Distribution and Variation of Forests in China from 2001 to 2011: A Study Based on Remotely Sensed Data

Zhao, Xiang; Xu, Peipei; Zhou, Tao; Li, Qing; Wu, Deming

doi:10.3390/f4030632

Cited by 16 publications

(10 citation statements)

References 46 publications

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“…In this context, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor instrument aboard the Terra and Aqua platforms [11] has been widely used for terrestrial monitoring due to its high temporal resolution and sensitivity to radiometric and geometric properties. Moreover, several phenological studies have been conducted using the vegetation indices of MODIS images in both natural ecosystems [12][13][14] and in anthropic landscapes such as agricultural expansion [15][16][17], crop phenology [18,19], pastures [20], and eucalyptus plantations [21].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

et al. 2015

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Abstract:We have mapped the primary native and exotic vegetation that occurs in the Cerrado-Caatinga transition zone in Central Brazil using MODIS-NDVI time series (product MOD09Q1) data over a two-year period (2011)(2012)(2013). Our methodology consists of the following steps: (a) the development of a three-dimensional cube composed of the NDVI-MODIS time series; (b) the removal of noise; (c) the selection of reference temporal curves and classification using similarity and distance measures; and (d) classification using support vector machines (SVMs). We evaluated different temporal classifications using similarity and distance measures of land use and land cover considering several combinations of attributes. Among the classification using distance and similarity measures, the best result employed the Euclidean distance with the NDVI-MODIS data by considering more than one reference temporal curve per class and adopting six mapping classes. In the majority of tests, the SVM classifications yielded better results than other methods. The best OPEN ACCESSRemote Sens. 2015, 7 12161 result among all the tested methods was obtained using the SVM classifier with a fourth-degree polynomial kernel; an overall accuracy of 80.75% and a Kappa coefficient of 0.76 were obtained. Our results demonstrate the potential of vegetation studies in semiarid ecosystems using time-series data.

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Section: Introductionmentioning

confidence: 99%

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

et al. 2015

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“…The Forestry Administration of Jiangxi Province expects that watershed management projects will increase forest cover to 63.1% by 2020 [57] However, forest cover in this watershed has already increased to 63.1% due to effective watershed management projects [22,58]. Meanwhile, the time needed for artificial forests to reach maturity is shorter than that required by natural forests.…”

Section: Discussionmentioning

confidence: 99%

Increased Vegetation Greenness Aggravates Water Conflicts during Lasting and Intensifying Drought in the Poyang Lake Watershed, China

Tang

Cai

Gong

et al. 2018

Forests

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An increase in vegetation greenness can improve ecosystem productivity, but also reduce the water supply, creating the potential for conflicting water demands between ecosystems and humans. This problem has been well-assessed and is most evident in dry environments. However, in humid regions, the potential effects of vegetation greenness on water yields under drought conditions are not well understood. To address this gap, we focused on the Poyang Lake watershed in the humid region of southern China. Based on the Standardized Precipitation Evapotranspiration Index and a satellite-derived leaf area index dataset during the growing seasons of 1984 to 2013, several typical dry growing seasons were selected as the study conditions. An existing Water Supply Stress Index model was modified to investigate how the changes in vegetation greenness affected water yield and to explore potentially conflicting water demands between ecosystems and humans under drought conditions. Our results showed that an increase of 20-80% in vegetation greenness generally resulted in a reduction of 3-27% in water yield under drought conditions. Large reductions in water yield mainly were observed in forested areas due to large increases in forest greenness. Moreover, increased vegetation greenness caused a 2 to 3 times greater reduction in water yield during continuing and intensifying droughts than during a short moderate drought period. Thus, in this study, during continuing and intensifying droughts, increased vegetation greenness can cause or aggravate water conflicts in sub-watersheds with high forest cover and high human water demands. Therefore, given the increasing frequency of extreme climatic events, afforestation with a targeted approach should be implemented as it would provide the most benefits. In addition, selective harvesting in forested areas with high density could be an effective strategy to maintain water supply in humid regions.

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“…Monitoring the trends to which ecosystem is changing by the use of indicators such as land cover and socio-demographic information will be essential in order to make proper planning for sustainable ecosystem management. Nowadays, the advancement of geospatial technology such as RS and geographic information system (GIS) present the best efficient tool for analyzing land cover trends as demonstrated by many researchers [5,6,7,8]. Geospatial technologies in addition to conventional inventories can facilitate quantitative evaluation and provide a baseline for monitoring the extent, impacts and trend of LCC.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Land Cover Change and Vegetation Dynamics Using Remote Sensing and DPSIR Framework in Kebbi State, Nigeria

Aliero¹,

M²,

M³

et al. 2017

Preprint

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Assessment of the trends of land cover and vegetation dynamics (VD) using remote sensing (RS) and indicators such as anthropogenic activities and the socio-demographic information is essential in order to make proper planning for sustainable management. This paper attempts to evaluate land cover change (LCC) and VD in Kebbi State, Nigeria using historical Landsat data from 1986-2016 by means of remote sensing. The Driver-Pressure-State-Impact-Response (DPSIR) framework was later employed using both primary and secondary data for a better understanding of the drivers, the state of the environmental condition, the causes as well as the impact of the change. The images were classified into five thematic land cover classes as Dense Vegetation, shrubs/built area, farmland, bare/grassland and water body by means of Maximum likelihood supervised classification technique in accordance with Anderson classification scheme level 1, with acceptable accuracy. Pre-classification and post-classification change detection (CD) methodologies were executed using Normalized difference vegetation index (NDVI) and Image differencing respectively. The study illustrates a steady decline in dense vegetation and shrubs/build areas while farmland and bare/grassland increases, however, water bodies remain unchanged. The DPSIR pin-point that the major drivers of change in the study area have been the pressing need for farming land as the population grows and socioeconomic demands including fuelwood consumption and endemic poverty. Expansion of Farming land, fuelwood consumption and the need for construction materials are identified as the main key elements exerting pressure for the change. The state of the condition indicates a steady decline in dense vegetation and shrubs areas while farmland and bare/grassland are increasing significantly. The impacts include land degradation, the decline in the provision ecosystem goods and services, biodiversity loss through loss of habitats. The study, however, noted that many international and national policies in response to land degradation are channelled toward land restoration and remediating of the environment, through afforestation programs and improving the livelihood of the rural people through providing alternative income sources since they depend heavily on land for sustenance. However, the state governments, communities and individual commonly organized annual tree planting campaign with the main purpose of environmental protection.

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Distribution and Variation of Forests in China from 2001 to 2011: A Study Based on Remotely Sensed Data

Cited by 16 publications

References 46 publications

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

Increased Vegetation Greenness Aggravates Water Conflicts during Lasting and Intensifying Drought in the Poyang Lake Watershed, China

Evaluation of Land Cover Change and Vegetation Dynamics Using Remote Sensing and DPSIR Framework in Kebbi State, Nigeria

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