A second modified normalized difference water index(SMNDWI) in the case of extracting the shoreline

Due to the fast development of industrialization and urbanization, shorelineextraction is necessary for the sustainable development and environment protection inmany countries. This study focused on the accurate methods of extracting theinstantaneous waterline —shoreline obtained as the same instant as the satellite imageis acquired. Based on NDWI (Normalized Difference Water Index) and MNDWI(Modified Normalized Difference Water Index), the study changed the bandcombination and proposed a second modified normalized water index (SMNDWI) toextract the waterline. And, this new index is applied to three types of coast to evaluatethe performance of this method with traditional ones. Results show that SNDWI isbetter than NDWI and suitable for applying to the waterline extraction.

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index, Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past.The Iraqi Kurdistan Region(IKR)is located in the north of Iraq,which has also suffered from extreme drought.In this study,the drought severity status in Sulaimaniyah Province,one of four provinces of the IKR,was investigated for the years from 1998 to 2017.Thus,Landsat time series dataset,including 40 images,were downloaded and used in this study.The Normalized Difference Vegetation Index(NDVI)and the Normalized Difference Water Index(NDWI)were utilized as spectral-based drought indices and the Standardized Precipitation Index(SPI)was employed as a meteorological-based drought index,to assess the drought severity and analyse the changes of vegetative cover and water bodies.The study area experienced precipitation deficiency and severe drought in 1999,2000,2008,2009,and 2012.Study findings also revealed a drop in the vegetative cover by 33.3%in the year 2000.Furthermore,the most significant shrinkage in water bodies was observed in the Lake Darbandikhan(LDK),which lost 40.5%of its total surface area in 2009.The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK(correlation coefficients of 0.92 and 0.72,respectively).The relationship between SPI and NDVI-based vegetation cover was positive but not significant.Low precipitation did not always correspond to vegetative drought;the delay of the effect of precipitation on NDVI was one year.

Effect of Water Level Fluctuations on Wintering Goose Abundance in Poyang Lake Wetlands of China

The Poyang Lake is a Ramsar site and is the important over-wintering site for migratory waterbirds along the East Asian-Australasian Fly way. Examining the effects of water level fluctuations on waterbird abundance and analyzing the influencing mechanism is critical to waterbird protection in the context of hydrological alteration. In this study, the effect of water level regime on wintering goose abundance was examined and the influencing mechanism was interpreted. Synchronous waterbirds survey data, hydro- logical data, Moderate Resolution Imaging Spectroradiometer-Normalized Difference Vegetation Index （MODIS-NDVI） data and habi- tat data derived from Landsat TNUETM data and HJ/CCD data were combined. The satellite-derived Green Wave Index （GWI） based on MODIS-NDVI dataset was applied to detect changes in goose food resources. It was found that habitat size and vegetation conditions are key factors determining goose abundance. Geese numbers were positively correlated with habitat area, while intermediate range of vegetation productivity might benefit the goose abundance. Water level affects goose abundance by changing available habitat areas and vegetation conditions. We suggested that matching hydrological regime and exposed meadows time to wintering geese dynamics was crucial in the Poyang Lake wetlands. Our study could provide sound scientific information for hydrological management in the context of waterbird conservation.

Automatic Generation of Water Masks from RapidEye Images

Water is a very important natural resource and it supports all life forms on earth. It is used by humans in various ways including drinking, agriculture and for scientific research. The aim of this research was to develop a routine to automatically extract water masks from RapidEye images, which could be used for further investigation such as water quality monitoring and change detection. A Python-based algorithm was therefore developed for this particular purpose. The developed routine combines three spectral indices namely Simple Ratios (SRs), Normalized Green Index (NGI) and Normalized Difference Water Index (NDWI). The two SRs are calculated between the NIR and green band, and between the NIR and red band. The NGI is calculated by rationing the green band to the sum of all bands in each image. The NDWI is calculated by differencing the green to the NIR and dividing by the sum of the green and NIR bands. The routine generates five intermediate water masks, which are spatially intersected to create a single intermediate water mask. In order to remove very small waterbodies and any remaining gaps in the intermediate water mask, morphological opening and closing were performed to generate the final water mask. This proposed algorithm was used to extract water masks from some RapidEye images. It yielded an Overall Accuracy of 95% and a mean Kappa Statistic of 0.889 using the confusion matrix approach.

