scholarly journals Livestock intensification potential in Brazil based on agricultural census and satellite data analysis

2018 ◽  
Vol 53 (9) ◽  
pp. 1053-1060 ◽  
Author(s):  
Arielle Elias Arantes ◽  
Victor Rezende de Moreira Couto ◽  
Edson Eyji Sano ◽  
Laerte Guimarães Ferreira
Keyword(s):  
Primary Productivity ◽  
Carrying Capacity ◽  
Dry Matter ◽  
Census Data ◽  
Stocking Rate ◽  
Agricultural Census ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Stocking Rates

Abstract: The objective of this work was to evaluate the potential of livestock intensification in Brazil. Beef cattle stocking rates were estimated according to agricultural census data on livestock production in Brazilian municipalities. Pasture carrying capacity was obtained by combining moderate resolution imaging spectroradiometer (Modis) images of gross primary productivity and data on dry matter demand per animal unit (AU). Cattle stocking rate for Brazil, in 2014/2015, was 0.97 AU ha-1, and the carrying capacity was 3.60 AU ha-1; therefore, there is an average livestock intensification potential of 2.63 AU ha-1. The highest average intensification potential was observed for the Southern region (3.62 AU ha-1), and the lowest for the Northern (2.13 AU ha-1) and Northeastern regions (2.22 AU ha-1). It is possible to estimate cattle stocking rate, pasture carrying capacity, and potential of livestock intensification by integrating data on agricultural census and remote sensing.

scholarly journals Response of net primary productivity to grassland phenological changes in Xinjiang, China

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10650
Author(s):  
Renping Zhang ◽  
Jing Guo ◽  
Gang Yin
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Growing Season ◽  
Casa Model ◽  
Phenological Changes ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Phenological Metrics ◽  
The Impact

Determining the relationship between net primary productivity (NPP) and grassland phenology is important for an in-depth understanding of the impact of climate change on ecosystems. In this study, the NPP of grassland in Xinjiang, China, was simulated using the Carnegie-Ames-Stanford approach (CASA) model with Moderate Resolution Imaging Spectroradiometer (MODIS) grassland phenological (MCD12Q2) data to study trends in phenological metrics, grassland NPP, and the relations between these factors from 2001–2014. The results revealed advancement of the start of the growing season (SOS) for grassland in most regions (55.2%) in Xinjiang. The percentage of grassland area in which the end of the growing season (EOS) was delayed (50.9%) was generally the same as that in which the EOS was advanced (49.1%). The percentage of grassland area with an increase in the length of the growing season (LOS) for the grassland area (54.6%) was greater than that with a decrease in the LOS (45.4%). The percentage of grassland area with an increase in NPP (61.6%) was greater than that with a decrease in NPP (38.4%). Warmer regions featured an earlier SOS and a later EOS and thus a longer LOS. Regions with higher precipitation exhibited a later SOS and an earlier EOS and thus a shorter LOS. In most regions, the SOS was earlier, and spring NPP was higher. A linear statistical analysis showed that at various humidity (K) levels, grassland NPP in all regions initially increased but then decreased with increasing LOS. At higher levels of K, when NPP gradually increased, the LOS gradually decreased.

scholarly journals Modis time series for irrigated-area mapping in hydrographic basins of the Brazilian Northeastern region

2018 ◽  
Vol 53 (1) ◽  
pp. 80-89 ◽  
Author(s):  
Andre Keiiti Ide ◽  
Gustavo Macedo de Mello Baptista
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Northeastern Region ◽  
Irrigated Area ◽  
Analysis Technique ◽  
Agricultural Census ◽  
Moderate Resolution ◽  
Annual Time Series ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract: The objective of this work was to evaluate the applicability of time series of the enhanced vegetation index (EVI), from the moderate resolution imaging spectroradiometer (Modis), in the mapping of irrigated areas in the Northeastern region of Brazil. Annual time series from 2006 to 2015 were classified with the iterative self-organizing data analysis technique (Isodata) algorithm, generating a binary map of irrigated and nonirrigated areas for each year. In the Sertão region, the classification showed an average kappa coefficient of 0.66, underestimating the irrigated area by 7.6%, compared with data of the 2006 agricultural census. In regions more humid than the Sertão, such as Agreste and Zona da Mata Nordestina, the methodology showed limitations to distinguish irrigated areas from natural vegetation, presenting average kappa coefficients of 0.26 and 0.00, respectively. The EVI time series from Modis are applicable for the mapping of irrigated areas in the Sertão of the Northeastern region of Brazil.

