Major threat that Pakistan faces today is water scarcity and any significant change in water availability from storage reservoirs coupled with below normal precipitation threatens food security of ...more than 207 million people. Two major reservoirs of Tarbela and Mangla on Indus and Jhelum rivers are studied. Landsat satellite's data are used to estimate the water extents of these reservoirs during 1981-2017. A long-term significant decrease of 15-25% decade
in water extent is found for Tarbela as compared to 37-70% decade
for Mangla, mainly during March to June. Significant water extents reductions are observed in the range of -23.9 to -53.4 km
(1991-2017) and -63.1 to -52.3 km
(2001-2010 and 2011-2017) for Tarbela and Mangla, respectively. The precipitation amount and areas receiving this precipitation show a significant decreasing trend of -4.68 to -8.40 mm year
and -358.1 to -309.9 km
year
for basins of Mangla and Tarbela, respectively. The precipitation and climatic oscillations are playing roles in variability of water extents. The ensuing multiple linear regression models predict water extents with an average error of 13% and 16% for Tarbela and Mangla, respectively.
There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated ...field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo‐Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.
This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017 where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo‐Wiki application. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available.
The association of climatic variables and climatic oscillations with wheat yield across 26 canal command areas (CCAs) in Punjab, Pakistan, is studied, for recent 34 years (1982–2015). Climatic ...variables include precipitation, temperature, dry/wet spell lengths, hot/cold spell lengths, wet/dry spell ratio along with climatic oscillations, and satellite-based vegetation index for the months of January to April (Rabi season). During Rabi season, temperature increase rate was 0.14 °C decade
−1
, whereas precipitation trends were spatially inhomogeneous and varied between – 2.7 mm decade
−1
and + 5.4 mm decade
−1
. The precipitation, temperature, cold spell length, smoothed NDVI (ND), and standard deviation of ND (SDND) displayed significant correlations (0.31–0.96) with wheat yield at varying time scales. The inter-annual wheat yield variability displayed a gain of 415.7 kg ha
−1
under present climatic conditions for all CCAs. Worse to extreme climatic conditions based on percentiles obtained from present climate displayed a reduction of wheat yield by 252.0 to 954.9 kg ha
−1
, respectively. The good to best climate in comparison to present climatic conditions added up 108.1 to 251.9 kg ha
−1
, respectively. The 11-year period of 1993–2003 was the most drought prone period with consecutive five years of drought (1998–2002), having decreased precipitation, small wet/dry spell ratio and increased temperature, and long dry/hot spell length during wheat growing season. The wheat yield is predicted based on multiple regression models with sizable skill (having an explained variance of 0.79 and a root mean squared error of 121.3 kg ha
−1
).
Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has ...the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel2 for Agriculture” system.
An integrated approach is developed to assess major crops water productivity (CWP) in relation to water supply across the irrigated areas of Punjab province in central Pakistan during 1982–2015. The ...role of precipitation (effective rainfall) in term of add on to water supply and impacts on wheat yield is also studied. The water supply from canals displayed a significant declining trend for Rabi season (wheat mainly) during 1996−2015. Crop water productivity for harvestable area (CWP
A
) has decreased; however, it has increased in case of production (CWP
P
) and yield (CWP
Y
). The role of tube wells is analyzed to assess the improved CWP even under decreased canal water supply. Contribution of water supply through effective rainfall showed a significant add on of 7.6 mm to 291.8 mm to water supply and 0.48 kg ha
−1
mm
−1
to 8.19 kg ha
−1
mm
−1
towards CWP
Y
during the studied 34-year period. The precipitation (effective rainfall) contribute water supply of 10.6 mm (6.64 mm), 23.4 mm (14.6 mm), and 25.5 mm (16.0 mm) for January, February, and March, respectively. Average canal water supply for irrigation is observed to be 254.9 mm against irrigation need of 418.6 mm with a deficit of 39.1%, across irrigated areas. The multiple regression models are developed with seasonal predictive capacity for wheat harvestable area and yields with an explained variability of ~ 81% and ~ 78%, respectively. A decrease in temporal satellite-based weekly composite NDVI profile during 1986, 1992, 1994, 1997, 2002, and 2010 corresponded to El Niño episodes, since negative phases of ENSO are known to cause droughts across Punjab province. The synthesized information calls for a more comprehensive management of declining canal water supply for sustainable major crops water productivity such as wheat which is a staple food crop.
