Chinese Journal of Applied Ecology ›› 2020, Vol. 31 ›› Issue (11): 3777-3785.doi: 10.13287/j.1001-9332.202011.012
Previous Articles Next Articles
WU Bing-lun1,2,3, SUN Hua1,2,3*, SHI Jun-nan1,2,3, ZHANG Yu-tian1,2,3, SHI Ling-jie1,2,3
Received:
2020-04-27
Accepted:
2020-08-20
Online:
2020-11-15
Published:
2021-06-10
Contact:
* E-mail: sunhua@csuft.edu.cn
Supported by:
WU Bing-lun, SUN Hua, SHI Jun-nan, ZHANG Yu-tian, SHI Ling-jie. Dynamic change and prediction of vegetation cover in Shenzhen, China from 2000 to 2018[J]. Chinese Journal of Applied Ecology, 2020, 31(11): 3777-3785.
[1] 齐亚霄, 张飞, 陈瑞, 等. 2001—2015年天山北坡植被覆盖动态变化研究. 生态学报, 2020, 40(11): 3677-3687 [Qi Y-X, Zhang F, Chen R, et al. Vegetation coverage dynamics in northern slope of Tianshan Mountains from 2001 to 2015. Acta Ecologica Sinica, 2020, 40(11): 3677-3687] [2] 穆少杰, 李建龙, 陈奕兆, 等. 2001—2010年内蒙古植被覆盖度时空变化特征. 地理学报, 2012, 67(9): 1255-1268 [Mu S-J, Li J-L, Chen Y-Z, et al. Spatial differences of variations of vegetation coverage in Inner Mongolia during 2001-2010. Acta Geographica Sinica, 2012, 67(9): 1255-1268] [3] 李晓松, 李增元, 高志海, 等. 基于NDVI与偏最小二乘回归的荒漠化地区植被覆盖度高光谱遥感估测. 中国沙漠, 2011, 31(1): 162-167 [Li X-S, Li Z-Y, Gao Z-H, et al. Estimation of vegetation cover in desertified regions from hyperion imageries using NDVI and partial least squares regression. Journal of Desert Research, 2011, 31(1): 162-167] [4] 王淑君, 管东生. 神经网络模型森林生物量遥感估测方法的研究. 生态环境, 2007, 16(1): 108-111 [Wang S-J, Guan D-S. Remote sensing method of forest biomass estimation by artificial neural network models. Ecology and Environmental Sciences, 2007, 16(1): 108-111] [5] 吕长春, 王忠武, 钱少猛. 混合像元分解模型综述. 遥感信息, 2003(3): 55-58 [Lyu C-C, Wang Z-W, Qian S-M. A review of pixel unmixing models. Remote Sensing Information, 2003(3): 55-58] [6] 王智. 深圳市植被动态变化及其对极端气候的响应. 硕士论文. 北京: 中国地质大学, 2018 [Wang Z. Varia-tion of Vegetation and Its Response to Extreme Climate in Shenzhen. Master Thesis. Beijing: Chinese University of Geosciences, 2018] [7] 李苗苗, 吴炳方, 颜长珍, 等. 密云水库上游植被覆盖度的遥感估算. 资源科学, 2004, 26(4): 153-159 [Li M-M, Wu B-F, Yan C-Z, et al. Estimation of vegetation fraction in the upper basin of Miyun Reservoir by remote sensing. Resources Science, 2004, 26(4): 153-159] [8] 李一静, 曾辉, 魏建兵. 基于归一化植被指数变化分级的深圳市植被变化. 应用生态学报, 2008, 19(5): 1064-1070 [Li Y-J, Zeng H, Wei J-B. Vegetation change in Shenzhen City based on NDVI change classification. Chinese Journal of Applied Ecology, 2008, 19(5): 1064-1070] [9] 贾坤, 姚云军, 魏香琴, 等. 植被覆盖度遥感估算研究进展. 地球科学进展, 2013, 28(7): 774-782 [Jia K, Yao Y-J, Wei X-Q, et al. A review on fractional vegetation cover estimation using remote sensing. Advances in Earth Science, 2013, 28(7): 774-782] [10] 深圳市统计局. 深圳统计年鉴2019 [EB/OL]. (2019-12-30) [2020-04-17]. http://tjj.sz.gov.cn/zwgk/zfxxgkml/tjsj/tjnj/201912/t20191230_18956670.htm [Statistics Bureau of Shenzhen Municipality. Shen-zhen Statistical Yearbook in 2019 [EB/OL]. (2019-12-30) [2020-04-17]. http://tjj.sz.gov.cn/zwgk/zfxxgkml/tjsj/tjnj/201912/t20191230_18956670.htm] [11] 滕明君, 曾立雄, 肖文发, 等. 长江三峡库区生态环境变化遥感研究进展. 