scholarly journals KUALITAS LINGKUNGAN PERAIRAN DAN POTENSI PRODUKSI IKAN KAWASAN KONSERVASI TERUBUK BENGKALIS (Tenualosa macrura Bleeker, 1852)

2018 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Khairul Amri ◽  
Gathot Winarso ◽  
Muchlizar Muchlizar
Keyword(s):  
Water Quality ◽  
Satellite Imagery ◽  
Primary Productivity ◽  
Landsat 8 ◽  
Productivity Level ◽  
Mangrove Vegetation ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Terubuk Bengkalis (Tenualosa macrura) yang hidup di perairan Bengkalis dinyatakan terancam punah akibat eksploitasi berlebih dan penurunan kualitas perairan. Penelitian ini bertujuan untuk menganalisa kualitas perairan habitat terubuk Bengkalis, menggunakan data parameter oseanografi hasil pengukuran in-situ. Selain itu, data penginderaan jauh berupa citra Landsat 8 digunakan untuk analisa tutupan mangrove (hutan bakau) serta citra MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer) untuk analisis produktivitas primer (NPP). Penelitian dilaksanakan selama April-November 2015. Hasil penelitian menunjukkan total luas tutupan mangrove yang teridentifikasi citra Satelit Landsat 8 (2015) mencapai 11.736,2 Ha, berkurang sekitar 4.470,8 Ha dalam waktu 12 tahun (2003-2015) dengan laju kehilangan 372,5 Ha/tahun. Dari aspek oseanografi, kawasan konservasi ikan terubuk merupakan perairan dangkal dengan tingkat kecerahan rendah (0,54-0,95 m); suhu perairan relatif tinggi berkisar 29,15-31,87 0C (rata-rata 300C) dan salinitas rata-rata tergolong rendah (28,77-29,22 ppt). Nilai sebaran pH dan oksigen terlarut/DO juga rendah yakni pH 6,3-8,9 (rata-rata pH 7) dan DO 3,90-4,98 mg/l (di bawah Baku Mutu Air Laut). Komposisi substrat dasar didominasi lumpur, dengan prosentase 67,4-89,8%, sehingga perairan ini umumnya keruh. Perairan ini tergolong subur (eutropik) dengan kelimpahan fitoplankton tinggi (23.584 - 95.616 sel/l) terdiri dari 32-52 genera. Produktivitas primer juga tinggi, rata-rata 288,87 mgC/m2/hari dengan potensi produksi ikan 3.680,2 ton/tahun. Terubuk Bengkalis (Tenualosa macrura) is an endemic tropical shad fish that live in Bengkalis waters.This species has been declared endangered due to over exploitation and environmental degradation. The current research aimed to analyze the environmental quality of the species. The data used in this research were consited of in-situ measurement and remote sensing data: Landsat 8 Satellite imagery for mangrove cover observation and MODIS (Moderate-resolution Imaging Spectroradiometer) imagery for Net Primary Productivity (NPP). The results showed that the cover of mangrove vegetation along the coast of Bengkalis Island dentified by Landsat 8 Satellite imagery was11.736,24 Ha. The total loss of cover mangrove vegetation is estimated about 4.470,83 Ha, decreased drastically in 12 years (2003-2015) with a loss rate of 372.5 Ha/year. The habitat of shad fish is shallow water category. The water quality was too turbid (brightness level 0.54-0.95 m); warm water temperature of 29.,15-31.87 0C (average 300C); and low salinity (28,77-29,22 ppt). The relatively low pH and dissolved oxygen content were determined: pH ranged between 6,3-8,9 (mean7) and the DO: 3,90-4,98 mg/l (under the Sea Water Quality Standard).The substrat was dominated by mud (67,4-89,8%) in Bengkalis Strait sub area due to the turbidity. However, these waters are euthropic level category with a high abundance of phytoplankton ranging from 23,584-95,616 cells/l and the species richness varies from 32-52 species. The primary productivity level of waters was also quite high was average of 288,87 mgC/m2/day resulting an estimation of potential of fish biomass value about 3.680,2 ton/year.

