Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco

In Morocco, no operational system actually exists for the early prediction of the grain yields of wheat (Triticum aestivum L.). This study proposes empirical ordinary least squares regression models to forecast the yields at provincial and national levels. The predictions were based on dekadal (10-daily) NDVI/AVHRR, dekadal rainfall sums and average monthly air temperatures. The Global Land Cover raster map (GLC2000) was used to select only the NDVI pixels that are related to agricultural land. Provincial wheat yields were assessed with errors varying from 80 to 762 kg ha⁻¹, depending on the province. At national level, wheat yield was predicted at the third dekad of April with 73 kg ha⁻¹ error, using NDVI and rainfall. However, earlier forecasts are possible, starting from the second dekad of March with 84 kg ha⁻¹ error, at least 1 month before harvest. At the provincial and national levels, most of the yield variation was accounted for by NDVI. The proposed models can be used in an operational context to early forecast wheat yields in Morocco.     

雪地上的森林冠层混合反照率模型

反照率通常定义为出射与入射的能量之比，是地表能量平衡中的关键因子。气候变化对反照率也很敏感。典型的气候变化预测是通过GCM与地表模型的结合进行的。目前在地表模型(如BATS模型)中，是通过空气动力学粗糙度Z0与降雪深度d两个参数来估计雪地上树冠的反照率的。在他们的工作基础上，重点考虑对于不同的太阳天顶角，直入一扇出反照率的方向性及其与叶面积指数(LAI)的关系。同时，为了保持BATS模型所需反照率模型的基本特征，主要在几何光学-辐射传输混合模型(GORT)的基础上做了一些近似来达到此目的。最后，以针叶林为例，用MODIS的反照率数据和BOREAS地面观测数据做了初步的模型验证。结果显示模型较符合实际情况。     

格陵兰地区GLASS反照率产品质量评价及反照率变化趋势分析

冰雪反照率是影响和评估全球气候变化的重要因子。北极格陵兰岛拥有世界第二大冰盖,定量获取该地区反照率是研究北半球能量收支变化的关键。全球陆表卫星(global land surface satellite,GLASS)产品系统生产的反照率产品是目前国际上时间序列最长（1981—2017年）的全球反照率产品。利用格陵兰气候观测网络(Greenland climate network, GC-Net)与格陵兰冰架监测计划(programme for monitoring of the Greenland ice sheet, PROMICE)网络观测的反照率数据,评估了格陵兰地区GLASS地表反照率产品的精度;并基于2000—2017年的GLASS地表反照率产品,分析了格陵兰地区7月份反照率的年际变化趋势与空间分布特征。结果表明：GLASS与GC-Net反照率的均方根误差(root mean squared error, RMSE)为0.077 8(决定系数R2=0.490 7),与PROMICE反照率差异的RMSE为0.078 6(R2=0.899 9),GLASS产品的反照率数值呈现一定...     

Formulation of Time Series Vegetation Index from Indian Geostationary Satellite and Comparison with Global Product

To study impact of climate change on vegetation time series vegetation index has a vital role to know the behaviour of vegetation dynamics over a time period. INSAT 3A CCD (Charged Couple Device) is the only geostationary sensor to acquire regular coverage of Asia continent at 1 km × 1 km spatial resolution with high temporal frequency (half-an-hour). A formulation of surface reflectances in red, near infrared (NIR), short wave infrared (SWIR) and NDVI from INSAT 3A CCD has been defined and integrated in the operational chain. The atmospheric correction of at-sensor reflectances using SMAC (Simple Model for Atmospheric Correction) model improved the NDVI by 5–40% and also increased its dynamic range. The temporal dynamics of 16-day NDVI composite at 0500 GMT for a growing year (June 2008–March 2009) showed matching profiles with reference to global products (MODIS TERRA) over known land targets. The root mean square deviation (RMSD) between the two was 0.14 with correlation coefficient (r) 0.84 from 200 paired datasets. This inter-sensor cross-correlation would help in NDVI calibration to add continuity in long term NDVI database for climate change studies.     

