Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM

Detection of crop water stress is crucial for efficient irrigation water management. Potential of Satellite data to provide spatial and temporal dynamics of crop growth conditions makes it possible to monitor crop water stress at regional level. This study was conducted in parts of western Uttar Pradesh and Haryana. Multi-temporal Landsat data were used for detecting wheat crop water stress using vegetation indices (VIs), viz. vegetation water stress index (VWSI) and land surface wetness index water stress factor (Ws_LSWI). The estimated water stress from satellite data-based VIs was validated by water stress factor (Ws) derived from flux-tower data. The study observed Ws_LSWI to be better index for water stress detection. The results indicated that Ws_LSWI was superior over other index showing RMSE = 0.12, R² = 0.65, whereas VWSI showed overestimated values with mean RD 4%.     

基于SPOT6遥感影像的滩涂湿地入侵种互花米草植株高度的反演研究

本文以SPOT6 高空间分辨率遥感影像为数据源,通过植被覆盖度和地上生物量两个参数进行滩涂湿地入侵种互花米草植株高度的估算研究。结果表明,三沙湾滩涂湿地互花米草植株高度平均值为2.04 m,以1~2 m和2~3 m植株为主要分布高度,分布面积分别为6.83 km2和10.31 km2,占研究区互花米草总面积的33.83%和51.06%,小于1 m和大于3 m的互花米草仅占9.26%和5.84%。估算值与真实值之间的均方根误差为0.204,绝对误差为0.04~0.37 m。该方法是对高空间分辨率光学影像应用研究的重要尝试,其反演方法具有较好的可行性,可较为准确的获取滩涂湿地植株高度信息。     

中国人口城镇化质量评价及省际差异分析

新型城镇化是中国的重要国策,对人的城镇(市)化的科学评价是正确认识城镇化和制定相关政策的重要基础.目前城--乡二元分析框架下的以城镇化率和城镇(或区域)城镇化质量为主的评价方法,难以反映城镇化过程中社会结构的变化,同时乡村人口的城镇化发展也被忽略.本文提出人口城镇化质量的概念,建立了衡量人口城镇化质量的指标体系.对1995,2000,2005,2010和2012年全国及各省市的城镇人口,乡村人口及总人口的城镇化质量进行了分析.研究发现:① 尽管城镇人口的城镇化速度显著快于乡村人口,但城镇化并非城镇人口独有的社会过程.② 城乡两类人口的城镇化质量在省域尺度上正逐步形成差异明显的空间格局.③ 北京,上海,浙江等少数省市乡村人口的城镇化质量已经超越部分内地省市城镇人口的城镇化质量.建议更新对城镇化的认识和评价标准,探索在城镇化发达的地区调整城--乡二元体制的新途径,促进中国城镇化的健康发展.     

关岭-贞丰石漠化治理示范区植被覆盖变化及其对气候因子的响应

为揭示喀斯特石漠化治理示范区植被覆盖变化以及气候因子对植被覆盖变化的影响,利用2006—2015年Landsat 30 m/16 d分辨率影像数据,采用最大合成法、NDVI差值指数和相关、偏相关分析法,系统分析示范区归一化植被指数的时空变化特征及其与气候因子的关系。结果表明:(1)2006—2015年最大NDVI平均值为0.39,NDVI较高覆盖区域在示范区南北边界,而较低覆区域以花江南岸为主;(2)2006年以来示范区极低(-1.210)、低(-0.669)和中等(-0.729)植被覆盖度呈减少趋势,高(1.359)和极高(1.247)植被覆盖度增加,整体上呈显著增加趋势;(3)本月NDVI与本月、上月、上上月降雨量和气温的相关性均通过显著水平0.05检验,且本月NDVI与本月降雨量相关性高于本月气温(RNDVI降雨 =0.782),本月NDVI与上月气温相关性高于上月降雨量(RNDVI气温 =0.771);(4)在月尺度上,示范区植被生长对降雨量无滞后期,而对气温存在1个月的滞后期。      

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.     

