ISPRS International Journal of Geo-Information

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21233 KiB

Open AccessArticle

Integrating Global Open Geo-Information for Major Disaster Assessment: A Case Study of the Myanmar Flood

by Suju Li, Yan Cui, Ming Liu, Haixia He and Shirish Ravan

ISPRS Int. J. Geo-Inf. 2017, 6(7), 201; https://doi.org/10.3390/ijgi6070201 - 6 Jul 2017

Cited by 13 | Viewed by 6480

Abstract

Major disasters typically impact large areas, cause considerable damages, and result in significant human and economic losses. The timely and accurate estimation of impacts and damages is essential to better understand disaster conditions and to support emergency response operations. Geo-information drawn from various [...] Read more.

Major disasters typically impact large areas, cause considerable damages, and result in significant human and economic losses. The timely and accurate estimation of impacts and damages is essential to better understand disaster conditions and to support emergency response operations. Geo-information drawn from various sources at multi spatial-temporal scales can be used for disaster assessments through a synthesis of hazard, exposure, and post disaster information based on pertinent approaches. Along with the increased availability of open sourced data and cooperation initiatives, more global scale geo-information, including global land cover datasets, has been produced and can be integrated with other information for disaster dynamic damage assessment (e.g., impact estimation immediately after a disaster occurs, physical damage assessment during the emergency response stage, and comprehensive assessment following an emergency response). Residential areas and arable lands affected by the flood disaster occurring from July to August 2015 in Myanmar were assessed based on satellite images, GlobeLand30 data, and other global open sourced information as a study case. The results show that integrating global open geo-information could serve as a practical and efficient means of assessing damage resulting from major disasters worldwide, especially at the early emergency response stage. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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4833 KiB

Open AccessArticle

Experimental Evaluation of the Usability of Cartogram for Representation of GlobeLand30 Data

by Rui Han, Zhilin Li, Peng Ti and Zhu Xu

ISPRS Int. J. Geo-Inf. 2017, 6(6), 180; https://doi.org/10.3390/ijgi6060180 - 21 Jun 2017

Cited by 16 | Viewed by 7392

Abstract

GlobeLand30 is the world’s first global land cover dataset at 30 m resolution for two epochs, i.e., 2000 and 2010. On the official website, the data are represented by qualitative thematic maps which show the distribution of global land cover, and some proportional [...] Read more.

GlobeLand30 is the world’s first global land cover dataset at 30 m resolution for two epochs, i.e., 2000 and 2010. On the official website, the data are represented by qualitative thematic maps which show the distribution of global land cover, and some proportional symbol maps which are quantitative representations of land cover data. However, researchers have also argued that the cartogram, a kind of value-by-area representation, has some advantages over these maps in some cases, while others doubt their usability because of the possible distortion in shape. This led us to conduct an experimental evaluation of the usability of the cartogram for the representation of GlobeLand30. This experimental evaluation is a comparative analysis between the cartogram and the proportional symbol map to examine which is more effective in various kinds of quantitative analyses. The results show that the thematic map is better than the cartogram for the representation of quantity (e.g., area size), but the cartogram performs better in the representation of tendency distribution and areas’ multiple relationships. The usability of the cartogram is notably affected by map projection and the irregularity in area shapes, but the equal-area projection does not necessarily perform better than equidistance projection, especially at high latitudes. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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16300 KiB

Open AccessArticle

Accuracy Assessment and Inter-Comparison of Eight Medium Resolution Forest Products on the Loess Plateau, China

by Zhiqi Yang, Jinwei Dong, Jiyuan Liu, Jun Zhai, Wenhui Kuang, Guosong Zhao, Wei Shen, Yan Zhou, Yuanwei Qin and And Xiangming Xiao

ISPRS Int. J. Geo-Inf. 2017, 6(5), 152; https://doi.org/10.3390/ijgi6050152 - 14 May 2017

Cited by 28 | Viewed by 6111

Abstract

Forests play an important role in maintaining ecosystem services, especially in ecologically fragile areas such as the Loess Plateau (LP) in China. However, there is still great uncertainty in the spatial extent and distribution of forests in such a fragmented region. In order [...] Read more.

