Dynamic responses of the coalfield ecosystem to mining intensity, spatio-temporal variation, and climate change derived from AVHRR/NDVI in Shendong coalfield
MA Chao1, TIAN Shu-jing2, ZOU You-feng1, GUO Zeng-zhang1, HAN Rui-mei1, XIE Shao-shao3
1. Key Laboratory of State Bureau of Surveying and Mapping of Mine Spatial Information Technology, Henan Polytechnic University, Jiaozuo 454000, China;
2. Department of Surveying and Mapping Geographic Information, Yunnan Land and Resources Vocational College, Kunming 652501, China;
3. Bowen College of Management, Guilin University of Technology, Guilin 541006, China
Study purpose on biological productivity inverted from a long time series, the multi-dimensional Normalized Difference Vegetation Index (NDVI) in mining-disturbed areas is to understand vegetation succession of non-natural ecological areas, while to provide guidance for natural restoration and artificial restoration of the vegetation under high-intensity mining conditions northwest fragile ecological areas in China. Shendong coalfield, as a directly affected area, an indirectly affected area (20 km buffer), and a natural ecological checked area were established. Using Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer derived NDVI dataset (GIMMS AVHRR/NDVI) (July 1981-December 2006, 25.5 years), combined with temperature and precipitation information (86 meteorological stations) and Shendong coal output, the aforementioned three areas are comparatively investigated for the effects of temporal, spatial, climatic, and mining intensities. Test validation is conducted by means of another long-term Moderate Resolution Imaging Spectroradiometer (MODIS: MOD17A3 and MOD13Q1) net primary productivity (NPP)/NDVI (2000~2010, 11 years) dataset. The results will provide new insights into ecological environment in mining:(1) under the background of climate change, the vegetation growing season was extended again in the Shendong mining area;(2) NDVI increment in the Shendong mining area was below the buffer, and NDVI increment in its buffer was lower than the natural ecological area;(3) In the mining area, with the increase in mining intensity, NDVI growth rate was lower than that of in the natural ecological area.
马超, 田淑静, 邹友峰, 郭增长, 韩瑞梅, 谢少少. 神东矿区AVHRR/NDVI的时空、开采强度和气候效应[J]. 中国环境科学, 2016, 36(9): 2749-2756.
MA Chao, TIAN Shu-jing, ZOU You-feng, GUO Zeng-zhang, HAN Rui-mei, XIE Shao-shao. Dynamic responses of the coalfield ecosystem to mining intensity, spatio-temporal variation, and climate change derived from AVHRR/NDVI in Shendong coalfield. CHINA ENVIRONMENTAL SCIENCECE, 2016, 36(9): 2749-2756.
JEONG S J, HO C H, GIM H J, et al. Phenology shifts at start vs. end of growing season in temperate vegetation over the Northern Hemisphere for the period 1982~2008[J]. Global Change Biology, 2011,17(7):2385-2399.
[4]
Brown M E, K M de Beurs, M.Marshall. Global phenological response to climate change in crop areas using satellite remote sensing of vegetation, humidity and temperature over 26years[J]. Remote Sensing of Environment, 2012,126:174-183.
de Jong R, de Bruin S, de Wit A, et al. Analysis of monotonic greening and browning trends from global NDVI time-series[J]. Remote Sensing of Environment, 2011,115(2):692-702.
[11]
Eastman J R, Sangermano F, Machado E A, et al. Global trends in seasonality of normalized difference vegetation index (NDVI), 1982~2011[J]. Remote Sensing, 2013,5(10):4799-4818.
[12]
Zhang Y, Gao J, Liu L, et al. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas[J]. Global and Planetary Change, 2013,108:139-148.
[13]
Reevesa M C, Baggett L S. A remote sensing protocol for identifying rangelands with degraded productive capacity[J]. Ecological Indicators, 2014,43:172-182.
[14]
Christina Eisfelder, Igor Klein, Markus Niklaus, et al. Net primary productivity in Kazakhstan, its spatio-temporal patterns and relation to meteorological variables[J]. Journal of Arid Environments, 2014,103:17-30.
[15]
Dannenberg M P, Conghe Song, Taehee Hwang, et al. Empirical evidence of El Niño-Southern Oscillation influence on land surface phenology and productivity in the western United States[J]. Remote Sensing of Environment, 2015,159:167-180.
Ma, C, Guo Z Z, Zhang X K, et al. Annual integral changes of time serial NDVI in mining subsidence area[J]. Transactions of Nonferrous Metals Society of China, 2011,21:583-588.
Tucker C J, Pinzon J E, Brown M E, et al. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data[J]. International Journal of Remote Sensing, 2005,26(20):4485-4498.
Li X B, Chen Y H, Fan Y D, et al. Detecting inter-annual variations of vegetation growth based on satellite-sensed vegetation index data from 1983 to 1999[C]//Chandrasekar V, Werle D, Emery B eds. Proceedings of IGARSS. Toulouse, France, 2003,(5):3263-3265.
Fensholt R, Proud S R. Evaluation of Earth Observation based global long term vegetation trends-Comparing GIMMS and MODIS global NDVI time series[J]. Remote Sensing of Environment, 2012,119:131-147.