Response of remotely sensed Normalized Difference Water Deviation Index to the 2006 Drought of eastern Sichuan Basin

One of the most serious droughts in last century occurred in eastern Sichuan Basin in the summer of 2006 (hereinafter called the Drought). The response of Moderate Resolution Imaging Spectroradiometer (MODIS, boarding on NASA satellites of Terra and Aqua) to the Drought was analyzed in order to reach one practicable monitoring solution for regional soil moisture. Temporal process and spatial extension of the Drought were firstly estimated with ground meteorological and hydrological observations. Then, for the whole region of Sichuan and Chongqing, the remotely sensed Normalized Difference Water In- dex (NDWI) for the summers of 2001―2006 were calculated based on 8-day composite MODIS products, which were further used to construct a new water index (Normalized Difference Water Deviation Index, NDWDI) to examine the sensitivity of remote sensing in the Drought. The study showed that the NDWDI is more sensitive to regional drought than other absolute-soil-moisture-based indices. With the new index, the study extracted the spatial-temporal characteristics of the 2006 Drought, and explored its developing and withdrawing processes, which agreed with related statistics. Compared with ground method of drought observation, the NDWDI-based remote sensing solution of this paper is more pref- erable and practicable in that the local soil properties of water consumption and supply are implicitly taken into account, and the spatial representativity limit of ground observation is circumvented to a degree as satellite remotely senses the earth surface in a way of two-dimensional pixel matrix. So, the NDWDI-based method can be used to monitor regional soil water stress situation more practically and efficiently.

Vegetation Change of Ecotone in West of Northeast China Plain Using Time-series Remote Sensing Data

Multi-temporal series of satellite SPOT-VEGETATION normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data from 1998 to 2007 were used for analyzing vegetation change of the ecotone in the west of the Northeast China Plain. The yearly and monthly maximal values,anomalies and change rates of NDVI and NDWI were calculated to reveal the interannual and seasonal changes in vegetation cover and vegetation water content. Linear regression method was adopted to characterize the trends in vegetation change. The yearly maximal NDVI decreased from 0.41 in 1998 to 0.37 in 2007,implying the decreasing trend of vegetation activity. There was a significant decrease of maximal NDVI in spring and summer over the study period,while an increase trend was observed in autumn. The vegetation-improved regions and vegetation-degraded regions occupied 17.03% and 20.30% of the study area,respectively. The maximal NDWI over growing season dropped by 0.027 in 1998–2007,and about 15.15% of the study area showed a decreasing trend of water content. Vegetation water stress in autumn was better than that in spring. Vegetation cover and water content variations were sensitive to annual precipitation,autumn precipitation and summer temperature. The vegetation degradation trend in this ecotone might be induced by the warm-drying climate especially continuous spring and summer drought in the recent ten years.

An automated method for glacial lake mapping in High Mountain Asia using Landsat 8 imagery

Glacial lakes in the High Mountain Asia(HMA)are sensitive to global warming and can result in much more severe flood disasters than some largesized lakes.An accurate and robust method for the extraction of glacial lakes is critical to effective management of these natural water resources.Conventional methods often have limitations in terms of low spectral contrast and heterogeneous backgrounds in an image.This study presents a robust and automated method for the yearly mapping of glacial lake over a large scale,which took advantage of the complementarity between the modified normalized difference water index(MNDWI)and the nonlocal active contour model,required only local homogeneity in reflectance features of lake.The cloud computing approach with the Google Earth Engine(GEE)platform was used to process the intensive amount of Landsat 8 images from 2015 (344 path/rows and approximately 7504 scenes).The experimental results were validated by very high resolution images from Chinese GaoFen-1 (GF-1) panchromatic multi-spectral(PMS)and appeared a general good agreement.This is the first time that information regarding the spatial distribution of glacial lakes over the HMA has been derived automatically within quite a short period of time.By integrating it with the relevant indices,it can also be applied to detect other land cover types such as snow or vegetation with improved accuracy.

Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

Wheat Yield Response to Water Deficit under Central Pivot Irrigation System Using Remote Sensing Techniques

Scarcity of rainfall and limited irrigation water resources is the main challenge for agricultural expanding policies and strategies. At the same time, there is a high concern to increase the area of wheat cultivation in order to meet the increasing local consumption. The big challenge is to incerese wheat production using same or less amount of irrigation water. In this trend, the study was carried out to analyze the sensitivity of wheat yield to water deficit using remotely sensed data in El-Salhia agricultural project which located in the eastern part of Nile delta. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were extracted from Landsat 7. Water Deficit Index (WDI) used both LST minus air temperature (Tair) and vegetation index to estimate the relative water status. Yield response factor (ky) was derived from relationship between relative yield decrease and relative evapotranspiration deficit. The relative Evapotranspiration deficit was replaced by WDI. Linear regression was found between predicted wheat yield and actual wheat yield with 0.2?6, 0.025, 0.252 and 0.76 as correlation coefficient on 30th of Dec. 2012, 15th of Jan. 2013, 16th of Feb. 2013 and 20th of Mar. 2013 respectively. The main objective of this study is using a combination between FAO 33 paper approach and remote sensing techniques to estimate wheat yield response to water.

Water bodies extraction from TM images

Aiming at the problems of high time-consuming, low accuracy and weak versatility of the existing methods of wa- ter extraction based on TM image, this paper combines principal component analysis （PCA） with the modified normalized difference water index （MNDWI） which was improved by XU Han-qiu to construct a false color composite image that could separate water from others easily. This method can realize the water extraction based on TM image by analyzing the spectral characteristics of water in this false color image and establishing a water extraction model. This paper also compares the effi- ciency of this method with MNDWI, （TM2 ＋ TM3） - （TM4 ＋ TM5） and new water index （NWI）, which were applied in the city and mountain of Taiyuan, respectively. The results show that the proposed method can extract water body from TM im- age more rapidly and efficiently and its accuracy is up to 94.03 %. In addition, this method does not require a manual selec- tion threshold, which meets the research reuuirement of high automaticm.

Impacts of Mau Forest Catchment on the Great Rift Valley Lakes in Kenya

Remote sensing and GIS applications are being widely used for various projects relating to natural resource management. Forests are very important national assets for economic, environmental protection, social and cultural values and should be conserved in order to realize all these benefits. Kenya’s forests are rapidly declining due to pressure from increased population, technological innovation, urbanization human development and other land uses. Mau forest is one of the major forests in Kenya that is a catchment area for many Great Rift Valley lakes within the country and faces a lot of destruction. Continued destruction of the Mau forest will cause catastrophic environmental damage, resulting in massive food crises and compromising the livelihoods of millions of Kenyans, and the possible collapse of the tourism industry. The purpose of this research was to investigate the relationship between the increasing rate of deforestation and the reduction of the volumes of water in the neighboring lakes between the years 1989 to 2010. Satellite images from Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper (ETM+) were used for the detection of changes in the Mau forest and the dynamics of the neighboring water bodies that included lakes: Naivasha, Baringo, Nakuru, Elementaita and Bogoria. The research showed that from a period of 1989 to 2010 Mau forest has been decreasing due to deforestation and the water bodies have irregular dynamics in that, from 1989 to 2000, there was rise in the volume of water, this is attributed to the El Nino rains experienced in the country during the year 1997 and 1998. But between 2000 and 2010 the volume decreased as the forest is also decreasing. It is recommended that the government creates awareness to sensitize the public on the importance of such forests as catchment areas in Kenya.

基于Sentinel-2的青铜峡灌区水稻和玉米种植分布早期识别

及时准确地掌握灌区内作物种植分布对于灌溉水资源高效配置、农田精准管理具有重要指导意义。以宁夏青铜峡灌区为研究对象,利用多时相Sentinel-2卫星数据,通过水稻和玉米早期特征分析,提取关键的“水淹”信号和“植被”信号,构建时序归一化差异水体指数(MNDWI)和归一化植被指数(NDVI)特征值数据集,并通过样本分析关键特征阈值,构建水稻和玉米早期种植分布决策树模型,提取2022年宁夏青铜峡灌区水稻和玉米种植的空间分布。结果表明(:1)玉米和水稻苗期的后半段5月15—31日,水淹信号和植被信号是区分二者关键时期。(2)基于早期作物物候特征的方法,在5月16—31日获取的水稻和玉米图像制图精度高于90%,用户精度超过91%,总体精度超过90%,Kappa系数高于0.88,明显高于同时期随机森林方法的分类精度。(3)本研究提出的方法在早期水稻和玉米种植分布提取方面具有较强的适用性,并且能够在时空尺度上以较少的实地样本进行延展,同时在时间上也更有优势。因此,该方法为青铜峡灌区水稻和玉米种植分布早期调查提供了重要的方法支撑。