Microplastic pollution has become a global concern, with potential negative impacts on various ecosystems and wildlife species. Among these species, ducks (
) are particularly vulnerable due to their ...feeding habits and proximity to aquatic environments contaminated with microplastics. The current study was designed to monitor microplastic (MP) pollutants in the freshwater ecosystem of the Panjkora River, Lower Dir, Pakistan. A total of twenty (20) duck samples were brought up for four months and 13 days on the banks of the river, with no food intake outside the river. When they reached an average weight of 2.41 ± 0.53 kg, all samples were sacrificed, dissected, and transported in an ice box to the laboratory for further analysis. After sample preparation, such as digestion with 10% potassium hydroxide (KOH), density separation, filtration, and identification, the MP content was counted. A total of 2033 MP particles were recovered from 20 ducks with a mean value of 44.6 ± 15.8 MPs/crop and 57.05 ± 18.7 MPs/gizzard. MPs detected in surface water were 31.2 ± 15.5 MPs/L. The major shape types of MPs recovered were fragments in crop (67%) and gizzard (58%) samples and fibers in surface water (56%). Other types of particles recovered were fibers, sheets, and foams. The majority of these detected MP particles were in the size range of 300-500 µm (63%) in crops, and 50-150 µm (55%) in gizzards, while in water samples the most detected particles were in the range of 150-300 µm (61%). Chemical characterization by FTIR found six types of polymers. Low-density polyethylene (LDPE) had the greatest polymer detection rate (39.2%), followed by polyvinyl chloride (PVC) (28.3%), high-density polyethylene (HDPE) (22.7%), polystyrene (6.6%), co-polymerized polypropylene (2.5%), and polypropylene homopolymer (0.7%). This study investigated the presence of microplastics in the crops and gizzards of ducks, as well as in river surface water. The results revealed the significant and pervasive occurrence of microplastics in both the avian digestive systems and the surrounding water environment. These findings highlight the potential threat of microplastic pollution to wildlife and ecosystems, emphasizing the need for further research and effective mitigation strategies to address this pressing environmental concern.
This research was to explore CoVID-19 at initial stage of 2020 based on statistical techniques using probability density function (PDF), with different statistical measures, polynomial data fitting ...along with 30 day projections. The Covid-19 analysis was carried out only for highly affected countries along with six different regions and global level for 64 days covering period of January to March during 2020. It was found that infection and recovery rate for cases were ranged from 0 ‒ 9.89 and 0 ‒ 8.89% at global level, respectively. The PDF was observed highly positive skewed, leptokurtic, for confirmed cases representing 6620 daily mean infected population for confirmed cases. Countries of USA, Chinas, Spain, France, Italy, Iran, UK and Switzerland were eexpected to be most affected countries with minimum 0.100 million infected population. The projection errors for infection rate remained -78.8 to 49.0%. The curve of CoVID-19 and PDF (skewness and kurtosis) measures provided understanding of data shape and peak height.
Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation ...activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki ( https://www.geo-wiki.org/ ). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.
A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around ...the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.
Research was conducted to determine the preference and non- preference behaviour of red flour beetle against wheat, rice, paddy and sunflower crushed grains under laboratory conditions in university ...of Arid Agriculture Rawalpindi, Pakistan during 2000. In the antixenosis experiment, the red flour beetles were observed at 24 h interval. Red flour beetle had shown highest preference to rice crushed grains with mean 9.250011.8875, medium preference to paddy crushed grains with mean value 5.250012.7500 and least preference to wheat and sunflower with mean value 1.500010.5000 and 1.500010.8660 respectively.
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