An integrated study of geospatial information technologies for surface runoff estimation in an agricultural watershed,India

Runoff is one of the important hydrologic variables used in most of the water resources applications. The Soil Conservation Service-Curve Number (SCS-CN) method is adopted for the estimation of surface runoff in the Mehadrigedda watershed area, Visakhapatnam district, India using multispectral remote sensing data, curve number approach and normal rainfall data. The main source of water in the Mehadrigedda watershed area is by rain, most of it drains off and only a little percolates into ground. The weighted curve number is determined based on antecedent moisture condition (AMC)-II with an integration of hydrologic soil groups (HSGs) and land use/land cover LULC categories. An integrated approach is applied to delineate the land use/land cover information as adopted from NRSA classification. The recording of daily rainfall data during the years 1997–2006 is collected from Indian Meteorological Department (IMD) rainguage center at Kottavalasa. It is observed that the annual rainfall-runoff relationship during 1997–2006, which is indicating that the overall increase in runoff with the rainfall of the watershed area. Integration of remote sensing (RS) and geographical infomation system (GIS) techniques provide reliable, accurate and up-to-date information on land and water resources.     

Spatial and Temporal Variability of Net Primary Productivity (NPP) over Terrestrial Biosphere of India Using NOAA-AVHRR Based GloPEM Model

The monitoring of terrestrial carbon dynamics is important in studies related with global climate change. This paper presents results of the inter-annual variability of Net Primary Productivity (NPP) from 1981 to 2000 derived using observations from NOAA-AVHRR data using Global Production Efficiency Model (GloPEM). The GloPEM model is based on physiological principles and uses the production efficiency concept, in which the canopy absorption of photosynthetically active radiation (APAR) is used with a conversion “efficiency” to estimate Gross Primary Production (GPP). NPP derived from GloPEM model over India showed maximum NPP about 3,000 gCm⁻²year⁻¹ in west Bengal and lowest up to 500 gCm⁻²year⁻¹ in Rajasthan. The India averaged NPP varied from 1,084.7 gCm⁻²year⁻¹ to 1,390.8 gCm⁻²year⁻¹ in the corresponding years of 1983 and 1998 respectively. The regression analysis of the 20 year NPP variability showed significant increase in NPP over India (r = 0.7, F = 17.53, p < 0.001). The mean rate of increase was observed as 10.43 gCm⁻²year⁻¹. Carbon fixation ability of terrestrial ecosystem of India is increasing with rate of 34.3 TgC annually (t = 4.18, p < 0.001). The estimated net carbon fixation over Indian landmass ranged from 3.56 PgC (in 1983) to 4.57 PgC (in 1998). Grid level temporal correlation analysis showed that agricultural regions are the source of increase in terrestrial NPP of India. Parts of forest regions (Himalayan in Nepal, north east India) are relatively less influenced over the study period and showed lower or negative correlation (trend). Finding of the study would provide valuable input in understanding the global change associated with vegetation activities as a sink for atmospheric carbon dioxide.     

Using GPS multipath to measure soil moisture fluctuations: initial results

Measurements of soil moisture are important for studies of climate and weather forecasting, flood prediction, and aquifer recharge studies. Although soil moisture measurement networks exist, most are sparsely distributed and lack standardized instrumentation. Measurements of soil moisture from satellites have extremely large spatial footprints (40–60 km). A methodology is described here that uses existing networks of continuously-operating GPS receivers to measure soil moisture fluctuations. In this technique, incoming signals are reflected off and attenuated by the ground before reception by the GPS receiver. These multipath reflections directly affect signal-to-noise ratio (SNR) data routinely collected by GPS receivers, creating amplitude variations that are a function of ground reflectivity and therefore soil moisture content. After describing this technique, multipath reflection amplitudes at a GPS site in Tashkent, Uzbekistan are compared to estimates of soil moisture from the Noah land surface model. Although the GPS multipath amplitudes and the land surface model are uncalibrated, over the 70-day period studied, they both rise sharply following each rainfall event and slowly decrease over a period of ∼10 days.     