基于时空数据融合的塔吉克斯坦中高时空分辨率NDVI数据集(2010-2020)

归一化植被指数(Normalized Difference Vegetation Index,NDVI)是研究植被最常用的遥感指数之一。NDVI长时间序列数据对于植被变化研究有着重要的意义。然而由于传感器的限制,遥感数据的时间分辨率与空间分辨率不能兼顾,因此在目前广泛使用的NDVI数据产品中,高时空分辨率的数据还较为缺乏。本产品基于Cubist模型对MODIS数据与Landsat及哨兵等遥感数据进行时空数据融合,得到了塔吉克斯坦2010–2020年中高时空分辨率Landsat-MODIS融合数据,以及2020年中高时空分辨率Sentinel-MODIS融合数据。为保证数据的准确性和可靠性,本数据集从数据源的质控,模型训练优化,以及模型独立验证三个方面对数据产品进行质量控制,且取得了较好的验证效果。本数据集可反映塔吉克斯坦2010–2020年NDVI时空变化情况,可为该地区植被变化分析、生态环境监测等提供长时间序列数据支撑。

基于高分一号遥感影像的水体提取方法对比分析与改进

以高分一号遥感影像为数据源,以安徽省黄山市屯溪流域内的东方红水库为研究对象,采用单波段阈值法、两波段差值法、波段比值法、归一化差分水体指数(NDWI)法、归一化差分植被指数(NDVI)法共5种水陆像元度量方法,分别应用平均值法和最大类间方差迭代法两种阈值选取方法对东方红水库进行水体提取,探索最大类间方差迭代法在水体提取变量上的改进效果,在此基础上提出了一种改进的最大类间方差联合水体提取法,并对比了改进前后的水体提取效果。结果表明:改进后的水体提取方法可以很好地降低影像提取中产生的噪点,提高水体提取的精度,提取成果的平均相对误差为4.69%,决定系数为0.8579,相比于改进前平均相对误差降低了0.68%,决定系数提高了0.0539。

青藏高原多尔索洞错水深反演与水量变化估算

利用由实测水深空间插值获得的水下地形数据估算湖泊水量及其变化往往存在较大误差。以Landsat系列影像数据及多尔索洞错12 m以下实测水深数据为基础,建立多波段组合模型进行水深模拟,结合多时相Landsat影像获取的多尔索洞错边界数据获取水深变化,估算1996~2016年多尔索洞错水量变化。实验结果表明:多因子反演模型的相关系数(R^(2))均在0.90以上,平均绝对误差低至0.48 m,相比空间插值方法能更精确地模拟多尔索洞错水深在12 m以下区域的水深分布情况;近20 a来多尔索洞错不断扩张,水位升高约0.40 m/a,水量增加约0.18 km^(3)/a。

1977—2021年博斯腾湖大湖区湖岸线动态变化

湖泊岸线的动态变化可以表征湖泊的变化。以博斯腾湖大湖区为研究区,基于1977—2021年的Landsat遥感影像数据和实测水位资料,利用MNDWI法提取水体信息,运用岸线发育系数与岸线强度,分析研究区岸线动态变化,探讨影响研究区岸线动态变化的主要因素。研究结果表明:1977—2021年研究区岸线变化最明显的区域主要是研究区北岸。1977—1989年北岸岸线向南迁移的最大距离为0.93 km;1989—2003年北岸岸线向北迁移的最大距离为5.12 km;2003—2013年北岸岸线向南迁移的最大距离为5.46 km;2013—2021年北岸岸线向北迁移的最大距离为5.11 km。1977—1989年研究区岸线长度以1.55 km/a的速率逐渐缩短;1989—2002年岸线以16.34 km/a的速率持续增长;2002—2012年岸线以22.67 km/a的速率明显缩短;2012—2021年岸线以14.36 km/a的速率快速增长。年降水量、年均气温以及开都河径流量等自然要素是研究区岸线、水位和水面面积变化的主要自然因素。研究区岸线长度和曲折性受水位和水面面积的影响较为明显,1977—2021年研究区水位、水面面积和岸线长度的变化趋势基本一致。