Forests play an important role in maintaining ecosystem services, especially in ecologically fragile areas such as the Loess Plateau (LP) in China. However, there is still great uncertainty in the spatial extent and distribution of forests in such a fragmented region. In order to examine the advantages and disadvantages of existing forest mapping products, we conducted a thorough accuracy assessment on the eight recent, medium resolution (30–50 m) products by using the LP in 2010 as the region of interest. These mapping products include Landsat and/or PALSAR images (including the forest products from GlobeLand30), FROM-GLC, Hansen, ChinaCover, NLCD-China, GLCF VCF, OU-FDL, and JAXA. The same validation data were used to assess and rank the accuracy of each product. Additionally, the spatial consistency of the different forest products and their dependence on the terrain were analyzed. The results showed that the overall accuracies of the eight forest products on the LP in 2010 were between 0.93 ± 0.003 and 0.97 ± 0.002 with a 95% confidence interval, and GlobeLand30 presented the highest overall accuracy (0.97 ± 0.002). Among them, the PALSAR-based products (OU-FDL and JAXA) indicated relatively high accuracies, while the six Landsat-based products showed a large diversity in the accuracy. According to the eight products, the total estimated forest area of the LP varied from 7.627 ± 0.077 to 10.196 ± 0.1 million ha with a 95% confidence interval. We also found that the consistency in the spatial distribution of forests between these maps: 1) increased substantially with increasing elevation until 2000m, but then decreased at higher elevations, and 2) showed mild variation along increasing slope, but had a slight rate of increase. Our findings implied that future forest mapping studies should consider topographical attributes such as elevation and slope in their final products. Our results are fundamental in guiding future applications of these existing forest maps. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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8927 KiB

Open AccessArticle

Assessment of Wetland Ecosystem Health in the Yangtze and Amazon River Basins

by Rui Sun, Pingping Yao, Wen Wang, Bing Yue and Gang Liu

ISPRS Int. J. Geo-Inf. 2017, 6(3), 81; https://doi.org/10.3390/ijgi6030081 - 14 Mar 2017

Cited by 54 | Viewed by 9886

Abstract

As “kidneys of the earth”, wetlands play an important role in ameliorating weather conditions, flood storage, and the control and reduction of environmental pollution. With the development of local economies, the wetlands in both the Amazon and Yangtze River Basins have been affected [...] Read more.

As “kidneys of the earth”, wetlands play an important role in ameliorating weather conditions, flood storage, and the control and reduction of environmental pollution. With the development of local economies, the wetlands in both the Amazon and Yangtze River Basins have been affected and threatened by human activities, such as urban expansion, reclamation of land from lakes, land degradation, and large-scale agricultural development. It is necessary and important to develop a wetland ecosystem health evaluation model and to quantitatively evaluate the wetland ecosystem health in these two basins. In this paper, GlobeLand30 land cover maps and socio-economic and climate data from 2000 and 2010 were adopted to assess the wetland ecosystem health of the Yangtze and Amazon River Basins on the basis of a pressure-state-response (PSR) model. A total of 13 indicators were selected to build the wetland health assessment system. Weights of these indicators and PSR model components, as well as normalized wetland health scores, were assigned and calculated based on the analytic hierarchy process method. The results showed that from 2000 to 2010, the value of the mean wetland ecosystem health index in the Yangtze River Basin decreased from 0.482 to 0.481, while it increased from 0.582 to 0.593 in the Amazon River Basin. This indicated that the average status of wetland ecosystem health in the Amazon River Basin is better than that in the Yangtze River Basin, and that wetland health improved over time in the Amazon River Basin but worsened in the Yangtze River Basin. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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10944 KiB

Open AccessArticle

Regions Set in Stone—Delimiting and Categorizing Regions in Europe by Settlement Patterns Derived from EO-Data

by Hannes Taubenböck, Joachim Ferstl and Stefan Dech

ISPRS Int. J. Geo-Inf. 2017, 6(2), 55; https://doi.org/10.3390/ijgi6020055 - 21 Feb 2017

Cited by 15 | Viewed by 9621

Abstract

The spatial patterns of landscapes are complex. Highly dense urban centers are not just mirrowed in a dichotomic sense by rural environments; landscapes are a spatially variable continuum. In this logic, nation-states (or any political or administrative unit) spatially integrate different types and [...] Read more.

The spatial patterns of landscapes are complex. Highly dense urban centers are not just mirrowed in a dichotomic sense by rural environments; landscapes are a spatially variable continuum. In this logic, nation-states (or any political or administrative unit) spatially integrate different types and physical appearances of land cover. Understanding regions in the sense that similar physical characteristics may construct alternative (natural) spatial entities which may sub-divide or cross-over adminstrative boundaries allows us to overcome common map projections. However, which indicators and which regional logics define and delimit regions is conceptually vague. With this paper we aim to add an empirical study to identify regional phenomena in Europe. To do so, we take advantage of a new data set from remote sensing, the Global Urban Footprint. It features European-wide consistent spatial information on settlement patterns. We use density and distribution of settlements as indicators for delimiting regions by similar characteristics. Our methodological approach classifies urban nodes (by settlement density and size), spans an unbounded soft space by the classification of spatial connectivity between nodes (by continuous settlement) and maps territorial entities (by density around nodes); the approach is following a space of place logic. From a geographic perspective we identify uneven development across Europe. The corridor streching from England via the Benelux areas via Germany, Switzerland, France to Northern Italy is mapped as the European backbone; however, new focal areas such as, e.g., towards eastern Europe are also detected. Applying a plausibility check reveals that the proxy settlement pattern corresponds well with regional conceptions presented in other studies. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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4596 KiB

