中国陆表自然资源综合观测台站布点优化

doi:10.18402/resci.2020.10.08

Abstract

Abstract:

This study focused on the geographical layout optimization of comprehensive observation stations for terrestrial surface natural resources including land, water, climate, and biology. The study was carried out following three steps according to the spatial statistic trinity. (1) The spatial distribution characteristics of terrestrial surface natural resources were analyzed, and the Eco-geographical Region System for China and the Normalized Difference Vegetation Index (NDVI) of the recent 10 years were adopted to characterize the spatially stratified heterogeneity and their spatial autocorrelation; (2) The point mean of the surface with stratified nonhomogeneity (P-MSN) was chosen as the inference method and its average estimation error variance was set as the objective function for the layout optimization; (3) Spatial simulated annealing was used to minimize the objective function to generate the geographical layout of comprehensive observation stations. The following conclusions were drawn: (1) Average NDVI of multiple years can characterize the spatial distribution characteristics of terrestrial surface natural resources; (2) P-MSN can adapt to the spatial distribution character of terrestrial surface natural resources and place dense stations in areas with large variance and sparse stations in areas with small variance; (3) The sample size-estimation error variance curve can be used to determine the best sample size and 1,000 stations are suggested in this study.

Key words: natural resources, comprehensive observation, station layout optimization, spatial statistic trinity, stratified nonhomogeneity, spatial simulated annealing

GAO Bingbo, WANG Jinfeng, HU Maogui, XU Chengdong, LIU Huilan, ZHOU Chenghu. Optimization of integrated observation station layout for terrestrial surface natural resources[J].Resources Science, 2020, 42(10): 1911-1920.

Figures/Tables 5

Figure 1

Table 1

Characterization of spatial distribution of terrestrial surface natural resources"

陆表自然资源类型	子类型	空间分布表征变量	表征依据
土地资源	土壤	生态地理区	生态地理划分区中考虑了全国土壤差异,能反映全国土壤的分异性
	地形	（1）生态地理区（2）多年NDVI	（1）生态地理划分区中考虑了大尺度的地形差异（2）中小尺度地形形成垂直地带性,影响植被分布,因此NDVI能间接表征中小尺度地形的空间分布特征
	利用方式	多年NDVI	不同土地利用方式具有不同的植被覆盖度,如裸土、建筑用地、农田、草原和林地等,年均NDVI具有较大的差异,因此NDVI能间接表征土地利用方式的差异
地表水资源	河流	多年NDVI	对可见光高反射,NDVI为负值,可用NDVI直接表征
	沼泽
	湖泊
	冰川
	永久性积雪
气候资源	大气水	（1）生态地理区（2）多年NDVI	（1）生态地理区考虑了降水条件,刻画了大尺度的大气水的空间分异性（2）不同大气水条件影响自然植被类型,形成如森林、草原和荒漠等差别,影响人工栽培植被的作物类型、熟制等,均在年均NDVI上有差异,因此多年NDVI能够间接表征大气水的空间分布特征
	光能和热能	（1）生态地理区（2）多年NDVI	（1）生态地理区考虑了光能和热能条件,刻画了大尺度的光能和热能的空间分异性（2）不同的光能热能影响自然植被与人工植被类型,在年均NDVI上有差异,因此可以用多年NDVI间接表征光能和热能的空间分布
	风能	生态地理区	生态地理区包含温度带和地形地貌,能过表征风能资源的空间分异
生物资源（植物）	森林	（1）生态地理区（2）多年NDVI	（1）生态地理区划分反映了植被差异（2）植被覆盖度越大,NDVI值越高;多年NVDI能直接表征森林空间分布特征
	草场	（1）生态地理区（2）多年NDVI	（1）生态地理区划分反映了植被差异（2）植被覆盖度越大,V值越高;多年NVDI能直接表征草场空间分布特征
	作物	（1）生态地理区（2）多年NDVI	（1）生态地理区划分反映了植被差异（2）植被覆盖度越大,NDVI值越高;多年NVDI能直接表征作物空间分布特征
	荒漠	（1）生态地理区（2）多年NDVI	（1）生态地理区划分了不同的荒漠区（2）植被覆盖度越低,NDVI值越低;多年NVDI能直接表征荒漠空间分布特征

Table 1

Figure 2

Figure 3

Table 2

References 30

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台站数量	覆盖区县比例/%		覆盖地市比例/%		覆盖省份比例/%
台站数量	P-MSN	OK	P-MSN	OK	P-MSN	OK
100	3.32	3.28	20.81	21.97	79.41	82.35
300	9.14	8.87	46.53	47.98	82.35	85.29
500	13.99	13.51	65.90	64.45	91.18	88.24
800	20.01	19.47	77.46	76.59	94.12	91.18
1000	23.37	23.74	83.53	84.68	94.12	94.12
3000	48.02	48.09	95.09	96.82	94.12	94.12
5000	61.09	62.00	97.40	97.11	97.06	94.12

Optimization of integrated observation station layout for terrestrial surface natural resources

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