应用生态学报, 2014, 25(12): 3683-3693 [Teng M-J, Zeng L-X, Xiao W-F, et al. Research progress on remote sensing of ecological and environmental changes in the Three Gorges Reservoir area, China. Chinese Journal of Applied Ecology, 2014, 25(12): 3683-3693] [12] 董显聪, 李晓洁. 草原植被覆盖度遥感估算模型的适用性比较. 测绘通报, 2019(10): 17-22 [Dong X-C, Li X-J. Comparison of applicability of remote sensing estimation model for grassland vegetation coverage. Bulletin of Surveying and Mapping, 2019(10): 17-22] [13] 柴国奇, 王静璞, 王光镇, 等. 基于MODIS数据的典型草原非光合植被覆盖度估算. 国土资源遥感, 2019, 31(3): 234-241 [Chai G-Q, Wang J-P, Wang G-Z, et al. Estimation of fractional cover of non-photosynthetic vegetation in typical steppe based on MODIS data. Remote Sensing for Land & Resources, 2019, 31(3): 234-241] [14] 彭继达, 张春桂. 基于高分一号遥感影像的植被覆盖遥感监测——以厦门市为例. 国土资源遥感, 2019, 31(4): 137-142 [Peng J-D, Zhang C-G. Remote sen-sing monitoring of vegetation coverage by GF-1 satellite: A case study in Xiamen City. Remote Sensing for Land & Resources, 2019, 31(4): 137-142] [15] 韩富圆, 王天明, 孙阳. 基于Landsat遥感数据武汉地区植被覆盖度动态变化监测分析. 测绘与空间地理信息, 2019, 42(4): 90-92 [Han F-Y, Wang T-M, Sun Y. Monitoring and analyzing dynamic change of vege-tation coverage in Wuhan area based on Landsat remote sensing data. Geomatics & Spatial Information Technology, 2019, 42(4): 90-92] [16] 吴蕾, 穆兴民, 高鹏, 等. 黄土高原地区植被盖度对产流产沙的影响. 水土保持研究, 2019, 26(6): 133-138 [Wu L, Mu X-M, Gao P, et al. Effects of vegetation coverage on runoff and sediment yield in the Loess Plateau. Research of Soil and Water Conservation, 2019, 26(6): 133-138] [17] 常松涛, 黄少燕, 查轩, 等. 雨强和植被覆盖度对红壤坡面产流产沙的影响. 水土保持学报, 2019, 33(3): 58-63 [Chang S-T, Huang S-Y, Zha X, et al. Effects of rainfall intensity and vegetation coverage on runoff and sediment yield on red soil slope. Journal of Soil and Water Conservation, 2019, 33(3): 58-63] [18] 陈秀妍, 付碧宏, 时丕龙, 等. 2000—2016年中亚天山植被变化及气候分异研究. 干旱区地理, 2019, 42(1): 162-171 [Chen X-Y, Fu B-H, Shi P-L, et al. Vegetation dynamics in response to climate change in Tianshan, Central Asia from 2000 to 2016. Arid Land Geography, 2019, 42(1): 162-171] [19] 摆万奇. 深圳市土地利用动态趋势分析. 自然资源学报, 2000, 15(2): 112-116 [Bai W-Q. Analysis on land use dynamics of Shenzhen. Journal of Natural Resources, 2000, 15(2): 112-116] [20] 王兆礼, 陈晓宏, 曾乐春, 等. 深圳市土地利用变化驱动力系统分析. 中国人口·资源与环境, 2006, 16(6): 124-128 [Wang Z-L, Chen X-H, Zeng Y-C, et al. Application of grey system theory to analyze the dri-ving force system of land use change in Shenzhen City. China Population, Resources and Environment, 2006, 16(6): 124-128] [21] 李国珍. 基于FLUS模型的深圳市土地利用变化与模拟研究. 硕士论文. 武汉: 武汉大学, 2018 [Li G-Z. Land Use Change and Simulation in Shenzhen Based on FLUS Model. Master Thesis. Wuhan: Wuhan University, 2018] [22] 陈勇, 孙冰, 廖绍波, 等. 深圳市主要植被群落类型划分及物种多样性研究. 林业科学研究, 2013, 26(5): 636-642 [Chen Y, Sun B, Liao S-B, et al. Classification of main phytocommunity and biodiversity in Shenzhen. Forest Research, 2013, 26(5): 636-642] [23] Li F, Chen W, Zeng Y, et al. Improving estimates of grassland fractional vegetation cover based on a pixel dichotomy model: A case study in Inner Mongolia, China. Remote Sensing, 2014, 6: 4705-4722 [24] 赵珍珍, 冯建迪. 1980—2016年科尔沁沙地土地利用重心的时空迁移特征. 