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Vegetation indicators and spatial distribution characteristics are the core and basis to study the complex human-natural coupled system. In this paper, with Landsat 5 and Landsat 8 remote sensing data, we quantitatively estimated vegetation coverage in Henan Province, China. According to the urbanization rate, altitude, slope degree, and slope exposure, we analyzed spatial and temporal variation laws of vegetation coverage under the action of different factors to provide a reference for the improvement of the ecological environment and the quality assessment of Chinese granary. From 2000 to 2013, the vegetation coverage in Henan Province declined by 30.49% and the ecological environment deteriorated. The spatial change of vegetation coverage was evenly distributed in Henan Province. The vegetation coverage was increased in the west, south, and southwest parts of Henan Province and slightly decreased in the central, east, and the eastern part of Taihang Mountain. Vegetation coverage in a city was related to its population urbanization rate. The population urbanization rate was often negatively correlated with the vegetation coverage. According to the results of terrain factors based analysis, the low-altitude areas were in a good vegetation cover condition with the high vegetation coverage grade; the areas with a smaller slope degree had the large vegetation coverage and the coverage decreased with the increase in the slope degree; the coverage showed no significant difference between sunny and shady slopes and was less limited by light, temperature, and humidity.

Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.

Drought is a noteworthy cause of low agricultural profitability and of crop production vulnerability, yet in numerous countries of Africa little to no consideration has been paid to readiness for drought calamity, particularly to spatial evaluation and indicators of drought occurrence. In this study, biophysical and socio-economic data, farmers’ community surveys and secondary data from remote sensing on soil characteristics and water demand were used to evaluate the predictors of drought in inland valley rice-based production systems and the factors affecting farmers’ mitigation measures. The study intervened in three West African countries located in the Sudan-Sahel zone, viz. Burkina Faso, Mali and Nigeria. Significant drying trends occurred at latitudes below 11°30′ whilst significant wetting trends were discerned at latitude above 11°30′. Droughts were more frequent and had their longest duration in the states of Niger and Kaduna located in Nigeria and in western Burkina Faso during the period 1995–2014. Among 21 candidate predictors, average annual standardized precipitation evapotranspiration index and duration of groundwater availability were the most important predictors of drought occurrence in inland valleys rice based-production systems. Land ownership and gender affected the commitment of rice farmers to use any mitigation measure against drought. Drought studies in inland valleys should include climatic water balance and groundwater data. Securing property rights and focusing on women’s association would improve farmers’ resilience and advance drought mitigation measures.

The aim of this work was to develop an equation to predict methane yield (CH4, g/kg dry matter intake) from dairy goats using milk fatty acid (FA) profile. Data from 12 research papers (30 treatments and 223 individual observations) were used in a meta-regression. Since most of the selected studies did not extensively report milk fat composition, palmitic acid (C16:0) was selected as a potential predictor. The obtained equation was: CH4 (g/kg dry matter intake) = 0.525 × C16:0 (% in milk fat). The coefficient of determination (R2 = 0.46), the root mean square error of prediction (RMSPE = 3.16 g/kg dry matter intake), and the concordance correlation coefficient (CCC = 0.65) indicated that the precision, accuracy and reproducibility of the model were moderate. The relationship between CH4 yield and C16:0 content in milk fat would be supported by the fact that diet characteristics that increase the amount of available hydrogen in the rumen for archaea to produce CH4, simultaneously favor the conditions for the synthesis of C16:0 in the mammary gland. The obtained equation might be useful, along with previous published equations based on diet characteristics, to evaluate the environmental impact of dairy goat farming.

To increase the spatial resolution of Soil Moisture Active Passive (SMAP), this study modifies the downscaling factor model based on the Temperature Vegetation Drought Index (TVDI) using data from the Project for On-Board Autonomy (PROBA-V). In the modified model, TVDI parameters were derived from the temperature-vegetation space and the Enhanced Vegetation Index (EVI). This study was conducted in the north China region using SMAP, PROBA-V, and Moderate Resolution Imaging Spectroradiometer satellite images. The 9-km spatial resolution SMAP data was downscaled to 0.3-km spatial resolution soil moisture using a modified downscaling method. Downscaling accuracies from the original and modified downscaling factor models were compared based on field observations. The results show that both methods generated similar spatial distributions in which soil moisture estimates increased as vegetation coverage increased from built-up areas to forest. However, based on the root mean square error between observations and estimations, the modified model demonstrated an increased estimation accuracy of 4.2% for soil moisture compared to the original method. This study also implies that downscaled soil moisture shows promise as a data source for subsequent watershed scale studies.

The Upper Yangtze River Basin comprises a densely-populated agricultural region with mountainous and hilly landforms. Intensive cultivation has been extended onto steep hillslopes, which constitute the principal source area for sediment production. Soil conservation on sloping arable lands is thus of utmost priority for persisting sustainable agricultural production and maintaining sound ecosystem services. Although there have been many soil conservation techniques, either promoted by the government or adopted by local farmers, the practiced area was very limited relative to the total area affected by soil erosion. This paper attempts to introduce four popular soil conservation measures on sloping arable lands in this region to enhance a broader scale of implementation, including hedgerow buffers, level trenches, sloping terraces and limited downslope tillage. These practices, although developed from local farmers’ indigenous knowledge for productive purposes, have well conformed to our contemporary understanding of soil erosion processes on sloping landscape affected by human disturbances, were of sound suitability to regional manual tillage agriculture and more trade-off-efficient on rill prevention, runoff harvest and nutrient management.

Sustainability of olive production is possible by adopting the modern techniques of irrigation and fertilization. In Tunisia, olive trees are usually cultivated in poor soils, under semi-arid conditions characterized by water scarcity. This study investigated the effects of different water supply and fertilization on leaf water status and crop yield of three different olive oil varieties cultivated in central Tunisia, during four experimental seasons (2014–2017). Three treatments were examined: trees conducted under rainfed conditions (TRF), which represented the control treatment, trees irrigated with 50% ETc (T50) and, finally, trees irrigated with 50% ETc and with additional fertilization (T50F). Leaf water content and potential, yield and water use efficiency have been monitored on three different varieties, Chetoui, Chemlali, and Koroneiki, which are quite typical in the considered region. For all the growing seasons, midday leaf water potentials were measured from April to September. Midday leaf water potentials (MLWP) were generally higher for the two irrigated treatments (T50 and T50F) than for non-irrigated trees (TRF). As the season proceeded, MLWPs tended to decrease during summer for all the treatments and varieties. The lowest values were observed for the non-irrigated trees, varying between −3.25 MPa to −4.75 MPa. Relative leaf water content followed the same trends of midday leaf water potentials. Chetoui showed the lowest yield, which did not exceed 1530 Kg/(ha year), even for irrigated and fertilized trees. On the other hand, the yields of Chemlali and Koroneiki, cumulated in the four years, reached the maximum value of about 20 tons/ha. For these two varieties, the cumulated yield obtained in the control treatment (TRF) resulted significantly lower than the corresponding of the other two treatments (T50 and T50F). The highest irrigation water use efficiency (WUE) was estimated for Chemlali (T50) and (TRF). WUE was equal to 1.22 Kg/m3 for Koroneiki under fertigated treatment (T50F). Application of the only water supply (50% ETc) or associated with fertilizer improved the tree water status and increased the productivity of Chemlali and Koroneiki varieties.