Assessing soil salinity using WorldView-2 multispectral images in Timpaki,Crete, Greece

Salinization is one of the major soil degradation threats occurring worldwide. This study evaluates the feasibility of operational surface soil salinity mapping based on state-of-the-art Earth Observation (EO) products captured by sensors on-board WorldView-2 (WV2) and Landsat 8 satellites. The proposed methods are tested in Timpaki, south-central Crete,Greece, where brackish water irrigation puts soil health at risk of soil salinization. In all cases, EO products are calibrated against soil samples collected from bare soil locations. Results indicate a moderate correlation of observed EC_e values with the investigated remote sensing parameters. Regarding sensitivity to saline soil, the yellow band displays higher values. Comparison between methods used in the literature shows that those developed specifically for soil salinity, and especially index S5, perform better. The proposed ‘detection index’ and 3D PCA transformation methodology perform reasonably well in detecting areas with high EC_e values and provide a simple and effective operational alternative for saline topsoil detection and mapping.     

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.     

Late Pleistocene and Holocene Afromontane vegetation and headwater wetland dynamics within the Eastern Mau Forest,Kenya

The Mau Forest Complex is Kenya's largest fragment of Afromontane forest, providing critical ecosystem services, and has been subject to intense land use changes since colonial times. It forms the upper catchment of rivers that drain into major drainage networks, thus supporting the livelihoods of millions of Kenyans and providing important wildlife areas. We present the results of a sedimentological and palynological analysis of a Late Pleistocene–Holocene sediment record of Afromontane forest change from Nyabuiyabui wetland in the Eastern Mau Forest, a highland region that has received limited geological characterization and palaeoecological study. Sedimentology, pollen, charcoal, X-ray fluorescence and radiocarbon data record environmental and ecosystem change over the last ~16 000 cal a bp. The pollen record suggests Afromontane forests characterized the end of the Late Pleistocene to the Holocene with dominant taxa changing from Apodytes, Celtis, Dracaena, Hagenia and Podocarpus to Cordia, Croton, Ficus, Juniperus and Olea. The Late Holocene is characterized by a more open Afromontane forest with increased grass and herbaceous cover. Continuous Poaceae, Cyperaceae and Juncaceae vegetation currently cover the wetland and the water level has been decreasing over the recent past. Intensive agroforestry since the 1920s has reduced Afromontane forest cover as introduced taxa have increased (Pinus, Cupressus and Eucalyptus).     

The relationship between groundwater and natural vegetation in Qaidam Basin

To accurately evaluate ecological risks trigged by groundwater exploitation, it must be clarified the relationship between vegetation and groundwater. Based on remote sensing data sets MOD13Q1, groundwater table depth (WTD) and total dissolved solids (TDS), the relationship between groundwater and natural vegetation was analyzed statistically in the main plain areas of Qaidam Basin. The results indicate that natural vegetation is groundwater-dependent in areas where WTD is less than 5.5 m and TDS is less than 7.5 g/L. Aquatic vegetation, hygrophytic vegetation and hygrophytic saline-alkali tolerant vegetation are mainly distributed in areas with WTD <1.1 m. Salt-tolerant and mesophytic vegetation mainly occur in areas with WTD of 1.4-3.5 m, while the xerophytic vegetation isprimarily present in areas where WTD ranges from 1.4 m to 5.5 m. Natural vegetation does not necessarily depend on groundwater in areas with WTD >5.5 m. For natural vegetation, the most suitable water TDS is less than 1.5 g/L, the moderately suitable TDS is 1.5-5.0 g/L, the basically suitable TDS is 5.0-7.5 g/L, and the unsuitable TDS is more than 7.5 g/L.     

基于时序遥感的庐山自然保护区植被分类及其变化分析

自然保护区是生物多样性最丰富的区域,针对近年来庐山自然保护区森林生物多样性进行调查,了解保护区内植被的分布及其变化,对于保护庐山境内的林业资源具有重要的意义.论文利用2015-2018年Proba-Ⅴ卫星100m分辨率5d植被指数产品,使用最大值合成法、Hants时间序列谐波分析方法对数据进行平滑降噪处理,并采用随机森...