水土保持通报, 2019, 39(4): 256-260 [Zhao Z-Z, Feng J-D. Spatial-temporal evolution features of land use gravity center in Horqin sandy land during 1980-2016. Bulletin of Soil and Water Conservation, 2019, 39(4): 256-260] [25] 原丽娟, 毕如田, 徐立帅, 等. 沁河流域植被覆盖时空分异特征. 生态学杂志, 2019, 38(4): 1093-1103 [Yuan L-J, Bi R-T, Xu L-S, et al. Spatiotemporal differentiation of vegetation coverage in Qinhe basin. Chinese Journal of Ecology, 2019, 38(4): 1093-1103] [26] 成超男, 胡杨, 冯尧, 等. 基于CA-Markov模型的城市生态分区构建研究——以晋中主城区为例. 生态学报, 2020, 40(4): 1455-1462 [Cheng C-N, Hu Y, Feng Y, et al. Construction of urban ecological zones based on CA-Markov model: A case study of the main urban area of Jinzhong. Acta Ecologica Sinica, 2020, 40(4): 1455-1462] [27] Crookston NL, Rehfeldt GE, Dixon GE, et al. Addres-sing climate change in the forest vegetation simulator to assess impacts on landscape forest dynamics. Forest Ecology and Management, 2010, 260: 1198-1211 [28] 刘伟玲, 张林波, 叶有华. 深圳市森林植被碳储量特征及其空间分布. 生态科学, 2012, 31(2): 144-154 [Liu W-L, Zhang L-B, Ye Y-H. Spatial distribution of forest vegetation carbon storage in Shenzhen City, China. Ecological Science, 2012, 31(2): 144-154] [29] 卜心国, 王仰麟, 沈春竹, 等. 深圳市地形对土地利用动态的影响. 地理研究, 2009, 28(4): 1011-1021 [Bu X-G, Wang Y-L, Shen C-Z, et al. Influence of landforms on the land use dynamics in Shenzhen City. Geographical Research, 2009, 28(4): 1011-1021] [30] Shobairi SO, Li M. Dynamic modelling of VFC from 2000 to 2010 using NDVI and DMSP/OLS time series: A study in Guangdong Province, China. Journal of Geographic Information System, 2016, 8: 205 [31] 郭燕燕. 基于CLUE-S模型的深圳市土地利用变化模拟. 硕士论文. 武汉: 武汉大学, 2017 [Guo Y-Y. Simulation of Land Use Change in Shenzhen Based on CLUE-S Model. Master Thesis. Wuhan: Wuhan University, 2017] |
[1] | ZHAO Yunge, JI Jingyi, ZHANG Wantao, MING Jiao, HUANG Wanyun, GAO Liqian. Characteristics of spatial and temporal variability in the distribution of biological soil crusts on the Loess Plateau, China [J]. Chinese Journal of Applied Ecology, 2024, 35(3): 739-748. |
[2] | LI Xiangling, CHEN Fengxian, CHEN Xijuan. Prediction of atrazine degradation in soil based on XGBoost model [J]. Chinese Journal of Applied Ecology, 2024, 35(3): 789-796. |
[3] | XIAO Chen, TIAN Dongyuan, MA Rong, DONG Lingbo. Compatibility predictive model for regeneration quantities of Larix gmelinii natural forest in Daxing’anling Mountains, China [J]. Chinese Journal of Applied Ecology, 2023, 34(9): 2345-2354. |
[4] | ZHOU Peng, HAN Lei, PENG Ling, LIU Lili, WANG Nana, MA Jun, MA Yunlei. Instantaneous sap flow velocity simulation of Euonymus bungeanus based on neural network optimization model [J]. Chinese Journal of Applied Ecology, 2023, 34(8): 2123-2132. |
[5] | XU Caiyao, REN Yan, KONG Fanbin. Impacts and prediction of land use change on ecosystem carbon sequestration in Zhejiang Province, China [J]. Chinese Journal of Applied Ecology, 2023, 34(6): 1610-1620. |