Sea level change in Hong Kong from tide gauge measurements of 1954–1999

 Tide gauge records of Hong Kong covering the past 45 years (1954.0–1999.0) are adopted to analyze the basic features of sea level changes in the region. Data sets of atmospheric pressure, southern oscillation index and sea surface temperature during the same time span are also used to determine the possible link between the sea level changes in Hong Kong and local and global geophysical processes. Results indicate that the sea level of Hong Kong has a rising trend of 1.9 ± 0.4 mm per year, and that there is an upward offset of about 15 cm in the pre-1957.0 tide gauge records. The effect of local atmospheric pressure variations on the amplitude of the annual sea level change is about 30% of the amplitude that is calculated after the effect is corrected. It is also found that the interannual variations in the sea level of Hong Kong are related to El Ni?o and La Ni?a events that happen frequently in the tropical Pacific. Received: 27 October 1999 / Accepted: 15 August 2000     

陆地表层覆盖变化对地表反照率影响的四国对比

陆表覆盖变化影响地表特征从而改变地表能量平衡是理解人类活动对全球气候变化影响的关键环节。选择国际气候谈判主要国家的美国、印度和巴西作为中国的对比国,对比分析不同国别、不同气候带典型陆表覆盖类型的地表反照率时空差异,进而模拟开垦和城市化等陆表覆盖变化对反照率的影响差异。结果表明：(1) 2000年—2015年,中国、美国的地表反照率年际变化存在明显的气候带空间分异特征,中国干旱半干旱区和美国中低纬湿润区表现出降低趋势,而中国亚热带湿润和美国高纬与中部干旱区则表现出明显的升高趋势,印度的地表反照率年际变化呈微弱下降趋势,而巴西为微弱上升趋势。(2)无雪覆盖时,耕地、林地、草地和人造地表反照率具有夏高、冬低的时间变化特征,干旱半干旱区反照率明显高于湿润区。4种类型的国别差异体现在,中国亚热带湿润区地表反照率均以上升为主,干旱半干旱区则相反;美国除耕地在干旱区呈较强的升高趋势外,其余类型基本为降低趋势;印度均表现为降低趋势;巴西则表现为略微升高趋势。(3)与无雪覆盖相比,有雪覆盖时不同陆表覆盖类型地表反照率均有所提高,林地提高幅度最小,约0.06—0.26,耕地提高最大,约为0.17—0.38,且中国林地反照率提高幅度略高于美国。(4)原陆表覆盖为林地时,开垦和城镇化均导致地表反照率升高,且干旱区升高幅度高于湿润区,湿润区的升高幅度随纬度降低而减弱;为草地时,开垦主要在巴西、印度和中、美亚热带湿润区引起地表反照率升高。而城镇化引起的反照率变化则受到原有地表覆盖、季节和气候背景影响存在较复杂的国别和气候带差异。     

Estimation and validation of snow surface temperature using modis data for snow-avalanche studies in NW-Himalaya

Snow avalanche studies require different snow-meteorological parameters for avalanche forecasting. Snow surface temperature is one of the major parameters, which is responsible for the evolution of snow pack characteristics. In the present paper, the snow surface temperature was estimated using TERRA satellite based — Moderate resolution imaging spectroradiometer (MODIS) sensor for NW-Himalayas. Ground data observed by automatic weather stations (AWS) was used to calibrate the brightness temperature obtained by MODIS thermal bands data into the actual snow surface temperature data through regression analysis. A split window technique has been implemented for the estimation of snow surface temperature. The multi-date satellite derived snow surface temperature was validated with ground data of winter 2004–05 and 2005–06 collected at various observation stations located in different ranges of NW-Himalaya. Good correlations were observed for Upper Himalaya (0.98, 0.98), Middle Himalaya (0.92, 0.96) and Lower Himalaya (0.88, 0.82) for 2004–05 and 2005–06 winter respectively. Further, estimated snow surface temperature was also verified with snow-cover information collected by manned observatories and area delineated by thematic maps of snow surface temperature was validated with the different snow climatic zones of NW-Himalaya.     

Water Balance Study for a Basin Integrating Remote Sensing Data and GIS

Water balance of a basin involves estimation of input precipitation, runoff, infiltration and evapotranspiration (ET). Although ET may have large variations over a big basin, it is commonly estimated using a few point measurements and this makes the estimation error prone. Satellite based remote sensing data provides few parameters for estimation of energy fluxes, at the land surface and atmosphere interaction in a distributed manner using the meteorological parameters. These parameters through surface energy balance equation have been used for the estimation of ET in this study. Various spatially distributed variables required for ET estimation; viz. NDVI, surface albedo, surface temperature etc. have been derived using remote sensing and ancillary data for Tapi basin located in western India. Beside this field data such as rainfall, air temperature, relative humidity, sunshine hours etc. have been used. For computation of runoff, Soil Conservation Services (SCS) approach has been considered. Tapi basin up to Ukai dam has been selected as the study area. Satellite data from National Oceanic and Atmospheric Administration (NOAA), Polar Orbiting Environmental Satellite, which carries the Advanced Very High Resolution Radiometer (AVHRR), have been used for preparation of various maps required for runoff and ET analysis. The results of runoff and ET have been compared with observed data for 2 years, 2002–2003 and the results have been found in good agreement with observed data.     