Open AccessArticle

Dynamic Monitoring of Agricultural Fires in China from 2010 to 2014 Using MODIS and GlobeLand30 Data

by Huan Xie, Li Du, Sicong Liu, Lei Chen, Sa Gao, Shuang Liu, Haiyan Pan and Xiaohua Tong

ISPRS Int. J. Geo-Inf. 2016, 5(10), 172; https://doi.org/10.3390/ijgi5100172 - 25 Sep 2016

Cited by 22 | Viewed by 6060

Abstract

In the summer and autumn, which is the primary cropland planting preparation and harvest time, cropland burning is very common in China. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra active fire product (MOD14) and GlobeLand30-2010 data are used here to analyze the fire [...] Read more.

In the summer and autumn, which is the primary cropland planting preparation and harvest time, cropland burning is very common in China. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra active fire product (MOD14) and GlobeLand30-2010 data are used here to analyze the fire activity of the predominant land cover types. A total of 44,852 scenes of MOD14 images and MOD03 images are used, covering the whole of China from 20 May to 31 October during 2010 to 2014. Agricultural burning is a significant contributor to fire activity in China, and accounts for 60% on average of all the fire activity over the last five years. The spatial and temporal distribution of agricultural burning in seven different geographical regions is analyzed in detail. The experiments showed that the Central and Eastern China regions are the largest contributors to agricultural burning, producing 59%–80% of all the agricultural fires. At the national scale, the number of agricultural fire counts peak in June, which is associated primarily with winter burning of wheat croplands. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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Review

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7041 KiB

Open AccessReview

Analysis and Applications of GlobeLand30: A Review

by Jun Chen, Xin Cao, Shu Peng and Huiru Ren

ISPRS Int. J. Geo-Inf. 2017, 6(8), 230; https://doi.org/10.3390/ijgi6080230 - 27 Jul 2017

Cited by 168 | Viewed by 11380

Abstract

Abstract: GlobeLand30, donated to the United Nations by China in September 2014, is the first wall-to-wall 30 m global land cover (GLC) data product. GlobeLand30 is widely used by scientists and users around the world. This paper provides a review of the [...] Read more.

Abstract: GlobeLand30, donated to the United Nations by China in September 2014, is the first wall-to-wall 30 m global land cover (GLC) data product. GlobeLand30 is widely used by scientists and users around the world. This paper provides a review of the analysis and applications of GlobeLand30 based on its data-downloading statistics and published studies. An average accuracy of 80% for full classes or one single class is achieved by third-party researchers from more than 10 countries through sample-based validation or comparison with existing data. GlobeLand30 has users from more than 120 countries on five continents, and from all five Social Benefit Areas. The significance of GlobeLand30 is demonstrated by a number of published papers dealing with land-cover status and change analysis, cause-and-consequence analysis, and the environmental parameterization of Earth system models. Accordingly, scientific data sharing in the field of geosciences and Earth observation is promoted, and fine-resolution GLC mapping and applications worldwide are stimulated. The future development of GlobeLand30, including comprehensive validation, continuous updating, and monitoring of sustainable development goals, is also discussed. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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1222 KiB

Open AccessReview

The Standardization and Harmonization of Land Cover Classification Systems towards Harmonized Datasets: A Review

by Hui Yang, Songnian Li, Jun Chen, Xiaolu Zhang and Shishuo Xu

ISPRS Int. J. Geo-Inf. 2017, 6(5), 154; https://doi.org/10.3390/ijgi6050154 - 19 May 2017

Cited by 47 | Viewed by 9126

Abstract

A number of national, regional and global land cover classification systems have been developed to meet specific user requirements for land cover mapping exercises, independent of scale, nomenclature and quality. However, this variety of land-cover classification systems limits the compatibility and comparability of [...] Read more.

A number of national, regional and global land cover classification systems have been developed to meet specific user requirements for land cover mapping exercises, independent of scale, nomenclature and quality. However, this variety of land-cover classification systems limits the compatibility and comparability of land cover data. Furthermore, the current lack of interoperability between different land cover datasets, often stemming from incompatible land cover classification systems, makes analysis of multi-source, heterogeneous land cover data for various applications a very difficult task. This paper provides a critical review of the harmonization of land cover classification systems, which facilitates the generation, use and analysis of land cover maps consistently. Harmonization of existing land cover classification systems is essential to improve their cross-comparison and validation for understanding landscape patterns and changes. The paper reviews major land cover classification standards according to different scales, summarizes studies on harmonizing land cover mapping, and discusses some research problems that need to be solved and some future research directions. Full article

(This article belongs to the Special Issue Analysis and Applications of Global Land Cover Data)

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