利用端元光谱内插的青海植被覆盖度估算研究     

杜英坤  燕琴  童李霞  王晓波 《测绘科学》2016,41(9):87-90,169

针对利用像元二分模型估算植被覆盖度的精度不高的问题,该文基于OSAVI,提出了选定模型参数(OSAVIs和OSAVIv)的方法,并将该方法应用于青海省植被覆盖度估算。该方法通过高分辨率影像在研究区内选取纯裸地和纯植被样点,并将纯裸地样点的OSAVI作为纯裸地样点像元的OSAVIs,将纯植被样点的OSAVI作为纯植被样点像元的OSAVIv,利用样点像元的OSAVIs和OSAVIv值,通过普通克里金内插法,求得研究区每个像元对应的OSAVIs和OSAVIv。经精度验证结果表明:此方法较常规的参数选取方法,RMSE由0.170降至0.156,MAE由0.137降至0.124。经进一步分析表明,此方法对边缘验证点和非边缘验证点的估算精度都有所提高,由于配准误差和周围地表漫反射的影响,边缘验证点的估算精度低于对非边缘验证点的估算精度。  相似文献   

An efficient application of fusion approach for hot spot detection with MODIS and PALSAR-1 data     

Tasneem Ahmed  Shweta Gupta  Balasubramanian Raman 《国际地球制图》2016,31(7):715-738

Hot spot detection with satellite images, especially with synthetic aperture radar (SAR) images is still a challenging task. Several researchers have used TM/optical data for identification of hot spot but the use of SAR data is very limited for this type of application. The fusion of SAR data with TM/optical data may add additional information which in turn will lead for enhancement of detection capability of the hot spot. Therefore, this study explores the possibility of fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and Phased Array L-band Synthetic Aperture Radar (PALSAR) satellite images for the hot spot detection. Image fusion is emerging as a powerful tool where information of various sensors can be used for obtaining better results. For this purpose, vegetation greenness and roughness information which is obtained from MODIS and PALSAR satellite images, respectively, are used for fusion, and then, a contextual-based thresholding algorithm is applied to the fused image for hot spot detection. The proposed approach comprises of two steps: (1) application of genetic algorithm-based scheme for image fusion of MODIS and PALSAR satellite images, and (2) classification of the fused image as either hot spot or non-hot spot pixels by employing a contextual thresholding technique. The algorithm is tested over the Jharia Coal Field region of India, where hot spot is one of the major problems and it is observed that the proposed thresholding technique classifies the each pixel of the fused image into two categories: hot spot and non-hot spot and the proposed approach detects the hot spot with better accuracy and less false alarm.  相似文献   

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

Nitika Dangwal  N.R. Patel  Mamta Kumari  S.K. Saha 《国际地球制图》2016,31(6):682-693

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%.  相似文献   

基于 ＲS 和 GIS 的土壤侵蚀强度快速分析: 以昌都市扎玉镇为例     

陆天启  陈圣波  范宪创  郭甜甜  涂媛  李亚洲 《世界地质》2016,35(4):1145-1150

以昌都市左贡县扎玉镇为例,选用中巴地球资源二号遥感数据、数字高程模型数据和土地利用类型数据,用遥感软件提取植被指数并进行密度分割,确定植被覆盖度,并对其进行分级; 用地理信息系统软件提取坡度信息,并对坡度进行分级; 在1∶ 5 万比例尺下修正已有的土地利用类型。结果统计扎玉镇 76. 26%的土壤处于轻度及以下侵蚀状态,强烈及以上的土壤侵蚀比例达 5. 48%,土壤侵蚀剧烈的地区主要分布在耕地部分,中度侵蚀的地区主要集中在林草地部分,因此土地利用合理化以及提高植被覆盖率可以有效减小土壤侵蚀强度。  相似文献   

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   总被引：1，自引：0，他引：1  

周在明  杨燕明  陈本清 《海洋学报》2016,38(6):1-7

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。  相似文献   

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     

曹洋  熊康宁  董晓超  肖华  全明英 《中国岩溶》2018,37(6):850-858

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。   相似文献   

定量评估我国西北干旱区土地利用变化对植被指数的影响     

姜雨青  李宝富  宋美帅  焦建飞  刘纹青 《冰川冻土》2018,40(3):616-624

在全球变化的背景下,定量区分人类活动和气候波动对干旱区植被的影响具有重要意义。采用多种统计学方法,分析了我国西北干旱区1990-2010年土地利用/覆被变化（LUCC）和1982-2010年归一化植被指数（NDVI）的时空变化特征,并定量评估了LUCC对NDVI变化的影响。结果表明：1990-2010年,西北干旱区耕地增加量最多,高达13 476 km²,其次是林地和水域,各地类增加的面积主要来自草地（12 590 km²）和未利用地（6 025 km²）。各土地类型变化速度快慢依次为：耕地 > 建设用地 > 水域 > 林地 > 草地 > 未利用地。2000-2010年,研究区土地利用程度综合指数（0.79）明显高于1990-2000年（0.23）,表明近年来人类活动对土地利用变化的影响程度显著增强。1982-2010年,西北干旱区NDVI呈增加态势,但近年来（2002-2010年）NDVI略有下降。其中,1990-2000年,LUCC对西北干旱区NDVI总变化的贡献率较低,仅为2.9%;而1990-2010,LUCC的贡献率为26.7%,表明气候变化对植被指数变化的贡献率高达73.3%。  相似文献   

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

Michael J. Friedel  Massimo Buscema  Luiz Eduardo Vicente  Fabio Iwashita  Andréa Koga-Vicente 《International Journal of Digital Earth》2018,11(7):670-690

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.  相似文献   

Assessing soil salinity using WorldView-2 multispectral images in Timpaki,Crete, Greece   总被引：2，自引：0，他引：2  

D. D. Alexakis  I. N. Daliakopoulos  I. S. Panagea  I. K. Tsanis 《国际地球制图》2018,33(4):321-338

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.  相似文献   

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

Amal Allbed  Lalit Kumar  Priyakant Sinha 《国际地球制图》2018,33(8):830-846

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.  相似文献