Relative humdity and Precipitation

A HOBO relative humidity/temperature and a precipitation gauge were added to the World Relief Office weather station.

Makeshift sun shield for the temperature recording device developed ad hoc
by Dr. Darcy Boellstorff and Zaine Venter

Collaborator Meetings

During the June trip, Dr. Darcy Boellstorff, Zaine Venter and WR team met with potential collaborators including:

·          Mr. P. Chikapa, the Assistant District Agriculture Development Officer in Mzimba

·          Mr. Mkinda, the Mbawa Extension Planning Area (EPA) Team Leader

·          Dr. Benesi, Government Plant Breeder at the Chitedze Agricultural Research Station in Lilongwe

·          The technical assistants of Dr. Chipungu at the Bvumbwe Agricultural Research Station in Bvumbwe

·          Melody McNeil – Agricultural Officer at USAID Malawi Mission

·          Faculty from Bunda College of Agriculture

Solar Irrigation Pump Installation

The first irrigation pump was presented to farmers from three villages who were collectively working on an irrigation scheme along a stretch of the Kakoma River (Dr. Darcy Boellstorff and WR Team).

Solar Irrigation Pump Installation

Training Materials

A training manual for using Quantum GIS and the survey database was developed for training World Relief staff in June. The manual exercises are geared to both introduce the user to GIS and to help understand the relationship and utility of the survey data in planning. Each exercise culminated in a finished-product map that were exported to a pdf format.

The exercises include:

• Adding Vector/Raster Layers
• Map Composition Using Malawi Districts, Roads, Water Bodies/Rivers
• Compare Image Resolutions – New Shp, Digitizing And Editing Layers
• Find Widowed-Female-Headed Households That Have Dependents
• Find Female-Headed Households That Earn 50,000 Mwk Or Less Per Year
• Find Women-Headed Households That Earn Less Than 50,000 Mkw, That Are Not Within A 20 Minute Walk Of A Storage Facility
• Farm Area - Rainfed Land
• Root Growing Rainfed Farms Near River Irrigation Source

A final map output from the GIS training.

Survey Database Building

The data from the farmer surveys were coded and organized into 13 relational tables which can be joined to their spatial location using a common item called “Survey_ID”. The tables were stored as Excel files and also as .dbf files for joining in Quantum GIS.  Metadata attribute tables were written that allow users to look up attribute definition and value codes.

Kabwandire market locations

Kabwandire markets are small adhoc markets that crop up at certain intersections along a main road or even within a larger village. These markets move location over the course of a year as different farmers have different crops come to harvest and demand changes. They’re important market locations to consider when mapping relationships between markets. These Kabwandire markets could serve as natural collection points for shared transportation to the larger market locations. 

In May, the World Relief promoters gathered the GPS locations of these markets and the data points were used in the training data set in the June training session.

Map by Zaine Venter

Survey Data

By mid-May, the total number of farmer surveys collected was 330. The data reveal information on household type, income, landuse, and agricultural support services used and needed by the Mzimba farmers. The data were collected from villages in the eastern portion of Mzukuzuku TA (map below).

World Relief promoters interview a woman from Mzukuzuku who heads a woman-headed household.

UC Davis - Solar Powered Technologies

A tour of the UC Davis Student Farm and Long Term Research on Agricultural Systems research area gave participants the opportunity to see in action a solar-powered coolbot and irrigation pump 

Coolbot: a small insulated storage building being cooled by an air conditioner (bottom photo) which is powered by solar panels (photo on the left). Irrigation Pump: an RV pump is directly connected to a 50 w solar panel.

Hort CRSP Spring 2011 Workshop, April 18-19

The two-day workshop brought together PIs and host-country personnel from all current Hort CRSP projects and gave everyone an opportunity to learn about the lessons of current project and scaling up projects for the future. Darcy Boellstorff from Bridgewater State University and Moses Jemitale from World Relief Malawi were in attendance.

A tour of the UC Davis Student Farm and Long Term Research on Agricultural Systems research area gave participants the opportunity to see in action a solar-powered coolbot and irrigation pump.

Moses and Darcy presented a poster that showed some of the same preliminary analyses from the AAG meetings earlier in the month. One part of this analysis included comparing NDVI results from 2010 Landsat TM scenes, one scene from the wet season (April (left)) and one from the dry season (August (right)). The comparison was done in order to determine an estimate of the amount of land cultivated during that year.

Association of American Geographers Meeting, April 12-14

Zaine Venter and Darcy Boellstorff presented their preliminary work in a session at the Association of American Geographers meeting in April. The meeting was held in Seattle, Washington and attended by thousands of geographers and others from around the world.

Location-Allocation

Some of the first GIS analyses done were for village locations using a location-allocation approach. We often consider location to be the most important factor in a successful organization. Given that villages provide a set of demand points for the need for transportation (of agricultural goods), farm inputs, processing, etc., the goal of using a method of analyses to determine best allocation is to locate new facilities that can supply the demand points. In this case, demand points being villages. ArcGIS provides a tool “location-allocation” that simultaneously addresses the two-fold problem of locating facilities and allocating demand points (villages) to those facilities.

Maximize coverage places facilities so that as many demand points as possible are allocated to solution facilities within the impedance cutoff. In this case an impedance cutoff of 10 km was used.

Minimize facilities was used so that as many demand points as possible were allocated to solution facilities within the 10 km. In addition, the number of facilities required to cover the village points is minimized. Finally, maximize attendance shows a solution such that as much demand weight as possible is allocated to facilities.

Fieldwork Photos

Digging the hole for the anemometers:

Hudson Starts the Digging

Moses Helps With Digging

Digging Continues

March Overview

Mar 9 Anemometer readings for 2-22 to 3-8                     

Mar 25 First set of GPS readings from the field                               

Mar 28-30 Acquisition of TM and ALOS scenes

ASTER Digital Elevation Data: March

The area to be reached by irrigation water source (boreholes, rivers, wells) can be modeled through viewshed analyses. The process takes into consideration an “observer point” (location of water source) and “observer height” the estimated elevation from the surface the water can be lifted using a pump (treadle, wind powered, solar powered, etc.).  A viewshed analysis requires an elevation raster data set to determine which areas can be “seen” from the observer point. ASTER 30 m pixel resolution data was acquired from the NASA WIST data portal for the study region.

 The images above show a preliminary modeling of areas within and near Mzukuzuku that would be irrigable (in green) from perennial streams with a lift height of 5 m (left) and 7 m (right).

Imagery Acquisition: March

Advance Land Observation Satellite (ALOS) imagery was purchased from East View Cartographic in late March. The data bands include spectral RGB and a NIR band, all with a spatial resolution (10 m). The date of collection was during the wet season (January 9) in 2009. The imagery will be used to update acquired shapefiles, for vegetation analysis and to create new layers of the point, line and polygon locations.

This data is added to the IKONOS imagery purchased in December. The 50 square km area of high resolution (4m RGB, NIR, 1 m Panchromatic) IKONOS imagery was purchased to test its utility versus price for producing data layers to be used in the GIS.

 

Two Landsat Thematic Mapper (TM) images (RGB, NIR, all 30 m) were acquired from the NASA WIST data portal. The images, one from the wet season and one from the dry season of 2010 represent a snapshot of coverage in the region of pre- and post- harvest land use. The larger spatial resolution data, as compared with the ALOS data, will be used for vegetation analysis and not useful for identifying smaller features.

 (Images: True color composites of the IKONOS, ALOS and TM images (1:10,000) at 4, 10 and 30 m spatial resolutions respectively.)