[6] | LIU Yanjiao, LIU Qing, HE Heliang, ZHAO Wenqiang, KOU Yongping. Changes in the structure and function of soil prokaryotic communities in subalpine Picea asperata plantations [J]. Chinese Journal of Applied Ecology, 2023, 34(12): 3279-3290. |
[7] | WANG Xing, YANG Teng, MAO Zi-kun, LIN Fei, YE Ji, FANG Shuai, DAI Guan-hua, HU Jia-rui, HAO Zhan-qing, WANG Xu-gao, YUAN Zuo-qiang. Community structure of phyllosphere fungi associated with dominant tree species in a broad-leaved Korean pine forest of Changbai Mountain, Northeast China [J]. Chinese Journal of Applied Ecology, 2022, 33(9): 2405-2412. |
[8] | WANG Xiao-fei, LUO Zhu-zhu, ZHANG Ren-zhi, NIU Yi-ning, LI Ling-ling, TIAN Jian-xia, SUN Peng-zhou, LIU Jia-he. Soil bacterial community characteristics and ecological function prediction of alfalfa and crop rotation systems in the Loess Plateau, Northwest China [J]. Chinese Journal of Applied Ecology, 2022, 33(4): 1109-1117. |
[9] | LIANG Yan, MING An-gang, HE You-jun, LUO Ying-hua, TAN Ling, QIN Lin. Structure and function of soil bacterial communities in the monoculture and mixed plantation of Pinus massoniana and Castanopsis hystrix in southern subtropical China [J]. Chinese Journal of Applied Ecology, 2021, 32(3): 878-886. |
[10] | XIN Shi-dong, YAN Yun-xian, JIANG Li-chun. Stand biomass model for Pinus koraiensis plantation based on different additive methods in Heilongjiang Province, China [J]. Chinese Journal of Applied Ecology, 2020, 31(10): 3322-3330. |
[11] | ZHAO Ya-nan, DU Yan-yan, MA Yan-ping, ZHAO Yan-bing, ZHOU Yu-rong, WANG Hong-mei. Soil organic carbon dynamics and the prediction of their spatial changes in response to anthropogenically introduced shrub encroachment in desert steppe of the Eastern Ningxia, China. [J]. Chinese Journal of Applied Ecology, 2019, 30(6): 1927-1935. |
[12] | CHEN Yan-ru, XIE Hui-min, LUO Huo-lin, YANG Bo-yun, XIONG Dong-jin. Impacts of climate change on the distribution of Cymbidium kanran and the simulation of distribution pattern [J]. Chinese Journal of Applied Ecology, 2019, 30(10): 3419-3425. |
[13] | XIE Long-fei, DONG Li-hu, LI Feng-ri. Predicting models of leaf area for trees in Larix olgensis plantation. [J]. Chinese Journal of Applied Ecology, 2018, 29(9): 2843-2851. |
[14] | ZHANG Chao, LIU Yong-mei, SUN Ya-nan, WANG Lei, LIU Jian-hong. Hyperspectral prediction model of soil nutrient content in the loess hilly-gully region, China. [J]. Chinese Journal of Applied Ecology, 2018, 29(9): 2835-2842. |
[15] | YU Hong-zhou, SHU Li-fu, DENG Ji-feng, YANG Guang, LIANG Qi, LI Jing-hao, ZHU Hang-yong. Prediction models and the extrapolation effects for water content of surface dead fuels in the typical stand of the Great Xing’an Mountains of China by one-hour time step [J]. Chinese Journal of Applied Ecology, 2018, 29(12): 3959-3968. |
Viewed | ||||||||||||||||||||||||||||||||||||||||||||||||||
Full text 292
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||
Abstract 933
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||