基于高分一号卫星影像的水体信息提取方法初探

本文以山西汾河水库为研究区域,利用高分一号卫星影像,分别选择阈值分割法、归一化差异水体指数法和面向对象法对研究区水体信息进行提取,并对3种方法提取结果进行精度检查。通过试验得出如下结论:阈值分割法对水体先验知识要求低,简单易用;归一化差异水体指数法由于未能消除阴影与水体的混淆问题,使得提取水体信息精度较低;面向对象法提取水体信息结果精度较高,但易丢失人工水塘与沟渠信息。该研究结果对利用高分一号卫星影像进行其他土地利用信息的提取具有一定借鉴意义。

西南地区灌区节水工程的综合评估及应用研究

在西南地区,灌区节水工程对于合理利用水资源和保护生态环境具有重要意义。在对具体西南地区灌区的分析基础上,提出灌区节水工程的综合评估方法。通过对灌区概况进行研究以及对灌溉水利用系数进行计算,建立灌区节水工程评估体系,确定评估结果分级标准。试验结果中,计算了5个灌区的12个指标无量纲化值,同时对灌区的12项指标进行准确评价,研究方法在西南地区灌区评估上具有实际意义。

基于水体指数的密云水库面积提取及变化监测

密云水库作为北京市惟一的地表饮用水源地,监测其水面的变化可服务于政府的管理和决策。本文在分析地物光谱特征的基础上,利用TM影像的短波红外波段(TM5)和红光波段(TM3),构造了修订型归一化水体指数(RNDWI)来提取水库水面。RNDWI法能够削弱混合像元因素和山体阴影的影响,精确地提取出水陆边界,甚至可以提取出狭窄条状水体。比较RNDWI、改进归一化差异水体指数(MNDWI)及单波段法的水库水面面积提取精度,发现单波段法精度低,MNDWI法精度高,而RNDWI法精度最高。并基于RNDWI法利用TM影像监测了密云水库近二十年的水面面积动态变化,1996年时面积最大(152.306km2),近十年水库面积逐渐减少,2004年面积最小(56.632km2)。

多源卫星遥感数据监测巢湖蓝藻水华爆发研究

湖泊蓝藻水华的精准动态监测,可为水利及环保部门评价污染水体的防治效果、优化和调整防治政策提供依据。论文以巢湖为研究对象,利用Landsat TM/OLI、HJ-1B CCD/IRS和NPP-VIIRS三种不同空间分辨率的影像数据,通过归一化水体指数(Normalized Difference Water Index,NDWI)实现巢湖水域范围提取,利用归一化植被指数(Normalized Difference Vegetation Index,NDVI)和浮游藻类指数(Floating Algae Index,FAI)提取2010~2014年共22景巢湖蓝藻的爆发区域。进一步的,对NDVI和FAI两种方法计算的蓝藻爆发区域进行对比分析,评价Landsat、HJ-1B以及VIIRS三种影像数据对巢湖蓝藻水华空间和时间的监测效果及适用性,进而结合气象因素分析不同气象因子对蓝藻水华爆发的影响。研究结果表明:(1)相比NDVI指数,FAI指数(Landsat和HJ-1B数据为主,VIIRS数据辅助)能降低薄云对蓝藻水华提取效果的影响,可提高蓝藻水华爆发区域、程度的识别能力;(2)气象因子中气温和日照时长加重了蓝藻水华爆发的严重程度,降水则对蓝藻水华的爆发起到一定的抑制作用。综上所述,论文引入VIIRS卫星影像研究巢湖蓝藻水华爆发,利用FAI指数降低薄云对蓝藻水华爆发面积提取精度的影响,取得的研究结果可为基于多源卫星遥感数据的巢湖蓝藻水华动态监测系统开发提供重要的方法支持,有利于推进卫星遥感技术在安徽省“河长制”和“湖长制”中发挥重要作用。