13], which has been widely used in object-based change detection workflows, was applied to a number of different feature difference signatures. Four methods were applied, including original features (Direct Feature differentiation based chi-square transformation (DFC)), MAD variates [12], the first three PCA components [24], and object multidate signatures (Mean and Standard deviation signature based chi-square transformation (MSC)).…”

Section: Methodsmentioning

confidence: 99%

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Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

Blaschke

et al. 2016

Remote Sensing

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Abstract:Object-based change detection (OBCD) has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI) information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD) always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters.

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Section: The Lack Of Accuracy Improvement With Additional Featuresmentioning

confidence: 76%

Section: Methodsmentioning

confidence: 99%

Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

Blaschke

et al. 2016

Remote Sensing

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“…Land use and land cover data also play a crucial role in hydrology research. They are often used to generate landscape-based metrics, monitor status and assess landscape conditions as well as trends over a specified time interval [59][60][61]. The 30 m ETM+ Landsat imagery ( Figure 1a) for year 2003 was obtained from the USGS earth explorer website and the main reason for using ETM+ sensor data was, firstly, due to availability.…”

Section: Acquisition Of Land Use Data and Processingmentioning

confidence: 99%

Relative Effect of Location Alternatives on Urban Hydrology. The Case of Greater Port-Harcourt Watershed, Niger Delta

Dan-Jumbo

Metzger

2019

Hydrology

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Globally, cities in developing countries are urbanising at alarming rates, and a major concern to hydrologists and planners are the options that affect the hydrologic functioning of watersheds. Environmental impact assessment (EIA) has been recognised as a key sustainable development tool for mitigating the adverse impacts of planned developments, however, research has shown that planned developments can affect people and the environment significantly due to urban flooding that arises from increased paved surfaces. Flooding is a major sustainable development issue, which often result from increased paved surfaces and decreased interception losses due to urbanisation and deforestation respectively. To date, several environmental assessment studies have advanced the concept of alternatives, yet, only a small number of hydrologic studies have discussed how the location of paved surface could influence catchment runoff. Specifically, research exploring the effects of location alternative in EIAs on urban hydrology is very rare. The Greater Port-Harcourt City (GPH) development established to meet the growth needs in Port-Harcourt city (in the Niger Delta) is a compelling example. The aim of this research is to examine the relative effect of EIA alternatives in three different locations on urban hydrology. The Hydrologic Engineering Centre’s hydrologic modelling system (HEC-HMS) hydrodynamic model was used to generate data for comparing runoff in three different basins. HEC-HMS software combine models that estimate: Loss, transformation, base flow and channel routing. Results reveal that developments with the same spatial extent had different effects on the hydrology of the basins and sub-basins in the area. Findings in this study suggest that basin size rather than location of the paved surface was the main factor influencing the hydrology of the watershed.

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“…Satellite remote sensing is a method that is frequently used to detect land-use changes on landscapes [27], involving the application of multi-sourced and multi-date satellite imageries to estimate the difference in the extent of land cover. Remotely sensed data can be effectively used to quantify changes in a consistent and accurate way over a range of temporal and geographical scales [27][28][29][30]. Moreover, satellite remote sensing provides the most common source of data for mapping the change patterns that can, in most cases, be readily and repeatedly obtained in a digital and georeferenced format [31].…”

Section: Introductionmentioning

confidence: 99%

“…In the past, researchers have applied a range of change detection methods that can broadly be grouped into pre-classification and post-classification [17,27,[32][33][34]. Pre-classification involves the analysis of transformed images from two different dates.…”

Section: Introductionmentioning

confidence: 99%

Urban Land-Use Dynamics in the Niger Delta: The Case of Greater Port Harcourt Watershed

2018

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Cities in developing countries are urbanising at a rapid rate, resulting in substantial pressures on environmental systems. Among the main factors that lead to flooding, controlling land-use change offers the greatest scope for the management of risk. However, traditional analysis of a “from–to” change matrix is not adequate to provide information of all the land-use changes that occur in a watershed. In this study, an in-depth analysis of land-use change enabled us to quantify the bulk of the changes accumulating from swap changes in a tropical watershed. This study assessed the historical and future land-use/land-cover (LULC) dynamics in the River State region of the Niger Delta. Land-use classification and change detection analysis was conducted using multi-source (Landsat TM, ETM, polygon map, and hard copy) data of the study area for 1986, 1995, and 2003, and projected conditions in 2060. The key findings indicate that historical urbanisation was rapid; urban expansion could increase by 80% in 2060 due to planned urban development; and 95% of the conversions to urban land occurred chiefly at the expense of agricultural land. Urban land was dominated by net changes rather than swap changes, which in the future could amplify flood risk and have other severe implications for the watershed.

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Land cover changed object detection in remote sensing data with medium spatial resolution

Cited by 21 publications

References 38 publications

Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

Relative Effect of Location Alternatives on Urban Hydrology. The Case of Greater Port-Harcourt Watershed, Niger Delta

Urban Land-Use Dynamics in the Niger Delta: The Case of Greater Port Harcourt Watershed

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