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All Summary Global cropwatch

Angola Main producing and exporting countries
作者: 编辑:


The reporting period covers the harvesting of wheat, which started in late October, as well as the preparation of  land and planting of the  2019/20 maize.

Rainfall was 62% above average, with the amount recorded in October above both fifteen-years average and fifteen-years maximum. Both temperature and radiation were close to average. The conditions resulted in a slight increase  in BIOMSS (+3%) but CALF fell by about 23%. In the southern part of the country, the NDVI development graph shows below-average crop conditions during the entire monitoring period. The VCIx was just 0.63.

The spatial distribution of the NDVI profiles reveals diverse behaviors. 71.2% of the cropped area, including most the southern provinces of Cuando, Cubango, Cunene and Huila had negative anomalies during the entire period. A positive NDVI anomaly persisted throughout the reporting period in Uige, Zaire, Kwanza Norte and Benguela Provinces, accounting for 15.6% of the total cropped area. The remaining regions registered complex spatial patterns with a mixture of negative, positive and about average NDVI anomalies but all  underwent a significant drop in late October.

Nationwide, the crop condition was unfavorable. The high precipitation had a significant negative impact on wheat  but will benefit the recently planted maize.

Regional Analysis

CropWatch subdivides Angola into five zones based on cropping systems, climatic zones and topography. They are referred to as Arid zone, Central Plateau, Humid zone, Semi-arid zone and Sub-humid zone. A mixture of double and single cropping characterizes the Humid and Subhumid zones. In these zones, the cropping intensity increased by about 9% and 5%, respectively. Remaining areas practice single cropping. The Arid zone is of marginal relevance for crops.

All the agro-ecological regions have recorded significant increases of rainfall above average during the reporting period. The Humid zone recorded the highest increases (up 108%). Except for the Arid zone, all regions recorded a slight decrease in the temperature. The radiation increased everywhere. With CALF decreasing in all the agro-ecological zones with the exception for the humid zone, the NDVI development graphs indicate bellow average crop conditions during the entire period in these regions. Compared with average, only slight variations in biomass were verified in all the agroecological zones. Considering, in addition, VCIx suggests poor crop prospects. However, the high rainfall has benefited the range-land and created favorable conditions for the ongoing planting of Maize.

In the Humid zone, where NDVI indicates favorable conditions from early august until the end of the monitoring period, crop prospects are excellent as the maximum VCIx reached 1.0 and CALF did not register any variations.

Figure 3.6. Angola’s crop condition, July-October 2019

(a) Phenology of major crops

(b) Crop condition development graph based on NDVI          (c) Maximum VCI

(d) Spatial NDVI patterns compared to 5YA                        (e) NDVI profiles

(f) National time-series rainfall profiles (g) National time-series temperature profiles

(h) Crop condition development graph based on NDVI (Arid zone (left) and Central Plateau (right))

(i) Crop condition development graph based on NDVI (Humid zone (left) and Semi-arid zone (right))

(j) Crop condition development graph based on NDVI - Subhumid zone

Table 3.3.Angola's agroclimatic indicators by sub‐national regions, current season's values and departure from 15YA, July - October 2019.

Region

RAIN

TEMP

RADPAR

BIOMASS

Current (mm)

Departure from 15YA (%)

Current (°C)

Departure from 15YA (°C)

Current (MJ/m2)

Departure from 15YA (%)

Current (gDM/m2)

Departure from 15YA (%)

Arid Zone

142

55

22.1

0.2

1339

1

590

7

Central Plateau

248

58

18.4

-0.5

1394

3

299

-9

Humid zone

652

23

23.5

-0.5

1285

3

660

1

Semi-Arid Zone

69

108

21.0

-0.1

1409

1

318

4

Sub-humid zone

324

66

21.9

-0.3

1314

1

472

4

Table 3.4. Angola's agronomic indicators by sub-national regions, current season's values and departures, July to October 2019

 

Region

CALF

Cropping Intensity

Maximum VCI

Current(%)

Departure from 5YA (%)

Current (%)

Departure from 5YA (%)

Current

Arid Zone

16

-37

61

-30

0.51

Central Plateau

36

-12

99

1

0.71

Humid zone

100

0

125

9

1.02

Semi-Arid Zone

13

-52

86

-8

0.53

Sub-humid zone

56

-15

119

5

0.70

菜单

  • Executive summary
    • Executive summary
  • Global agroclimatic patterns
    • Global agroclimatic patterns
  • Crop and environmental conditions in major production zones
    • Overview
    • West Africa
    • North America
    • South America
    • South and Southeast Asia
    • Western Europe
    • Central Europe to Western Russia
  • Main producing and exporting countries
    • Overview
    • Country analysis
    • Afghanistan
    • Angola
    • Argentina
    • Australia
    • Bangladesh
    • Belarus
    • Brazil
    • Canada
    • Germany
    • Egypt
    • Ethiopia
    • France
    • United Kingdom
    • Hungary
    • Indonesia
    • India
    • Iran
    • Italy
    • Kazakhstan
    • Kenya
    • Cambodia
    • Sri Lanka
    • Morocco
    • Mexico
    • Myanmar
    • Mongolia
    • Mozambique
    • Nigeria
    • Pakistan
    • Philippines
    • Poland
    • Romania
    • Russia
    • Thailand
    • Turkey
    • Ukraine
    • United States
    • Uzbekistan
    • Viet Nam
    • South Africa
    • Zambia
    • Kyrgyzstan
  • China
    • Overview
    • China’s crop production
    • Northeast region
    • Inner Mongolia
    • Huanghuaihai
    • Loess region
    • Lower Yangtze region
    • Southwest China
    • Southern China
    • Pest and diseases monitoring
    • Major crops trade prospects
  • Focus and perspectives
    • 2019 Global production outlook
    • Disaster events
    • Update on El Niño
  • Annex
    • Annex A. Agroclimatic indicators and BIOMSS
    • Annex B. Quick reference guide to CropWatch indicators, spatial units, and production estimation methodology

Figures

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