中国地表积雪动态分布及反照率的变化

地表特征和下垫面物理性质在时分布上的差异,造成地表能量分布的不均。地表积寻由于其分布广、反照率高、高节性强等特点,对局地气修乃至全球气修变化都具有深远的影响。遥感动态监测地表特征的变化和反演大面积反照率是一种实际有效的技术手段,该文应用遥感技术、分析研究了我国地表积雪分布和反照率的动态变化。     

Recent Trends of Arctic and Antarctic Summer Sea-Ice Cover Observed from Space-Borne Scatterometer

Long term variations in Sea ice distribution strongly influence the atmosphere and ocean in the polar regions. In the recent period significant variations in sea ice cover have been observed in both the hemispheres. In the past, studies have been carried out that report the trends either at the Arctic/Antarctic level or at sector level. However, only a few studies have concentrated on the investigation of trends at grid level using scatterometer data. The present study focuses on the investigations of the sea ice trend at 1 × 1 degree grid level over the period 2000–2007 using QuickSCAT 0.2-degree resolution Scatterometer data. It was observed that in the Arctic overall monthly trend is negative in all the sectors, with the Arctic level decline of 3.26% per year. In the Antarctic, region-wise different trends have been observed. Negative trend is observed in the Amundsen- Bellingshausen Seas and also in the Indian Ocean sector near the continental Ice shelves. It was highlighted that significant trends exists within the pockets of marginal seas.     

Application of remote sensing and GIS to assess land use changes in Jhunjhunun district of arid Rajasthan

Over the last four decades exploitation of natural resources to meet increasing societal demands for land based products has caused significant changes in land use and land cover not only in nature’s best gifted regions but also environmentally sensitive arid regions. Through digital interpretation of IRS LISS-III data of 2004 supported with field survey, the present land use map of Jhunjhunun district of arid Rajasthan has been prepared. Agriculture is the dominant land use constituting 84% (including 38% irrigated cropland) area. The land use changes over time and space are worked out by comparing with Landsat 2 MSS data of 1975 and Land use/land cover map of 1988–89. These changes are correlated by analyzing historical land use and cropping pattern data from 1957–58 to 2004–05. The region witnessed record increase in irrigated area but sharply depleted ground water and rendered hectares of irrigated double cropland into dry land agriculture. Strategies and technologies are suggested for sustainable use and management of different category of land.     

Land surface temperature retrieval and its validation using NOAA AVHRR thermal data

The retrieval of land (soil-vegetation complex) surface temperature (LST) was carried out over semi-arid mixed agriculture landscape of Gujarat using thermal bands (channel 4 and 5) and ground emissivity from atmospherically corrected NDVI of NOAA AVHRR LAC images. The atmospheric correction of Visible and NIR band reflectance was done using SMAC model. The LST computed from split-window method and subsequently corrected with fractional vegetation cover were then compared with near synchronous ground observations of soil and air temperatures made during 13–17 January and April, 1997 at five Land Surface Processes Experiment (LASPEX) sites of Anand, Sanand, Derol, Arnej and Khandha covering 100 km x 100 km. The fractional vegetation cover corrected LST at noon hrs. varied from 301.6 – 311.9K in January and from 315.8 – 325.6K in April. The LST_corr were found to lie in the mid way between AT and ST during January. But in April, LST were found to be more close to ST which may be due to relatively poor vegetation growth as indicated by lower NDVI values in April indicating more contribution to LST from exposed soil surface.     

