Exploring the potential of Sentinel-2A satellite data for aboveground biomass estimation in fragmented Himalayan subtropical pine forest

The Sentinel-2 A satellite having embedded advantage of red edge spectral bands offers multispectral imageries with improved spatial,spectral and temporal resolutions as compared to the other contemporary satellites providing medium resolution data.Our study was aimed at exploring the potential of Sentinel-2 A imagery to estimate Above Ground Biomass(AGB) of Subtropical Pine Forest in Pakistan administered Kashmir.We developed an AGB predictive model using field inventory and Sentinel 2 A based spectral and textural parameters along with topographic features derived from ALOS Digital Elevation Model(DEM).Field inventory data was collected from 108 randomly distributed plots(0.1 ha each) across the study area.The stepwise linear regression method was employed to investigate the potential relationship between field data and corresponding satellite data.Biomass and carbon mapping of the study area was carried out through established AGB estimation model with R(o.86),R2(0.74),adjusted R2(0.72) and RMSE value of 33 t/ha.Our results showed that first order textures(mean,standard deviation and variance) significantly contributed in AGB predictive modeling while only one spectral band ratio made contribution from spectral domain.Our study leads to the conclusion that Sentinel-2 A optical data is a potential source for AGB estimation in subtropical pine forest of the area of interest with added benefit of its free of cost availability,higher quality data and long-term continuity that can be utilized for biomass carbon distribution mapping in the resource constraint study area for sustainable forest management.

Compounding soils to improve cropland quality:A study based on field experiments and model simulations in the loess hilly-gully region,China

Increasing the quantity and improving the quality of cropland can alleviate the human-land contradiction and promote the sustainable development of agriculture especially in mountainous areas.With the support of the central government’s policies,Yan’an,Northern Shaanxi,China implemented a major land consolidation engineering project in the loess hilly-gully region from 2013 to 2018,achieving 33,333.3 ha of new cropland.However,the poor quality of some newly-constructed cropland at the initial stage hindered its efficient utilization.In order to overcome this problem,red clay and Malan loess were compounded in different volume ratios to explore the method to improve the cropland quality.The Root Zone Water Quality Model was used to simulate the effects of different soil treatments on soil water,nitrogen and maize growth.Experimental data were collected from 2018 to 2019 to calibrate and validate the model.The root mean square error(RMSE)of soil water content,nitrate nitrogen concentration,above-ground biomass,leaf area index were in the range of 11.72-14.06 mm,4.06-11.73 mg kg^(-1),835.21-1151.28 kg ha^(-1)and 0.24-0.47,respectively,while the agreement index(d)between measured and simulated values ranged from 0.70 to 0.96.It was showed that,compared with land constructed with Malan loess only(T1),the soil structure and hydraulic characteristics of land with a volume ratio of red clay and Malan loess of 2:1(T3)was better.Simulation indicated that,compared with T1,the soil water content and available water content of T3 increased by 14.4%and 19.0%,respectively,while N leaching decreased by 16.9%.The aboveground biomass and maize yield of T3 were 7.9%and 6.7%higher than that of T1,respectively.Furthermore,the water productivity and nitrogen use efficiency of T3 increased by 21.0%and 16.6%compared with that of T1.These results indicated that compounding red clay and Malan loess in an appropriate ratio was an effective method to improve soil quality.This study provides a technical idea and specific technical parameters for the construction or improvement of cropland in loess hilly-gully region,which may also provide reference for similar projects in other places.

近20年中国粮食生产变化特征及其对区域粮食供需格局的影响

中国是一个农业大国,用占世界不到9%的耕地养活了占世界近20%的人口。国家及区域尺度粮食安全问题一直备受关注。以省为研究单元,借助GIS空间分析与统计工具,分析了1999—2018年中国粮食生产变化的总体特征、地域格局演变特征及这些变化对区域粮食供需格局的影响。研究结果表明:全国粮食总产量呈现显著增加的趋势,增长率为0.11亿t/年。北方粮食总产量呈显著增长趋势,而南方粮食总产量基本维持稳定。玉米产量的增加对这些变化起到了主导作用。在省域尺度上,近20年五种主要粮食作物(稻谷、小麦、玉米、豆类和薯类)产量时空变化具有较大差异。粮食产量的变化对区域粮食供需格局产生了较大影响。特别是东南沿海地区的广东、浙江、福建三省,从稻谷和小麦两大口粮供过于求型变为了供给不足型省份。但在全国尺度上,人均粮食占有量在Y 1999—2003时段(1999—2003年五年平均情况)和Y 2014—2018时段(2014—2018年五年平均情况)分别为368.0 kg/人和461.5 kg/人;人均两大口粮占有量在Y 1999—2003时段和Y 2014—2018时段分别为220.3 kg/人和247.6 kg/人。播种面积的变化是全国及区域尺度上粮食作物产量变化的直接原因。但其根本原因则更多归因于土地利用价值驱动的属性、功能及质量的变化。此外,根据导致耕地减少的四种主要类型——"非农化""非粮化""荒废化"和"生态化",探讨了其形成原因并提出相应的提高区域粮食生产的对策建议,以期对区域粮食种植格局调整及实现两大口粮需求省份向自给型省份转型提供参考。

边境贫困县建设用地变化特征与驱动因素——以广西龙州为例

边境贫困县的土地利用、城镇发展与脱贫攻坚事关边境稳定和可持续发展大局。论文选取广西壮族自治区的龙州县为案例研究区域,以2011年和2016年高分影像作为主要数据源,结合社会经济数据,探讨该县近年建设用地时空变化特征及驱动因素。研究结果表明:1)龙州县主要建设用地的增幅达10.08%,其中城镇用地、农村宅基地、独立工矿用地、交通设施用地和旅游设施用地的增量分别占建设用地增量的37.74%、25.48%、20.96%、15.49%和0.33%;2)县城涉及的龙州镇、上龙乡建设用地增加较快,边境口岸城镇的建设用地增速也较快;3)从建设用地扩展模式来看,县城龙州镇为填充式扩张,其他乡镇为边缘式扩张;4)城镇发展提速、农民新房建设、工业园区建设、交通设施建设是建设用地扩张的直接驱动因素,近年来精准扶贫战略的深化落实、边境贸易活动的不断增多,是重要的政策驱动力。研究建议:深化落实贫困县建设用地倾斜政策,针对贫困县的建设用地,在省市层面要明确总量、增加流量,在县域层面要用好增量、优化布局、提高效率,切实助力脱贫攻坚和乡村振兴。