scholarly journals Prediction of High-Quality MODIS-NPP Product Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1458
Author(s):  
Zhenhua Liu ◽  
Ting Wang ◽  
Yonghua Qu ◽  
Huiming Liu ◽  
Xiaofang Wu ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Ecological Indicator ◽  
Discrete Wavelet ◽  
Atmospheric Variability ◽  
High Quality ◽  
Aerosol Pollution ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Net primary productivity (NPP) is a key vegetation parameter and ecological indicator for tracking natural environmental change. High-quality Moderate Resolution Imaging Spectroradiometer Net primary productivity (MODIS-NPP) products are critical for assuring the scientific rigor of NPP analyses. However, obtaining high-quality MODIS-NPP products consistently is challenged by factors such as cloud contamination, heavy aerosol pollution, and atmospheric variability. This paper proposes a method combining the discrete wavelet transform (DWT) with an extended Kalman filter (EKF) for generating high-quality MODIS-NPP data. In this method, the DWT is used to remove noise in the original MODIS-NPP data, and the EKF is applied to the de-noised images. The de-noised images are modeled as a triply modulated cosine function that predicts the NPP data values when excessive cloudiness is present. This study was conducted in South China. By comparing measured NPP data to original MODIS-NPP and NPP estimates derived from combining the DWT and EKF, we found that the accuracy of the NPP estimates was significantly improved. The MODIS-NPP estimates had a mean relative error (RE) of 13.96% and relative root mean square error (rRMSE) of 15.67%, while the original MODIS-NPP had a mean RE of 23.58% and an rRMSE of 24.98%. The method combining DWT and EKF provides a feasible approach for generating new, high-quality NPP data in the absence of high-quality original MODIS-NPP data.

scholarly journals Evaluating the Performance of Sentinel-3A OLCI Land Products for Gross Primary Productivity Estimation Using AmeriFlux Data

2020 ◽  
Vol 12 (12) ◽  
pp. 1927 ◽  
Author(s):  
Zhijiang Zhang ◽  
Lin Zhao ◽  
Aiwen Lin
Keyword(s):  
Primary Productivity ◽  
Land Surface ◽  
Vegetation Index ◽  
Meteorological Data ◽  
Gross Primary Productivity ◽  
Carbon Cycles ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Relationship

Accurate and reliable estimation of gross primary productivity (GPP) is of great significance in monitoring global carbon cycles. The fraction of absorbed photosynthetically active radiation (FAPAR) and vegetation index products of the Moderate Resolution Imaging Spectroradiometer (MODIS) are currently the most widely used data in evaluating GPP. The launch of the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite provides the FAPAR and the OLCI Terrestrial Chlorophyll Index (OTCI) products with higher temporal resolution and smoother spatial distribution than MODIS, having the potential to monitor terrain GPP. OTCI is one of the red-edge indices and is particularly sensitive to canopy chlorophyll content related to GPP. The purpose of the study is to evaluate the performance of OLCI FAPAR and OTCI for the estimation of GPP across seven biomes in 2017–2018. To this end, OLCI FAPAR and OTCI products in combination with insitu meteorological data were first integrated into the MODIS GPP algorithm and in three OTCI-driven models to simulate GPP. The modeled GPP (GPPOLCI-FAPAR and GPPOTCI) were then compared with flux tower GPP (GPPEC) for each site. Furthermore, the GPPOLCI-FAPAR and GPP derived from the MODIS FAPAR (GPPMODIS-FAPAR) were compared. Results showed that the performance of GPPOLCI-FAPAR was varied in different sites, with the highest R2 of 0.76 and lowest R2 of 0.45. The OTCI-driven models that include APAR data exhibited a significant relationship with GPPEC for all sites, and models using only OTCI provided the most varied performance, with the relationship between GPPOTCI and GPPEC from strong to nonsignificant. Moreover, GPPOLCI-FAPAR (R2 = 0.55) performed better than GPPMODIS-FAPAR (R2 = 0.44) across all biomes. These results demonstrate the potential of OLCI FAPAR and OTCI products in GPP estimation, and they also provide the basis for their combination with the soon-to-launch Fluorescence Explorer satellite and their integration with the Sentinel-3 land surface temperature product into light use models for GPP monitoring at regional and global scales.

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

scholarly journals A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data

2021 ◽  
Vol 13 (15) ◽  
pp. 2895
Author(s):  
Maria Gavrouzou ◽  
Nikolaos Hatzianastassiou ◽  
Antonis Gkikas ◽  
Christos J. Lolis ◽  
Nikolaos Mihalopoulos
Keyword(s):  
Mediterranean Basin ◽  
Eastern Mediterranean ◽  
Mean Value ◽  
Early Spring ◽  
Dust Aerosol ◽  
Ozone Monitoring Instrument ◽  
Central Mediterranean ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

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