Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhang, Geli; Shimada, Masanobu; Liu, Jiyuan; Li, Chungan; Kou, Weili; Moore, Berrien

doi:10.1016/j.isprsjprs.2015.08.010

Cited by 84 publications

(81 citation statements)

References 51 publications

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“…Due to limitations in the availability of remote sensing data and the technological incapacity to acquire and process large amounts of remote sensing data prior to 2010, the existing global and regional forest maps were generally based on data obtained using sensors with coarse resolutions [13]. For example, these coarse platforms include the IGBP DISCOVER land cover data based on the Advanced Very High Resolution Radiometer (AVHRR) [14], the UMD Land Cover Data Set based on the AVHRR [15], the GLC2000 data based on the SPOT-VGT [16], the GlobCover data based on the MEdium Resolution Imaging Spectrometer (MERIS) [17], and the MCD12Q1 data based on the Moderate Resolution Imaging Spectroradiometer (MODIS) [18].…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the global scale products, several national scale forest mapping efforts have been made in China. Through the integration of PALSAR and MODIS/Landsat data, Qin et al [13] generated a new forest map of China. Another land cover and land use product widely used in China is the NLCD-China from the Chinese Academy of Sciences [23], which has produced several epochs of datasets for 1990,1995,2000,2005,2010, and 2015.…”

Section: Introductionmentioning

confidence: 99%

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

Yang

Dong

Liu

et al. 2017

IJGI

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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 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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Yang

Dong

Liu

et al. 2017

IJGI

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“…Global forests occupy 31% (4.0 × 10 7 km 2 ) of the total land area [1]. Tropical forests play a very important role in global carbon cycles, water and heat fluxes [2,3], biodiversity, and water and soil conservation, and produce half of the total Net Primary Production (NPP) of the world.…”

Section: Introductionmentioning

confidence: 99%

“…Several Landsat-based global forest products have been generated, including a global map of mangroves [13], a 30-m global land cover map between 1999 to 2011 [14], and a global forest cover change map [15]. Landsat missions (Thematic Mapper TM, Enhanced Thematic Mapper /ETM+, and the Operational Land Imager /OLI) have been extensively used to map forests [1,15,16], but due to frequent cloud cover, high-quality images are hard to capture in tropical regions. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery with a temporal resolution of eight days increases the chance to obtain quality data for target objects, and helps alleviate the shortage of other optical remote sensing sensors.…”

Section: Introductionmentioning

confidence: 99%

Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery

Kou

Liang

Wei

et al. 2017

Forests

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Updated extent, area, and spatial distribution of tropical evergreen forests from inventory data provides valuable knowledge for research of the carbon cycle, biodiversity, and ecosystem services in tropical regions. However, acquiring these data in mountainous regions requires labor-intensive, often cost-prohibitive field protocols. Here, we report about validated methods to rapidly identify the spatial distribution of tropical forests, and obtain accurate extent estimates using phenology-based procedures that integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat imagery. Firstly, an analysis of temporal profiles of annual time-series MODIS Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) was developed to identify the key phenology phase for extraction of tropical evergreen forests in five typical lands cover types. Secondly, identification signatures of tropical evergreen forests were selected and their related thresholds were calculated based on Landsat NDVI, EVI, and LSWI extracted from ground true samples of different land cover types during the key phenology phase. Finally, a map of tropical evergreen forests was created by a pixel-based thresholding. The developed methods were tested in Xishuangbanna, China, and the results show: (1) Integration of Landsat and MODIS images performs well in extracting evergreen forests in tropical complex mountainous regions. The overall accuracy of the resulting map of the case study was 92%; (2) Annual time series of high-temporal-resolution remote sensing images (MODIS) can effectively be used for identification of the key phenology phase (between Julian Date 20 and 120) to extract tropical evergreen forested areas through analysis of NDVI, EVI, and LSWI of different land cover types; (3) NDVI and LSWI are two effective metrics (NDVI ≥ 0.670 and 0.447 ≥ LSWI ≥ 0.222) to depict evergreen forests from other land cover types during the key phenology phase in tropical complex mountainous regions. This method can make full use of the Landsat and MODIS archives as well as their advantages for tropical evergreen forests geospatial inventories, and is simple and easy to use. This method is suggested for use with other similar regions.

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“…Forests and their changes are important to the regional and global carbon cycle, biodiversity and ecosystem services (Qin et al, 2015). Forest production is important for the supply of forest products needed both locally and globally, and a substantial portion of the population of the world depends on forest products for energy, construction material and paper (Nzunda, 2012).…”

Section: Introductionmentioning

confidence: 99%

Forest insurance market participants’ game behavior in China: An analysis based on tripartite dynamic game model

Zuo

Liu

et al. 2015

JIEM

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Abstract:Purpose: In forest insurance market, there are three main participants including the insurance company, the forest farmer and the government. As different participant has different benefit object, there will be a complex and dynamic game relationship among all participants. The purpose of this paper is to make the game relationship among all participants in forest insurance market clear, and then to put forward some policy suggestions on the implementation of forest insurance from the view of game theory.Design/methodology/approach: Firstly, the static game model between the insurance company and the forest farmer is set up. According to the result of static game model, it's difficult to implement forest insurance without government. Secondly, the tripartite dynamic game model among the government, the insurance company and the forest farmer is proposed, and the equilibrium solution of tripartite dynamic game model is acquired. Finally, the behavioral characteristics of all participants are analyzed according to the equilibrium solution of tripartite dynamic game model. Findings:The government's allowance will be an important positive factor to implement forest insurance. The loss of the insurance company, which the lower insurance premium brings, can be compensated by the allowance from the government. The more the government provides allowance, the more actively the insurance company will implement forest insurance at -1533-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1550 a low insurance premium. In this situation, the forest farmer will be more likely to purchase the forest insurance, then the scope of forest insurance implementation will expend. Originality/value: There is a complex and dynamic game relationship among all participants in forest insurance market. Based on the tripartite dynamic game model, to make the game relationship between each participant clear is conducive to the implementation of forest insurance market in China.

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Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI

Cited by 84 publications

References 51 publications

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

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

Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery

Forest insurance market participants’ game behavior in China: An analysis based on tripartite dynamic game model

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