甘肃省草原产草量动态监测模型

利用MODIS数据和地面实测资料,研究了甘肃省不同草原区的最适草原生物量遥感估算模型,并反演了甘肃省2005-2009年的草原产草量,分析了其空间分布特征.结果表明,不同草原区适合的植被指数和反演模型类型存异,其中河西走廊高平原荒漠草原区适合的植被指数是RVI、模型类型为对数模型,甘南高原草甸草原区适合的植被指数是EVI、模型类型为指数模型,而黄土高原温性草原区适合的植被指数是NDVI、模型类型为二次多项式模型.甘肃省2009年草原总产鲜草3 718.30万t,整体呈现东北低、西南高的空间变化过程,形成3个高产中心,分别是甘南高原、祁连山北麓中东段和陇南南部.与1985年相比,2005年草原明显减产(相对变化率V=19.34％),但2005-2009年间甘肃省草原产草量有总体上升的趋势.     

Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data:a case study in Shihezi,Northwest China

Scientific interest in geophysical information about land surface temperature （LST） is ever increasing, as such information provides a base for a large number of applications, including environmental and agricultural monitoring. Therefore, the research of LST retrieval has become a hot topic. Recent availability of Landsat-8 satel- lite imagery provides a new data source for LST retrieval. Hence, exploring an adaptive method with reliable ac- curacy seems to be essential. In this study, basing on features of Landsat-8 TIRS thermal infrared channels, we re-calculated parameters in the atmospheric transmittance empirical models of the existing split-window algorithm, and estimated the ground emissivity with the help of the land cover classification map of the study area. Further- more, a split-window algorithm was rebuilt by virtual of the estimation model of the updated atmospheric transmit- tance and the ground emissivity, and then a remote sensing retrieval for the LST of Shihezi city in Xinjiang Uygur autonomous region of Northwest China was conducted on the basis of this modified algorithm. Finally, precision validation of the new model was implemented by using the MODIS LST products. The results showed that the LST retrieval from Landsat-8 TIRS data based on our algorithm has a higher credibility, and the retrieved LST is more consistent with the MODIS LST products. This indicated that the modified algorithm is suitable for retrieving LST with competitive accuracy. With higher resolutions, Landsat-8 TIRS data may provide more accurate observation for LST retrieval.     

宁夏中部生态移民区土地利用时空变化分析

通过解译宁夏中部红寺堡区1989年、1999年、2006年、2012年TM遥感影像,获取该区域生态移民前后4期土地利用数据,对1989~2012年以来土地利用变化情况进行了分析。结果表明,各个时间段的土地利用变化差异性显著。1989~1999年,由于大规模的土地开荒和红寺堡灌区的建设,耕地面积持续增加,同时该区域开始有了水浇地,而林草面积相应减少;1999~2006年,由于退耕还林还草政策的实施,耕地中的旱地被逐渐退耕为草地或发展为水浇地,林草面积开始由减少转为增加,区域土地利用开始合理化;2006~2012年,随着生态移民工程和生态建设工程的成熟发展,林草覆盖面积进一步增加,水浇地面积继续稳步增加,而未利用地和旱地面积持续下降。研究结果为区域土地资源的合理利用及生态移民工程的进一步顺利开展提供可靠依据。     

分块子空间追踪算法

压缩传感理论是一种充分利用信号稀疏性或者可压缩性的全新信号采样理论。该理论表明，通过采集少量的信号测量值就能够实现可稀疏信号的精确重构。本文在研究现有经典重构算法的基础上，提出结合图像分块思想和回溯思想的分块子空间追踪算法（Block Subspace Pursuit, B_SP）用于压缩传感信号的重构。该算法以块结构获取图像，利用回溯过程实现支撑集的自适应筛选，最终实现图像信号的精确重构。实验结果表明，在相同测试条件下，该算法的重构效果无论从主观视觉上还是客观数据上都有不同程度的提高。     

Changes in Physical Properties of Soils with Land Use Time in the Brazilian Savanna Environment

Soils from central Brazil have been intensively used over the last decades because of the rapid conversion of savannas ( Cerrado ) into corn/soybean fields. The objective of this work is to study modifications in the physical properties of soils in the Rio Verde watershed, as a function of the land use time for agriculture, determined from classification of Landsat satellite images between 1980 and 2010. Soil samples were collected at surface (0–20 cm) and subsurface (20–40 cm) horizons for the different classes of land use time (<10, 10–20, 20–30, and >30 years). The following physical properties were measured: bulk density (BD), air permeability (K_a), penetration resistance (PR), microporosity (MI), macroporosity (MA), and total porosity (TP). Results showed a strong expansion with time of agriculture that occupied 35·3% (1980), 37·4% (1990), 51·3% (2000), and 60·9% (2010) of the watershed area. When properties were compared with those from the reference areas (preserved soils under native vegetation), significant differences were observed for all the physical attributes of soils for a land use time higher than 20 years. Overall, BD and PR increased with land use time, and the opposite was verified for K_a, MA, and TP. Some physical properties presented values (e.g., 1·54 g cm⁻³ for BD and 0.06 cm³ cm⁻³ for MA) close to the critical ones reported to affect crop development, but they were not still impacting on local soybean yield. Copyright © 2013 John Wiley & Sons, Ltd.     