Seasonal length-of-day changes and atmospheric angular momentum oscillations in their temporal variability

Recently, effective atmospheric-angular-momentum (AAM) functions as calculated from National Centers for Environmental Prediction (NCEP) (formerly National Meteorological Center, NMC) and National Center for Atmospheric Research (NCAR) Reanalyses have become available for the years 1958 to 1998. Concerning the wind terms, the top level in the atmosphere used here is 10 hPa. Compared with earlier NMC model versions, which incorporate wind fields up to 100 hPa since 1976 and up to 50 hPa since 1981, the reanalyses have produced improved data series over a longer period than before. The axial AAM component χ₃ is associated with changes in length of day (LOD). Motivated by better quality and continuity of the series AAM (NCEP) Reanalysis, the problem of the seasonal imbalances in the solid Earth–atmosphere axial angular momentum budget is re-examined. To assess better the estimates of the annual and semiannual oscillations in LOD and AAM and of the residual oscillations derived as difference series between LOD and AAM, the series of LOD data from three analysis centers [International Earth Rotation Service (IERS), GeoForschungZentrum Potsdam (GFZ) and Jet Propulsion Laboratory Pasadena (JPL)] and of AAM data in terms of χ₃(W), χ₃(P) and χ₃(P+IB) from four meteorological centers [NCEP, Japan Meteorological Agency (JMA), European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Meteorological Office (UKMO)] are used in this study. The main analysis steps were removing gaps, filtering out the seasonal oscillations, calculating optimal estimates of the parameters of the oscillations and calculating the difference series between the LOD and AAM systems as well as the residuals in the axial angular momentum budget in the LOD–AAM systems. The results derived as difference series between the different LOD, AAM and LOD–AAM systems show to what extent the variations reflect systematic differences and significant signals, respectively, which is important for future activities in this field. Received: 2 February 1999 / Accepted: 30 November 1999     

利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化(英文)

The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover h...     

Black sea annual and inter-annual water mass variations from space

This study evaluates the performance of two widely used GRACE solutions (CNES/GRGS RL02 and CSR RL04) in deriving annual and inter-annual water mass variations in the Black Sea for the period 2003–2007. It is demonstrated that the GRACE derived water mass variations in the Black Sea are heavily influenced by the leakage of hydrological signals from the surrounding land. After applying the corresponding correction, we found a good agreement with water mass variations derived from steric-corrected satellite altimetry observations. Both GRACE and altimetry show significant annual water mass variations of roughly 7 cm amplitude peaking in May and a semi-annual signal of roughly 3 cm peaking in June and in December. The amplitude of the annual water mass signal varies significantly from year to year and is significantly larger during 2004–2006 than in 2003 and 2007. This is also in agreement with the steric corrected altimetry.     

Land use/land cover dynamics in Umngot watershed of Meghalaya using geospatial tools

Meghalaya is a landlocked state where the progress of industrialization is very slow. Majority of the population (rural) depends on agriculture. Agriculture in the state is carried on in primitive ways with Jhumming prevailing in many parts. This practice is considered destructive as vast forest areas are cleared and burnt. Such areas are used for cultivation and left out. After a gap of few years (2–3 years as of now and 15–20 years in past) the area is revisited for cultivation without allowing to rejuvenate. The present work provides a status and trend of Land use land cover dynamics in parts (at watershed level) of Meghalaya. The geospatial tools have been used to assess (a) the changes in land use land cover since 1970s to 2005; (b) patch dynamics for understanding the degree of fragmentation; (c) changes along the terrain topography. Umngot watershed of Meghalaya is taken as experimental area, which is a representative of mid-altitudinal watershed particularly in the Jaintia hills district of Meghalaya.     

Forward a spatio-temporal trend surface for long-term ground-measured albedo upscaling over heterogeneous land surface

Upscaling ground albedo is challenged by the serious discrepancy between the heterogeneity of land surfaces and the small number of ground-based measurements. Conventional ground-based measurements cannot provide sufficient information on the characteristics of surface albedo at the scale of coarse pixels over heterogeneous land surfaces. One method of overcoming this problem is to introduce high-resolution albedo imagery as ancillary information for upscaling. However, due to the low frequency of updating of high-resolution albedo maps, upscaling time series of ground-based albedo measurements is difficult. This paper proposes a method that is based on the idea of conceptual universal scaling methodology for establishing a spatiotemporal trend surface using very few high-resolution images and time series of ground-based measurements for spatial-temporal upscaling of albedo. The construction of the spatiotemporal trend surface incorporates the spatial information provided by auxiliary remote sensing images and the temporal information provided by long time series of ground observations. This approach was illustrated by upscaling ground-based fine-scale albedo measurements to a coarse scale over the core study area in HiWATER. The results indicate that this method can characterize the spatiotemporal variations in surface albedo well, and the overall correlation coefficient was 0.702 during the study period.