基于"3S"技术的甘肃子午岭自然保护区土地利用变化研究

以甘肃省子午岭自然保护区为研究对象,运用"3S"技术,对研究区的地形图、不同时相的TM遥感影像进行数据预处理,并分类提取了研究区2个时段的土地利用信息.对分类信息进行统计分析后并与实地调查数据进行比较,结果表明,近20年来甘肃子午岭自然保护区的森林覆盖面积在稳步提高,乔木林面积明显增加.为甘肃子午岭自然保护区工程的建设提供了基础信息,为林区植物种群生长及分布调查研究提供了宏观数据,并且输出了研究区不同时相土地利用专题图.     

Detection of Ecballium elaterium in hedgerow olive orchards using a low-cost uncrewed aerial vehicle and open-source algorithms

BACKGROUND

Ecballium elaterium (common name: squirting cucumber) is an emerging weed problem in hedgerow or superintensive olive groves under no tillage. It colonizes the inter-row area infesting the natural or sown cover crops, and is considered a hard-to-control weed. Research in other woody crops has shown E. elaterium has a patchy distribution, which makes this weed susceptible to design a site-specific control strategy only addressed to E. elaterium patches. Therefore, the aim of this work was to develop a methodology based on the analysis of imagery acquired with an uncrewed aerial vehicle (UAV) to detect and map E. elaterium infestations in hedgerow olive orchards.

RESULTS

The study was conducted in two superintensive olive orchards, and the images were taken using a UAV equipped with an RGB sensor. Flights were conducted on two dates: in May, when there were various weeds infesting the orchard, and in September, when E. elaterium was the only infesting weed. UAV-orthomosaics in the first scenario were classified using random forest models, and the orthomosaics from September with E. elaterium as the only weed, were analyzed using an unsupervised algorithm. In both cases, the overall accuracies were over 0.85, and the producer's accuracies for E. elaterium ranged between 0.74 and 1.00.

CONCLUSION

These results allow the design of a site-specific and efficient herbicide control protocol which would represent a step forward in sustainable weed management. The development of these algorithms in free and open-source software fosters their application in small and medium farms. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

基于土地利用/覆盖的甘肃省景观生态风险时空变化特征

甘肃省景观类型丰富多样,在中国西部地区的生态安全中起关键性作用,也为当地发展提供着重要的物质基础和生态服务。由于气候变化和人类不合理活动的影响,甘肃省部分地区生态环境的安全与稳定遭到严峻挑战。本研究基于欧洲航空局全球土地利用/覆盖数据（CCI-LC）,利用动态度、转移矩阵方法分析了2005-2019年甘肃省土地利用/覆盖变化特征;通过构建景观生态风险指数并运用空间自相关分析法分析了景观生态风险的空间分布特征。结果显示：1)2005-2019年间,裸地面积减少最多,变化率1.88%,耕地次之,变化率2.31%;草地面积增加最多,变化率1.83%,建设用地次之,变化率191.08%。2）所有土地利用/覆盖类型中,建设用地的动态度最高且在整个研究时期内变化速率都保持在较高水平,综合动态度最大的时期为2010-2019年。3）土地利用/覆盖转移矩阵主要表现为耕地、林地、草地、裸地之间的转入与转出以及其他土地类型向建设用地的转入。4)2019年整体的生态风险值较2005年明显上升。其中低风险区和较低风险区面积最多,转化最频繁;中等风险区、较高风险区和高风险区面积虽然较少,但都存在不同程度的增长。...     

坝上生态农业工程生态效益监测与评价研究

利用遥感技术、地理信息系统和全球定位系统对河北坝上实施生态农业工程建设后的生态效益进行了监测与评价。定量描述了坝上生态环境的动态变化趋势，并对坝上生态农业工程的气候效益、土壤改良效益、农业水文生态效益进行了分析与评价。研究结果表明，通过工程治理，使农业生态系统的功能增强，结构合理，取得了显著的生态效益。     

基于随机森林回归算法的小麦叶片SPAD值遥感估算

使用机器学习中的随机森林(RF)回归算法构建小麦叶片SPAD值遥感反演模型。以2010—2013年江苏地区试验点稻茬小麦3个生育期(拔节、孕穗、开花)的叶片为材料,结合我国自主研发的环境减灾卫星HJ-1对研究区域进行同步监测,分析了各生育期叶片SPAD值与8种植被指数间的相关性;以0.01水平下显著相关的植被指数作为输入参数,使用RF回归算法构建了每个生育期的小麦SPAD反演算法模型,即RF-SPAD模型,以支持向量回归(SVR)和反向传播(BP)神经网络算法构建的SVR-SPAD模型和BP-SPAD模型作为比较模型,以R2和均方根误差(RMSE)为指标,分析了每个生育期3个模型的学习能力和回归预测能力,结果表明:RF-SPAD模型在3个生育期都表现出最强的学习能力,R2和RMSE在拔节期分别为0.89和1.54,孕穗期分别为0.85和1.49,开花期分别为0.80和1.71;RF-SPAD模型在3个生育期的回归预测能力都高于BP-SPAD模型,高于或接近于SVR-SPAD模型,R2和RMSE在拔节期分别为0.55和2.11,孕穗期分别为0.72和2.20,开花期分别为0.60和3.16。